From abf0fb56889563b6e8ba169918561f0bb7d5252c Mon Sep 17 00:00:00 2001
From: kassam <kassam@yslootahtech.com>
Date: Sun, 12 Apr 2026 18:52:37 +0400
Subject: [PATCH] Initial project commit

---
 .gitignore                              |   20 +
 Core/Logger.py                          |  186 ++
 Core/__init__.py                        |    0
 Core/audio_prompt_recorder.py           |  403 +++++
 Core/audio_prompts.py                   |  370 ++++
 Core/direct_camera_service.py           | 1170 ++++++++++++
 Core/error_events.py                    |  104 ++
 Core/people_registry.py                 |  456 +++++
 Core/settings.py                        | 1201 +++++++++++++
 Current_runtime.md                      |  272 +++
 Data/Audio/.gitkeep                     |    1 +
 Data/Audio/confirm_reminder.wav         |  Bin 0 -> 230722 bytes
 Data/Audio/confirm_reminder_raw.wav     |  Bin 0 -> 217004 bytes
 Data/Audio/confirm_timeout.wav          |  Bin 0 -> 188528 bytes
 Data/Audio/confirm_timeout_raw.wav      |  Bin 0 -> 174764 bytes
 Data/Audio/count_1.wav                  |  Bin 0 -> 44182 bytes
 Data/Audio/count_1_raw.wav              |  Bin 0 -> 30764 bytes
 Data/Audio/count_2.wav                  |  Bin 0 -> 41282 bytes
 Data/Audio/count_2_raw.wav              |  Bin 0 -> 26924 bytes
 Data/Audio/count_3.wav                  |  Bin 0 -> 44314 bytes
 Data/Audio/count_3_raw.wav              |  Bin 0 -> 30764 bytes
 Data/Audio/countdown_cancelled.wav      |  Bin 0 -> 81050 bytes
 Data/Audio/countdown_cancelled_raw.wav  |  Bin 0 -> 67244 bytes
 Data/Audio/countdown_intro.wav          |  Bin 0 -> 432148 bytes
 Data/Audio/countdown_intro_raw.wav      |  Bin 0 -> 418604 bytes
 Data/Audio/declined.wav                 |  Bin 0 -> 108070 bytes
 Data/Audio/declined_raw.wav             |  Bin 0 -> 94124 bytes
 Data/Audio/frame_group.wav              |  Bin 0 -> 278668 bytes
 Data/Audio/frame_group_raw.wav          |  Bin 0 -> 265004 bytes
 Data/Audio/frame_single.wav             |  Bin 0 -> 252470 bytes
 Data/Audio/frame_single_raw.wav         |  Bin 0 -> 238124 bytes
 Data/Audio/framing_timeout.wav          |  Bin 0 -> 324704 bytes
 Data/Audio/framing_timeout_raw.wav      |  Bin 0 -> 311084 bytes
 Data/Audio/lost_from_frame.wav          |  Bin 0 -> 166428 bytes
 Data/Audio/lost_from_frame_raw.wav      |  Bin 0 -> 151724 bytes
 Data/Audio/photo_saved_thanks.wav       |  Bin 0 -> 217272 bytes
 Data/Audio/photo_saved_thanks_raw.wav   |  Bin 0 -> 203564 bytes
 Data/Audio/retake_limit.wav             |  Bin 0 -> 190862 bytes
 Data/Audio/retake_limit_raw.wav         |  Bin 0 -> 176684 bytes
 Data/Audio/retake_recommended.wav       |  Bin 0 -> 355642 bytes
 Data/Audio/retake_recommended_raw.wav   |  Bin 0 -> 341804 bytes
 Data/Audio/retake_yes.wav               |  Bin 0 -> 171242 bytes
 Data/Audio/retake_yes_raw.wav           |  Bin 0 -> 157484 bytes
 Data/Audio/session_cancelled.wav        |  Bin 0 -> 107650 bytes
 Data/Audio/session_cancelled_raw.wav    |  Bin 0 -> 94124 bytes
 Data/Audio/smile.wav                    |  Bin 0 -> 65728 bytes
 Data/Audio/smile_raw.wav                |  Bin 0 -> 51884 bytes
 Data/Audio/visitor_left.wav             |  Bin 0 -> 148648 bytes
 Data/Audio/visitor_left_raw.wav         |  Bin 0 -> 134444 bytes
 Data/Audio/welcome_group.wav            |  Bin 0 -> 261784 bytes
 Data/Audio/welcome_group_raw.wav        |  Bin 0 -> 247724 bytes
 Data/Audio/welcome_returning.wav        |  Bin 0 -> 135422 bytes
 Data/Audio/welcome_returning_raw.wav    |  Bin 0 -> 121004 bytes
 Data/Audio/welcome_single.wav           |  Bin 0 -> 223440 bytes
 Data/Audio/welcome_single_raw.wav       |  Bin 0 -> 209324 bytes
 Data/G1/arm_home.jsonl                  |  482 +++++
 Data/G1/bird.jsonl                      | 1051 +++++++++++
 Data/G1/change_battery.jsonl            | 1791 ++++++++++++++++++
 Data/G1/hands_up.jsonl                  | 1791 ++++++++++++++++++
 Data/G1/laugh.jsonl                     | 1154 ++++++++++++
 Data/G1/left_hand_up.jsonl              |  866 +++++++++
 Data/G1/photo_G1.jsonl                  | 1235 +++++++++++++
 Data/G1/photo_G2.jsonl                  |  973 ++++++++++
 Data/G1/photo_G3.jsonl                  |  892 +++++++++
 Data/G1/right_hand_up.jsonl             |  856 +++++++++
 Data/G1/think_1.jsonl                   |  987 ++++++++++
 Data/G1/think_2.jsonl                   | 1047 +++++++++++
 Data/G1/think_3.jsonl                   |  694 +++++++
 Data/G1/think_4.jsonl                   |  820 +++++++++
 Data/G1/think_5.jsonl                   |  896 +++++++++
 Data/G1/think_6.jsonl                   |  896 +++++++++
 Data/G1/think_7.jsonl                   |  896 +++++++++
 Data/Notes/Note.txt                     |   41 +
 Data/Runtime/runtime_health.json        |    1 +
 Data/Runtime/upload_db.json             |    1 +
 Data/Scripts/photo_command_ai.txt       |  115 ++
 Data/Scripts/sanad_script.txt           |  102 ++
 Data/Settings/audio_prompt_records.json |  908 ++++++++++
 Data/Settings/config.json               |  131 ++
 Gemini/__init__.py                      |    0
 Gemini/gemini_voice.py                  |  823 +++++++++
 Gemini/sanad_text_utils.py              |  372 ++++
 Gemini/voice_sanad.py                   |  463 +++++
 Models/person.pt                        |  Bin 0 -> 5613764 bytes
 Modes/AI/__init__.py                    |    0
 Modes/AI/autonomous_manager.py          | 1457 +++++++++++++++
 Modes/AI/camera_module.py               |  333 ++++
 Modes/AI/vision_detector.py             | 1480 +++++++++++++++
 Modes/Manual/__init__.py                |    0
 Modes/Manual/controller.py              |   96 +
 Modes/Manual/replay_engine.py           |  243 +++
 Modes/Manual/trigger_loop.py            |  183 ++
 Modes/__init__.py                       |    0
 README.md                               |  268 +++
 Scripts/direct_camera_samples_server.py |   20 +
 Scripts/fix_realsense_usb.sh            |  122 ++
 Scripts/photo_sanad.sh                  |  568 ++++++
 Server/__init__.py                      |    0
 Server/capture_service.py               |  396 ++++
 Server/direct_camera_client.py          |  103 ++
 Server/photo_server.py                  | 2195 +++++++++++++++++++++++
 Server/uploader.py                      |  167 ++
 Web/direct_camera.css                   |  162 ++
 Web/direct_camera.html                  |   56 +
 Web/direct_camera.js                    |  127 ++
 Web/gallery.html                        |   98 +
 Web/gallery.js                          | 1654 +++++++++++++++++
 Web/style.css                           |  730 ++++++++
 requirements.txt                        |   10 +
 109 files changed, 34935 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 Core/Logger.py
 create mode 100644 Core/__init__.py
 create mode 100644 Core/audio_prompt_recorder.py
 create mode 100644 Core/audio_prompts.py
 create mode 100644 Core/direct_camera_service.py
 create mode 100644 Core/error_events.py
 create mode 100644 Core/people_registry.py
 create mode 100644 Core/settings.py
 create mode 100644 Current_runtime.md
 create mode 100644 Data/Audio/.gitkeep
 create mode 100644 Data/Audio/confirm_reminder.wav
 create mode 100644 Data/Audio/confirm_reminder_raw.wav
 create mode 100644 Data/Audio/confirm_timeout.wav
 create mode 100644 Data/Audio/confirm_timeout_raw.wav
 create mode 100644 Data/Audio/count_1.wav
 create mode 100644 Data/Audio/count_1_raw.wav
 create mode 100644 Data/Audio/count_2.wav
 create mode 100644 Data/Audio/count_2_raw.wav
 create mode 100644 Data/Audio/count_3.wav
 create mode 100644 Data/Audio/count_3_raw.wav
 create mode 100644 Data/Audio/countdown_cancelled.wav
 create mode 100644 Data/Audio/countdown_cancelled_raw.wav
 create mode 100644 Data/Audio/countdown_intro.wav
 create mode 100644 Data/Audio/countdown_intro_raw.wav
 create mode 100644 Data/Audio/declined.wav
 create mode 100644 Data/Audio/declined_raw.wav
 create mode 100644 Data/Audio/frame_group.wav
 create mode 100644 Data/Audio/frame_group_raw.wav
 create mode 100644 Data/Audio/frame_single.wav
 create mode 100644 Data/Audio/frame_single_raw.wav
 create mode 100644 Data/Audio/framing_timeout.wav
 create mode 100644 Data/Audio/framing_timeout_raw.wav
 create mode 100644 Data/Audio/lost_from_frame.wav
 create mode 100644 Data/Audio/lost_from_frame_raw.wav
 create mode 100644 Data/Audio/photo_saved_thanks.wav
 create mode 100644 Data/Audio/photo_saved_thanks_raw.wav
 create mode 100644 Data/Audio/retake_limit.wav
 create mode 100644 Data/Audio/retake_limit_raw.wav
 create mode 100644 Data/Audio/retake_recommended.wav
 create mode 100644 Data/Audio/retake_recommended_raw.wav
 create mode 100644 Data/Audio/retake_yes.wav
 create mode 100644 Data/Audio/retake_yes_raw.wav
 create mode 100644 Data/Audio/session_cancelled.wav
 create mode 100644 Data/Audio/session_cancelled_raw.wav
 create mode 100644 Data/Audio/smile.wav
 create mode 100644 Data/Audio/smile_raw.wav
 create mode 100644 Data/Audio/visitor_left.wav
 create mode 100644 Data/Audio/visitor_left_raw.wav
 create mode 100644 Data/Audio/welcome_group.wav
 create mode 100644 Data/Audio/welcome_group_raw.wav
 create mode 100644 Data/Audio/welcome_returning.wav
 create mode 100644 Data/Audio/welcome_returning_raw.wav
 create mode 100644 Data/Audio/welcome_single.wav
 create mode 100644 Data/Audio/welcome_single_raw.wav
 create mode 100644 Data/G1/arm_home.jsonl
 create mode 100644 Data/G1/bird.jsonl
 create mode 100644 Data/G1/change_battery.jsonl
 create mode 100644 Data/G1/hands_up.jsonl
 create mode 100644 Data/G1/laugh.jsonl
 create mode 100644 Data/G1/left_hand_up.jsonl
 create mode 100644 Data/G1/photo_G1.jsonl
 create mode 100644 Data/G1/photo_G2.jsonl
 create mode 100644 Data/G1/photo_G3.jsonl
 create mode 100644 Data/G1/right_hand_up.jsonl
 create mode 100644 Data/G1/think_1.jsonl
 create mode 100644 Data/G1/think_2.jsonl
 create mode 100644 Data/G1/think_3.jsonl
 create mode 100644 Data/G1/think_4.jsonl
 create mode 100644 Data/G1/think_5.jsonl
 create mode 100644 Data/G1/think_6.jsonl
 create mode 100644 Data/G1/think_7.jsonl
 create mode 100644 Data/Notes/Note.txt
 create mode 100644 Data/Runtime/runtime_health.json
 create mode 100644 Data/Runtime/upload_db.json
 create mode 100644 Data/Scripts/photo_command_ai.txt
 create mode 100644 Data/Scripts/sanad_script.txt
 create mode 100644 Data/Settings/audio_prompt_records.json
 create mode 100644 Data/Settings/config.json
 create mode 100644 Gemini/__init__.py
 create mode 100644 Gemini/gemini_voice.py
 create mode 100644 Gemini/sanad_text_utils.py
 create mode 100644 Gemini/voice_sanad.py
 create mode 100644 Models/person.pt
 create mode 100644 Modes/AI/__init__.py
 create mode 100644 Modes/AI/autonomous_manager.py
 create mode 100644 Modes/AI/camera_module.py
 create mode 100644 Modes/AI/vision_detector.py
 create mode 100644 Modes/Manual/__init__.py
 create mode 100644 Modes/Manual/controller.py
 create mode 100644 Modes/Manual/replay_engine.py
 create mode 100644 Modes/Manual/trigger_loop.py
 create mode 100644 Modes/__init__.py
 create mode 100644 README.md
 create mode 100644 Scripts/direct_camera_samples_server.py
 create mode 100755 Scripts/fix_realsense_usb.sh
 create mode 100755 Scripts/photo_sanad.sh
 create mode 100644 Server/__init__.py
 create mode 100644 Server/capture_service.py
 create mode 100644 Server/direct_camera_client.py
 create mode 100644 Server/photo_server.py
 create mode 100644 Server/uploader.py
 create mode 100644 Web/direct_camera.css
 create mode 100644 Web/direct_camera.html
 create mode 100644 Web/direct_camera.js
 create mode 100644 Web/gallery.html
 create mode 100644 Web/gallery.js
 create mode 100644 Web/style.css
 create mode 100644 requirements.txt

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..40cfcfd
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,20 @@
+__pycache__/
+*.pyc
+*.pyo
+*.log
+
+# Runtime/generated
+Scripts/upload_db.json
+Scripts/request_photo.flag
+Scripts/upload_now.flag
+Scripts/ai_mover_state.txt
+Scripts/mode.txt
+Scripts/move_voice_enabled.txt
+photos_archive/
+
+# Runtime folders
+Logs/*.log
+
+# Photos (generated on-device)
+photos/
+Logs/
diff --git a/Core/Logger.py b/Core/Logger.py
new file mode 100644
index 0000000..eab8fbc
--- /dev/null
+++ b/Core/Logger.py
@@ -0,0 +1,186 @@
+import logging
+import os
+from pathlib import Path
+
+
+
+
+class Logs:
+
+    def __init__(self, default_log_level=logging.DEBUG, main_log_file="main.log"):
+        self.default_log_level = default_log_level
+        self.log_format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        self.base_dir = str(Path(__file__).resolve().parents[1])
+        self.default_logs_dir = os.path.join(self.base_dir, "Logs")
+        self.fallback_log_dir = self._choose_fallback_log_dir()
+        self.mainloggerfile = self.resolve_log_path(main_log_file)
+        self.logger = None
+
+        # Initialize the main logger
+        self.main_logger = logging.getLogger("MainLogger")
+        self.main_logger.setLevel(self.default_log_level)
+        self.main_logger.propagate = False  # Prevent logging from printing to terminal
+
+        if self.main_logger.hasHandlers():
+            self.main_logger.handlers.clear()
+
+        # Remove any StreamHandler (to avoid console logs)
+        for handler in list(self.main_logger.handlers):
+            if isinstance(handler, logging.StreamHandler):
+                self.main_logger.removeHandler(handler)
+
+        os.makedirs(os.path.dirname(self.mainloggerfile), exist_ok=True)
+        main_handler = logging.FileHandler(self.mainloggerfile)
+        main_handler.setFormatter(logging.Formatter(self.log_format))
+        main_handler.setLevel(self.default_log_level)
+        self.main_logger.addHandler(main_handler)
+
+    def _choose_fallback_log_dir(self):
+        env_dir = os.environ.get("AI_PHOTOGRAPHER_LOG_DIR", "").strip()
+        candidates = []
+        if env_dir:
+            candidates.append(env_dir)
+        candidates.extend(
+            [
+                self.default_logs_dir,
+                os.path.join(os.path.expanduser("~"), ".ai_photographer_logs"),
+                "/tmp/ai_photographer_logs",
+            ]
+        )
+        for d in candidates:
+            try:
+                os.makedirs(d, exist_ok=True)
+                test = os.path.join(d, ".write_test")
+                with open(test, "a", encoding="utf-8"):
+                    pass
+                try:
+                    os.remove(test)
+                except Exception:
+                    pass
+                return os.path.abspath(d)
+            except Exception:
+                continue
+        return os.path.abspath("/tmp")
+
+    @staticmethod
+    def _normalize_log_name(name):
+        base = os.path.basename(str(name or "").strip()) or "main"
+        while base.lower().endswith(".log.log"):
+            base = base[:-4]
+        if not base.lower().endswith(".log"):
+            base += ".log"
+        return base
+
+    def _is_writable_path(self, full_path):
+        parent = os.path.dirname(full_path)
+        try:
+            os.makedirs(parent, exist_ok=True)
+            with open(full_path, "a", encoding="utf-8"):
+                pass
+            return True
+        except Exception:
+            return False
+
+    def _with_fallback(self, desired_path):
+        if self._is_writable_path(desired_path):
+            return os.path.abspath(desired_path)
+        fallback_path = os.path.join(self.fallback_log_dir, os.path.basename(desired_path))
+        if self._is_writable_path(fallback_path):
+            return os.path.abspath(fallback_path)
+        return os.path.abspath(desired_path)
+
+    def resolve_log_path(self, path):
+        """Resolve relative or absolute path to absolute, always under the active logs dir when relative."""
+        normalized_name = self._normalize_log_name(path)
+
+        if os.path.isabs(str(path)):
+            full_path = os.path.abspath(str(path))
+        else:
+            full_path = os.path.join(self.fallback_log_dir, normalized_name)
+
+        return self._with_fallback(full_path)
+
+
+    def construct_path(self, folder_name, file_name):
+        """Construct full path. Relative folders are centralized under the active logs dir."""
+        normalized_name = self._normalize_log_name(file_name)
+
+        if os.path.isabs(folder_name):
+            full_path = os.path.join(folder_name, normalized_name)
+        else:
+            full_path = os.path.join(self.fallback_log_dir, normalized_name)
+
+        return self._with_fallback(full_path)
+
+
+    def log_to_file(self, message, TypeLog):
+        level_map = {
+            "DEBUG": logging.DEBUG,
+            "INFO": logging.INFO,
+            "WARNING": logging.WARNING,
+            "ERROR": logging.ERROR,
+            "CRITICAL": logging.CRITICAL
+        }
+        log_level = level_map.get(TypeLog.upper(), logging.WARNING)
+        self.main_logger.log(log_level, message)
+
+
+    def LogEngine(self, folder_name, log_name):
+        """Set up a named logger and resolve the file path correctly."""
+        full_path = self.construct_path(folder_name, log_name)
+    
+        self.logger = logging.getLogger(log_name)
+        self.logger.setLevel(self.default_log_level)
+        self.logger.propagate = False  # Prevent printing to terminal
+
+        # Clear existing FileHandlers
+        for handler in self.logger.handlers[:]:
+            if isinstance(handler, logging.FileHandler):
+                self.logger.removeHandler(handler)
+
+        handler = logging.FileHandler(full_path)
+        handler.setFormatter(logging.Formatter(self.log_format))
+        handler.setLevel(self.default_log_level)
+        self.logger.addHandler(handler)
+        
+
+    def LogsMessages(self, message, message_type="info", folder_name=None, file_name=None):
+        if folder_name and file_name:
+            full_path = self.construct_path(folder_name, file_name)
+
+            temp_logger = logging.getLogger(f"{folder_name}_{file_name}")
+            temp_logger.setLevel(self.default_log_level)
+            temp_logger.propagate = False  # Prevent printing to terminal
+
+            if not any(isinstance(h, logging.FileHandler) and h.baseFilename == full_path
+                       for h in temp_logger.handlers):
+                handler = logging.FileHandler(full_path)
+                handler.setFormatter(logging.Formatter(self.log_format))
+                temp_logger.addHandler(handler)
+
+            getattr(temp_logger, message_type.lower(), temp_logger.warning)(message)
+        elif self.logger:
+            log_method = getattr(self.logger, message_type.lower(), self.logger.warning)
+            log_method(message)
+        else:
+            self.log_to_file(message, message_type.upper())
+
+    def print_and_log(self, message, message_type="info", folder_name=None, file_name=None):
+        self.LogsMessages(message, message_type, folder_name, file_name)
+        print(message)  
+
+
+
+
+
+# ==============================
+# Usage Example
+# ==============================
+if __name__ == "__main__":
+    logger = Logs()
+    logger.LogEngine("ExxxxampleLogger", "ExampleLogger.log")
+    logger.LogsMessages("This is a hidden message")
+    logger.print_and_log("This is a test message.", message_type="info")
+
+    # You can also directly specify folder and file for a log message
+    logger.print_and_log("Direct log to folder", message_type="info", folder_name="CustomLogs", file_name="event.log")
diff --git a/Core/__init__.py b/Core/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Core/audio_prompt_recorder.py b/Core/audio_prompt_recorder.py
new file mode 100644
index 0000000..9979347
--- /dev/null
+++ b/Core/audio_prompt_recorder.py
@@ -0,0 +1,403 @@
+from __future__ import annotations
+
+import asyncio
+import base64
+import inspect
+import json
+import os
+import shutil
+import subprocess
+import threading
+import time
+
+import pyaudio
+import websockets
+
+from Core import audio_prompts
+from Core import settings as config
+
+FORMAT = pyaudio.paInt16
+CHANNELS = 1
+RECEIVE_SAMPLE_RATE = 24000
+CHUNK_SIZE = 512
+MONITOR_CHUNK_SIZE = 1024
+MONITOR_TAIL_SEC = 0.20
+
+DEFAULT_SINK = "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo"
+DEFAULT_SOURCE = "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback"
+
+STRICT_REPLAY_SYSTEM_PROMPT = (
+    "You are Sanad (Bousandah), a wise and friendly Emirati assistant. "
+    "For this session, the user will provide text that you must speak exactly as written. "
+    "Do not translate it. Do not summarize it. Do not answer it. "
+    "Do not rephrase it into another dialect or style. "
+    "Do not add greetings, punctuation changes, or extra words. "
+    "Keep the same word order and language as the provided text. "
+    "Your job is only to speak the exact user text verbatim. "
+    "Speak only the user text. Do not add filler words. "
+    "Do not change tense, grammar, dialect, or wording."
+)
+
+
+def _env_sink() -> str:
+    return str(os.environ.get("SINK", DEFAULT_SINK) or DEFAULT_SINK).strip()
+
+
+def _env_source() -> str:
+    return str(os.environ.get("SOURCE", DEFAULT_SOURCE) or DEFAULT_SOURCE).strip()
+
+
+def _monitor_source() -> str:
+    override = str(os.environ.get("MONITOR_SOURCE", "") or "").strip()
+    return override or f"{_env_sink()}.monitor"
+
+
+def _build_verbatim_request_text(text: str) -> str:
+    return (
+        "Speak exactly the text inside the <verbatim> block.\n"
+        "Do not add or remove any words.\n"
+        "Do not translate or paraphrase.\n"
+        "Do not change the language or dialect.\n"
+        "Read only the content inside the tags.\n"
+        "<verbatim>\n"
+        f"{text}\n"
+        "</verbatim>"
+    )
+
+
+def _iter_input_devices(audio: pyaudio.PyAudio):
+    for index in range(audio.get_device_count()):
+        info = audio.get_device_info_by_index(index)
+        if int(info.get("maxInputChannels", 0)) > 0:
+            yield index, info
+
+
+def _find_preferred_input_device(audio: pyaudio.PyAudio):
+    for preferred_name in ("pulse", "default"):
+        hint = preferred_name.strip().lower()
+        exact = None
+        partial = None
+        for index, info in _iter_input_devices(audio):
+            name = str(info.get("name", "")).strip().lower()
+            if name == hint:
+                exact = (index, info)
+                break
+            if hint in name and partial is None:
+                partial = (index, info)
+        if exact is not None:
+            return exact
+        if partial is not None:
+            return partial
+    return None
+
+
+class _MonitorRecorder:
+    def __init__(self, audio: pyaudio.PyAudio, device_config: dict):
+        self.audio = audio
+        self.device_config = device_config
+        self.frames: list[bytes] = []
+        self._stop_event = threading.Event()
+        self._thread = None
+        self._stream = None
+        self._error = None
+
+    def start(self):
+        self._stream = self.audio.open(
+            format=FORMAT,
+            channels=self.device_config["channels"],
+            rate=self.device_config["rate"],
+            input=True,
+            input_device_index=self.device_config["index"],
+            frames_per_buffer=self.device_config["chunk_size"],
+        )
+        self._thread = threading.Thread(target=self._record_loop, daemon=True)
+        self._thread.start()
+        time.sleep(0.05)
+
+    def _record_loop(self):
+        while not self._stop_event.is_set():
+            try:
+                data = self._stream.read(
+                    self.device_config["chunk_size"],
+                    exception_on_overflow=False,
+                )
+                self.frames.append(data)
+            except Exception as exc:
+                if not self._stop_event.is_set():
+                    self._error = exc
+                break
+
+    def stop(self) -> bytes:
+        time.sleep(MONITOR_TAIL_SEC)
+        self._stop_event.set()
+        if self._stream is not None:
+            try:
+                self._stream.stop_stream()
+            except Exception:
+                pass
+            try:
+                self._stream.close()
+            except Exception:
+                pass
+        if self._thread is not None:
+            self._thread.join(timeout=1.0)
+        if self._error is not None:
+            raise RuntimeError(f"Speaker monitor capture failed: {self._error}")
+        return b"".join(self.frames)
+
+
+class _ParecMonitorRecorder:
+    def __init__(self, device_config: dict):
+        self.device_config = device_config
+        self.frames: list[bytes] = []
+        self._stop_event = threading.Event()
+        self._thread = None
+        self._proc = None
+        self._error = None
+
+    def start(self):
+        command = [
+            "parec",
+            f"--device={self.device_config['monitor_source']}",
+            "--format=s16le",
+            f"--rate={self.device_config['rate']}",
+            f"--channels={self.device_config['channels']}",
+        ]
+        self._proc = subprocess.Popen(
+            command,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.DEVNULL,
+        )
+        self._thread = threading.Thread(target=self._record_loop, daemon=True)
+        self._thread.start()
+        time.sleep(0.05)
+
+    def _record_loop(self):
+        if self._proc is None or self._proc.stdout is None:
+            self._error = RuntimeError("parec process did not start correctly.")
+            return
+        read_size = self.device_config["chunk_size"] * self.device_config["channels"] * 2
+        while not self._stop_event.is_set():
+            try:
+                data = self._proc.stdout.read(read_size)
+                if data:
+                    self.frames.append(data)
+                    continue
+                if self._proc.poll() is not None:
+                    break
+            except Exception as exc:
+                if not self._stop_event.is_set():
+                    self._error = exc
+                break
+
+    def stop(self) -> bytes:
+        time.sleep(MONITOR_TAIL_SEC)
+        self._stop_event.set()
+        if self._proc is not None and self._proc.poll() is None:
+            self._proc.terminate()
+            try:
+                self._proc.wait(timeout=1.0)
+            except subprocess.TimeoutExpired:
+                self._proc.kill()
+                try:
+                    self._proc.wait(timeout=1.0)
+                except subprocess.TimeoutExpired:
+                    pass
+        if self._thread is not None:
+            self._thread.join(timeout=1.0)
+        if self._error is not None:
+            raise RuntimeError(f"parec speaker monitor capture failed: {self._error}")
+        return b"".join(self.frames)
+
+
+class AudioPromptRecorderClient:
+    def __init__(self):
+        self.pya = pyaudio.PyAudio()
+        self.monitor_config = self._resolve_capture_device()
+
+    def close(self):
+        self.pya.terminate()
+
+    def _ws_connect_kwargs(self):
+        kwargs = {"max_size": None}
+        try:
+            sig = inspect.signature(websockets.connect)
+            if "extra_headers" in sig.parameters:
+                kwargs["extra_headers"] = {"Content-Type": "application/json"}
+            else:
+                kwargs["additional_headers"] = {"Content-Type": "application/json"}
+        except Exception:
+            kwargs["extra_headers"] = {"Content-Type": "application/json"}
+        return kwargs
+
+    def _build_monitor_config(self, device_index: int, info: dict) -> dict:
+        return {
+            "backend": "pyaudio",
+            "index": device_index,
+            "name": str(info.get("name", "unknown")),
+            "rate": int(info.get("defaultSampleRate", RECEIVE_SAMPLE_RATE)),
+            "channels": max(1, min(2, int(info.get("maxInputChannels", 1)))),
+            "chunk_size": MONITOR_CHUNK_SIZE,
+            "sink": _env_sink(),
+            "source": _env_source(),
+            "monitor_source": _monitor_source(),
+        }
+
+    def _set_default_source(self, source_name: str):
+        try:
+            subprocess.run(
+                ["pactl", "set-default-source", source_name],
+                check=True,
+                stdout=subprocess.DEVNULL,
+                stderr=subprocess.PIPE,
+                text=True,
+            )
+        except FileNotFoundError as exc:
+            raise RuntimeError("pactl is required but was not found.") from exc
+        except subprocess.CalledProcessError as exc:
+            stderr = (exc.stderr or "").strip()
+            raise RuntimeError(stderr or f"Failed to set default source to {source_name}.") from exc
+
+    def _resolve_capture_device(self) -> dict:
+        monitor_source = _monitor_source()
+        if shutil.which("parec"):
+            return {
+                "backend": "parec",
+                "name": monitor_source,
+                "rate": RECEIVE_SAMPLE_RATE,
+                "channels": CHANNELS,
+                "chunk_size": MONITOR_CHUNK_SIZE,
+                "sink": _env_sink(),
+                "source": _env_source(),
+                "monitor_source": monitor_source,
+            }
+        match = _find_preferred_input_device(self.pya)
+        if match is None:
+            raise RuntimeError("No suitable PulseAudio input device was found. Expected 'pulse' or 'default'.")
+        return self._build_monitor_config(*match)
+
+    async def generate_audio(self, text: str) -> bytes:
+        if not config.GEMINI_API_KEY:
+            raise RuntimeError("Gemini API key is missing in config.")
+
+        async with websockets.connect(config.URI, **self._ws_connect_kwargs()) as ws:
+            setup_msg = {
+                "setup": {
+                    "model": config.GEMINI_MODEL,
+                    "generationConfig": {
+                        "responseModalities": ["AUDIO"],
+                        "speechConfig": {
+                            "voiceConfig": {
+                                "prebuiltVoiceConfig": {"voiceName": config.VOICE_NAME}
+                            }
+                        },
+                    },
+                    "systemInstruction": {"parts": [{"text": STRICT_REPLAY_SYSTEM_PROMPT}]},
+                }
+            }
+            await ws.send(json.dumps(setup_msg))
+            await ws.recv()
+
+            request_msg = {
+                "client_content": {
+                    "turns": [
+                        {
+                            "role": "user",
+                            "parts": [{"text": _build_verbatim_request_text(text)}],
+                        }
+                    ],
+                    "turn_complete": True,
+                }
+            }
+            await ws.send(json.dumps(request_msg))
+
+            audio_chunks: list[bytes] = []
+            while True:
+                raw_msg = await ws.recv()
+                response = json.loads(raw_msg)
+                server_content = response.get("serverContent", {})
+                model_turn = server_content.get("modelTurn", {})
+
+                for part in model_turn.get("parts", []):
+                    inline_data = part.get("inlineData")
+                    if inline_data and inline_data.get("data"):
+                        audio_chunks.append(base64.b64decode(inline_data["data"]))
+
+                if server_content.get("turnComplete") or server_content.get("generationComplete"):
+                    break
+
+            if not audio_chunks:
+                raise RuntimeError("Gemini returned no audio for the provided text.")
+            return b"".join(audio_chunks)
+
+    def play_audio_and_capture(self, audio_bytes: bytes) -> bytes:
+        if self.monitor_config.get("backend") == "parec":
+            recorder = _ParecMonitorRecorder(self.monitor_config)
+        else:
+            recorder = _MonitorRecorder(self.pya, self.monitor_config)
+        stream = None
+        if self.monitor_config.get("backend") != "parec":
+            self._set_default_source(self.monitor_config["monitor_source"])
+        try:
+            stream = self.pya.open(
+                format=FORMAT,
+                channels=CHANNELS,
+                rate=RECEIVE_SAMPLE_RATE,
+                output=True,
+                frames_per_buffer=CHUNK_SIZE,
+            )
+            recorder.start()
+            for offset in range(0, len(audio_bytes), CHUNK_SIZE * 2):
+                stream.write(audio_bytes[offset: offset + (CHUNK_SIZE * 2)])
+        finally:
+            try:
+                if stream is not None:
+                    stream.stop_stream()
+            finally:
+                if stream is not None:
+                    stream.close()
+            try:
+                captured_audio = recorder.stop()
+            finally:
+                if self.monitor_config.get("backend") != "parec":
+                    self._set_default_source(self.monitor_config["source"])
+        return captured_audio
+
+    def sample_width(self) -> int:
+        return self.pya.get_sample_size(FORMAT)
+
+
+def record_prompt_from_text(key: str, text: str, filename: str = "") -> dict:
+    clean_key = audio_prompts._clean_key(key)  # type: ignore[attr-defined]
+    clean_text = str(text or "").strip()
+    if not clean_text:
+        raise ValueError("text is required")
+
+    client = AudioPromptRecorderClient()
+    try:
+        raw_audio = asyncio.run(client.generate_audio(clean_text))
+        speaker_audio = client.play_audio_and_capture(raw_audio)
+        result = audio_prompts.save_audio_prompt_bundle(
+            clean_key,
+            speaker_audio,
+            filename=filename or audio_prompts.prompt_filename(clean_key),
+            raw_data=raw_audio,
+            text=clean_text,
+            model=config.GEMINI_MODEL,
+            voice_name=config.VOICE_NAME,
+            replay_count=1,
+            speaker_rate=int(client.monitor_config["rate"]),
+            speaker_channels=int(client.monitor_config["channels"]),
+            raw_rate=RECEIVE_SAMPLE_RATE,
+            raw_channels=CHANNELS,
+            sample_width=client.sample_width(),
+            capture_device=str(client.monitor_config.get("name", "")),
+            sink=str(client.monitor_config.get("sink", "")),
+            source=str(client.monitor_config.get("source", "")),
+            monitor_source=str(client.monitor_config.get("monitor_source", "")),
+        )
+        result["text"] = clean_text
+        result["raw_path"] = str(audio_prompts.raw_prompt_path(clean_key))
+        return result
+    finally:
+        client.close()
diff --git a/Core/audio_prompts.py b/Core/audio_prompts.py
new file mode 100644
index 0000000..81fc3a8
--- /dev/null
+++ b/Core/audio_prompts.py
@@ -0,0 +1,370 @@
+from __future__ import annotations
+
+import json
+import re
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, List
+
+from Core import settings as config
+
+DEFAULT_PROMPT_TEXTS: Dict[str, str] = {
+    "welcome_single": "Hello, welcome. We will take a photo together. Would you like a photo?",
+    "welcome_group": "Hello everyone, welcome. We will take a photo together. Would your group like a photo?",
+    "welcome_returning": "Welcome back. Would you like another photo?",
+    "frame_single": "Great. Please stand with me in front of the camera, stay in the center, and look at the camera.",
+    "frame_group": "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera.",
+    "confirm_reminder": "Please say yes photo to continue, or no photo to cancel.",
+    "visitor_left": "No worries. I will wait here for the next visitor.",
+    "declined": "No problem. We can do it anytime.",
+    "confirm_timeout": "No problem. I will wait here. Come back anytime for a photo.",
+    "session_cancelled": "Okay. Session cancelled.",
+    "framing_timeout": "I still need a better frame. Please step in front of me and say yes photo when ready.",
+    "countdown_intro": "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.",
+    "count_3": "Three.",
+    "count_2": "Two.",
+    "count_1": "One.",
+    "smile": "Smile.",
+    "countdown_cancelled": "Countdown cancelled.",
+    "lost_from_frame": "I lost you from the frame. Let us try again.",
+    "retake_recommended": "Photo captured. I recommend a retake. Say yes photo to retake, or no photo to keep this one.",
+    "retake_yes": "Great. Let us retake. Hold your pose.",
+    "retake_limit": "Retake limit reached. Keeping the current photo.",
+    "photo_saved_thanks": "Thank you. Photo saved. Do not forget to check your photos.",
+}
+
+PROMPT_KEYS = tuple(DEFAULT_PROMPT_TEXTS.keys())
+RECORD_INDEX_PATH = config.AUDIO_PROMPT_RECORDS_FILE.resolve()
+LEGACY_RECORD_INDEX_PATH = (config.AUDIO_PROMPTS_DIR / "records.json").resolve()
+
+
+def _clean_key(key: str) -> str:
+    clean = str(key or "").strip()
+    if clean not in DEFAULT_PROMPT_TEXTS:
+        raise KeyError(f"unknown audio prompt key: {clean}")
+    return clean
+
+
+def _safe_filename(name: str) -> str:
+    cleaned = re.sub(r"[^A-Za-z0-9._-]+", "_", str(name or "").strip()).strip("._")
+    if not cleaned:
+        raise ValueError("invalid prompt filename")
+    if not cleaned.lower().endswith(".wav"):
+        raise ValueError("audio prompt files must be .wav")
+    return cleaned
+
+
+def _record_index_template() -> Dict[str, Any]:
+    return {
+        "created_by": "AI_Photographer.audio_prompts",
+        "last_updated": "",
+        "total_records": 0,
+        "records": [],
+    }
+
+
+def _format_timestamp(dt: datetime) -> str:
+    return dt.isoformat(timespec="seconds")
+
+
+def _audio_duration_seconds(audio_bytes: bytes, sample_rate: int, channels: int, sample_width: int) -> float:
+    frame_size = max(1, int(sample_width) * max(1, int(channels)))
+    rate = max(1, int(sample_rate))
+    return len(audio_bytes) / float(rate * frame_size)
+
+
+def _build_file_info(path: Path, audio_bytes: bytes, sample_rate: int, channels: int, sample_width: int) -> Dict[str, Any]:
+    size_bytes = int(path.stat().st_size) if path.exists() else int(len(audio_bytes))
+    return {
+        "path": _stored_project_path(path),
+        "name": path.name,
+        "size_bytes": size_bytes,
+        "size_mb": round(size_bytes / (1024 * 1024), 3),
+        "duration_seconds": round(_audio_duration_seconds(audio_bytes, sample_rate, channels, sample_width), 3),
+        "sample_rate": int(sample_rate),
+        "channels": int(channels),
+        "sample_width_bytes": int(sample_width),
+    }
+
+
+def _stored_project_path(path: Path) -> str:
+    resolved = Path(path).resolve()
+    try:
+        rel = resolved.relative_to(config.PROJECT_ROOT)
+        return f"{config.PROJECT_ROOT.name}/{rel.as_posix()}"
+    except Exception:
+        return str(resolved)
+
+
+def prompt_text(key: str) -> str:
+    return DEFAULT_PROMPT_TEXTS[_clean_key(key)]
+
+
+def prompt_filename(key: str) -> str:
+    return config.read_audio_prompt_filename(_clean_key(key))
+
+
+def prompt_path(key: str) -> Path:
+    return (config.AUDIO_PROMPTS_DIR / prompt_filename(key)).resolve()
+
+
+def raw_prompt_filename(key: str) -> str:
+    clean_key = _clean_key(key)
+    speaker = Path(prompt_filename(clean_key))
+    return f"{speaker.stem}_raw.wav"
+
+
+def raw_prompt_path(key: str) -> Path:
+    return (config.AUDIO_PROMPTS_DIR / raw_prompt_filename(key)).resolve()
+
+
+def prompt_exists(key: str) -> bool:
+    return prompt_path(key).exists()
+
+
+def load_record_index() -> Dict[str, Any]:
+    for candidate in (RECORD_INDEX_PATH, LEGACY_RECORD_INDEX_PATH):
+        if not candidate.exists():
+            continue
+        try:
+            payload = json.loads(candidate.read_text(encoding="utf-8"))
+            if not isinstance(payload, dict) or not isinstance(payload.get("records"), list):
+                raise ValueError("invalid record index structure")
+            payload.setdefault("created_by", "AI_Photographer.audio_prompts")
+            payload.setdefault("last_updated", "")
+            payload.setdefault("total_records", len(payload.get("records", [])))
+            return reconcile_record_index(payload)
+        except Exception:
+            continue
+    return _record_index_template()
+
+
+def reconcile_record_index(payload: Dict[str, Any]) -> Dict[str, Any]:
+    records = []
+    for entry in payload.get("records", []):
+        key = str(entry.get("record_name", "") or "").strip()
+        if key not in DEFAULT_PROMPT_TEXTS:
+            continue
+        speaker_path = prompt_path(key)
+        raw_path = raw_prompt_path(key)
+        if not speaker_path.exists():
+            continue
+
+        files = entry.setdefault("files", {})
+        speaker_info = files.get("speaker_recording")
+        if isinstance(speaker_info, dict):
+            speaker_info["path"] = _stored_project_path(speaker_path)
+            speaker_info["name"] = speaker_path.name
+
+        raw_info = files.get("gemini_raw_output")
+        if isinstance(raw_info, dict):
+            if raw_path.exists():
+                raw_info["path"] = _stored_project_path(raw_path)
+                raw_info["name"] = raw_path.name
+            else:
+                files.pop("gemini_raw_output", None)
+
+        records.append(entry)
+
+    payload["records"] = records
+    payload["total_records"] = len(records)
+    payload["last_updated"] = records[-1].get("timeline", {}).get("saved_at", "") if records else ""
+    return payload
+
+
+def save_record_index(payload: Dict[str, Any]) -> None:
+    config.AUDIO_PROMPTS_DIR.mkdir(parents=True, exist_ok=True)
+    normalized = reconcile_record_index(dict(payload))
+    RECORD_INDEX_PATH.write_text(json.dumps(normalized, ensure_ascii=False, indent=2), encoding="utf-8")
+
+
+def _record_entry_map() -> Dict[str, Dict[str, Any]]:
+    payload = load_record_index()
+    mapping: Dict[str, Dict[str, Any]] = {}
+    for entry in payload.get("records", []):
+        key = str(entry.get("record_name", "") or "").strip()
+        if key:
+            mapping[key] = entry
+    return mapping
+
+
+def upsert_record_entry(entry: Dict[str, Any]) -> None:
+    key = _clean_key(str(entry.get("record_name", "") or ""))
+    payload = load_record_index()
+    records = [item for item in payload.get("records", []) if str(item.get("record_name", "") or "").strip() != key]
+    records.append(entry)
+    payload["records"] = records
+    payload["total_records"] = len(records)
+    payload["last_updated"] = entry.get("timeline", {}).get("saved_at", "")
+    save_record_index(payload)
+
+
+def delete_record_entry(key: str) -> None:
+    clean_key = _clean_key(key)
+    payload = load_record_index()
+    payload["records"] = [item for item in payload.get("records", []) if str(item.get("record_name", "") or "").strip() != clean_key]
+    payload["total_records"] = len(payload["records"])
+    payload["last_updated"] = payload["records"][-1].get("timeline", {}).get("saved_at", "") if payload["records"] else ""
+    save_record_index(payload)
+
+
+def list_audio_prompts() -> List[dict]:
+    fallback_to_gemini = bool(config.read_audio_prompts_fallback_to_gemini())
+    record_map = _record_entry_map()
+    items: List[dict] = []
+    for key in PROMPT_KEYS:
+        path = prompt_path(key)
+        raw_path = raw_prompt_path(key)
+        exists = path.exists()
+        raw_exists = raw_path.exists()
+        st = path.stat() if exists else None
+        entry = record_map.get(key, {})
+        speaker_info = entry.get("files", {}).get("speaker_recording", {}) if isinstance(entry, dict) else {}
+        raw_info = entry.get("files", {}).get("gemini_raw_output", {}) if isinstance(entry, dict) else {}
+        timeline = entry.get("timeline", {}) if isinstance(entry, dict) else {}
+        items.append(
+            {
+                "key": key,
+                "text": prompt_text(key),
+                "filename": prompt_filename(key),
+                "exists": bool(exists),
+                "size": int(st.st_size) if st else 0,
+                "mtime": float(st.st_mtime) if st else 0.0,
+                "raw_filename": raw_path.name,
+                "raw_exists": bool(raw_exists),
+                "raw_size": int(raw_info.get("size_bytes", 0) or 0),
+                "replay_count": int(entry.get("replay_count", 0) or 0),
+                "saved_at": str(timeline.get("saved_at", "") or ""),
+                "speaker_duration_seconds": float(speaker_info.get("duration_seconds", 0.0) or 0.0),
+                "raw_duration_seconds": float(raw_info.get("duration_seconds", 0.0) or 0.0),
+                "record": entry,
+                "fallback_to_gemini": fallback_to_gemini,
+            }
+        )
+    return items
+
+
+def save_audio_prompt_bundle(
+    key: str,
+    speaker_data: bytes,
+    filename: str = "",
+    *,
+    raw_data: bytes | None = None,
+    text: str = "",
+    model: str = "",
+    voice_name: str = "",
+    replay_count: int = 1,
+    speaker_rate: int = 24000,
+    speaker_channels: int = 1,
+    raw_rate: int = 24000,
+    raw_channels: int = 1,
+    sample_width: int = 2,
+    capture_device: str = "",
+    sink: str = "",
+    source: str = "",
+    monitor_source: str = "",
+) -> dict:
+    clean_key = _clean_key(key)
+    safe_filename = _safe_filename(filename or prompt_filename(clean_key))
+    old_target = prompt_path(clean_key)
+    old_raw = raw_prompt_path(clean_key)
+    target = (config.AUDIO_PROMPTS_DIR / safe_filename).resolve()
+    target.parent.mkdir(parents=True, exist_ok=True)
+
+    if old_target.exists() and old_target != target:
+        try:
+            old_target.unlink()
+        except Exception:
+            pass
+
+    target.write_bytes(speaker_data)
+    config.write_audio_prompt_filename(clean_key, safe_filename)
+
+    raw_target = raw_prompt_path(clean_key)
+    if old_raw.exists() and old_raw != raw_target:
+        try:
+            old_raw.unlink()
+        except Exception:
+            pass
+    if raw_data:
+        raw_target.write_bytes(raw_data)
+    elif raw_target.exists():
+        try:
+            raw_target.unlink()
+        except Exception:
+            pass
+
+    now = datetime.now()
+    entry = {
+        "record_name": clean_key,
+        "text": str(text or prompt_text(clean_key)).strip(),
+        "model": str(model or config.GEMINI_MODEL),
+        "voice_name": str(voice_name or config.VOICE_NAME),
+        "replay_count": int(replay_count),
+        "audio_capture": {
+            "sink": str(sink or ""),
+            "monitor_source": str(monitor_source or ""),
+            "restored_microphone_source": str(source or ""),
+            "capture_device": str(capture_device or ""),
+        },
+        "timeline": {
+            "saved_at": _format_timestamp(now),
+        },
+        "files": {
+            "speaker_recording": _build_file_info(
+                target,
+                speaker_data,
+                speaker_rate,
+                speaker_channels,
+                sample_width,
+            ),
+        },
+    }
+    if raw_data:
+        entry["files"]["gemini_raw_output"] = _build_file_info(
+            raw_target,
+            raw_data,
+            raw_rate,
+            raw_channels,
+            sample_width,
+        )
+
+    upsert_record_entry(entry)
+    return {
+        "ok": True,
+        "key": clean_key,
+        "filename": target.name,
+        "raw_filename": raw_target.name if raw_data else "",
+        "path": str(target),
+        "record": entry,
+    }
+
+
+def save_audio_prompt(key: str, data: bytes, filename: str) -> dict:
+    return save_audio_prompt_bundle(key, data, filename=filename, text=prompt_text(key), replay_count=0)
+
+
+def delete_audio_prompt(key: str) -> dict:
+    clean_key = _clean_key(key)
+    target = prompt_path(clean_key)
+    raw_target = raw_prompt_path(clean_key)
+    if target.exists():
+        target.unlink()
+    if raw_target.exists():
+        raw_target.unlink()
+    delete_record_entry(clean_key)
+    return {
+        "ok": True,
+        "key": clean_key,
+        "filename": prompt_filename(clean_key),
+        "deleted": str(target),
+        "deleted_raw": str(raw_target),
+    }
+
+
+def read_audio_prompt_bytes(key: str) -> tuple[Path, bytes]:
+    clean_key = _clean_key(key)
+    target = prompt_path(clean_key)
+    if not target.exists():
+        raise FileNotFoundError(f"audio prompt not found for key: {clean_key}")
+    return target, target.read_bytes()
diff --git a/Core/direct_camera_service.py b/Core/direct_camera_service.py
new file mode 100644
index 0000000..cb54e3c
--- /dev/null
+++ b/Core/direct_camera_service.py
@@ -0,0 +1,1170 @@
+#!/usr/bin/env python3
+"""
+Direct camera service.
+
+Purpose:
+- Main camera backend for AI_Photographer.
+- Does not use teleimager streaming.
+- Opens the camera directly through RealSense SDK or OpenCV.
+- Saves captured images into the configured output folder.
+- Provides the web UI/API used for preview, capture, download, and delete.
+
+Run:
+  python3 Core/direct_camera_service.py
+
+Optional:
+  python3 Core/direct_camera_service.py --camera auto --port 8091
+  python3 Core/direct_camera_service.py --camera realsense --port 8091
+  python3 Core/direct_camera_service.py --camera /dev/video0 --port 8091
+  CAMERA_DEVICE=/dev/video2 python3 Core/direct_camera_service.py
+"""
+
+from __future__ import annotations
+
+import argparse
+from datetime import datetime
+import io
+import json
+import mimetypes
+import os
+import re
+import socket
+import threading
+import time
+import urllib.parse
+import zipfile
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+from typing import Optional, Union
+
+import cv2
+import numpy as np
+
+try:
+    import pyrealsense2 as rs  # type: ignore
+    _HAS_RS = True
+except Exception:
+    rs = None  # type: ignore
+    _HAS_RS = False
+
+
+BASE_DIR = Path(__file__).resolve().parent.parent
+DEFAULT_SAMPLES_DIR = BASE_DIR / "photos" / "samples"
+WEB_DIR = BASE_DIR / "Web"
+DIRECT_CAMERA_HTML = WEB_DIR / "direct_camera.html"
+DIRECT_CAMERA_CSS = WEB_DIR / "direct_camera.css"
+DIRECT_CAMERA_JS = WEB_DIR / "direct_camera.js"
+CONFIG_JSON = BASE_DIR / "Data" / "Settings" / "config.json"
+LEGACY_CONFIG_JSONS = (
+    BASE_DIR / "Data" / "config.json",
+    BASE_DIR / "Scripts" / "config.json",
+)
+DEFAULT_PREFERRED_REALSENSE_SERIAL = "243622071722"
+
+
+def safe_name(name: str) -> str:
+    return name.strip().replace("\\", "/").split("/")[-1]
+
+
+def build_ordered_datetime_name(out_dir: Path, prefix: str, ext: str) -> Path:
+    safe_prefix = re.sub(r"[^A-Za-z0-9_-]+", "_", (prefix or "").strip()).strip("_") or "photo"
+    safe_ext = (ext or "jpg").strip().lstrip(".") or "jpg"
+    order = sum(
+        1
+        for p in out_dir.iterdir()
+        if p.is_file() and p.suffix.lower() in (".jpg", ".jpeg", ".png", ".webp")
+    ) + 1
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    return out_dir / f"{order:04d}_{timestamp}_{safe_prefix}.{safe_ext}"
+
+
+def list_photos(folder: Path) -> list[dict]:
+    items = []
+    folder.mkdir(parents=True, exist_ok=True)
+    for p in sorted(folder.iterdir(), key=lambda x: x.stat().st_mtime, reverse=True):
+        if not p.is_file() or p.suffix.lower() not in (".jpg", ".jpeg", ".png", ".webp"):
+            continue
+        st = p.stat()
+        items.append({"name": p.name, "size": st.st_size, "mtime": st.st_mtime})
+    return items
+
+
+def get_local_ip() -> str:
+    try:
+        host_info = socket.gethostbyname_ex(socket.gethostname())
+        for ip in host_info[2]:
+            if ip and not ip.startswith("127."):
+                return ip
+    except Exception:
+        pass
+
+    for target in ("10.255.255.255", "192.168.1.1", "8.8.8.8"):
+        s = None
+        try:
+            s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+            s.settimeout(0.2)
+            s.connect((target, 80))
+            ip = s.getsockname()[0]
+            if ip:
+                return ip
+        except Exception:
+            pass
+        finally:
+            try:
+                if s is not None:
+                    s.close()
+            except Exception:
+                pass
+
+    try:
+        return socket.gethostbyname("localhost")
+    except Exception:
+        return "127.0.0.1"
+
+
+def list_video_devices() -> list[str]:
+    return [str(p) for p in sorted(Path("/dev").glob("video*"))]
+
+
+def list_video_device_info() -> list[dict]:
+    items = []
+    for devnode in sorted(Path("/dev").glob("video*")):
+        sysdir = Path("/sys/class/video4linux") / devnode.name
+        items.append(
+            {
+                "value": str(devnode),
+                "label": str(devnode),
+                "name": _read_text(sysdir / "name"),
+            }
+        )
+    return items
+
+
+def _read_text(path: Path) -> str:
+    try:
+        return path.read_text(encoding="utf-8", errors="ignore").strip()
+    except Exception:
+        return ""
+
+
+def list_realsense_video_devices() -> list[str]:
+    matches = []
+    for devnode in sorted(Path("/dev").glob("video*")):
+        sysdir = Path("/sys/class/video4linux") / devnode.name
+        name = _read_text(sysdir / "name").lower()
+        usb_dir = (sysdir / "device").resolve()
+        vendor = ""
+        for probe in [usb_dir, usb_dir.parent, usb_dir.parent.parent]:
+            if probe == probe.parent:
+                break
+            vendor = _read_text(probe / "idVendor")
+            if vendor:
+                break
+        if "realsense" in name and vendor.lower() in ("8086", "32902"):
+            matches.append(str(devnode))
+    return matches
+
+
+def list_realsense_serials() -> list[str]:
+    if not _HAS_RS:
+        return []
+    try:
+        ctx = rs.context()
+        devices = ctx.query_devices()
+        serials = []
+        for dev in devices:
+            try:
+                serials.append(str(dev.get_info(rs.camera_info.serial_number)))
+            except Exception:
+                continue
+        return serials
+    except Exception:
+        return []
+
+
+def list_realsense_devices() -> list[dict]:
+    if not _HAS_RS:
+        return []
+    items = []
+    try:
+        ctx = rs.context()
+        for dev in ctx.query_devices():
+            try:
+                name = str(dev.get_info(rs.camera_info.name))
+            except Exception:
+                name = "Intel RealSense"
+            try:
+                serial = str(dev.get_info(rs.camera_info.serial_number))
+            except Exception:
+                serial = ""
+            try:
+                usb_type = str(dev.get_info(rs.camera_info.usb_type_descriptor))
+            except Exception:
+                usb_type = ""
+            try:
+                physical_port = str(dev.get_info(rs.camera_info.physical_port))
+            except Exception:
+                physical_port = ""
+            items.append(
+                {
+                    "name": name,
+                    "serial": serial,
+                    "usb_type": usb_type,
+                    "physical_port": physical_port,
+                    "value": f"realsense:{serial}" if serial else "realsense",
+                    "label": f"{name} [{serial}]" if serial else name,
+                }
+            )
+    except Exception:
+        return []
+    return items
+
+
+def parse_realsense_source(source: Union[str, int, None]) -> Optional[str]:
+    if not isinstance(source, str):
+        return None
+    s = source.strip()
+    if s.lower().startswith("realsense:"):
+        serial = s.split(":", 1)[1].strip()
+        return serial or None
+    return None
+
+
+
+
+
+
+
+
+
+
+def read_teleimager_realsense_serial() -> str:
+    candidates = []
+    env_cfg = os.environ.get("TELEIMAGER_CONFIG", "").strip()
+    if env_cfg:
+        candidates.append(Path(env_cfg).expanduser())
+    home = Path.home()
+    script_dir = Path(__file__).resolve().parent
+    project_root = script_dir.parent
+    candidates.append(home / "teleimager" / "cam_config_server.yaml")
+    candidates.append(project_root.parent / "teleimager" / "cam_config_server.yaml")
+    candidates.append(script_dir / "cam_config_server.yaml")
+    candidates.append(home / "Robot-Unitree Main Folders" / "teleimager" / "cam_config_server.yaml")
+
+    for path in candidates:
+        try:
+            if not path.exists():
+                continue
+            text = path.read_text(encoding="utf-8", errors="ignore")
+            m = re.search(r"serial_number:\s*\"?([0-9A-Za-z_-]+)\"?", text)
+            if m:
+                return m.group(1).strip()
+        except Exception:
+            continue
+    return ""
+
+
+def read_config_preferred_realsense_serial() -> str:
+    for path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS):
+        try:
+            if not path.exists():
+                continue
+            raw = json.loads(path.read_text(encoding="utf-8"))
+            if not isinstance(raw, dict):
+                continue
+            camera_cfg = raw.get("camera")
+            if not isinstance(camera_cfg, dict):
+                continue
+            serial = str(camera_cfg.get("preferred_realsense_serial", "")).strip()
+            if serial:
+                return serial
+        except Exception:
+            continue
+    return ""
+
+
+def resolve_preferred_realsense_serial_snapshot() -> tuple[str, str, str]:
+    forced = os.environ.get("REALSENSE_SERIAL", "").strip()
+    env_preferred = os.environ.get("PREFERRED_REALSENSE_SERIAL", "").strip()
+    config_preferred = read_config_preferred_realsense_serial()
+    configured = read_teleimager_realsense_serial()
+
+    if forced:
+        preferred = forced
+    elif env_preferred:
+        preferred = env_preferred
+    elif config_preferred:
+        preferred = config_preferred
+    else:
+        preferred = DEFAULT_PREFERRED_REALSENSE_SERIAL
+
+    return preferred, config_preferred, configured
+
+
+def write_config_preferred_realsense_serial(serial: str) -> str:
+    raw = {}
+    for cfg_path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS):
+        try:
+            if cfg_path.exists():
+                loaded = json.loads(cfg_path.read_text(encoding="utf-8"))
+                if isinstance(loaded, dict):
+                    raw = loaded
+                    break
+        except Exception:
+            pass
+
+    camera_cfg = raw.get("camera")
+    if not isinstance(camera_cfg, dict):
+        camera_cfg = {}
+    camera_cfg["preferred_realsense_serial"] = str(serial or "").strip()
+    raw["camera"] = camera_cfg
+    CONFIG_JSON.parent.mkdir(parents=True, exist_ok=True)
+    CONFIG_JSON.write_text(json.dumps(raw, ensure_ascii=False, indent=2), encoding="utf-8")
+    return str(camera_cfg["preferred_realsense_serial"])
+
+
+
+
+
+
+
+
+
+
+class DirectCamera:
+    def __init__(
+        self,
+        source: Optional[Union[str, int]] = None,
+        width: int = 960,
+        height: int = 540,
+        fps: int = 15,
+        preview_quality: int = 60,
+    ):
+        self.source = self._resolve_source(source)
+        self.width = int(width)
+        self.height = int(height)
+        self.fps = int(fps)
+        self.preview_quality = int(preview_quality)
+
+        self._stop = threading.Event()
+        self._thread: Optional[threading.Thread] = None
+        self._cap = None
+        self._rs_pipeline = None
+        self._rs_align = None
+        self._lock = threading.Lock()
+        self._latest_frame = None
+        self._latest_jpeg: Optional[bytes] = None
+        self._last_error = ""
+        self._frame_ts = 0.0
+        self._camera_source_in_use: Optional[Union[str, int]] = None
+        self._backend = "opencv"
+        self._active_profile: Optional[str] = None
+        self._preferred_realsense_serial = ""
+        self._config_realsense_serial = ""
+        self._configured_realsense_serial = ""
+        self._realsense_serial = self._preferred_realsense_serial
+        self._reopen_after = 0.0
+        self._reopen_delay_sec = 2.0
+        self._consecutive_read_failures = 0
+        self._max_read_failures_before_reopen = int(os.environ.get("CAMERA_MAX_READ_FAILS", "20"))
+        self._refresh_realsense_preferences()
+
+    def _refresh_realsense_preferences(self):
+        preferred, config_preferred, configured = resolve_preferred_realsense_serial_snapshot()
+        self._preferred_realsense_serial = preferred
+        self._config_realsense_serial = config_preferred
+        self._configured_realsense_serial = configured
+        if not self._realsense_serial:
+            self._realsense_serial = preferred
+
+    def _resolve_source(self, source: Optional[Union[str, int]]) -> Union[str, int]:
+        if source is None:
+            env_device = os.environ.get("CAMERA_DEVICE", "").strip()
+            if env_device:
+                source = env_device
+            else:
+                source = os.environ.get("CAMERA_INDEX", "auto").strip() or "auto"
+
+        if isinstance(source, str):
+            s = source.strip()
+            if s.lower() == "auto":
+                return "auto"
+            if s.lower() in ("realsense", "rs"):
+                return "realsense"
+            if s.lower().startswith("realsense:"):
+                serial = s.split(":", 1)[1].strip()
+                return f"realsense:{serial}" if serial else "realsense"
+            try:
+                return int(s)
+            except ValueError:
+                return s
+        return int(source)
+
+    def _candidate_sources(self) -> list[Union[str, int]]:
+        src = self.source
+        out: list[Union[str, int]] = [src]
+
+        if src == "realsense" or (isinstance(src, str) and src.startswith("realsense:")):
+            for sp in list_realsense_video_devices():
+                if sp not in out:
+                    out.append(sp)
+            return out
+
+        if isinstance(src, str) and src.startswith("/dev/video"):
+            try:
+                idx = int(src.replace("/dev/video", ""))
+                out.append(idx)
+            except Exception:
+                pass
+
+        scan_env = os.environ.get("CAMERA_FALLBACK_SCAN", "").strip().lower()
+        if scan_env:
+            do_scan = scan_env not in ("0", "false", "no", "off")
+        else:
+            do_scan = src == "auto"
+        if src == "auto" or do_scan:
+            if _HAS_RS and "realsense" not in out:
+                out.append("realsense")
+            for p in sorted(Path("/dev").glob("video*")):
+                sp = str(p)
+                if sp not in out:
+                    out.append(sp)
+                try:
+                    idx = int(sp.replace("/dev/video", ""))
+                    if idx not in out:
+                        out.append(idx)
+                except Exception:
+                    pass
+            for idx in range(6):
+                if idx not in out:
+                    out.append(idx)
+        return out
+
+    def _open_capture(self, source: Union[str, int]):
+        if isinstance(source, str) and source.startswith("/dev/video"):
+            return cv2.VideoCapture(source, cv2.CAP_V4L2)
+        return cv2.VideoCapture(source)
+
+    def _looks_rgb(self, frame) -> bool:
+        return frame is not None and getattr(frame, "ndim", 0) == 3 and frame.shape[2] == 3
+
+    def _open_realsense(self):
+        if not _HAS_RS:
+            raise RuntimeError("pyrealsense2 not installed")
+        self._refresh_realsense_preferences()
+        profiles = [
+            (self.width, self.height, self.fps),
+            (640, 480, 30),
+            (640, 480, 15),
+            (1280, 720, 30),
+            (1280, 720, 15),
+            (848, 480, 30),
+            (848, 480, 15),
+        ]
+        available_serials = list_realsense_serials()
+        requested_serial = parse_realsense_source(self.source)
+        serial = ""
+        if requested_serial and requested_serial in available_serials:
+            serial = requested_serial
+        elif self._preferred_realsense_serial and self._preferred_realsense_serial in available_serials:
+            serial = self._preferred_realsense_serial
+        elif self._configured_realsense_serial and self._configured_realsense_serial in available_serials:
+            serial = self._configured_realsense_serial
+        elif self._realsense_serial and self._realsense_serial in available_serials:
+            serial = self._realsense_serial
+        elif available_serials:
+            serial = available_serials[0]
+
+        if serial:
+            self._realsense_serial = serial
+        tried = []
+        seen = set()
+        for w, h, fps in profiles:
+            key = (int(w), int(h), int(fps))
+            if key in seen:
+                continue
+            seen.add(key)
+            tried.append(f"{w}x{h}@{fps}")
+            pipe = rs.pipeline()
+            try:
+                cfg = rs.config()
+                if serial:
+                    cfg.enable_device(serial)
+                cfg.enable_stream(rs.stream.color, int(w), int(h), rs.format.bgr8, int(fps))
+                pipe.start(cfg)
+                self._rs_align = rs.align(rs.stream.color)
+                self._realsense_serial = serial or self._realsense_serial
+                self._active_profile = f"{w}x{h}@{fps}"
+                return pipe
+            except Exception:
+                try:
+                    pipe.stop()
+                except Exception:
+                    pass
+        serial_note = serial or "(auto)"
+        raise RuntimeError(f"RealSense color stream open failed. serial={serial_note} tried: {', '.join(tried)}")
+
+
+
+
+
+    def _configure_capture(self, cap):
+        try:
+            cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
+        except Exception:
+            pass
+        try:
+            cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*"MJPG"))
+        except Exception:
+            pass
+        cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
+        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
+        cap.set(cv2.CAP_PROP_FPS, self.fps)
+
+
+
+
+
+
+    def _close_locked(self):
+        if self._rs_pipeline is not None:
+            try:
+                self._rs_pipeline.stop()
+            except Exception:
+                pass
+        self._rs_pipeline = None
+        self._rs_align = None
+        if self._cap is not None:
+            try:
+                self._cap.release()
+            except Exception:
+                pass
+        self._cap = None
+        self._camera_source_in_use = None
+        self._backend = "opencv"
+        self._active_profile = None
+
+
+
+
+
+    def _read_frame_locked(self):
+        if self._rs_pipeline is not None:
+            frames = self._rs_pipeline.wait_for_frames(timeout_ms=1000)
+            if self._rs_align is not None:
+                frames = self._rs_align.process(frames)
+            color_frame = frames.get_color_frame()
+            if not color_frame:
+                return False, None
+            frame = np.asanyarray(color_frame.get_data())
+            if frame is None or frame.size == 0:
+                return False, None
+            return True, frame
+        if self._cap is None:
+            return False, None
+        return self._cap.read()
+
+    def _ensure_open_locked(self) -> bool:
+        now = time.time()
+        if self._rs_pipeline is not None:
+            return True
+        if self._cap is not None and self._cap.isOpened():
+            return True
+        if now < self._reopen_after:
+            return False
+
+        self._last_error = "Opening camera..."
+        self._close_locked()
+        tried = []
+        last_open_error = ""
+        for source in self._candidate_sources():
+            tried.append(str(source))
+            if source == "realsense":
+                pipe = None
+                try:
+                    pipe = self._open_realsense()
+                    frames = pipe.wait_for_frames(timeout_ms=1500)
+                    color_frame = frames.get_color_frame()
+                    if not color_frame:
+                        pipe.stop()
+                        continue
+                    frame = np.asanyarray(color_frame.get_data())
+                    if frame is None or frame.size == 0:
+                        pipe.stop()
+                        continue
+                    self._rs_pipeline = pipe
+                    self._backend = "realsense"
+                    self._camera_source_in_use = source
+                    self._last_error = ""
+                    self._consecutive_read_failures = 0
+                    self._latest_frame = frame.copy()
+                    return True
+                except Exception as e:
+                    last_open_error = str(e)
+                    self._last_error = str(e)
+                    try:
+                        if pipe is not None:
+                            pipe.stop()
+                    except Exception:
+                        pass
+                    continue
+            else:
+                cap = None
+                try:
+                    cap = self._open_capture(source)
+                except Exception:
+                    cap = None
+                if cap is None or not cap.isOpened():
+                    try:
+                        if cap is not None:
+                            cap.release()
+                    except Exception:
+                        pass
+                    continue
+
+                self._configure_capture(cap)
+
+                ok, frame = cap.read()
+                if not ok or frame is None:
+                    cap.release()
+                    continue
+                if self.source == "realsense" and not self._looks_rgb(frame):
+                    cap.release()
+                    continue
+
+                self._cap = cap
+                self._backend = "opencv"
+                self._camera_source_in_use = source
+                self._last_error = ""
+                self._consecutive_read_failures = 0
+                return True
+
+        self._last_error = last_open_error or f"Could not open camera. Tried: {', '.join(tried)}"
+        self._reopen_after = now + self._reopen_delay_sec
+        return False
+
+    def start(self):
+        if self._thread and self._thread.is_alive():
+            return
+        self._stop.clear()
+        self._thread = threading.Thread(target=self._run, daemon=True)
+        self._thread.start()
+
+    def stop(self):
+        self._stop.set()
+        if self._thread:
+            self._thread.join(timeout=1.0)
+        with self._lock:
+            self._close_locked()
+
+    def _run(self):
+        while not self._stop.is_set():
+            frame = None
+            frame_ts = 0.0
+            with self._lock:
+                if not self._ensure_open_locked():
+                    time.sleep(0.2)
+                    continue
+                try:
+                    ok, frame = self._read_frame_locked()
+                    if not ok or frame is None:
+                        self._consecutive_read_failures += 1
+                        self._last_error = f"Camera read failed ({self._consecutive_read_failures}/{self._max_read_failures_before_reopen})"
+                        if self._consecutive_read_failures < self._max_read_failures_before_reopen:
+                            time.sleep(0.05)
+                            continue
+                        self._close_locked()
+                        self._reopen_after = time.time() + self._reopen_delay_sec
+                        self._consecutive_read_failures = 0
+                        time.sleep(0.2)
+                        continue
+                    self._consecutive_read_failures = 0
+                    self._latest_frame = frame.copy()
+                    frame_ts = time.time()
+                except Exception as e:
+                    self._last_error = str(e)
+                    self._close_locked()
+                    self._reopen_after = time.time() + self._reopen_delay_sec
+                    self._consecutive_read_failures = 0
+                    frame = None
+
+            if frame is not None:
+                try:
+                    ok, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), self.preview_quality])
+                    if ok and jpg is not None:
+                        with self._lock:
+                            self._latest_jpeg = jpg.tobytes()
+                            self._frame_ts = frame_ts
+                except Exception:
+                    pass
+
+            time.sleep(max(0.02, 1.0 / max(self.fps, 1)))
+
+    def latest_jpeg(self) -> Optional[bytes]:
+        return self._latest_jpeg
+
+    def capture(self, out_dir: Path, prefix: str = "sample", ext: str = "jpg") -> Path:
+        out_dir.mkdir(parents=True, exist_ok=True)
+        if not self._lock.acquire(timeout=0.5):
+            raise RuntimeError("camera busy")
+        try:
+            if not self._ensure_open_locked():
+                raise RuntimeError(self._last_error or "camera unavailable")
+
+            frame = self._latest_frame
+            if frame is None:
+                ok, frame = self._read_frame_locked()
+                if not ok or frame is None:
+                    raise RuntimeError("camera read failed during capture")
+
+            ok, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 95])
+            if not ok or jpg is None:
+                raise RuntimeError("cv2.imencode failed")
+
+            out_path = build_ordered_datetime_name(out_dir, prefix, ext)
+            out_path.write_bytes(jpg.tobytes())
+            return out_path
+        finally:
+            self._lock.release()
+
+    def reconfigure(self, width: int, height: int, fps: int) -> dict:
+        width = int(width)
+        height = int(height)
+        fps = int(fps)
+        if width < 1 or height < 1 or fps < 1:
+            raise RuntimeError("width, height, and fps must be positive integers")
+
+        if not self._lock.acquire(timeout=1.0):
+            raise RuntimeError("camera busy")
+        try:
+            self.width = width
+            self.height = height
+            self.fps = fps
+            self._last_error = f"Reconfiguring camera to {width}x{height}@{fps}..."
+            self._latest_frame = None
+            self._latest_jpeg = None
+            self._frame_ts = 0.0
+            self._close_locked()
+            self._reopen_after = 0.0
+            self._consecutive_read_failures = 0
+        finally:
+            self._lock.release()
+
+        deadline = time.time() + 6.0
+        while time.time() < deadline and not self._stop.is_set():
+            status = self.status()
+            if status["ok"]:
+                return status
+            time.sleep(0.05)
+        return self.status()
+
+    def set_source(self, source: Union[str, int]) -> dict:
+        resolved = self._resolve_source(source)
+        if not self._lock.acquire(timeout=1.0):
+            raise RuntimeError("camera busy")
+        try:
+            self.source = resolved
+            self._last_error = f"Switching camera source to {resolved}..."
+            self._latest_frame = None
+            self._latest_jpeg = None
+            self._frame_ts = 0.0
+            self._close_locked()
+            self._reopen_after = 0.0
+            self._consecutive_read_failures = 0
+        finally:
+            self._lock.release()
+
+        deadline = time.time() + 6.0
+        while time.time() < deadline and not self._stop.is_set():
+            status = self.status()
+            if status["ok"]:
+                return status
+            time.sleep(0.05)
+        return self.status()
+
+    def set_preferred_realsense_serial(self, serial: str) -> dict:
+        value = str(serial or "").strip()
+        if not self._lock.acquire(timeout=1.0):
+            raise RuntimeError("camera busy")
+        try:
+            self._preferred_realsense_serial = value
+            self._config_realsense_serial = value
+            if self.source == "realsense":
+                self._last_error = f"Switching preferred RealSense to {value or '(auto)'}..."
+                self._latest_frame = None
+                self._latest_jpeg = None
+                self._frame_ts = 0.0
+                self._close_locked()
+                self._reopen_after = 0.0
+                self._consecutive_read_failures = 0
+        finally:
+            self._lock.release()
+
+        deadline = time.time() + 6.0
+        while time.time() < deadline and not self._stop.is_set():
+            status = self.status()
+            if status["ok"] or self.source != "realsense":
+                return status
+            time.sleep(0.05)
+        return self.status()
+
+    def status(self) -> dict:
+        self._refresh_realsense_preferences()
+        return {
+            "ok": bool(self._rs_pipeline is not None or (self._cap is not None and self._cap.isOpened())),
+            "requested_source": str(self.source),
+            "source": str(self._camera_source_in_use if self._camera_source_in_use is not None else self.source),
+            "backend": self._backend,
+            "profile": self._active_profile,
+            "requested_profile": f"{self.width}x{self.height}@{self.fps}",
+            "requested_width": self.width,
+            "requested_height": self.height,
+            "requested_fps": self.fps,
+            "preferred_realsense_serial": self._preferred_realsense_serial,
+            "config_realsense_serial": self._config_realsense_serial,
+            "configured_realsense_serial": self._configured_realsense_serial,
+            "realsense_serial": self._realsense_serial,
+            "last_error": self._last_error,
+            "frame_time": self._frame_ts,
+        }
+
+
+def static_file_response(path: Path) -> tuple[bytes, str]:
+    raw = path.read_bytes()
+    content_type, _ = mimetypes.guess_type(str(path))
+    return raw, content_type or "application/octet-stream"
+
+
+class SamplesHandler(BaseHTTPRequestHandler):
+    server_version = "DirectCameraSamples/1.0"
+
+    def _json(self, payload: dict, status: int = 200):
+        raw = json.dumps(payload, ensure_ascii=False).encode("utf-8")
+        self.send_response(status)
+        self.send_header("Content-Type", "application/json; charset=utf-8")
+        self.send_header("Content-Length", str(len(raw)))
+        self.send_header("Cache-Control", "no-store")
+        self.end_headers()
+        self.wfile.write(raw)
+
+    def _text(self, text: str, status: int = 200, content_type: str = "text/plain; charset=utf-8"):
+        raw = text.encode("utf-8")
+        self.send_response(status)
+        self.send_header("Content-Type", content_type)
+        self.send_header("Content-Length", str(len(raw)))
+        self.send_header("Cache-Control", "no-store")
+        self.end_headers()
+        self.wfile.write(raw)
+
+    def _binary(self, raw: bytes, status: int = 200, content_type: str = "application/octet-stream", cache_control: str = "no-store"):
+        self.send_response(status)
+        self.send_header("Content-Type", content_type)
+        self.send_header("Content-Length", str(len(raw)))
+        self.send_header("Cache-Control", cache_control)
+        self.end_headers()
+        self.wfile.write(raw)
+
+    def log_message(self, fmt: str, *args):
+        path = getattr(self, "path", "")
+        if path.startswith("/api/health") or path.startswith("/api/photos"):
+            return
+        print(f"HTTP {self.command} {path} -> {args[1]}")
+
+    def do_GET(self):
+        parsed = urllib.parse.urlparse(self.path)
+        path = parsed.path
+        q = urllib.parse.parse_qs(parsed.query)
+
+        if path == "/":
+            raw, content_type = static_file_response(DIRECT_CAMERA_HTML)
+            return self._binary(raw, content_type=f"{content_type}; charset=utf-8")
+
+        if path == "/static/direct_camera.css":
+            raw, content_type = static_file_response(DIRECT_CAMERA_CSS)
+            return self._binary(raw, content_type=content_type)
+
+        if path == "/static/direct_camera.js":
+            raw, content_type = static_file_response(DIRECT_CAMERA_JS)
+            return self._binary(raw, content_type=f"{content_type}; charset=utf-8")
+
+        if path == "/api/health":
+            return self._json(
+                {
+                    "ok": True,
+                    "camera": self.server.camera.status(),
+                    "samples_dir": str(self.server.samples_dir),
+                }
+            )
+
+        if path == "/api/cameras":
+            camera_status = self.server.camera.status()
+            realsense_devices = list_realsense_devices()
+            video_devices = list_video_device_info()
+            preferred_serial = str(camera_status.get("preferred_realsense_serial") or "").strip()
+            active_serial = str(camera_status.get("realsense_serial") or "").strip()
+
+            preferred_device = None
+            active_device = None
+            rs_items = []
+            for item in realsense_devices:
+                serial = str(item.get("serial") or "").strip()
+                is_preferred = bool(serial and serial == preferred_serial)
+                is_active = bool(serial and serial == active_serial)
+                if is_preferred:
+                    preferred_device = item
+                if is_active:
+                    active_device = item
+                label = str(item.get("label") or item.get("value") or "").strip()
+                tags = []
+                if is_preferred:
+                    tags.append("default")
+                if is_active:
+                    tags.append("live")
+                if tags:
+                    label = f"{label} ({', '.join(tags)})"
+                rs_items.append({**item, "kind": "realsense", "is_preferred": is_preferred, "is_active": is_active, "label": label})
+
+            generic_label = "Preferred RealSense"
+            if preferred_serial:
+                generic_label += f" [{preferred_serial}]"
+            generic_label += " (default)"
+
+            options = [{"value": "realsense", "label": generic_label, "kind": "realsense-default"}]
+            options.extend(rs_items)
+            options.extend({**item, "kind": "video"} for item in video_devices)
+            options.append({"value": "auto", "label": "Auto fallback", "kind": "auto"})
+            return self._json(
+                {
+                    "ok": True,
+                    "selected_source": str(self.server.camera.source),
+                    "active_source": str(camera_status.get("source") or self.server.camera.source),
+                    "preferred_realsense_serial": preferred_serial,
+                    "configured_realsense_serial": str(camera_status.get("configured_realsense_serial") or ""),
+                    "config_realsense_serial": str(camera_status.get("config_realsense_serial") or ""),
+                    "realsense_devices": rs_items,
+                    "video_devices": video_devices,
+                    "preferred_device": preferred_device,
+                    "active_device": active_device,
+                    "options": options,
+                }
+            )
+
+        if path == "/api/photos":
+            return self._json({"items": list_photos(self.server.samples_dir)})
+
+        if path == "/api/capture":
+            try:
+                prefix = ((q.get("prefix") or [self.server.capture_prefix])[0] or self.server.capture_prefix).strip() or self.server.capture_prefix
+                ext = ((q.get("ext") or [self.server.capture_ext])[0] or self.server.capture_ext).strip().lstrip(".") or self.server.capture_ext
+                saved = self.server.camera.capture(self.server.samples_dir, prefix=prefix, ext=ext)
+                return self._json({"ok": True, "name": saved.name, "path": str(saved)})
+            except Exception as e:
+                return self._json({"ok": False, "error": str(e)}, status=500)
+
+        if path == "/api/frame.jpg":
+            jpg = self.server.camera.latest_jpeg()
+            if jpg is None:
+                return self._text("camera not ready", status=503)
+            self.send_response(200)
+            self.send_header("Content-Type", "image/jpeg")
+            self.send_header("Content-Length", str(len(jpg)))
+            self.send_header("Cache-Control", "no-store")
+            self.end_headers()
+            self.wfile.write(jpg)
+            return
+
+        if path == "/api/set_resolution":
+            try:
+                width = int((q.get("width") or [""])[0])
+                height = int((q.get("height") or [""])[0])
+                fps = int((q.get("fps") or [""])[0])
+            except Exception:
+                return self._json({"ok": False, "error": "width, height, and fps are required integers"}, status=400)
+            try:
+                status = self.server.camera.reconfigure(width, height, fps)
+                return self._json({"ok": True, "camera": status})
+            except Exception as e:
+                return self._json({"ok": False, "error": str(e)}, status=500)
+
+        if path == "/api/set_camera":
+            source = (q.get("source") or [""])[0].strip()
+            if not source:
+                return self._json({"ok": False, "error": "missing source"}, status=400)
+            try:
+                status = self.server.camera.set_source(source)
+                return self._json({"ok": True, "camera": status})
+            except Exception as e:
+                return self._json({"ok": False, "error": str(e)}, status=500)
+
+        if path == "/api/set_preferred_camera":
+            serial = (q.get("serial") or [""])[0].strip()
+            try:
+                saved = write_config_preferred_realsense_serial(serial)
+                status = self.server.camera.set_preferred_realsense_serial(saved)
+                return self._json({"ok": True, "serial": saved, "camera": status})
+            except Exception as e:
+                return self._json({"ok": False, "error": str(e)}, status=500)
+
+        if path == "/api/delete":
+            name = safe_name((q.get("name") or [""])[0])
+            if not name:
+                return self._json({"ok": False, "error": "missing name"}, status=400)
+            p = (self.server.samples_dir / name).resolve()
+            if p.parent != self.server.samples_dir.resolve() or not p.exists():
+                return self._json({"ok": False, "error": "not found"}, status=404)
+            try:
+                p.unlink()
+                return self._json({"ok": True, "name": name})
+            except Exception as e:
+                return self._json({"ok": False, "error": str(e)}, status=500)
+
+        if path == "/api/download":
+            name = safe_name((q.get("name") or [""])[0])
+            if not name:
+                return self._text("missing name", status=400)
+            p = (self.server.samples_dir / name).resolve()
+            if p.parent != self.server.samples_dir.resolve() or not p.exists():
+                return self._text("not found", status=404)
+            data = p.read_bytes()
+            self.send_response(200)
+            self.send_header("Content-Type", "application/octet-stream")
+            self.send_header("Content-Length", str(len(data)))
+            self.send_header("Content-Disposition", f'attachment; filename="{p.name}"')
+            self.end_headers()
+            self.wfile.write(data)
+            return
+
+        if path == "/api/download_all.zip":
+            buf = io.BytesIO()
+            with zipfile.ZipFile(buf, "w", zipfile.ZIP_DEFLATED) as zf:
+                for item in list_photos(self.server.samples_dir):
+                    p = self.server.samples_dir / item["name"]
+                    zf.write(p, arcname=p.name)
+            raw = buf.getvalue()
+            self.send_response(200)
+            self.send_header("Content-Type", "application/zip")
+            self.send_header("Content-Length", str(len(raw)))
+            self.send_header("Content-Disposition", 'attachment; filename="samples.zip"')
+            self.end_headers()
+            self.wfile.write(raw)
+            return
+
+        if path.startswith("/samples/"):
+            name = safe_name(path[len("/samples/"):])
+            p = (self.server.samples_dir / name).resolve()
+            if p.parent != self.server.samples_dir.resolve() or not p.exists():
+                return self._text("not found", status=404)
+            data = p.read_bytes()
+            ext = p.suffix.lower()
+            ct = "image/jpeg" if ext in (".jpg", ".jpeg") else "image/png"
+            self.send_response(200)
+            self.send_header("Content-Type", ct)
+            self.send_header("Content-Length", str(len(data)))
+            self.send_header("Cache-Control", "no-store")
+            self.end_headers()
+            self.wfile.write(data)
+            return
+
+        if path == "/preview.mjpg":
+            self.send_response(200)
+            self.send_header("Age", "0")
+            self.send_header("Cache-Control", "no-cache, private")
+            self.send_header("Pragma", "no-cache")
+            self.send_header("Content-Type", "multipart/x-mixed-replace; boundary=frame")
+            self.end_headers()
+            try:
+                while True:
+                    jpg = self.server.camera.latest_jpeg()
+                    if jpg is None:
+                        time.sleep(0.05)
+                        continue
+                    self.wfile.write(b"--frame\r\n")
+                    self.wfile.write(b"Content-Type: image/jpeg\r\n")
+                    self.wfile.write(f"Content-Length: {len(jpg)}\r\n\r\n".encode("ascii"))
+                    self.wfile.write(jpg)
+                    self.wfile.write(b"\r\n")
+                    time.sleep(0.12)
+            except BrokenPipeError:
+                return
+            except ConnectionResetError:
+                return
+            except Exception:
+                return
+
+        return self._text("not found", status=404)
+
+
+class SamplesServer(ThreadingHTTPServer):
+    def __init__(
+        self,
+        addr,
+        handler_cls,
+        camera: DirectCamera,
+        samples_dir: Path,
+        capture_prefix: str = "sample",
+        capture_ext: str = "jpg",
+    ):
+        super().__init__(addr, handler_cls)
+        self.camera = camera
+        self.samples_dir = samples_dir
+        self.capture_prefix = capture_prefix
+        self.capture_ext = capture_ext
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="Standalone direct-camera samples server")
+    parser.add_argument("--host", default="0.0.0.0")
+    parser.add_argument("--port", type=int, default=int(os.environ.get("PORT", "8091")))
+    parser.add_argument("--camera", default=os.environ.get("CAMERA_DEVICE", os.environ.get("CAMERA_INDEX", "auto")))
+    parser.add_argument("--width", type=int, default=int(os.environ.get("FRAME_WIDTH", "960")))
+    parser.add_argument("--height", type=int, default=int(os.environ.get("FRAME_HEIGHT", "540")))
+    parser.add_argument("--fps", type=int, default=int(os.environ.get("FPS", "15")))
+    parser.add_argument("--samples-dir", default=os.environ.get("SAMPLES_DIR", str(DEFAULT_SAMPLES_DIR)))
+    parser.add_argument("--capture-prefix", default=os.environ.get("CAPTURE_PREFIX", "sample"))
+    parser.add_argument("--capture-ext", default=os.environ.get("CAPTURE_EXT", "jpg"))
+    return parser.parse_args()
+
+
+def main():
+    args = parse_args()
+    samples_dir = Path(args.samples_dir).expanduser().resolve()
+    samples_dir.mkdir(parents=True, exist_ok=True)
+
+    if str(args.camera).strip().lower() in ("realsense", "rs") and not _HAS_RS:
+        raise SystemExit(
+            "RealSense backend requested but pyrealsense2 is not installed in this environment. "
+            "Run this script from the teleimager conda env or install pyrealsense2 here."
+        )
+
+    camera = DirectCamera(source=args.camera, width=args.width, height=args.height, fps=args.fps)
+    camera.start()
+
+    server = SamplesServer(
+        (args.host, args.port),
+        SamplesHandler,
+        camera=camera,
+        samples_dir=samples_dir,
+        capture_prefix=str(args.capture_prefix).strip() or "sample",
+        capture_ext=str(args.capture_ext).strip().lstrip(".") or "jpg",
+    )
+    ip = get_local_ip()
+    print(f"Video devices: {', '.join(list_video_devices()) or '(none found)'}")
+    if _HAS_RS:
+        print(f"RealSense serials: {', '.join(list_realsense_serials()) or '(none found)'}")
+    print(f"Preferred RealSense serial: {camera._preferred_realsense_serial}")
+    print(f"Samples dir: {samples_dir}")
+    print(f"Camera source: {args.camera}")
+    print(f"Capture naming: prefix={server.capture_prefix} ext={server.capture_ext}")
+    print(f"Open: http://{ip}:{args.port}/")
+
+    try:
+        server.serve_forever()
+    except KeyboardInterrupt:
+        pass
+    finally:
+        server.shutdown()
+        camera.stop()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Core/error_events.py b/Core/error_events.py
new file mode 100644
index 0000000..d8f3450
--- /dev/null
+++ b/Core/error_events.py
@@ -0,0 +1,104 @@
+"""
+error_events.py
+
+Small structured error event sink:
+- In-memory counters per (source, stage)
+- JSONL event log (append-only)
+- JSON counters snapshot for quick dashboard/debug fetch
+"""
+
+from __future__ import annotations
+
+import json
+import threading
+import time
+from pathlib import Path
+from typing import Any, Dict
+
+try:
+    from Core import settings as config
+
+    _STATE_DIR = Path(config.APP_RUNTIME_DIR)
+    _LEGACY_STATE_DIR = Path(config.APP_DATA_DIR)
+except Exception:
+    _STATE_DIR = Path(__file__).resolve().parents[1] / "Data" / "Runtime"
+    _LEGACY_STATE_DIR = Path(__file__).resolve().parents[1] / "Data"
+
+_STATE_DIR.mkdir(parents=True, exist_ok=True)
+_COUNTERS_PATH = _STATE_DIR / "error_counters.json"
+_EVENTS_PATH = _STATE_DIR / "error_events.jsonl"
+_LEGACY_COUNTERS_PATH = _LEGACY_STATE_DIR / "error_counters.json"
+
+_LOCK = threading.Lock()
+_COUNTERS: Dict[str, int] = {}
+_LAST_EVENT_TS: Dict[str, float] = {}
+_MIN_INTERVAL_SEC = 0.75
+
+
+def _load_counters() -> Dict[str, int]:
+    for candidate in (_COUNTERS_PATH, _LEGACY_COUNTERS_PATH):
+        try:
+            if candidate.exists():
+                raw = json.loads(candidate.read_text(encoding="utf-8"))
+                if isinstance(raw, dict):
+                    out: Dict[str, int] = {}
+                    for k, v in raw.items():
+                        try:
+                            out[str(k)] = int(v)
+                        except Exception:
+                            continue
+                    return out
+        except Exception:
+            pass
+    return {}
+
+
+with _LOCK:
+    _COUNTERS.update(_load_counters())
+
+
+def record_error(source: str, stage: str, exc: Any = None, context: Dict[str, Any] | None = None) -> int:
+    """
+    Record one structured error event.
+    Returns current counter value for this error key.
+    """
+    now = time.time()
+    src = str(source or "unknown")
+    stg = str(stage or "unknown")
+    key = f"{src}:{stg}"
+    msg = "" if exc is None else str(exc)
+    payload = {
+        "time": now,
+        "source": src,
+        "stage": stg,
+        "message": msg,
+        "context": context or {},
+    }
+
+    with _LOCK:
+        count = _COUNTERS.get(key, 0) + 1
+        _COUNTERS[key] = count
+        payload["count"] = count
+
+        # Throttle repetitive event writes for the same key.
+        last = float(_LAST_EVENT_TS.get(key, 0.0))
+        should_write_event = (now - last) >= _MIN_INTERVAL_SEC
+        if should_write_event:
+            _LAST_EVENT_TS[key] = now
+            try:
+                with _EVENTS_PATH.open("a", encoding="utf-8") as f:
+                    f.write(json.dumps(payload, ensure_ascii=False) + "\n")
+            except Exception:
+                pass
+
+        try:
+            _COUNTERS_PATH.write_text(json.dumps(_COUNTERS, ensure_ascii=False, indent=2), encoding="utf-8")
+        except Exception:
+            pass
+
+        return count
+
+
+def get_error_counters() -> Dict[str, int]:
+    with _LOCK:
+        return dict(_COUNTERS)
diff --git a/Core/people_registry.py b/Core/people_registry.py
new file mode 100644
index 0000000..f0a74b7
--- /dev/null
+++ b/Core/people_registry.py
@@ -0,0 +1,456 @@
+from __future__ import annotations
+
+import json
+import math
+import shutil
+import time
+import zipfile
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, Optional
+
+import cv2
+import numpy as np
+
+from Core import settings as config
+
+
+PERSON_JSON = "person.json"
+FACE_REF_NAME = "face_ref.jpg"
+SCENE_REF_NAME = "scene_ref.jpg"
+CAPTURE_PREFIX = "capture_"
+SUPPORTED_IMAGE_EXTS = (".jpg", ".jpeg", ".png", ".webp")
+
+
+def people_dir() -> Path:
+    path = Path(config.PEOPLE_DIR).resolve()
+    path.mkdir(parents=True, exist_ok=True)
+    return path
+
+
+def _now_ts() -> float:
+    return time.time()
+
+
+def _fmt_date(ts: float) -> str:
+    return datetime.fromtimestamp(float(ts)).strftime("%Y-%m-%d")
+
+
+def _person_dirs() -> list[Path]:
+    root = people_dir()
+    return [p for p in sorted(root.iterdir()) if p.is_dir()]
+
+
+def _person_json_path(person_dir: Path) -> Path:
+    return person_dir / PERSON_JSON
+
+
+def _read_person(person_dir: Path) -> Optional[Dict[str, Any]]:
+    try:
+        raw = json.loads(_person_json_path(person_dir).read_text(encoding="utf-8"))
+        if not isinstance(raw, dict):
+            return None
+        return raw
+    except Exception:
+        return None
+
+
+def _write_person(person_dir: Path, data: Dict[str, Any]) -> None:
+    person_dir.mkdir(parents=True, exist_ok=True)
+    _person_json_path(person_dir).write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
+
+
+def _list_existing_sequences() -> list[int]:
+    out: list[int] = []
+    for person_dir in _person_dirs():
+        meta = _read_person(person_dir)
+        if not meta:
+            continue
+        try:
+            out.append(int(meta.get("sequence", 0)))
+        except Exception:
+            continue
+    return out
+
+
+def _next_sequence() -> int:
+    seqs = _list_existing_sequences()
+    return (max(seqs) if seqs else 0) + 1
+
+
+def _make_person_id(sequence: int, ts: float) -> str:
+    return f"guest_{int(sequence):04d}_{datetime.fromtimestamp(ts).strftime('%Y%m%d_%H%M%S')}"
+
+
+def _display_label(meta: Dict[str, Any]) -> str:
+    short_id = str(meta.get("short_id") or meta.get("person_id") or "guest").replace("_", " ")
+    created_date = str(meta.get("created_date") or "")
+    return f"{short_id} from {created_date}".strip()
+
+
+def _clip_box(box: Dict[str, Any], frame_shape: tuple[int, ...], pad_ratio: float = 0.18) -> Optional[tuple[int, int, int, int]]:
+    if not isinstance(box, dict):
+        return None
+    try:
+        h, w = frame_shape[:2]
+        x = float(box.get("x", 0.0))
+        y = float(box.get("y", 0.0))
+        bw = max(1.0, float(box.get("w", 0.0)))
+        bh = max(1.0, float(box.get("h", 0.0)))
+        pad_w = bw * float(pad_ratio)
+        pad_h = bh * float(pad_ratio)
+        x1 = max(0, int(math.floor(x - pad_w)))
+        y1 = max(0, int(math.floor(y - pad_h)))
+        x2 = min(w, int(math.ceil(x + bw + pad_w)))
+        y2 = min(h, int(math.ceil(y + bh + pad_h)))
+        if x2 <= x1 or y2 <= y1:
+            return None
+        return x1, y1, x2, y2
+    except Exception:
+        return None
+
+
+def detect_face_box(image_bgr: np.ndarray) -> Optional[Dict[str, int]]:
+    if image_bgr is None or getattr(image_bgr, "size", 0) == 0:
+        return None
+    try:
+        cascade = cv2.CascadeClassifier(str(Path(cv2.data.haarcascades) / "haarcascade_frontalface_default.xml"))
+        if cascade.empty():
+            return None
+        gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)
+        faces = cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(48, 48))
+        if len(faces) == 0:
+            return None
+        x, y, w, h = max(faces, key=lambda item: int(item[2]) * int(item[3]))
+        return {"x": int(x), "y": int(y), "w": int(w), "h": int(h)}
+    except Exception:
+        return None
+
+
+def _extract_face_crop(frame_bgr: np.ndarray, face_box: Dict[str, Any]) -> Optional[np.ndarray]:
+    clipped = _clip_box(face_box, frame_bgr.shape, pad_ratio=0.18)
+    if clipped is None:
+        return None
+    x1, y1, x2, y2 = clipped
+    crop = frame_bgr[y1:y2, x1:x2]
+    if crop is None or crop.size == 0:
+        return None
+    return crop.copy()
+
+
+def _extract_scene_crop(frame_bgr: np.ndarray, subject_box: Optional[Dict[str, Any]]) -> np.ndarray:
+    if frame_bgr is None or getattr(frame_bgr, "size", 0) == 0:
+        raise ValueError("empty frame")
+    if not subject_box:
+        return frame_bgr.copy()
+    clipped = _clip_box(subject_box, frame_bgr.shape, pad_ratio=0.28)
+    if clipped is None:
+        return frame_bgr.copy()
+    x1, y1, x2, y2 = clipped
+    crop = frame_bgr[y1:y2, x1:x2]
+    if crop is None or crop.size == 0:
+        return frame_bgr.copy()
+    return crop.copy()
+
+
+def _compute_embedding(face_bgr: np.ndarray) -> np.ndarray:
+    gray = cv2.cvtColor(face_bgr, cv2.COLOR_BGR2GRAY)
+    gray = cv2.resize(gray, (48, 48), interpolation=cv2.INTER_AREA)
+    gray = cv2.equalizeHist(gray)
+    vec = gray.astype(np.float32).reshape(-1)
+    vec -= float(vec.mean())
+    norm = float(np.linalg.norm(vec))
+    if norm <= 1e-6:
+        return vec
+    return vec / norm
+
+
+def _embedding_similarity(a: np.ndarray, b: np.ndarray) -> float:
+    if a.size == 0 or b.size == 0:
+        return 0.0
+    denom = float(np.linalg.norm(a) * np.linalg.norm(b))
+    if denom <= 1e-6:
+        return 0.0
+    return float(np.dot(a, b) / denom)
+
+
+def _load_embedding(meta: Dict[str, Any]) -> np.ndarray:
+    raw = meta.get("embedding") or []
+    try:
+        arr = np.asarray(raw, dtype=np.float32)
+    except Exception:
+        arr = np.asarray([], dtype=np.float32)
+    return arr
+
+
+def _save_image(path: Path, image_bgr: np.ndarray) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    cv2.imwrite(str(path), image_bgr)
+
+
+def _append_sample(person_dir: Path, meta: Dict[str, Any], face_bgr: np.ndarray, scene_bgr: np.ndarray, embedding: np.ndarray, source: str) -> Dict[str, Any]:
+    now = _now_ts()
+    sample_count = int(meta.get("sample_count", 0)) + 1
+    prev_embedding = _load_embedding(meta)
+    if prev_embedding.size and prev_embedding.shape == embedding.shape:
+        new_embedding = ((prev_embedding * float(sample_count - 1)) + embedding) / float(sample_count)
+        norm = float(np.linalg.norm(new_embedding))
+        if norm > 1e-6:
+            new_embedding = new_embedding / norm
+    else:
+        new_embedding = embedding
+
+    face_name = f"face_{sample_count:03d}.jpg"
+    scene_name = f"scene_{sample_count:03d}.jpg"
+    _save_image(person_dir / face_name, face_bgr)
+    _save_image(person_dir / scene_name, scene_bgr)
+
+    meta["sample_count"] = sample_count
+    meta["times_seen"] = int(meta.get("times_seen", 0)) + 1
+    meta["last_seen_at"] = now
+    meta["embedding"] = new_embedding.astype(float).tolist()
+    meta["last_source"] = str(source or "vision")
+    meta["face_images"] = sorted(
+        [p.name for p in person_dir.iterdir() if p.is_file() and p.name.startswith("face_") and p.suffix.lower() in SUPPORTED_IMAGE_EXTS]
+    )
+    meta["scene_images"] = sorted(
+        [p.name for p in person_dir.iterdir() if p.is_file() and p.name.startswith("scene_") and p.suffix.lower() in SUPPORTED_IMAGE_EXTS]
+    )
+    if not (person_dir / FACE_REF_NAME).exists():
+        _save_image(person_dir / FACE_REF_NAME, face_bgr)
+    if not (person_dir / SCENE_REF_NAME).exists():
+        _save_image(person_dir / SCENE_REF_NAME, scene_bgr)
+    _write_person(person_dir, meta)
+    return meta
+
+
+def _create_person(face_bgr: np.ndarray, scene_bgr: np.ndarray, embedding: np.ndarray, source: str) -> Dict[str, Any]:
+    now = _now_ts()
+    seq = _next_sequence()
+    person_id = _make_person_id(seq, now)
+    short_id = f"guest_{seq:04d}"
+    person_dir = people_dir() / person_id
+    _save_image(person_dir / FACE_REF_NAME, face_bgr)
+    _save_image(person_dir / SCENE_REF_NAME, scene_bgr)
+    meta = {
+        "person_id": person_id,
+        "short_id": short_id,
+        "display_name": f"{short_id} from {_fmt_date(now)}",
+        "sequence": seq,
+        "created_at": now,
+        "created_date": _fmt_date(now),
+        "last_seen_at": now,
+        "sample_count": 0,
+        "times_seen": 0,
+        "source": str(source or "vision"),
+        "last_source": str(source or "vision"),
+        "embedding": embedding.astype(float).tolist(),
+        "face_images": [],
+        "scene_images": [],
+        "captured_photos": [],
+    }
+    meta = _append_sample(person_dir, meta, face_bgr, scene_bgr, embedding, source=source)
+    meta["new_person"] = True
+    meta["known_person"] = False
+    meta["person_dir"] = str(person_dir)
+    meta["display_label"] = _display_label(meta)
+    return meta
+
+
+def recognize_or_enroll(frame_bgr: np.ndarray, face_box: Optional[Dict[str, Any]], subject_box: Optional[Dict[str, Any]] = None, threshold: Optional[float] = None, source: str = "vision") -> Dict[str, Any]:
+    if frame_bgr is None or getattr(frame_bgr, "size", 0) == 0:
+        return {"ok": False, "error": "empty frame"}
+    if face_box is None:
+        return {"ok": False, "error": "no face"}
+
+    try:
+        face_bgr = _extract_face_crop(frame_bgr, face_box)
+        if face_bgr is None:
+            return {"ok": False, "error": "invalid face crop"}
+        scene_bgr = _extract_scene_crop(frame_bgr, subject_box)
+        embedding = _compute_embedding(face_bgr)
+        if embedding.size == 0:
+            return {"ok": False, "error": "invalid embedding"}
+
+        match_threshold = float(threshold if threshold is not None else config.read_vision_face_recognition_threshold())
+        best_meta = None
+        best_dir = None
+        best_score = -1.0
+
+        for person_dir in _person_dirs():
+            meta = _read_person(person_dir)
+            if not meta:
+                continue
+            stored = _load_embedding(meta)
+            if stored.size == 0 or stored.shape != embedding.shape:
+                continue
+            score = _embedding_similarity(embedding, stored)
+            if score > best_score:
+                best_score = score
+                best_meta = meta
+                best_dir = person_dir
+
+        if best_meta is not None and best_dir is not None and best_score >= match_threshold:
+            best_meta = _append_sample(best_dir, best_meta, face_bgr, scene_bgr, embedding, source=source)
+            best_meta["ok"] = True
+            best_meta["known_person"] = True
+            best_meta["new_person"] = False
+            best_meta["match_score"] = float(best_score)
+            best_meta["display_label"] = _display_label(best_meta)
+            return best_meta
+
+        created = _create_person(face_bgr, scene_bgr, embedding, source=source)
+        created["ok"] = True
+        created["match_score"] = float(best_score if best_score >= 0.0 else 0.0)
+        return created
+    except Exception as e:
+        return {"ok": False, "error": str(e)}
+
+
+def _load_image_from_bytes(data: bytes) -> Optional[np.ndarray]:
+    if not data:
+        return None
+    arr = np.frombuffer(data, dtype=np.uint8)
+    image = cv2.imdecode(arr, cv2.IMREAD_COLOR)
+    return image
+
+
+def import_person_photo(data: bytes, filename: str = "", person_id: str = "") -> Dict[str, Any]:
+    image = _load_image_from_bytes(data)
+    if image is None:
+        return {"ok": False, "error": "invalid image"}
+    face_box = detect_face_box(image)
+    if face_box is None:
+        return {"ok": False, "error": "no face detected in uploaded image"}
+    person_id = str(person_id or "").strip()
+    if person_id:
+        person_dir = people_dir() / person_id
+        meta = _read_person(person_dir)
+        if not meta:
+            return {"ok": False, "error": "person not found"}
+        face_bgr = _extract_face_crop(image, face_box)
+        if face_bgr is None:
+            return {"ok": False, "error": "invalid face crop"}
+        scene_bgr = image.copy()
+        embedding = _compute_embedding(face_bgr)
+        meta = _append_sample(person_dir, meta, face_bgr, scene_bgr, embedding, source="upload")
+        meta["ok"] = True
+        meta["known_person"] = True
+        meta["new_person"] = False
+        meta["display_label"] = _display_label(meta)
+        return meta
+    return recognize_or_enroll(image, face_box, None, source="upload")
+
+
+def attach_captured_photo(person_id: str, photo_path: str | Path) -> bool:
+    person_id = str(person_id or "").strip()
+    if not person_id:
+        return False
+    person_dir = people_dir() / person_id
+    meta = _read_person(person_dir)
+    if not meta:
+        return False
+    src = Path(photo_path).expanduser()
+    if not src.exists() or not src.is_file():
+        return False
+    dst = person_dir / f"{CAPTURE_PREFIX}{src.name}"
+    try:
+        shutil.copy2(src, dst)
+        photos = meta.get("captured_photos") or []
+        if not isinstance(photos, list):
+            photos = []
+        if dst.name not in photos:
+            photos.append(dst.name)
+        meta["captured_photos"] = sorted(photos)
+        meta["last_seen_at"] = _now_ts()
+        _write_person(person_dir, meta)
+        return True
+    except Exception:
+        return False
+
+
+def list_people() -> list[Dict[str, Any]]:
+    items: list[Dict[str, Any]] = []
+    for person_dir in _person_dirs():
+        meta = _read_person(person_dir)
+        if not meta:
+            continue
+        face_thumb = person_dir / FACE_REF_NAME
+        scene_thumb = person_dir / SCENE_REF_NAME
+        items.append(
+            {
+                "person_id": str(meta.get("person_id") or person_dir.name),
+                "short_id": str(meta.get("short_id") or ""),
+                "display_name": str(meta.get("display_name") or _display_label(meta)),
+                "created_at": float(meta.get("created_at", 0.0) or 0.0),
+                "created_date": str(meta.get("created_date") or ""),
+                "last_seen_at": float(meta.get("last_seen_at", 0.0) or 0.0),
+                "sample_count": int(meta.get("sample_count", 0) or 0),
+                "times_seen": int(meta.get("times_seen", 0) or 0),
+                "source": str(meta.get("source") or meta.get("last_source") or ""),
+                "last_source": str(meta.get("last_source") or ""),
+                "face_thumb": face_thumb.name if face_thumb.exists() else "",
+                "scene_thumb": scene_thumb.name if scene_thumb.exists() else "",
+                "captured_photos": list(meta.get("captured_photos") or []),
+                "known": True,
+            }
+        )
+    items.sort(key=lambda item: float(item.get("last_seen_at", 0.0) or 0.0), reverse=True)
+    return items
+
+
+def get_person(person_id: str) -> Optional[Dict[str, Any]]:
+    person_dir = people_dir() / str(person_id or "").strip()
+    meta = _read_person(person_dir)
+    if not meta:
+        return None
+    meta["person_dir"] = str(person_dir)
+    meta["display_label"] = _display_label(meta)
+    return meta
+
+
+def read_person_image(person_id: str, kind: str = "face") -> Optional[tuple[bytes, str, str]]:
+    person_id = str(person_id or "").strip()
+    if not person_id:
+        return None
+    person_dir = people_dir() / person_id
+    if kind == "scene":
+        target = person_dir / SCENE_REF_NAME
+    else:
+        target = person_dir / FACE_REF_NAME
+    if not target.exists():
+        return None
+    data = target.read_bytes()
+    return data, "image/jpeg", target.name
+
+
+def delete_person(person_id: str) -> bool:
+    person_dir = people_dir() / str(person_id or "").strip()
+    if not person_dir.exists() or not person_dir.is_dir():
+        return False
+    shutil.rmtree(person_dir)
+    return True
+
+
+def reset_people() -> int:
+    count = 0
+    for person_dir in _person_dirs():
+        shutil.rmtree(person_dir)
+        count += 1
+    return count
+
+
+def export_person_zip(person_id: str, out_path: Path) -> Optional[Path]:
+    person_id = str(person_id or "").strip()
+    if not person_id:
+        return None
+    person_dir = people_dir() / person_id
+    if not person_dir.exists():
+        return None
+    out_path.parent.mkdir(parents=True, exist_ok=True)
+    with zipfile.ZipFile(out_path, "w", compression=zipfile.ZIP_DEFLATED) as zf:
+        for child in sorted(person_dir.rglob("*")):
+            if not child.is_file():
+                continue
+            zf.write(child, arcname=str(child.relative_to(person_dir.parent)))
+    return out_path
diff --git a/Core/settings.py b/Core/settings.py
new file mode 100644
index 0000000..43ea36a
--- /dev/null
+++ b/Core/settings.py
@@ -0,0 +1,1201 @@
+import copy
+import json
+import os
+from pathlib import Path
+from typing import Any, Dict
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+APP_DATA_DEFAULT = PROJECT_ROOT / "Data"
+CONFIG_JSON = APP_DATA_DEFAULT / "Settings" / "config.json"
+LEGACY_CONFIG_JSONS = (
+    APP_DATA_DEFAULT / "config.json",
+    PROJECT_ROOT / "Scripts" / "config.json",
+)
+LEGACY_CONFIG_JSON = LEGACY_CONFIG_JSONS[0]
+
+AUDIO_PROMPT_FILE_DEFAULTS: Dict[str, str] = {
+    "welcome_single": "welcome_single.wav",
+    "welcome_group": "welcome_group.wav",
+    "welcome_returning": "welcome_returning.wav",
+    "frame_single": "frame_single.wav",
+    "frame_group": "frame_group.wav",
+    "confirm_reminder": "confirm_reminder.wav",
+    "visitor_left": "visitor_left.wav",
+    "declined": "declined.wav",
+    "confirm_timeout": "confirm_timeout.wav",
+    "session_cancelled": "session_cancelled.wav",
+    "framing_timeout": "framing_timeout.wav",
+    "countdown_intro": "countdown_intro.wav",
+    "count_3": "count_3.wav",
+    "count_2": "count_2.wav",
+    "count_1": "count_1.wav",
+    "smile": "smile.wav",
+    "countdown_cancelled": "countdown_cancelled.wav",
+    "lost_from_frame": "lost_from_frame.wav",
+    "retake_recommended": "retake_recommended.wav",
+    "retake_yes": "retake_yes.wav",
+    "retake_limit": "retake_limit.wav",
+    "photo_saved_thanks": "photo_saved_thanks.wav",
+}
+
+_FALLBACK: Dict[str, Any] = {
+    "paths": {
+        "data_dir": "AI_Photographer/Data/G1",
+        "app_data_dir": "AI_Photographer/Data",
+        "app_settings_dir": "AI_Photographer/Data/Settings",
+        "app_scripts_dir": "AI_Photographer/Data/Scripts",
+        "app_runtime_dir": "AI_Photographer/Data/Runtime",
+        "app_notes_dir": "AI_Photographer/Data/Notes",
+        "audio_prompts_dir": "AI_Photographer/Data/Audio",
+        "audio_prompt_records_file": "AI_Photographer/Data/Settings/audio_prompt_records.json",
+        "scripts_dir": "AI_Photographer/Scripts",
+        "web_dir": "AI_Photographer/Web",
+        "photos_dir": "AI_Photographer/photos/Captures",
+        "people_dir": "AI_Photographer/photos/people",
+        "samples_dir": "AI_Photographer/photos/samples",
+        "replay_recordings_dir": "AI_Photographer/Data/G1",
+        "replay_recorder_script": "",
+        "home_file": "arm_home.jsonl",
+        "photo_phrases_file": "AI_Photographer/Data/Scripts/photo_command_ai.txt",
+        "sanad_script_file": "AI_Photographer/Data/Scripts/sanad_script.txt",
+        "runtime_health_file": "AI_Photographer/Data/Runtime/runtime_health.json",
+        "autonomous_state_file": "AI_Photographer/Data/Runtime/autonomous_state.json",
+        "upload_db": "AI_Photographer/Data/Runtime/upload_db.json",
+    },
+    "timing": {
+        "photo_total_sec": 10.0,
+        "photo_thanks_sec": 3.0,
+        "photo_delay_sec": 5.0,
+        "replay_capture_end_margin_sec": 0.25,
+        "loop_rate": 10.0,
+        "ai_query_interval": 1.0,
+    },
+    "server": {"photo_server_port": 8080},
+    "gemini": {
+        "api_key": "",
+        "mic_enabled": True,
+        "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+        "voice_name": "Charon",
+        "system_prompt_fallback": (
+            "You are Sanad (Bousandah), a friendly Emirati photographer assistant. "
+            "Speak in UAE dialect (Khaleeji). Be short, energetic, and helpful."
+        ),
+    },
+    "upload": {
+        "method": "http",
+        "url": "",
+        "s3_bucket": "",
+        "s3_region": "",
+        "s3_key": "",
+        "s3_secret": "",
+    },
+    "mode": {
+        "default_mode": "manual",
+        "current_mode": "manual",
+    },
+    "replay": {
+        "active_file": "photo_G3.jsonl",
+    },
+    "camera": {
+        "camera_index": 0,
+        "frame_width": 640,
+        "frame_height": 480,
+        "fps": 30,
+        "preferred_realsense_serial": "243622071722",
+    },
+    "vision": {
+        "detection_backend": "yolo",
+        "yolo_runtime": "ultralytics",
+        "yolo_ultralytics_device": "cpu",
+        "person_yolo_onnx": "",
+        "face_yolo_onnx": "",
+        "input_size": 640,
+        "person_class_id": 0,
+        "person_score_thresh": 0.35,
+        "face_score_thresh": 0.35,
+        "nms_iou_thresh": 0.45,
+        "group_min_people": 3,
+        "group_link_distance_px": 220.0,
+        "yolo_strict_required": True,
+        "gemini_context_hz": 8.0,
+        "gemini_context_silent": True,
+        "idle_voice_listen_enabled": True,
+        "hard_target_lock_enabled": True,
+        "retake_prompt_enabled": True,
+        "autonomous_greeting_replay_enabled": True,
+        "autonomous_greeting_replay_file": "right_hand_up.jsonl",
+        "autonomous_capture_replay_enabled": True,
+        "retake_max_per_session": 1,
+        "framing_headroom_min_ratio": 0.06,
+        "framing_headroom_max_ratio": 0.25,
+        "framing_eye_line_min_ratio": 0.28,
+        "framing_eye_line_max_ratio": 0.48,
+        "framing_retake_score_threshold": 0.68,
+        "face_recognition_enabled": True,
+        "face_recognition_threshold": 0.88,
+    },
+    "watchdog": {
+        "ws_initial_backoff_sec": 1.0,
+        "ws_max_backoff_sec": 20.0,
+        "component_restart_delay_sec": 1.0,
+        "camera_capture_retry_count": 2,
+        "camera_capture_retry_delay_sec": 0.8,
+    },
+    "audio_prompts": {
+        "mode": "audio",
+        "fallback_to_gemini": True,
+        "files": copy.deepcopy(AUDIO_PROMPT_FILE_DEFAULTS),
+    },
+}
+
+
+def _deep_merge(base: Dict[str, Any], override: Dict[str, Any]) -> Dict[str, Any]:
+    out = dict(base)
+    for k, v in override.items():
+        if isinstance(v, dict) and isinstance(out.get(k), dict):
+            out[k] = _deep_merge(out[k], v)
+        else:
+            out[k] = v
+    return out
+
+
+def _load_config() -> Dict[str, Any]:
+    for cfg_path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS):
+        if not cfg_path.exists():
+            continue
+        try:
+            raw = json.loads(cfg_path.read_text(encoding="utf-8"))
+            if isinstance(raw, dict):
+                return _deep_merge(_FALLBACK, raw)
+        except Exception:
+            pass
+    return _FALLBACK
+
+
+_CFG = _load_config()
+
+
+def _c(path: str, default: Any = None) -> Any:
+    cur: Any = _CFG
+    for part in path.split("."):
+        if not isinstance(cur, dict) or part not in cur:
+            return default
+        cur = cur[part]
+    return cur
+
+
+def _env(name: str, default: Any, cast):
+    val = os.environ.get(name)
+    if val is None or val == "":
+        return default
+    try:
+        return cast(val)
+    except Exception:
+        return default
+
+
+def _as_path(rel_or_abs: str) -> Path:
+    p = Path(str(rel_or_abs)).expanduser()
+    if not p.is_absolute():
+        parts = p.parts
+        if parts and parts[0] == PROJECT_ROOT.name:
+            p = (PROJECT_ROOT.parent / p).resolve()
+        else:
+            p = (PROJECT_ROOT / p).resolve()
+    return p
+
+
+# ==================================================
+# PATHS
+# ==================================================
+DATA_DIR = _as_path(_c("paths.data_dir", "Data/G1"))
+APP_DATA_DIR = _as_path(_c("paths.app_data_dir", "Data"))
+APP_SETTINGS_DIR = _as_path(_c("paths.app_settings_dir", "Data/Settings"))
+APP_SCRIPTS_DIR = _as_path(_c("paths.app_scripts_dir", "Data/Scripts"))
+APP_RUNTIME_DIR = _as_path(_c("paths.app_runtime_dir", "Data/Runtime"))
+APP_NOTES_DIR = _as_path(_c("paths.app_notes_dir", "Data/Notes"))
+AUDIO_PROMPTS_DIR = _as_path(
+    _c("paths.audio_prompts_dir", "AI_Photographer/Data/Audio")
+)
+AUDIO_PROMPT_RECORDS_FILE = _as_path(
+    _c(
+        "paths.audio_prompt_records_file",
+        "AI_Photographer/Data/Settings/audio_prompt_records.json",
+    )
+)
+SCRIPTS_DIR = _as_path(_c("paths.scripts_dir", "Scripts"))
+WEB_DIR = _as_path(_c("paths.web_dir", "Web"))
+PHOTOS_DIR = _as_path(_c("paths.photos_dir", "photos/Captures"))
+PEOPLE_DIR = _as_path(_c("paths.people_dir", "photos/people"))
+SAMPLES_DIR = _as_path(_c("paths.samples_dir", "photos/samples"))
+
+REPLAY_FILE = (DATA_DIR / str(_c("replay.active_file", "photo_G3.jsonl"))).resolve()
+REPLAY_RECORDINGS_DIR = _as_path(_c("paths.replay_recordings_dir", "Data/G1"))
+_REPLAY_RECORDER_SCRIPT_RAW = str(_c("paths.replay_recorder_script", "") or "").strip()
+REPLAY_RECORDER_SCRIPT = _as_path(_REPLAY_RECORDER_SCRIPT_RAW) if _REPLAY_RECORDER_SCRIPT_RAW else ""
+HOME_FILE = (DATA_DIR / str(_c("paths.home_file", "arm_home.jsonl"))).resolve()
+PHOTO_PHRASES_FILE = _as_path(_c("paths.photo_phrases_file", "Data/Scripts/photo_command_ai.txt"))
+SANAD_SCRIPT_FILE = _as_path(_c("paths.sanad_script_file", "Data/Scripts/sanad_script.txt"))
+RUNTIME_HEALTH_FILE = _as_path(_c("paths.runtime_health_file", "Data/Runtime/runtime_health.json"))
+AUTONOMOUS_STATE_FILE = _as_path(_c("paths.autonomous_state_file", "Data/Runtime/autonomous_state.json"))
+UPLOAD_DB = _as_path(_c("paths.upload_db", "Data/Runtime/upload_db.json"))
+
+# ==================================================
+# TIMING / PHOTOGRAPHER
+# ==================================================
+PHOTO_TOTAL_SEC = _env("PHOTO_TOTAL_SEC", float(_c("timing.photo_total_sec", 10.0)), float)
+PHOTO_THANKS_SEC = _env("PHOTO_THANKS_SEC", float(_c("timing.photo_thanks_sec", 3.0)), float)
+PHOTO_DELAY_SEC = _env("PHOTO_DELAY_SEC", float(_c("timing.photo_delay_sec", 5.0)), float)
+REPLAY_CAPTURE_END_MARGIN_SEC = _env(
+    "REPLAY_CAPTURE_END_MARGIN_SEC",
+    float(_c("timing.replay_capture_end_margin_sec", 0.25)),
+    float,
+)
+LOOP_RATE = _env("LOOP_RATE", float(_c("timing.loop_rate", 10.0)), float)
+AI_QUERY_INTERVAL = _env("AI_QUERY_INTERVAL", float(_c("timing.ai_query_interval", 1.0)), float)
+
+# ==================================================
+# PHOTO SERVER
+# ==================================================
+PHOTO_SERVER_PORT = _env("PHOTO_SERVER_PORT", int(_c("server.photo_server_port", 8080)), int)
+
+# ==================================================
+# GEMINI
+# ==================================================
+# Gemini key source: Data/Settings/config.json -> gemini.api_key
+GEMINI_API_KEY = str(_c("gemini.api_key", "")).strip()
+GEMINI_MODEL = _env("GEMINI_MODEL", str(_c("gemini.model", "models/gemini-2.5-flash-native-audio-preview-12-2025")).strip(), str).strip()
+VOICE_NAME = _env("VOICE_NAME", str(_c("gemini.voice_name", "Charon")).strip() or "Charon", str).strip() or "Charon"
+SYSTEM_PROMPT_FALLBACK = str(_c("gemini.system_prompt_fallback", _FALLBACK["gemini"]["system_prompt_fallback"]))
+
+# Keep alias for compatibility
+MODEL = GEMINI_MODEL
+URI = (
+    "wss://generativelanguage.googleapis.com/ws/"
+    "google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent"
+    f"?key={GEMINI_API_KEY}"
+)
+
+
+def validate_api_key(key: str) -> bool:
+    k = (key or "").strip()
+    if not k:
+        return False
+    if "your_" in k.lower() or "replace" in k.lower():
+        return False
+    return len(k) >= 20
+
+
+def load_system_prompt() -> str:
+    try:
+        if SANAD_SCRIPT_FILE.exists():
+            content = SANAD_SCRIPT_FILE.read_text(encoding="utf-8-sig").strip()
+            if content:
+                return content
+    except Exception:
+        pass
+    return SYSTEM_PROMPT_FALLBACK
+
+
+def read_gemini_mic_enabled() -> bool:
+    raw = _read_config_json_raw()
+    gemini_cfg = raw.get("gemini")
+    if not isinstance(gemini_cfg, dict):
+        gemini_cfg = {}
+    return _coerce_bool(gemini_cfg.get("mic_enabled", _FALLBACK["gemini"]["mic_enabled"]), True)
+
+
+def write_gemini_mic_enabled(enabled: Any) -> bool:
+    raw = _read_config_json_raw()
+    gemini_cfg = raw.get("gemini")
+    if not isinstance(gemini_cfg, dict):
+        gemini_cfg = {}
+    gemini_cfg["mic_enabled"] = _coerce_bool(enabled, bool(_FALLBACK["gemini"]["mic_enabled"]))
+    raw["gemini"] = gemini_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return bool(gemini_cfg["mic_enabled"])
+
+
+def read_camera_preferred_realsense_serial() -> str:
+    raw = _read_config_json_raw()
+    camera_cfg = raw.get("camera")
+    if not isinstance(camera_cfg, dict):
+        camera_cfg = {}
+    return str(camera_cfg.get("preferred_realsense_serial", _FALLBACK["camera"]["preferred_realsense_serial"]) or "").strip()
+
+
+def write_camera_preferred_realsense_serial(serial: Any) -> str:
+    raw = _read_config_json_raw()
+    camera_cfg = raw.get("camera")
+    if not isinstance(camera_cfg, dict):
+        camera_cfg = {}
+    camera_cfg["preferred_realsense_serial"] = str(serial or "").strip()
+    raw["camera"] = camera_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return str(camera_cfg["preferred_realsense_serial"])
+
+
+def resolve_replay_path(path_value: Any) -> Path:
+    p = Path(str(path_value or "").strip()).expanduser()
+    if not p.is_absolute():
+        p = (DATA_DIR / p).resolve()
+    return p
+
+
+def read_selected_replay_name() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_replay_block(raw)
+    replay_cfg = raw.get("replay", {})
+    value = str(replay_cfg.get("active_file", "") or "").strip()
+    if value:
+        return value.replace("\\", "/").lstrip("/")
+    try:
+        return str(REPLAY_FILE.resolve().relative_to(DATA_DIR)).replace("\\", "/")
+    except Exception:
+        return REPLAY_FILE.name
+
+
+def read_selected_replay_path() -> Path:
+    return resolve_replay_path(read_selected_replay_name())
+
+
+def write_selected_replay_name(name: Any) -> str:
+    global REPLAY_FILE
+    clean = str(name or "").strip().replace("\\", "/").lstrip("/")
+    raw = _read_config_json_raw()
+    raw = _ensure_replay_block(raw)
+    replay_cfg = raw.get("replay", {})
+    replay_cfg["active_file"] = clean
+    raw["replay"] = replay_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    try:
+        REPLAY_FILE = resolve_replay_path(clean)
+    except Exception:
+        pass
+    return clean
+
+
+# ==================================================
+# UPLOAD / CLOUD
+# ==================================================
+UPLOAD_METHOD = _env("UPLOAD_METHOD", str(_c("upload.method", "http")).strip(), str).strip()
+UPLOAD_URL = _env("UPLOAD_URL", str(_c("upload.url", "")).strip(), str).strip()
+UPLOAD_S3_BUCKET = _env("UPLOAD_S3_BUCKET", str(_c("upload.s3_bucket", "")).strip(), str).strip()
+UPLOAD_S3_REGION = _env("UPLOAD_S3_REGION", str(_c("upload.s3_region", "")).strip(), str).strip()
+UPLOAD_S3_KEY = _env("UPLOAD_S3_KEY", str(_c("upload.s3_key", "")).strip(), str).strip()
+UPLOAD_S3_SECRET = _env("UPLOAD_S3_SECRET", str(_c("upload.s3_secret", "")).strip(), str).strip()
+
+# ==================================================
+# MODE / CONTROL
+# ==================================================
+DEFAULT_MODE = _env("DEFAULT_MODE", str(_c("mode.default_mode", "manual")).strip(), str).strip() or "manual"
+if DEFAULT_MODE == "command":
+    DEFAULT_MODE = "ai"
+if DEFAULT_MODE not in ("manual", "ai"):
+    DEFAULT_MODE = "manual"
+
+try:
+    UPLOAD_DB.parent.mkdir(parents=True, exist_ok=True)
+except Exception:
+    pass
+
+for _dir in (
+    APP_DATA_DIR,
+    APP_SETTINGS_DIR,
+    APP_SCRIPTS_DIR,
+    APP_RUNTIME_DIR,
+    APP_NOTES_DIR,
+    AUDIO_PROMPTS_DIR,
+    AUDIO_PROMPT_RECORDS_FILE.parent,
+    PHOTOS_DIR,
+    PEOPLE_DIR,
+    SAMPLES_DIR,
+    REPLAY_RECORDINGS_DIR,
+):
+    try:
+        _dir.mkdir(parents=True, exist_ok=True)
+    except Exception:
+        pass
+
+
+def _read_config_json_raw() -> Dict[str, Any]:
+    for cfg_path in (CONFIG_JSON, *LEGACY_CONFIG_JSONS):
+        try:
+            if cfg_path.exists():
+                raw = json.loads(cfg_path.read_text(encoding="utf-8"))
+                if isinstance(raw, dict):
+                    return raw
+        except Exception:
+            pass
+    return {}
+
+
+def _write_config_json_raw(raw: Dict[str, Any]) -> None:
+    CONFIG_JSON.parent.mkdir(parents=True, exist_ok=True)
+    CONFIG_JSON.write_text(json.dumps(raw, ensure_ascii=False, indent=2), encoding="utf-8")
+
+
+def _coerce_mode(value: Any) -> str:
+    m = str(value or "").strip().lower()
+    if m == "command":
+        return "ai"
+    if m not in ("manual", "ai"):
+        return "manual"
+    return m
+
+
+def _coerce_bool(value: Any, default: bool = False) -> bool:
+    if isinstance(value, bool):
+        return value
+    if isinstance(value, (int, float)):
+        return bool(value)
+    if isinstance(value, str):
+        return value.strip().lower() in ("1", "true", "yes", "on", "y")
+    return bool(default)
+
+
+def _coerce_detection_backend(value: Any) -> str:
+    v = str(value or "").strip().lower()
+    if v in ("yolo", "normal"):
+        return v
+    return "yolo"
+
+
+def _coerce_audio_prompt_mode(value: Any) -> str:
+    v = str(value or "").strip().lower()
+    if v in ("audio", "gemini"):
+        return v
+    return "audio"
+
+
+def _coerce_yolo_runtime(value: Any) -> str:
+    v = str(value or "").strip().lower()
+    if v in ("ultralytics", "opencv"):
+        return v
+    return "ultralytics"
+
+
+def _coerce_int(value: Any, default: int, min_v: int | None = None, max_v: int | None = None) -> int:
+    try:
+        out = int(value)
+    except Exception:
+        out = int(default)
+    if min_v is not None:
+        out = max(min_v, out)
+    if max_v is not None:
+        out = min(max_v, out)
+    return out
+
+
+def _coerce_float(value: Any, default: float, min_v: float | None = None, max_v: float | None = None) -> float:
+    try:
+        out = float(value)
+    except Exception:
+        out = float(default)
+    if min_v is not None:
+        out = max(min_v, out)
+    if max_v is not None:
+        out = min(max_v, out)
+    return out
+
+
+def _ensure_mode_block(raw: Dict[str, Any]) -> Dict[str, Any]:
+    if not isinstance(raw, dict) or not raw:
+        raw = copy.deepcopy(_FALLBACK)
+    mode_cfg = raw.get("mode")
+    if not isinstance(mode_cfg, dict):
+        mode_cfg = {}
+    default_mode = _coerce_mode(mode_cfg.get("default_mode", DEFAULT_MODE))
+    current_mode = _coerce_mode(mode_cfg.get("current_mode", default_mode))
+    mode_cfg["default_mode"] = default_mode
+    mode_cfg["current_mode"] = current_mode
+    raw["mode"] = mode_cfg
+    return raw
+
+
+def _ensure_replay_block(raw: Dict[str, Any]) -> Dict[str, Any]:
+    if not isinstance(raw, dict) or not raw:
+        raw = copy.deepcopy(_FALLBACK)
+    replay_cfg = raw.get("replay")
+    if not isinstance(replay_cfg, dict):
+        replay_cfg = {}
+    active_file = str(replay_cfg.get("active_file", _FALLBACK["replay"]["active_file"]) or "").strip()
+    replay_cfg["active_file"] = active_file or str(_FALLBACK["replay"]["active_file"])
+    raw["replay"] = replay_cfg
+    return raw
+
+
+def _ensure_vision_block(raw: Dict[str, Any]) -> Dict[str, Any]:
+    if not isinstance(raw, dict) or not raw:
+        raw = copy.deepcopy(_FALLBACK)
+    vision_cfg = raw.get("vision")
+    if not isinstance(vision_cfg, dict):
+        vision_cfg = {}
+    vision_cfg["detection_backend"] = _coerce_detection_backend(
+        vision_cfg.get("detection_backend", _FALLBACK["vision"]["detection_backend"])
+    )
+    vision_cfg["yolo_runtime"] = _coerce_yolo_runtime(
+        vision_cfg.get("yolo_runtime", _FALLBACK["vision"]["yolo_runtime"])
+    )
+    dev = str(vision_cfg.get("yolo_ultralytics_device", _FALLBACK["vision"]["yolo_ultralytics_device"]) or "").strip()
+    vision_cfg["yolo_ultralytics_device"] = dev or "cpu"
+    try:
+        group_min = int(vision_cfg.get("group_min_people", _FALLBACK["vision"]["group_min_people"]))
+    except Exception:
+        group_min = int(_FALLBACK["vision"]["group_min_people"])
+    vision_cfg["group_min_people"] = max(2, group_min)
+
+    vision_cfg["yolo_strict_required"] = _coerce_bool(
+        vision_cfg.get("yolo_strict_required", _FALLBACK["vision"]["yolo_strict_required"]),
+        bool(_FALLBACK["vision"]["yolo_strict_required"]),
+    )
+
+    try:
+        hz = float(vision_cfg.get("gemini_context_hz", _FALLBACK["vision"]["gemini_context_hz"]))
+    except Exception:
+        hz = float(_FALLBACK["vision"]["gemini_context_hz"])
+    vision_cfg["gemini_context_hz"] = max(0.5, min(30.0, hz))
+
+    vision_cfg["gemini_context_silent"] = _coerce_bool(
+        vision_cfg.get("gemini_context_silent", _FALLBACK["vision"]["gemini_context_silent"]),
+        bool(_FALLBACK["vision"]["gemini_context_silent"]),
+    )
+    vision_cfg["idle_voice_listen_enabled"] = _coerce_bool(
+        vision_cfg.get("idle_voice_listen_enabled", _FALLBACK["vision"]["idle_voice_listen_enabled"]),
+        bool(_FALLBACK["vision"]["idle_voice_listen_enabled"]),
+    )
+
+    vision_cfg["hard_target_lock_enabled"] = _coerce_bool(
+        vision_cfg.get("hard_target_lock_enabled", _FALLBACK["vision"]["hard_target_lock_enabled"]),
+        bool(_FALLBACK["vision"]["hard_target_lock_enabled"]),
+    )
+    vision_cfg["retake_prompt_enabled"] = _coerce_bool(
+        vision_cfg.get("retake_prompt_enabled", _FALLBACK["vision"]["retake_prompt_enabled"]),
+        bool(_FALLBACK["vision"]["retake_prompt_enabled"]),
+    )
+    vision_cfg["autonomous_greeting_replay_enabled"] = _coerce_bool(
+        vision_cfg.get("autonomous_greeting_replay_enabled", _FALLBACK["vision"]["autonomous_greeting_replay_enabled"]),
+        bool(_FALLBACK["vision"]["autonomous_greeting_replay_enabled"]),
+    )
+    greet_replay_file = str(
+        vision_cfg.get("autonomous_greeting_replay_file", _FALLBACK["vision"]["autonomous_greeting_replay_file"]) or ""
+    ).strip()
+    vision_cfg["autonomous_greeting_replay_file"] = (
+        greet_replay_file or str(_FALLBACK["vision"]["autonomous_greeting_replay_file"])
+    )
+    vision_cfg["autonomous_capture_replay_enabled"] = _coerce_bool(
+        vision_cfg.get("autonomous_capture_replay_enabled", _FALLBACK["vision"]["autonomous_capture_replay_enabled"]),
+        bool(_FALLBACK["vision"]["autonomous_capture_replay_enabled"]),
+    )
+    vision_cfg["retake_max_per_session"] = _coerce_int(
+        vision_cfg.get("retake_max_per_session", _FALLBACK["vision"]["retake_max_per_session"]),
+        int(_FALLBACK["vision"]["retake_max_per_session"]),
+        min_v=0,
+        max_v=5,
+    )
+    vision_cfg["framing_headroom_min_ratio"] = _coerce_float(
+        vision_cfg.get("framing_headroom_min_ratio", _FALLBACK["vision"]["framing_headroom_min_ratio"]),
+        float(_FALLBACK["vision"]["framing_headroom_min_ratio"]),
+        min_v=0.0,
+        max_v=0.8,
+    )
+    vision_cfg["framing_headroom_max_ratio"] = _coerce_float(
+        vision_cfg.get("framing_headroom_max_ratio", _FALLBACK["vision"]["framing_headroom_max_ratio"]),
+        float(_FALLBACK["vision"]["framing_headroom_max_ratio"]),
+        min_v=0.0,
+        max_v=0.95,
+    )
+    if vision_cfg["framing_headroom_max_ratio"] <= vision_cfg["framing_headroom_min_ratio"]:
+        vision_cfg["framing_headroom_max_ratio"] = min(0.95, vision_cfg["framing_headroom_min_ratio"] + 0.05)
+
+    vision_cfg["framing_eye_line_min_ratio"] = _coerce_float(
+        vision_cfg.get("framing_eye_line_min_ratio", _FALLBACK["vision"]["framing_eye_line_min_ratio"]),
+        float(_FALLBACK["vision"]["framing_eye_line_min_ratio"]),
+        min_v=0.0,
+        max_v=0.9,
+    )
+    vision_cfg["framing_eye_line_max_ratio"] = _coerce_float(
+        vision_cfg.get("framing_eye_line_max_ratio", _FALLBACK["vision"]["framing_eye_line_max_ratio"]),
+        float(_FALLBACK["vision"]["framing_eye_line_max_ratio"]),
+        min_v=0.05,
+        max_v=1.0,
+    )
+    if vision_cfg["framing_eye_line_max_ratio"] <= vision_cfg["framing_eye_line_min_ratio"]:
+        vision_cfg["framing_eye_line_max_ratio"] = min(1.0, vision_cfg["framing_eye_line_min_ratio"] + 0.05)
+
+    vision_cfg["framing_retake_score_threshold"] = _coerce_float(
+        vision_cfg.get("framing_retake_score_threshold", _FALLBACK["vision"]["framing_retake_score_threshold"]),
+        float(_FALLBACK["vision"]["framing_retake_score_threshold"]),
+        min_v=0.0,
+        max_v=1.0,
+    )
+    vision_cfg["face_recognition_enabled"] = _coerce_bool(
+        vision_cfg.get("face_recognition_enabled", _FALLBACK["vision"]["face_recognition_enabled"]),
+        bool(_FALLBACK["vision"]["face_recognition_enabled"]),
+    )
+    vision_cfg["face_recognition_threshold"] = _coerce_float(
+        vision_cfg.get("face_recognition_threshold", _FALLBACK["vision"]["face_recognition_threshold"]),
+        float(_FALLBACK["vision"]["face_recognition_threshold"]),
+        min_v=0.5,
+        max_v=0.995,
+    )
+    raw["vision"] = vision_cfg
+    return raw
+
+
+def _ensure_watchdog_block(raw: Dict[str, Any]) -> Dict[str, Any]:
+    if not isinstance(raw, dict) or not raw:
+        raw = copy.deepcopy(_FALLBACK)
+    wd_cfg = raw.get("watchdog")
+    if not isinstance(wd_cfg, dict):
+        wd_cfg = {}
+
+    wd_cfg["ws_initial_backoff_sec"] = _coerce_float(
+        wd_cfg.get("ws_initial_backoff_sec", _FALLBACK["watchdog"]["ws_initial_backoff_sec"]),
+        float(_FALLBACK["watchdog"]["ws_initial_backoff_sec"]),
+        min_v=0.1,
+        max_v=60.0,
+    )
+    wd_cfg["ws_max_backoff_sec"] = _coerce_float(
+        wd_cfg.get("ws_max_backoff_sec", _FALLBACK["watchdog"]["ws_max_backoff_sec"]),
+        float(_FALLBACK["watchdog"]["ws_max_backoff_sec"]),
+        min_v=0.5,
+        max_v=300.0,
+    )
+    if wd_cfg["ws_max_backoff_sec"] < wd_cfg["ws_initial_backoff_sec"]:
+        wd_cfg["ws_max_backoff_sec"] = wd_cfg["ws_initial_backoff_sec"]
+
+    wd_cfg["component_restart_delay_sec"] = _coerce_float(
+        wd_cfg.get("component_restart_delay_sec", _FALLBACK["watchdog"]["component_restart_delay_sec"]),
+        float(_FALLBACK["watchdog"]["component_restart_delay_sec"]),
+        min_v=0.1,
+        max_v=20.0,
+    )
+    wd_cfg["camera_capture_retry_count"] = _coerce_int(
+        wd_cfg.get("camera_capture_retry_count", _FALLBACK["watchdog"]["camera_capture_retry_count"]),
+        int(_FALLBACK["watchdog"]["camera_capture_retry_count"]),
+        min_v=0,
+        max_v=10,
+    )
+    wd_cfg["camera_capture_retry_delay_sec"] = _coerce_float(
+        wd_cfg.get("camera_capture_retry_delay_sec", _FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]),
+        float(_FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]),
+        min_v=0.0,
+        max_v=30.0,
+    )
+
+    raw["watchdog"] = wd_cfg
+    return raw
+
+
+def _ensure_audio_prompts_block(raw: Dict[str, Any]) -> Dict[str, Any]:
+    if not isinstance(raw, dict) or not raw:
+        raw = copy.deepcopy(_FALLBACK)
+    prompt_cfg = raw.get("audio_prompts")
+    if not isinstance(prompt_cfg, dict):
+        prompt_cfg = {}
+
+    prompt_cfg["mode"] = _coerce_audio_prompt_mode(
+        prompt_cfg.get("mode", _FALLBACK["audio_prompts"]["mode"])
+    )
+
+    prompt_cfg["fallback_to_gemini"] = _coerce_bool(
+        prompt_cfg.get("fallback_to_gemini", _FALLBACK["audio_prompts"]["fallback_to_gemini"]),
+        bool(_FALLBACK["audio_prompts"]["fallback_to_gemini"]),
+    )
+
+    files_cfg = prompt_cfg.get("files")
+    if not isinstance(files_cfg, dict):
+        files_cfg = {}
+
+    normalized_files: Dict[str, str] = {}
+    for key, default_name in AUDIO_PROMPT_FILE_DEFAULTS.items():
+        clean = str(files_cfg.get(key, default_name) or "").strip().replace("\\", "/").lstrip("/")
+        normalized_files[key] = clean or default_name
+
+    prompt_cfg["files"] = normalized_files
+    raw["audio_prompts"] = prompt_cfg
+    return raw
+
+
+def _refresh_cached_cfg(raw: Dict[str, Any]) -> None:
+    global _CFG
+    _CFG = _deep_merge(_FALLBACK, raw if isinstance(raw, dict) else {})
+
+
+def read_runtime_mode() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_mode_block(raw)
+    mode_cfg = raw.get("mode", {})
+    return _coerce_mode(mode_cfg.get("current_mode", mode_cfg.get("default_mode", DEFAULT_MODE)))
+
+
+def write_runtime_mode(mode: str) -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_mode_block(raw)
+    mode_cfg = raw.get("mode", {})
+    mode_cfg["current_mode"] = _coerce_mode(mode)
+    raw["mode"] = mode_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return mode_cfg["current_mode"]
+
+
+def read_vision_detector_backend() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    return _coerce_detection_backend(vision_cfg.get("detection_backend", "yolo"))
+
+
+def write_vision_detector_backend(backend: str) -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    vision_cfg["detection_backend"] = _coerce_detection_backend(backend)
+    raw["vision"] = vision_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return str(vision_cfg["detection_backend"])
+
+
+def read_vision_yolo_runtime() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    return _coerce_yolo_runtime(vision_cfg.get("yolo_runtime", _FALLBACK["vision"]["yolo_runtime"]))
+
+
+def read_vision_yolo_ultralytics_device() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    dev = str(vision_cfg.get("yolo_ultralytics_device", _FALLBACK["vision"]["yolo_ultralytics_device"]) or "").strip()
+    return dev or "cpu"
+
+
+def read_vision_yolo_strict_required() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    return _coerce_bool(vision_cfg.get("yolo_strict_required", _FALLBACK["vision"]["yolo_strict_required"]), True)
+
+
+def read_vision_gemini_context_hz() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    try:
+        hz = float(vision_cfg.get("gemini_context_hz", _FALLBACK["vision"]["gemini_context_hz"]))
+    except Exception:
+        hz = float(_FALLBACK["vision"]["gemini_context_hz"])
+    return max(0.5, min(30.0, hz))
+
+
+def read_vision_gemini_context_silent() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    return _coerce_bool(vision_cfg.get("gemini_context_silent", _FALLBACK["vision"]["gemini_context_silent"]), True)
+
+
+def read_vision_idle_voice_listen_enabled() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    return _coerce_bool(
+        vision_cfg.get("idle_voice_listen_enabled", _FALLBACK["vision"]["idle_voice_listen_enabled"]),
+        True,
+    )
+
+
+def _write_vision_cfg_value(key: str, value: Any, *, bool_field: bool = False) -> Any:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    raw = _ensure_watchdog_block(raw)
+    vision_cfg = raw.get("vision", {})
+    if bool_field:
+        vision_cfg[key] = _coerce_bool(value, bool(_FALLBACK["vision"].get(key, False)))
+    else:
+        vision_cfg[key] = value
+    raw["vision"] = vision_cfg
+    raw = _ensure_vision_block(raw)
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return raw.get("vision", {}).get(key)
+
+
+def read_vision_hard_target_lock_enabled() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    return _coerce_bool(raw.get("vision", {}).get("hard_target_lock_enabled", True), True)
+
+
+def write_vision_hard_target_lock_enabled(enabled: Any) -> bool:
+    return bool(_write_vision_cfg_value("hard_target_lock_enabled", enabled, bool_field=True))
+
+
+def read_vision_retake_prompt_enabled() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    return _coerce_bool(raw.get("vision", {}).get("retake_prompt_enabled", True), True)
+
+
+def write_vision_retake_prompt_enabled(enabled: Any) -> bool:
+    return bool(_write_vision_cfg_value("retake_prompt_enabled", enabled, bool_field=True))
+
+
+def read_vision_autonomous_greeting_replay_enabled() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    return _coerce_bool(
+        raw.get("vision", {}).get(
+            "autonomous_greeting_replay_enabled",
+            _FALLBACK["vision"]["autonomous_greeting_replay_enabled"],
+        ),
+        bool(_FALLBACK["vision"]["autonomous_greeting_replay_enabled"]),
+    )
+
+
+def read_vision_autonomous_greeting_replay_file() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    val = str(
+        raw.get("vision", {}).get(
+            "autonomous_greeting_replay_file",
+            _FALLBACK["vision"]["autonomous_greeting_replay_file"],
+        )
+        or ""
+    ).strip()
+    return val or str(_FALLBACK["vision"]["autonomous_greeting_replay_file"])
+
+
+def read_vision_autonomous_capture_replay_enabled() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    return _coerce_bool(
+        raw.get("vision", {}).get(
+            "autonomous_capture_replay_enabled",
+            _FALLBACK["vision"]["autonomous_capture_replay_enabled"],
+        ),
+        bool(_FALLBACK["vision"]["autonomous_capture_replay_enabled"]),
+    )
+
+
+def write_vision_autonomous_greeting_replay_enabled(enabled: Any) -> bool:
+    return bool(_write_vision_cfg_value("autonomous_greeting_replay_enabled", enabled, bool_field=True))
+
+
+def write_vision_autonomous_greeting_replay_file(filename: Any) -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    cleaned = str(filename or "").strip().replace("\\", "/").lstrip("/")
+    vision_cfg["autonomous_greeting_replay_file"] = cleaned or str(
+        _FALLBACK["vision"]["autonomous_greeting_replay_file"]
+    )
+    raw["vision"] = vision_cfg
+    raw = _ensure_vision_block(raw)
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return str(raw.get("vision", {}).get("autonomous_greeting_replay_file", ""))
+
+
+def write_vision_autonomous_capture_replay_enabled(enabled: Any) -> bool:
+    return bool(_write_vision_cfg_value("autonomous_capture_replay_enabled", enabled, bool_field=True))
+
+
+def read_vision_retake_max_per_session() -> int:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get("retake_max_per_session", _FALLBACK["vision"]["retake_max_per_session"])
+    return _coerce_int(v, int(_FALLBACK["vision"]["retake_max_per_session"]), min_v=0, max_v=5)
+
+
+def read_vision_framing_headroom_min_ratio() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get("framing_headroom_min_ratio", _FALLBACK["vision"]["framing_headroom_min_ratio"])
+    return _coerce_float(v, float(_FALLBACK["vision"]["framing_headroom_min_ratio"]), min_v=0.0, max_v=0.8)
+
+
+def read_vision_framing_headroom_max_ratio() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get("framing_headroom_max_ratio", _FALLBACK["vision"]["framing_headroom_max_ratio"])
+    return _coerce_float(v, float(_FALLBACK["vision"]["framing_headroom_max_ratio"]), min_v=0.0, max_v=0.95)
+
+
+def read_vision_framing_eye_line_min_ratio() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get("framing_eye_line_min_ratio", _FALLBACK["vision"]["framing_eye_line_min_ratio"])
+    return _coerce_float(v, float(_FALLBACK["vision"]["framing_eye_line_min_ratio"]), min_v=0.0, max_v=0.9)
+
+
+def read_vision_framing_eye_line_max_ratio() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get("framing_eye_line_max_ratio", _FALLBACK["vision"]["framing_eye_line_max_ratio"])
+    return _coerce_float(v, float(_FALLBACK["vision"]["framing_eye_line_max_ratio"]), min_v=0.05, max_v=1.0)
+
+
+def read_vision_framing_retake_score_threshold() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get(
+        "framing_retake_score_threshold",
+        _FALLBACK["vision"]["framing_retake_score_threshold"],
+    )
+    return _coerce_float(v, float(_FALLBACK["vision"]["framing_retake_score_threshold"]), min_v=0.0, max_v=1.0)
+
+
+def read_vision_face_recognition_enabled() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    return _coerce_bool(
+        raw.get("vision", {}).get("face_recognition_enabled", _FALLBACK["vision"]["face_recognition_enabled"]),
+        bool(_FALLBACK["vision"]["face_recognition_enabled"]),
+    )
+
+
+def write_vision_face_recognition_enabled(enabled: Any) -> bool:
+    return bool(_write_vision_cfg_value("face_recognition_enabled", enabled, bool_field=True))
+
+
+def read_vision_face_recognition_threshold() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    v = raw.get("vision", {}).get("face_recognition_threshold", _FALLBACK["vision"]["face_recognition_threshold"])
+    return _coerce_float(v, float(_FALLBACK["vision"]["face_recognition_threshold"]), min_v=0.5, max_v=0.995)
+
+
+def write_vision_face_recognition_threshold(value: Any) -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_vision_block(raw)
+    vision_cfg = raw.get("vision", {})
+    vision_cfg["face_recognition_threshold"] = _coerce_float(
+        value,
+        float(_FALLBACK["vision"]["face_recognition_threshold"]),
+        min_v=0.5,
+        max_v=0.995,
+    )
+    raw["vision"] = vision_cfg
+    raw = _ensure_vision_block(raw)
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return float(raw.get("vision", {}).get("face_recognition_threshold", _FALLBACK["vision"]["face_recognition_threshold"]))
+
+
+def read_watchdog_ws_initial_backoff_sec() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_watchdog_block(raw)
+    wd = raw.get("watchdog", {})
+    return _coerce_float(
+        wd.get("ws_initial_backoff_sec", _FALLBACK["watchdog"]["ws_initial_backoff_sec"]),
+        float(_FALLBACK["watchdog"]["ws_initial_backoff_sec"]),
+        min_v=0.1,
+        max_v=60.0,
+    )
+
+
+def read_watchdog_ws_max_backoff_sec() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_watchdog_block(raw)
+    wd = raw.get("watchdog", {})
+    return _coerce_float(
+        wd.get("ws_max_backoff_sec", _FALLBACK["watchdog"]["ws_max_backoff_sec"]),
+        float(_FALLBACK["watchdog"]["ws_max_backoff_sec"]),
+        min_v=0.5,
+        max_v=300.0,
+    )
+
+
+def read_watchdog_component_restart_delay_sec() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_watchdog_block(raw)
+    wd = raw.get("watchdog", {})
+    return _coerce_float(
+        wd.get("component_restart_delay_sec", _FALLBACK["watchdog"]["component_restart_delay_sec"]),
+        float(_FALLBACK["watchdog"]["component_restart_delay_sec"]),
+        min_v=0.1,
+        max_v=20.0,
+    )
+
+
+def read_watchdog_camera_capture_retry_count() -> int:
+    raw = _read_config_json_raw()
+    raw = _ensure_watchdog_block(raw)
+    wd = raw.get("watchdog", {})
+    return _coerce_int(
+        wd.get("camera_capture_retry_count", _FALLBACK["watchdog"]["camera_capture_retry_count"]),
+        int(_FALLBACK["watchdog"]["camera_capture_retry_count"]),
+        min_v=0,
+        max_v=10,
+    )
+
+
+def read_watchdog_camera_capture_retry_delay_sec() -> float:
+    raw = _read_config_json_raw()
+    raw = _ensure_watchdog_block(raw)
+    wd = raw.get("watchdog", {})
+    return _coerce_float(
+        wd.get("camera_capture_retry_delay_sec", _FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]),
+        float(_FALLBACK["watchdog"]["camera_capture_retry_delay_sec"]),
+        min_v=0.0,
+        max_v=30.0,
+    )
+
+
+def read_audio_prompts_fallback_to_gemini() -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_audio_prompts_block(raw)
+    prompt_cfg = raw.get("audio_prompts", {})
+    return _coerce_bool(prompt_cfg.get("fallback_to_gemini", True), True)
+
+
+def read_audio_prompt_mode() -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_audio_prompts_block(raw)
+    prompt_cfg = raw.get("audio_prompts", {})
+    return _coerce_audio_prompt_mode(prompt_cfg.get("mode", "audio"))
+
+
+def write_audio_prompt_mode(mode: Any) -> str:
+    raw = _read_config_json_raw()
+    raw = _ensure_audio_prompts_block(raw)
+    prompt_cfg = raw.get("audio_prompts", {})
+    prompt_cfg["mode"] = _coerce_audio_prompt_mode(mode)
+    raw["audio_prompts"] = prompt_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return str(prompt_cfg["mode"])
+
+
+def write_audio_prompts_fallback_to_gemini(enabled: Any) -> bool:
+    raw = _read_config_json_raw()
+    raw = _ensure_audio_prompts_block(raw)
+    prompt_cfg = raw.get("audio_prompts", {})
+    prompt_cfg["fallback_to_gemini"] = _coerce_bool(enabled, True)
+    raw["audio_prompts"] = prompt_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return bool(prompt_cfg["fallback_to_gemini"])
+
+
+def read_audio_prompt_files() -> Dict[str, str]:
+    raw = _read_config_json_raw()
+    raw = _ensure_audio_prompts_block(raw)
+    prompt_cfg = raw.get("audio_prompts", {})
+    files_cfg = prompt_cfg.get("files", {})
+    out: Dict[str, str] = {}
+    for key, default_name in AUDIO_PROMPT_FILE_DEFAULTS.items():
+        clean = str(files_cfg.get(key, default_name) or "").strip().replace("\\", "/").lstrip("/")
+        out[key] = clean or default_name
+    return out
+
+
+def read_audio_prompt_filename(key: str) -> str:
+    key = str(key or "").strip()
+    if key not in AUDIO_PROMPT_FILE_DEFAULTS:
+        raise KeyError(f"unknown audio prompt key: {key}")
+    return str(read_audio_prompt_files().get(key, AUDIO_PROMPT_FILE_DEFAULTS[key]))
+
+
+def write_audio_prompt_filename(key: str, filename: Any) -> str:
+    key = str(key or "").strip()
+    if key not in AUDIO_PROMPT_FILE_DEFAULTS:
+        raise KeyError(f"unknown audio prompt key: {key}")
+    raw = _read_config_json_raw()
+    raw = _ensure_audio_prompts_block(raw)
+    prompt_cfg = raw.get("audio_prompts", {})
+    files_cfg = prompt_cfg.get("files", {})
+    clean = str(filename or "").strip().replace("\\", "/").lstrip("/")
+    files_cfg[key] = clean or AUDIO_PROMPT_FILE_DEFAULTS[key]
+    prompt_cfg["files"] = files_cfg
+    raw["audio_prompts"] = prompt_cfg
+    _write_config_json_raw(raw)
+    _refresh_cached_cfg(raw)
+    return str(files_cfg[key])
+
+
+# Ensure runtime mode keys exist in config.json.
+try:
+    _raw_cfg = _read_config_json_raw()
+    _normalized = _ensure_mode_block(_raw_cfg)
+    _normalized = _ensure_vision_block(_normalized)
+    _normalized = _ensure_watchdog_block(_normalized)
+    _normalized = _ensure_audio_prompts_block(_normalized)
+    if _normalized != _raw_cfg or not CONFIG_JSON.exists():
+        _write_config_json_raw(_normalized)
+    _refresh_cached_cfg(_normalized)
+except Exception:
+    pass
+
+# CAMERA
+# ==================================================
+CAMERA_INDEX = _env("CAMERA_INDEX", int(_c("camera.camera_index", 0)), int)
+FRAME_WIDTH = _env("FRAME_WIDTH", int(_c("camera.frame_width", 640)), int)
+FRAME_HEIGHT = _env("FRAME_HEIGHT", int(_c("camera.frame_height", 480)), int)
+FPS = _env("FPS", int(_c("camera.fps", 30)), int)
+
+# ==================================================
+# VISION / DETECTOR
+# ==================================================
+VISION_DETECTION_BACKEND = _coerce_detection_backend(_c("vision.detection_backend", "yolo"))
+VISION_YOLO_RUNTIME = _coerce_yolo_runtime(_c("vision.yolo_runtime", "ultralytics"))
+VISION_YOLO_ULTRALYTICS_DEVICE = str(_c("vision.yolo_ultralytics_device", "cpu") or "").strip() or "cpu"
+VISION_PERSON_YOLO_ONNX = str(_c("vision.person_yolo_onnx", "")).strip()
+VISION_FACE_YOLO_ONNX = str(_c("vision.face_yolo_onnx", "")).strip()
+VISION_INPUT_SIZE = _env("DETECTOR_INPUT_SIZE", int(_c("vision.input_size", 640)), int)
+VISION_PERSON_CLASS_ID = _env("DETECTOR_PERSON_CLASS_ID", int(_c("vision.person_class_id", 0)), int)
+VISION_PERSON_SCORE_THRESH = _env(
+    "DETECTOR_PERSON_SCORE_THRESH",
+    float(_c("vision.person_score_thresh", 0.35)),
+    float,
+)
+VISION_FACE_SCORE_THRESH = _env(
+    "DETECTOR_FACE_SCORE_THRESH",
+    float(_c("vision.face_score_thresh", 0.35)),
+    float,
+)
+VISION_NMS_IOU_THRESH = _env("DETECTOR_NMS_IOU_THRESH", float(_c("vision.nms_iou_thresh", 0.45)), float)
+VISION_GROUP_MIN_PEOPLE = _env("DETECTOR_GROUP_MIN_PEOPLE", int(_c("vision.group_min_people", 3)), int)
+VISION_GROUP_LINK_DISTANCE_PX = _env(
+    "DETECTOR_GROUP_LINK_DISTANCE_PX",
+    float(_c("vision.group_link_distance_px", 220.0)),
+    float,
+)
+VISION_YOLO_STRICT_REQUIRED = _coerce_bool(_c("vision.yolo_strict_required", True), True)
+VISION_GEMINI_CONTEXT_HZ = max(0.5, float(_c("vision.gemini_context_hz", 8.0)))
+VISION_GEMINI_CONTEXT_SILENT = _coerce_bool(_c("vision.gemini_context_silent", True), True)
+VISION_HARD_TARGET_LOCK_ENABLED = _coerce_bool(_c("vision.hard_target_lock_enabled", True), True)
+VISION_RETAKE_PROMPT_ENABLED = _coerce_bool(_c("vision.retake_prompt_enabled", True), True)
+VISION_RETAKE_MAX_PER_SESSION = _coerce_int(_c("vision.retake_max_per_session", 1), 1, min_v=0, max_v=5)
+VISION_FRAMING_HEADROOM_MIN_RATIO = _coerce_float(_c("vision.framing_headroom_min_ratio", 0.06), 0.06, min_v=0.0, max_v=0.8)
+VISION_FRAMING_HEADROOM_MAX_RATIO = _coerce_float(_c("vision.framing_headroom_max_ratio", 0.25), 0.25, min_v=0.0, max_v=0.95)
+VISION_FRAMING_EYE_LINE_MIN_RATIO = _coerce_float(_c("vision.framing_eye_line_min_ratio", 0.28), 0.28, min_v=0.0, max_v=0.9)
+VISION_FRAMING_EYE_LINE_MAX_RATIO = _coerce_float(_c("vision.framing_eye_line_max_ratio", 0.48), 0.48, min_v=0.05, max_v=1.0)
+VISION_FRAMING_RETAKE_SCORE_THRESHOLD = _coerce_float(_c("vision.framing_retake_score_threshold", 0.68), 0.68, min_v=0.0, max_v=1.0)
+
+# ==================================================
+# WATCHDOG
+# ==================================================
+WATCHDOG_WS_INITIAL_BACKOFF_SEC = _coerce_float(_c("watchdog.ws_initial_backoff_sec", 1.0), 1.0, min_v=0.1, max_v=60.0)
+WATCHDOG_WS_MAX_BACKOFF_SEC = _coerce_float(_c("watchdog.ws_max_backoff_sec", 20.0), 20.0, min_v=0.5, max_v=300.0)
+WATCHDOG_COMPONENT_RESTART_DELAY_SEC = _coerce_float(
+    _c("watchdog.component_restart_delay_sec", 1.0),
+    1.0,
+    min_v=0.1,
+    max_v=20.0,
+)
+WATCHDOG_CAMERA_CAPTURE_RETRY_COUNT = _coerce_int(_c("watchdog.camera_capture_retry_count", 2), 2, min_v=0, max_v=10)
+WATCHDOG_CAMERA_CAPTURE_RETRY_DELAY_SEC = _coerce_float(
+    _c("watchdog.camera_capture_retry_delay_sec", 0.8),
+    0.8,
+    min_v=0.0,
+    max_v=30.0,
+)
diff --git a/Current_runtime.md b/Current_runtime.md
new file mode 100644
index 0000000..6f5353d
--- /dev/null
+++ b/Current_runtime.md
@@ -0,0 +1,272 @@
+# Current Runtime
+
+Production runtime architecture (as implemented now):
+
+`photo_sanad.sh -> voice_sanad.py -> persistent component loops + WS supervisor -> mode-gated command handling -> unified replay/capture -> server/dashboard/upload`
+
+## Process Model
+
+- `Scripts/photo_sanad.sh` resets `mode.current_mode` to `mode.default_mode` on each launch.
+- Default full runtime path:
+- startup mode is normally `manual`
+- `photo_sanad.sh` resolves active PulseAudio sink/source, launches `Core/direct_camera_service.py` in the `teleimager` env, then starts `Gemini/voice_sanad.py` in the gemini env
+- `Core/direct_camera_service.py` is backend-first and serves external UI assets from `Web/direct_camera.html`, `Web/direct_camera.css`, and `Web/direct_camera.js`
+- preferred RealSense default is read from `Data/Settings/config.json -> camera.preferred_realsense_serial` and falls back to another detected camera if absent
+- in the default full runtime path, `Gemini/voice_sanad.py`, the dashboard server, the direct camera server, and replay/trigger services remain running in both `manual` and `ai`
+- in the full runtime path, `AUTONOMOUS_ENABLE` is auto-armed by default so dashboard mode can switch from `manual` to `ai` without restart
+- Optional lean manual path:
+- `MANUAL_LEAN_RUNTIME=1`
+- skips the direct camera server and the heavy manual/AI runtime services
+- keeps Gemini + dashboard only
+- `Gemini/voice_sanad.py` is the single long-lived orchestrator process.
+- Runtime logs are centralized under `Logs/`, with one stable file per component.
+- It starts these loops once and keeps them alive:
+- `capture_mic`
+- `receive_audio`
+- `play_audio`
+- `keepalive`
+- `Modes/Manual/trigger_loop.py` in the full runtime path
+- autonomous-mode supervisor in the full runtime path
+- `Modes/AI/autonomous_manager.py` only while `AUTONOMOUS_ENABLE=1` and runtime mode is `ai`
+- Runtime health writer (`Data/Runtime/runtime_health.json`)
+- Mode policy sync
+- Gemini WebSocket is managed by a dedicated reconnect supervisor. WS reconnect does not restart other loops.
+- In the normal full runtime path, mode switches change gating/state only; they do not tear down `voice_sanad.py`, the dashboard server, the direct camera server, or replay services.
+
+## Mode Control
+
+- Source of truth is `Data/Settings/config.json`:
+- `mode.current_mode` in `manual|ai`
+- launcher resets `mode.current_mode` to `mode.default_mode` at process start
+- API updates mode live via `Server/photo_server.py`:
+- `/api/set_mode`
+- Voice command gating is enforced on user transcription events in `Gemini/gemini_voice.py`.
+
+## Mode Semantics
+
+| Mode | Voice photo commands (`request_photo/yes_photo/no_photo`) | Manual R2+X | Autonomous flow |
+|---|---|---|---|
+| `manual` | Off | On | Paused |
+| `ai` | On | On | On only if `AUTONOMOUS_ENABLE=1` |
+
+Additional mode rules:
+- Gemini conversation can stay active in both modes when `gemini.mic_enabled=true`.
+- In full runtime, `manual` still includes the direct camera server, replay/trigger, uploader, and dashboard capture services.
+- In full runtime, switching dashboard mode from `manual` to `ai` does not restart the process.
+- In full runtime, switching between `manual` and `ai` does not stop `voice_sanad.py`, the dashboard server, the direct camera server, or replay/trigger services.
+- If `AUTONOMOUS_ENABLE=1`, autonomous manager is armed and starts live when runtime mode becomes `ai`.
+- Switching back to `manual` pauses autonomous flow again.
+- In optional `MANUAL_LEAN_RUNTIME=1`, capture/replay/autonomous services are intentionally unavailable.
+
+Removed from this project:
+- command-mode functionality was extracted to `G1_Lootah/AI_Command`
+
+## Remote Safety Controls
+
+- `R2+X`: starts replay + photographer talk + unified capture pipeline.
+- `R2+L1`: global hard cancel safety combo (active in runtime loops):
+- cancels pending capture
+- cancels active replay path
+- resets autonomous interaction session to `IDLE`
+
+## AI/Autonomous Runtime
+
+State machine in `Modes/AI/autonomous_manager.py`:
+
+`IDLE -> WAIT_CONFIRM -> FRAMING -> COUNTDOWN -> RETAKE_CONFIRM (optional) -> COMPLETE -> IDLE`
+
+Special blocked state:
+
+`IDLE_BLOCKED` when strict YOLO readiness fails.
+
+Behavior:
+
+- Autonomous manager is supervised by runtime mode:
+- `manual` -> paused
+- `ai` -> active when `AUTONOMOUS_ENABLE=1`
+- In full runtime, autonomous services can already be armed while still paused in `manual`, so mode switches are live.
+- In full runtime, the direct camera server and replay infrastructure remain started while autonomous manager is paused in `manual`.
+- On stable intent, manager opens audio gate, triggers a short greeting-hand replay, and asks whether the visitor wants a photo.
+- On stable single-person intent, manager can identify a returning guest or enroll a new guest into `photos/people/`.
+- Group-first greeting is used when group is detected.
+- Confirmation uses flag commands from voice layer (`request_photo.flag`, `confirm_yes.flag`, `confirm_no.flag`).
+- Hard target lock can pin one subject/group through the session.
+- Framing checks: center, size, blur, exposure, headroom, eye-line.
+- AI greeting replay is controlled by `vision.autonomous_greeting_replay_enabled` and `vision.autonomous_greeting_replay_file`.
+- AI photo-time replay is controlled by `vision.autonomous_capture_replay_enabled`.
+- When AI photo-time replay is enabled, autonomous capture uses the active replay file from `Data/Settings/config.json -> replay.active_file`, same as manual `R2+X`.
+- When a capture succeeds for an identified guest, the saved photo is attached into that guest's folder in `photos/people/`.
+- After capture, retake recommendation can move flow to `RETAKE_CONFIRM` (max retakes from config).
+- On completion: CTA prompt and cooldown reset.
+
+## Vision Runtime
+
+`Modes/AI/vision_detector.py` provides:
+
+- Backend selection `normal|yolo`.
+- YOLO runtime selection `ultralytics|opencv`.
+- Person/face detection and group clustering.
+- Intent detection using depth-first logic and bbox-area fallback.
+- Target lock fields:
+- `target_lock_active`, `target_lock_type`, `target_lock_id`, `target_switch_blocked_count`
+- Camera/depth health fields:
+- `camera_ok`, `depth_ok`, `camera_restarts`, `depth_restarts`
+
+Strict production gate:
+
+- If `vision.yolo_strict_required=true` and YOLO readiness is not valid, AI session is blocked in `IDLE_BLOCKED`.
+
+## Gemini Integration
+
+`Gemini/gemini_voice.py`:
+
+- Uses WS attach/detach model:
+- `attach_ws()`
+- `detach_ws()`
+- `is_ws_connected()`
+- Live-safe sends:
+- `send_text_prompt_live()`
+- `send_vision_context_live()`
+- Command matching uses user transcription events, not model text.
+- Continuous vision context is streamed from autonomous manager.
+- Context can be silent (`vision.gemini_context_silent=true`) and model audio is suppressed for context-only turns.
+- Exposes runtime health snapshot for dashboard/API.
+- In `manual`, Gemini conversation can remain available while AI photo flags stay disabled.
+- Mic state is controlled live through `/api/mic` and `/api/set_mic`.
+
+## Unified Capture Pipeline
+
+All capture paths use `Server/capture_service.py`:
+
+- Replay execution + trigger marker callback capture.
+- Timed fallback capture if trigger marker is missing.
+- Capture retries using watchdog settings:
+- `watchdog.camera_capture_retry_count`
+- `watchdog.camera_capture_retry_delay_sec`
+- Upload trigger flag is touched after successful capture.
+
+Replay integrity is validated at startup and fallback replay can be selected automatically.
+
+## Component Recovery (Watchdog)
+
+- WS failure: reconnect WS channel only.
+- Mic failure: restart mic component only.
+- Speaker failure: restart speaker component only.
+- Detector frame starvation: recover detector camera/depth inputs only.
+- Capture camera failure: retry capture call only.
+- Process stays alive unless startup fatal occurs (for example empty Gemini API key).
+
+## Server and Dashboard
+
+`Server/photo_server.py` + `Web/gallery.js` provide:
+
+- Mode APIs:
+- `/api/mode`, `/api/set_mode`, `/api/mode_policy`
+- Mic APIs:
+- `/api/mic`, `/api/set_mic`
+- Detector/AI readiness APIs:
+- `/api/detector_backend`, `/api/set_detector_backend`
+- `/api/ai_readiness`
+- AI options APIs:
+- `/api/ai_options`
+- `/api/set_ai_options?hard_target_lock_enabled=0|1&retake_prompt_enabled=0|1&autonomous_greeting_replay_enabled=0|1&autonomous_greeting_replay_file=...&autonomous_capture_replay_enabled=0|1&face_recognition_enabled=0|1&face_recognition_threshold=...`
+- Replay APIs:
+- `/api/replays`
+- `/api/get_replay`
+- `/api/set_replay?name=...`
+- `/api/delete_replay?name=...`
+- `/api/rename_replay?old=...&new=...`
+- `/api/download_replay?name=...`
+- `/api/replay_record_status`
+- `/api/replay_record_start?name=...&seconds=...`
+- `/api/replay_test_status`
+- `/api/test_replay?name=...`
+- `/api/upload_replay`
+- Runtime state APIs:
+- `/api/autonomous_state`
+- `/api/runtime_health`
+- Camera APIs:
+- `/api/camera_health`
+- `/api/camera_sources`
+- `/api/set_camera_source?source=...`
+- `/api/set_camera_resolution?width=...&height=...&fps=...`
+- `/api/set_preferred_camera?serial=...`
+- Photo APIs:
+- `/api/capture`, `/api/photos`, `/api/delete`, `/api/reupload`, `/api/upload_now`, `/api/download_zip`
+- Live preview:
+- `/preview.mjpg`
+- preview is off by default and only runs when requested from the dashboard
+- preview camera/OpenCV is loaded lazily when preview is requested
+
+Dashboard panels include mode controls, detector backend/readiness, AI options, autonomous state, runtime health, live camera preview, camera source switching, camera resolution changes, preferred RealSense serial persistence, active replay selection, replay inventory management, and replay recording controls.
+
+Replay-management rules:
+- replay inventory covers the full `Data/G1` tree
+- replay recording is allowed only in `manual`
+- replay test/play is allowed only in `manual`
+- rename/download/delete/upload remain available from the dashboard inventory tools
+- People APIs:
+- `/api/people`
+- `/api/person_image?id=...&kind=face|scene`
+- `/api/download_person?id=...`
+- `/api/delete_person?id=...`
+- `/api/reset_people`
+- `/api/upload_person`
+- Audio prompt APIs:
+- `/api/audio_prompts`
+- `/api/set_audio_prompt_mode?mode=audio|gemini`
+- `/api/set_audio_prompt_fallback?enabled=0|1`
+- `/api/audio_prompt_record_status`
+- `/api/download_audio_prompt?key=...`
+- `/api/delete_audio_prompt?key=...`
+- `/api/upload_audio_prompt`
+- `/api/audio_prompt_record`
+
+Dashboard audio-prompt behavior:
+- operators can upload prerecorded WAV clips for each AI situation key
+- operators can delete or download existing clips
+- operators can record a prompt clip directly from text using the same Gemini replay path as `Project/SanadVoice/gemini_voice/sanad_replay.py`
+- operators can switch fixed AI situation speech between:
+  - `audio`: recorded prompt clips first
+  - `gemini`: Gemini speech for those same fixed situations
+- if a prompt clip is missing while `audio_prompts.mode=audio`, runtime falls back to Gemini text when `audio_prompts.fallback_to_gemini=true`
+
+Dashboard people-registry behavior:
+- sidebar shows enrolled guests with face + scene thumbnails
+- operators can upload a new face image to create or extend a guest profile
+- operators can attach additional photos to an existing guest profile
+- operators can download or delete one guest, or reset the whole registry
+
+`Core/direct_camera_service.py` serves its own camera UI from external web assets under `Web/` rather than embedding HTML/CSS/JS in Python.
+
+## Runtime State Files
+
+- `Data/Settings/config.json`
+- `Data/Runtime/autonomous_state.json`
+- `Data/Runtime/runtime_health.json`
+- `Data/Runtime/error_counters.json`
+- `Data/Runtime/error_events.jsonl`
+- `Data/Runtime/upload_db.json`
+- `Data/Audio/`
+- `Data/Settings/audio_prompt_records.json`
+- `photos/people/`
+- `photos/Captures/`
+- `photos/samples/`
+
+These runtime JSON files are generated lazily. In a clean project tree, some of them will not exist until the corresponding component starts writing state.
+
+## Core Config Blocks
+
+- `mode`: runtime mode.
+- `vision`: backend/runtime, strict YOLO, context stream settings, hard lock, retake, framing thresholds, greeting replay, and AI capture replay.
+- `vision`: backend/runtime, strict YOLO, context stream settings, hard lock, retake, framing thresholds, greeting replay, AI capture replay, and face-recognition controls.
+- `watchdog`: WS backoff, component restart delay, capture retry policy.
+
+## Notes
+
+- Capture choreography is unified across manual trigger, autonomous flow, and dashboard capture.
+- Hands/replay behavior during capture remains driven by replay files in `Data/G1`.
+- Replay recordings created from the dashboard are stored directly under `Data/G1` and become selectable as active replays without restart.
+- Imported AI prompt recordings are stored under `Data/Audio/` and indexed by `Data/Settings/audio_prompt_records.json`.
+- In `audio` prompt mode, AI detection, greeting, confirmation, countdown, refusal, retake, and thank-you situations use recorded clips first.
+- After a fixed prompt finishes, runtime returns to normal Gemini conversation flow automatically.
diff --git a/Data/Audio/.gitkeep b/Data/Audio/.gitkeep
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/Data/Audio/.gitkeep
@@ -0,0 +1 @@
+
diff --git a/Data/Audio/confirm_reminder.wav b/Data/Audio/confirm_reminder.wav
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diff --git a/Data/G1/arm_home.jsonl b/Data/G1/arm_home.jsonl
new file mode 100644
index 0000000..a7b1b62
--- /dev/null
+++ b/Data/G1/arm_home.jsonl
@@ -0,0 +1,482 @@
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diff --git a/Data/G1/bird.jsonl b/Data/G1/bird.jsonl
new file mode 100644
index 0000000..97a01c9
--- /dev/null
+++ b/Data/G1/bird.jsonl
@@ -0,0 +1,1051 @@
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diff --git a/Data/G1/change_battery.jsonl b/Data/G1/change_battery.jsonl
new file mode 100644
index 0000000..5f95c92
--- /dev/null
+++ b/Data/G1/change_battery.jsonl
@@ -0,0 +1,1791 @@
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diff --git a/Data/G1/hands_up.jsonl b/Data/G1/hands_up.jsonl
new file mode 100644
index 0000000..22a2de2
--- /dev/null
+++ b/Data/G1/hands_up.jsonl
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diff --git a/Data/G1/laugh.jsonl b/Data/G1/laugh.jsonl
new file mode 100644
index 0000000..7357230
--- /dev/null
+++ b/Data/G1/laugh.jsonl
@@ -0,0 +1,1154 @@
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diff --git a/Data/G1/left_hand_up.jsonl b/Data/G1/left_hand_up.jsonl
new file mode 100644
index 0000000..6b93844
--- /dev/null
+++ b/Data/G1/left_hand_up.jsonl
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diff --git a/Data/G1/photo_G1.jsonl b/Data/G1/photo_G1.jsonl
new file mode 100644
index 0000000..1884a8e
--- /dev/null
+++ b/Data/G1/photo_G1.jsonl
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diff --git a/Data/G1/photo_G2.jsonl b/Data/G1/photo_G2.jsonl
new file mode 100644
index 0000000..a3ad7ca
--- /dev/null
+++ b/Data/G1/photo_G2.jsonl
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diff --git a/Data/G1/photo_G3.jsonl b/Data/G1/photo_G3.jsonl
new file mode 100644
index 0000000..aa0ec72
--- /dev/null
+++ b/Data/G1/photo_G3.jsonl
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diff --git a/Data/G1/right_hand_up.jsonl b/Data/G1/right_hand_up.jsonl
new file mode 100644
index 0000000..ee17d76
--- /dev/null
+++ b/Data/G1/right_hand_up.jsonl
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diff --git a/Data/G1/think_1.jsonl b/Data/G1/think_1.jsonl
new file mode 100644
index 0000000..d6bc1bb
--- /dev/null
+++ b/Data/G1/think_1.jsonl
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diff --git a/Data/G1/think_2.jsonl b/Data/G1/think_2.jsonl
new file mode 100644
index 0000000..7bd1c22
--- /dev/null
+++ b/Data/G1/think_2.jsonl
@@ -0,0 +1,1047 @@
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diff --git a/Data/G1/think_3.jsonl b/Data/G1/think_3.jsonl
new file mode 100644
index 0000000..e3b6602
--- /dev/null
+++ b/Data/G1/think_3.jsonl
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diff --git a/Data/G1/think_4.jsonl b/Data/G1/think_4.jsonl
new file mode 100644
index 0000000..ef59c1c
--- /dev/null
+++ b/Data/G1/think_4.jsonl
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diff --git a/Data/G1/think_5.jsonl b/Data/G1/think_5.jsonl
new file mode 100644
index 0000000..55271e1
--- /dev/null
+++ b/Data/G1/think_5.jsonl
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diff --git a/Data/G1/think_6.jsonl b/Data/G1/think_6.jsonl
new file mode 100644
index 0000000..05cbb50
--- /dev/null
+++ b/Data/G1/think_6.jsonl
@@ -0,0 +1,896 @@
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diff --git a/Data/G1/think_7.jsonl b/Data/G1/think_7.jsonl
new file mode 100644
index 0000000..1b31c6c
--- /dev/null
+++ b/Data/G1/think_7.jsonl
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diff --git a/Data/Notes/Note.txt b/Data/Notes/Note.txt
new file mode 100644
index 0000000..b22f27f
--- /dev/null
+++ b/Data/Notes/Note.txt
@@ -0,0 +1,41 @@
+
+
+
+
+
+
+
+
+
+welcome_single = "Hello, welcome. We will take a photo together. Would you like a photo?"
+
+
+
+
+welcome_group = "Hello everyone, welcome. We will take a photo together. Would your group like a photo?"
+welcome_returning = "Welcome back. Would you like another photo?"
+
+frame_single = "Great. Please stand with me in front of the camera, stay in the center, and look at the camera."
+frame_group = "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera."
+
+confirm_reminder = "Please say yes photo to continue, or no photo to cancel."
+visitor_left = "No worries. I will wait here for the next visitor."
+declined = "No problem. We can do it anytime."
+confirm_timeout = "No problem. I will wait here. Come back anytime for a photo."
+session_cancelled = "Okay. Session cancelled."
+framing_timeout = "I still need a better frame. Please step in front of me and say yes photo when ready."
+
+countdown_intro = "Come on, ready... one, two, three, smile!"
+count_3 = "Three."
+count_2 = "Two."
+count_1 = "One."
+smile = "Smile."
+
+countdown_cancelled = "Countdown cancelled."
+lost_from_frame = "I lost you from the frame. Let us try again."
+
+retake_recommended = "Photo captured. I recommend a retake. Say yes photo to retake, or no photo to keep this one."
+retake_yes = "Great. Let us retake. Hold your pose."
+retake_limit = "Retake limit reached. Keeping the current photo."
+
+photo_saved_thanks = "Thank you. Photo saved. Do not forget to check your photos."
\ No newline at end of file
diff --git a/Data/Runtime/runtime_health.json b/Data/Runtime/runtime_health.json
new file mode 100644
index 0000000..0945ca9
--- /dev/null
+++ b/Data/Runtime/runtime_health.json
@@ -0,0 +1 @@
+{"ws_connected": true, "ws_state": "connected", "ws_restarts": 0, "ws_last_error": "", "ws_last_event_ts": 1773214526.9045713, "ws_last_reason": "attach", "mic_state": "running", "mic_restarts": 0, "mic_last_error": "", "mic_last_event_ts": 1773214526.3342426, "speaker_state": "running", "speaker_restarts": 0, "speaker_last_error": "", "speaker_last_event_ts": 1773214526.3344123, "speaker_queue_drops": 0, "speaker_queue_max": 0, "mic_enabled": true, "audio_gate_open": true, "passive_listen_only": false, "speaking": false, "interrupted": false, "speaker_queue_size": 0, "time": 1773214533.2199197, "model": "models/gemini-2.5-flash-native-audio-preview-12-2025"}
\ No newline at end of file
diff --git a/Data/Runtime/upload_db.json b/Data/Runtime/upload_db.json
new file mode 100644
index 0000000..0967ef4
--- /dev/null
+++ b/Data/Runtime/upload_db.json
@@ -0,0 +1 @@
+{}
diff --git a/Data/Scripts/photo_command_ai.txt b/Data/Scripts/photo_command_ai.txt
new file mode 100644
index 0000000..12ef8fa
--- /dev/null
+++ b/Data/Scripts/photo_command_ai.txt
@@ -0,0 +1,115 @@
+request_photo
+take photo
+take my photo
+take a photo
+take a picture
+take our photo
+take group photo
+picture please
+please take a photo
+please take our photo
+photo please
+photo now
+can you take my photo
+could you take a photo
+can we take a photo
+can you take a picture
+snap photo
+i want a photo
+صورني
+صورنا
+ابغى صورة
+ابي صورة
+نبي صورة
+نبغى صورة
+ممكن صورة
+خذ صورة
+صورتني
+التقط صورة
+تصورني
+ساعدني تصوّر
+تصويري
+خلنا نتصور
+
+yes_photo
+yes
+yes photo
+yes take photo
+yes take picture
+yes please
+yeah
+yep
+yup
+sure
+ok
+okay
+please do
+do it
+let's do it
+ready
+ready now
+confirm
+confirmed
+i agree
+go ahead
+start photo
+ok photo
+okay photo
+نعم
+اي
+ايوه
+ايوا
+اوكي
+تمام
+تفضل
+يلا
+اكيد
+موافق
+موافقين
+ابشر
+صور
+صور الحين
+يلا صور
+نعم صورة
+ايوا صورة
+
+no_photo
+no
+no photo
+nope
+nah
+negative
+not now
+not now please
+maybe later
+no not now
+don't take photo
+do not take photo
+cancel photo
+cancel
+cancel it
+no thanks
+stop photo
+stop it
+skip photo
+no need
+not interested
+later
+لا
+لا لا
+لا الحين
+مو الحين
+بعدين
+يمكن بعدين
+وقف
+الغ
+الغ الصورة
+لا تصور
+لا تلتقط
+ما ابغى صورة
+مابي صورة
+ما نبي صورة
+خلها بعدين
+مش الحين
+لا صورة
+لا شكرا
diff --git a/Data/Scripts/sanad_script.txt b/Data/Scripts/sanad_script.txt
new file mode 100644
index 0000000..e9be1b1
--- /dev/null
+++ b/Data/Scripts/sanad_script.txt
@@ -0,0 +1,102 @@
+أنت "بوسنده" — مساعد صوتي إماراتي ذكي تابع لروبوت شركة لوتاه تيك Lootah Tech.
+
+الأسلوب:
+- تكلم باللهجة الإماراتية بشكل طبيعي (بدون فصحى ثقيلة وبدون مبالغة).
+- خلك محترم وودود ومباشر.
+- ركّز على الزبدة والحل العملي.
+- تقدر تجاوب على أي سؤال حتى لو المستخدم ما قال "بوسنده".
+- إذا قال المستخدم "بوسنده" أو "Bousandah"، تفاعل أكثر واعطي تفاصيل شوي زيادة.
+
+اللغة (تبديل فوري):
+- إذا المستخدم يتكلم عربي: أرد بالعربي بلهجة إماراتية.
+- إذا المستخدم غيّر اللغة لأي لغة ثانية في أي لحظة: أغيّر فورًا وأرد بنفس اللغة الجديدة في نفس الرد.
+- إذا المستخدم رجع للعربي: أرجع فورًا للعربي (لهجة إماراتية).
+- القاعدة: "آخر لغة كتب فيها المستخدم" هي اللغة اللي أرد فيها.
+- ممنوع أخلط لغتين في نفس الرد إلا إذا المستخدم طلب ترجمة أو مقارنة صريحة.
+
+مفردات خفيفة (استخدمها بشكل طبيعي):
+- وايد، هيه، علومك؟، طال عمرك، وأنا أخوك
+- مرحبابك، يا هلا، يا مرحبا
+- أبشر، أبشر بعزك، ما طلبت شي
+- السموحة منك، المعذرة، تسلم، الله يسلمك
+- زين، مضبوط، تمام
+- شوف طال عمرك، خلّنا نمشيها خطوة خطوة
+- على السريع، الزبدة، مختصر المفيد
+- لا تشيل هم، الأمور طيبة، بنرتبها
+- تامر أمر، من عيوني، حاضر
+- عساك بخير، الله يحييك
+- دربك خضر، الله يحفظك، الله يوفقك
+(لا تكررهم كل سطر، استخدمها من وقت لوقت وبشكل طبيعي)
+
+تنويع البداية (مهم):
+- لا تكرر نفس عبارة البداية في كل رد.
+- بدّل بين عبارات الاستقبال بشكل طبيعي، وممنوع تكرر نفس العبارة مرتين متتاليتين.
+- استخدم واحدة فقط في بداية الرد، وأحياناً ابدأ مباشرة بدون أي عبارة:
+  1) فالك طيب
+  2) أبشر بعزك
+  3) ما طلبت شي
+  4) مرحبابك
+  5) يا هلا
+  6) تمام طال عمرك
+  7) هيه حاضر
+- إذا الرد تقني سريع أو كود: ممكن تبدأ مباشرة بدون مقدمات.
+
+التفاعل:
+- إذا السؤال واضح: جاوب مباشرة.
+- إذا تقدر تضيف نصيحة مفيدة مرتبطة: اقترح شيء واحد (اختياري).
+- إذا السؤال ناقصه معلومة تمنع الحل الصح: اسأل سؤال واحد فقط وبشكل لطيف.
+
+التفاعل والوناسة (Engagement):
+- خلك اجتماعي وتفاعلي وخفف الجو.
+- مزح خفيف ولطيف عند الحاجة بدون إساءة.
+- إذا المستخدم متوتر أو متضايق: طمّنه بكلمة طيبة.
+- إذا المستخدم طالب شغل أو كود: أعطه الزبدة أول، وبعدها مزحة قصيرة اختيارية.
+- ممنوع أي نكت أو محتوى حساس (دين، عرق، سياسة، إلخ).
+
+التكرار (Repeat Mode):
+- إذا المستخدم قال: "كرر" / "أعد" / "repeat" / "say it again" / "عيد الكلام":
+  - أعيد نفس الكلام بنفس اللغة الحالية.
+  - نفس المعنى ونفس الخطوات.
+  - إذا قال "بنفس الكلمات" أو "حرفياً": أعيد حرفياً قدر الإمكان.
+  - إذا ما حدّد وش أعيد: أعيد آخر نقطة أو آخر خطوة أو آخر كود.
+- إذا طلب إعادة كود: أعيد الكود كامل داخل بلوك كود مثل ما هو.
+
+إنجاز المهام:
+- إذا طُلب كود: اكتب كود نظيف وجاهز للنسخ والتشغيل، والشرح بسيط وباللهجة الإماراتية.
+- إذا طُلب خطوات نظام/لينكس: أوامر واضحة ومسارات دقيقة.
+- إذا طُلب رسالة/إيميل: مسودة جاهزة.
+
+الأمان والخصوصية:
+- إذا المستخدم كتب API key أو Password أو Token: نبهه فوراً يمسحه ويبدله.
+- لا تطلب بيانات حساسة إلا إذا ضرورية جداً وبطريقة محترمة.
+
+الذاكرة داخل المحادثة (Contextual Memory):
+- اعتبر كل تفاصيل المستخدم داخل نفس المحادثة مهمة.
+- اربط كلامك بآخر 5–20 رسالة إذا الموضوع يحتاج.
+- تعامل مع الإعدادات والمسارات والأسماء كثوابت.
+- إذا المستخدم صححك:
+  قل: "زين نبهتني يا الشيخ، انحفرت في الذاكرة."
+- بعد كل خطوة مهمة:
+  أعط ملخص سريع (اختياري):
+  "ملخص سريع: المسار = ... | الأمر = ... | الملف = ..."
+- إذا قال المستخدم "تذكر" أو "memorize": اعتبرها أولوية داخل المحادثة.
+
+السرعة (Fast Response):
+- جاوب بسرعة وباختصار (2 إلى 6 سطور غالباً).
+- الزبدة أول.
+- خطوات مرقمة قصيرة إذا لزم.
+- سؤال واحد فقط إذا المعلومة ناقصة.
+- لا تطوّل إلا إذا طُلب شرح كامل.
+- التزم بهذا البرومبت حرفياً بدون تعديل أو إعادة صياغة.
+
+
+
+مهمّة إضافية (Photographer Mode):
+- أنت "بوسنده" المصوّر (Photographer) داخل روبوت هومانويد.
+- دورك: ترحّب بالسياح، توجّههم للوضعية، تعطي تعليمات تصوير خفيفة، وتعدّ 3..2..1، وتقول لهم "يلا ابتسم".
+- أسلوبك: إماراتي لطيف ومرح، جمل قصيرة وسريعة.
+- كلمات مصوّر طبيعية تستخدمها وقت اللزوم:
+  "يلا ابتسم"، "قرب شوي"، "على يمينك شوي"، "ارفع راسك"، "ثبّت"، "زين ممتاز"، "واحد.. اثنين.. ثلاثة"،
+  "لا تتحرك"، "شوف الكاميرا"، "جاهزين؟"، "لقطة حلوة"، "يلا آخر لقطة"
+- إذا تم تفعيل وضع المصوّر من الكنترول: تتكلم بشكل متواصل تقريباً 15 ثانية بتوجيهات تصوير،
+  وبآخر 5 ثواني تركز على الشكر وتقول: "thank youooo" (بنبرة لطيفة ومطوّلة).
diff --git a/Data/Settings/audio_prompt_records.json b/Data/Settings/audio_prompt_records.json
new file mode 100644
index 0000000..77446e8
--- /dev/null
+++ b/Data/Settings/audio_prompt_records.json
@@ -0,0 +1,908 @@
+{
+  "created_by": "AI_Photographer.audio_prompts import",
+  "last_updated": "2026-03-17T18:30:37",
+  "total_records": 22,
+  "records": [
+    {
+      "record_name": "welcome_single",
+      "text": "Hello, welcome. We will take a photo together. Would you like a photo?",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 2,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:37:09",
+        "audio_generated_at": "2026-03-13T14:37:13",
+        "last_playback_finished_at": "2026-03-13T14:37:25",
+        "saved_at": "2026-03-13T14:37:30"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/welcome_single.wav",
+          "name": "welcome_single.wav",
+          "size_bytes": 223440,
+          "size_mb": 0.213,
+          "duration_seconds": 4.654,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/welcome_single_raw.wav",
+          "name": "welcome_single_raw.wav",
+          "size_bytes": 209324,
+          "size_mb": 0.2,
+          "duration_seconds": 4.36,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "welcome_group",
+      "text": "Hello everyone, welcome. We will take a photo together. Would your group like a photo?",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 2,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:38:05",
+        "audio_generated_at": "2026-03-13T14:38:09",
+        "last_playback_finished_at": "2026-03-13T14:38:27",
+        "saved_at": "2026-03-13T14:38:38"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/welcome_group.wav",
+          "name": "welcome_group.wav",
+          "size_bytes": 261784,
+          "size_mb": 0.25,
+          "duration_seconds": 5.453,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/welcome_group_raw.wav",
+          "name": "welcome_group_raw.wav",
+          "size_bytes": 247724,
+          "size_mb": 0.236,
+          "duration_seconds": 5.16,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "welcome_returning",
+      "text": "Welcome back. Would you like another photo?",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:39:33",
+        "audio_generated_at": "2026-03-13T14:39:36",
+        "last_playback_finished_at": "2026-03-13T14:39:38",
+        "saved_at": "2026-03-13T14:39:46"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/welcome_returning.wav",
+          "name": "welcome_returning.wav",
+          "size_bytes": 135422,
+          "size_mb": 0.129,
+          "duration_seconds": 2.82,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/welcome_returning_raw.wav",
+          "name": "welcome_returning_raw.wav",
+          "size_bytes": 121004,
+          "size_mb": 0.115,
+          "duration_seconds": 2.52,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "frame_single",
+      "text": "Great. Please stand with me in front of the camera, stay in the center, and look at the camera.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 2,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:40:15",
+        "audio_generated_at": "2026-03-13T14:40:19",
+        "last_playback_finished_at": "2026-03-13T14:40:41",
+        "saved_at": "2026-03-13T14:40:43"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/frame_single.wav",
+          "name": "frame_single.wav",
+          "size_bytes": 252470,
+          "size_mb": 0.241,
+          "duration_seconds": 5.259,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/frame_single_raw.wav",
+          "name": "frame_single_raw.wav",
+          "size_bytes": 238124,
+          "size_mb": 0.227,
+          "duration_seconds": 4.96,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "frame_group",
+      "text": "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:41:03",
+        "audio_generated_at": "2026-03-13T14:41:07",
+        "last_playback_finished_at": "2026-03-13T14:41:12",
+        "saved_at": "2026-03-13T14:41:17"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/frame_group.wav",
+          "name": "frame_group.wav",
+          "size_bytes": 278668,
+          "size_mb": 0.266,
+          "duration_seconds": 5.805,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/frame_group_raw.wav",
+          "name": "frame_group_raw.wav",
+          "size_bytes": 265004,
+          "size_mb": 0.253,
+          "duration_seconds": 5.52,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "confirm_reminder",
+      "text": "Please say yes photo to continue, or no photo to cancel.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:41:42",
+        "audio_generated_at": "2026-03-13T14:41:47",
+        "last_playback_finished_at": "2026-03-13T14:41:51",
+        "saved_at": "2026-03-13T14:41:58"
+      },
+      "files": {
+        "speaker_recording": {
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+          "name": "confirm_reminder.wav",
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+        },
+        "gemini_raw_output": {
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+          "name": "confirm_reminder_raw.wav",
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "visitor_left",
+      "text": "No worries. I will wait here for the next visitor.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
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+        "audio_generated_at": "2026-03-13T14:42:12",
+        "last_playback_finished_at": "2026-03-13T14:42:15",
+        "saved_at": "2026-03-13T14:42:28"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/visitor_left.wav",
+          "name": "visitor_left.wav",
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+        },
+        "gemini_raw_output": {
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+          "name": "visitor_left_raw.wav",
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "declined",
+      "text": "No problem. We can do it anytime.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 2,
+      "audio_capture": {
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+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
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+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:42:46",
+        "audio_generated_at": "2026-03-13T14:42:48",
+        "last_playback_finished_at": "2026-03-13T14:43:03",
+        "saved_at": "2026-03-13T14:43:16"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/declined.wav",
+          "name": "declined.wav",
+          "size_bytes": 108070,
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+        },
+        "gemini_raw_output": {
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "confirm_timeout",
+      "text": "No problem. I will wait here. Come back anytime for a photo.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
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+        "audio_generated_at": "2026-03-13T14:43:50",
+        "last_playback_finished_at": "2026-03-13T14:43:54",
+        "saved_at": "2026-03-13T14:44:04"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/confirm_timeout.wav",
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+        },
+        "gemini_raw_output": {
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "session_cancelled",
+      "text": "Okay. Session cancelled.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
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+        "audio_generated_at": "2026-03-13T14:44:25",
+        "last_playback_finished_at": "2026-03-13T14:44:27",
+        "saved_at": "2026-03-13T14:44:39"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/session_cancelled.wav",
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+        "gemini_raw_output": {
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+          "channels": 1,
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+        }
+      }
+    },
+    {
+      "record_name": "framing_timeout",
+      "text": "I still need a better frame. Please step in front of me and say yes photo when ready.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+      },
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+        "audio_generated_at": "2026-03-13T14:45:02",
+        "last_playback_finished_at": "2026-03-13T14:45:09",
+        "saved_at": "2026-03-13T14:45:22"
+      },
+      "files": {
+        "speaker_recording": {
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+        "gemini_raw_output": {
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "countdown_intro",
+      "text": "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
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+      "audio_capture": {
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+      },
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+        "last_playback_finished_at": "2026-03-17T18:30:31",
+        "saved_at": "2026-03-17T18:30:37"
+      },
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+        "speaker_recording": {
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+        "gemini_raw_output": {
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+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "countdown_cancelled",
+      "text": "Countdown cancelled.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+      },
+      "timeline": {
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+        "audio_generated_at": "2026-03-13T14:46:36",
+        "last_playback_finished_at": "2026-03-13T14:46:37",
+        "saved_at": "2026-03-13T14:46:42"
+      },
+      "files": {
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+        "gemini_raw_output": {
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "lost_from_frame",
+      "text": "I lost you from the frame. Let us try again.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+      },
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+        "audio_generated_at": "2026-03-13T14:47:00",
+        "last_playback_finished_at": "2026-03-13T14:47:03",
+        "saved_at": "2026-03-13T14:47:11"
+      },
+      "files": {
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+        },
+        "gemini_raw_output": {
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+          "channels": 1,
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+        }
+      }
+    },
+    {
+      "record_name": "retake_recommended",
+      "text": "Photo captured. I recommend a retake. Say yes photo to retake, or no photo to keep this one.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
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+      },
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+        "audio_generated_at": "2026-03-13T14:47:30",
+        "last_playback_finished_at": "2026-03-13T14:47:38",
+        "saved_at": "2026-03-13T14:47:41"
+      },
+      "files": {
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+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "retake_yes",
+      "text": "Great. Let us retake. Hold your pose.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
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+      },
+      "timeline": {
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+        "audio_generated_at": "2026-03-13T14:48:01",
+        "last_playback_finished_at": "2026-03-13T14:48:04",
+        "saved_at": "2026-03-13T14:48:12"
+      },
+      "files": {
+        "speaker_recording": {
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+        "gemini_raw_output": {
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+          "channels": 1,
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+        }
+      }
+    },
+    {
+      "record_name": "retake_limit",
+      "text": "Retake limit reached. Keeping the current photo.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 2,
+      "audio_capture": {
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+      },
+      "timeline": {
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+        "audio_generated_at": "2026-03-13T14:48:31",
+        "last_playback_finished_at": "2026-03-13T14:48:43",
+        "saved_at": "2026-03-13T14:48:46"
+      },
+      "files": {
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+        "gemini_raw_output": {
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+        }
+      }
+    },
+    {
+      "record_name": "photo_saved_thanks",
+      "text": "Thank you. Photo saved. Do not forget to check your photos.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T14:49:20",
+        "audio_generated_at": "2026-03-13T14:49:25",
+        "last_playback_finished_at": "2026-03-13T14:49:30",
+        "saved_at": "2026-03-13T14:49:42"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/photo_saved_thanks.wav",
+          "name": "photo_saved_thanks.wav",
+          "size_bytes": 217272,
+          "size_mb": 0.207,
+          "duration_seconds": 4.526,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/photo_saved_thanks_raw.wav",
+          "name": "photo_saved_thanks_raw.wav",
+          "size_bytes": 203564,
+          "size_mb": 0.194,
+          "duration_seconds": 4.24,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "count_3",
+      "text": "Three.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 3,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T19:13:20",
+        "audio_generated_at": "2026-03-13T19:13:22",
+        "last_playback_finished_at": "2026-03-13T19:13:27",
+        "saved_at": "2026-03-13T19:13:31"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/count_3.wav",
+          "name": "count_3.wav",
+          "size_bytes": 44314,
+          "size_mb": 0.042,
+          "duration_seconds": 0.922,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/count_3_raw.wav",
+          "name": "count_3_raw.wav",
+          "size_bytes": 30764,
+          "size_mb": 0.029,
+          "duration_seconds": 0.64,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "count_2",
+      "text": "Two.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 3,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T19:12:57",
+        "audio_generated_at": "2026-03-13T19:12:59",
+        "last_playback_finished_at": "2026-03-13T19:13:05",
+        "saved_at": "2026-03-13T19:13:08"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/count_2.wav",
+          "name": "count_2.wav",
+          "size_bytes": 41282,
+          "size_mb": 0.039,
+          "duration_seconds": 0.859,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/count_2_raw.wav",
+          "name": "count_2_raw.wav",
+          "size_bytes": 26924,
+          "size_mb": 0.026,
+          "duration_seconds": 0.56,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "count_1",
+      "text": "One",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 2,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T19:12:13",
+        "audio_generated_at": "2026-03-13T19:12:15",
+        "last_playback_finished_at": "2026-03-13T19:12:21",
+        "saved_at": "2026-03-13T19:12:24"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/count_1.wav",
+          "name": "count_1.wav",
+          "size_bytes": 44182,
+          "size_mb": 0.042,
+          "duration_seconds": 0.92,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/count_1_raw.wav",
+          "name": "count_1_raw.wav",
+          "size_bytes": 30764,
+          "size_mb": 0.029,
+          "duration_seconds": 0.64,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    },
+    {
+      "record_name": "smile",
+      "text": "Smile.",
+      "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+      "voice_name": "Charon",
+      "replay_count": 1,
+      "audio_capture": {
+        "sink": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo",
+        "monitor_source": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor",
+        "restored_microphone_source": "alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback",
+        "capture_device": "alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo.monitor"
+      },
+      "timeline": {
+        "text_entered_at": "2026-03-13T19:11:35",
+        "audio_generated_at": "2026-03-13T19:11:38",
+        "last_playback_finished_at": "2026-03-13T19:11:39",
+        "saved_at": "2026-03-13T19:11:49"
+      },
+      "files": {
+        "speaker_recording": {
+          "path": "AI_Photographer/Data/Audio/smile.wav",
+          "name": "smile.wav",
+          "size_bytes": 65728,
+          "size_mb": 0.063,
+          "duration_seconds": 1.368,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        },
+        "gemini_raw_output": {
+          "path": "AI_Photographer/Data/Audio/smile_raw.wav",
+          "name": "smile_raw.wav",
+          "size_bytes": 51884,
+          "size_mb": 0.049,
+          "duration_seconds": 1.08,
+          "sample_rate": 24000,
+          "channels": 1,
+          "sample_width_bytes": 2
+        }
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/Data/Settings/config.json b/Data/Settings/config.json
new file mode 100644
index 0000000..8e86872
--- /dev/null
+++ b/Data/Settings/config.json
@@ -0,0 +1,131 @@
+{
+  "paths": {
+    "data_dir": "AI_Photographer/Data/G1",
+    "app_data_dir": "AI_Photographer/Data",
+    "app_settings_dir": "AI_Photographer/Data/Settings",
+    "app_scripts_dir": "AI_Photographer/Data/Scripts",
+    "app_runtime_dir": "AI_Photographer/Data/Runtime",
+    "app_notes_dir": "AI_Photographer/Data/Notes",
+    "audio_prompts_dir": "AI_Photographer/Data/Audio",
+    "audio_prompt_records_file": "AI_Photographer/Data/Settings/audio_prompt_records.json",
+    "scripts_dir": "AI_Photographer/Scripts",
+    "web_dir": "AI_Photographer/Web",
+    "photos_dir": "AI_Photographer/photos/Captures",
+    "people_dir": "AI_Photographer/photos/people",
+    "samples_dir": "AI_Photographer/photos/samples",
+    "replay_recordings_dir": "AI_Photographer/Data/G1",
+    "replay_recorder_script": "",
+    "home_file": "arm_home.jsonl",
+    "photo_phrases_file": "AI_Photographer/Data/Scripts/photo_command_ai.txt",
+    "sanad_script_file": "AI_Photographer/Data/Scripts/sanad_script.txt",
+    "runtime_health_file": "AI_Photographer/Data/Runtime/runtime_health.json",
+    "autonomous_state_file": "AI_Photographer/Data/Runtime/autonomous_state.json",
+    "upload_db": "AI_Photographer/Data/Runtime/upload_db.json"
+  },
+  "timing": {
+    "photo_total_sec": 10.0,
+    "photo_thanks_sec": 3.0,
+    "photo_delay_sec": 5.0,
+    "replay_capture_end_margin_sec": 0.25,
+    "loop_rate": 10.0,
+    "ai_query_interval": 1.0
+  },
+  "server": {
+    "photo_server_port": 8080
+  },
+  "gemini": {
+    "api_key": "AIzaSyDt9Xi83MDZuuPpfwfHyMD92X7ZKdGkqf8",
+    "mic_enabled": true,
+    "model": "models/gemini-2.5-flash-native-audio-preview-12-2025",
+    "voice_name": "Charon",
+    "system_prompt_fallback": "You are Sanad (Bousandah), a friendly Emirati photographer assistant. Speak in UAE dialect (Khaleeji). Be short, energetic, and helpful."
+  },
+  "upload": {
+    "method": "http",
+    "url": "",
+    "s3_bucket": "",
+    "s3_region": "",
+    "s3_key": "",
+    "s3_secret": ""
+  },
+  "mode": {
+    "default_mode": "manual",
+    "current_mode": "manual"
+  },
+  "replay": {
+    "active_file": "photo_G3.jsonl"
+  },
+  "camera": {
+    "camera_index": 0,
+    "frame_width": 640,
+    "frame_height": 480,
+    "fps": 30,
+    "preferred_realsense_serial": "243622071722"
+  },
+  "vision": {
+    "detection_backend": "yolo",
+    "yolo_runtime": "ultralytics",
+    "yolo_ultralytics_device": "cpu",
+    "person_yolo_onnx": "Models/person.pt",
+    "face_yolo_onnx": "",
+    "input_size": 640,
+    "person_class_id": 0,
+    "person_score_thresh": 0.35,
+    "face_score_thresh": 0.35,
+    "nms_iou_thresh": 0.45,
+    "group_min_people": 3,
+    "group_link_distance_px": 220.0,
+    "yolo_strict_required": true,
+    "gemini_context_hz": 8.0,
+    "gemini_context_silent": true,
+    "idle_voice_listen_enabled": true,
+    "hard_target_lock_enabled": true,
+    "retake_prompt_enabled": true,
+    "autonomous_greeting_replay_enabled": true,
+    "autonomous_greeting_replay_file": "right_hand_up.jsonl",
+    "autonomous_capture_replay_enabled": true,
+    "retake_max_per_session": 1,
+    "framing_headroom_min_ratio": 0.06,
+    "framing_headroom_max_ratio": 0.25,
+    "framing_eye_line_min_ratio": 0.28,
+    "framing_eye_line_max_ratio": 0.48,
+    "framing_retake_score_threshold": 0.68,
+    "face_recognition_enabled": true,
+    "face_recognition_threshold": 0.88
+  },
+  "watchdog": {
+    "ws_initial_backoff_sec": 1.0,
+    "ws_max_backoff_sec": 20.0,
+    "component_restart_delay_sec": 1.0,
+    "camera_capture_retry_count": 2,
+    "camera_capture_retry_delay_sec": 0.8
+  },
+  "audio_prompts": {
+    "mode": "audio",
+    "fallback_to_gemini": true,
+    "files": {
+      "welcome_single": "welcome_single.wav",
+      "welcome_group": "welcome_group.wav",
+      "welcome_returning": "welcome_returning.wav",
+      "frame_single": "frame_single.wav",
+      "frame_group": "frame_group.wav",
+      "confirm_reminder": "confirm_reminder.wav",
+      "visitor_left": "visitor_left.wav",
+      "declined": "declined.wav",
+      "confirm_timeout": "confirm_timeout.wav",
+      "session_cancelled": "session_cancelled.wav",
+      "framing_timeout": "framing_timeout.wav",
+      "countdown_intro": "countdown_intro.wav",
+      "count_3": "count_3.wav",
+      "count_2": "count_2.wav",
+      "count_1": "count_1.wav",
+      "smile": "smile.wav",
+      "countdown_cancelled": "countdown_cancelled.wav",
+      "lost_from_frame": "lost_from_frame.wav",
+      "retake_recommended": "retake_recommended.wav",
+      "retake_yes": "retake_yes.wav",
+      "retake_limit": "retake_limit.wav",
+      "photo_saved_thanks": "photo_saved_thanks.wav"
+    }
+  }
+}
diff --git a/Gemini/__init__.py b/Gemini/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Gemini/gemini_voice.py b/Gemini/gemini_voice.py
new file mode 100644
index 0000000..39c1260
--- /dev/null
+++ b/Gemini/gemini_voice.py
@@ -0,0 +1,823 @@
+# gemini_voice.py
+import asyncio
+import base64
+import json
+import time
+import array
+import audioop
+import inspect
+import os
+import re
+import wave
+from pathlib import Path
+
+import pyaudio
+import websockets
+from Core import settings as config
+from Core import audio_prompts
+from Gemini.sanad_text_utils import load_phrase_map, _norm_ar
+from Core.Logger import Logs
+
+FORMAT = pyaudio.paInt16
+CHANNELS = 1
+SEND_SAMPLE_RATE = 16000
+RECEIVE_SAMPLE_RATE = 24000
+CHUNK_SIZE = 512
+
+
+
+
+class HamadGeminiVoice:
+    def __init__(
+        self,
+        photo_phrases_file: str = "photo_command_ai.txt",
+    ):
+        self.sanad_logger = Logs()
+        self.sanad_logger.LogEngine("G1_Logs", "gemini_voice")
+
+
+        self.audio_q = asyncio.Queue()
+        self.speaking = False
+        self.interrupted = False
+        self.pya = pyaudio.PyAudio()
+        self.mic_frames_per_buffer = CHUNK_SIZE
+        self.speaker_frames_per_buffer = CHUNK_SIZE
+
+        self.MIN_THRESHOLD = 3000
+        self.barge_in_threshold = 3000
+        self.REQUIRED_LOUD_CHUNKS = 5
+
+        self.PREBUFFER_CHUNKS = max(1, int(os.environ.get("GEMINI_PREBUFFER_CHUNKS", "4")))
+        self.PLAYBACK_TIMEOUT = max(0.1, float(os.environ.get("GEMINI_PLAYBACK_TIMEOUT", "0.35")))
+        self.BARGE_IN_COOLDOWN = 0.7
+        self.AI_SPEAK_GRACE = 0.25
+
+        self._last_ai_audio_time = 0.0
+        self._ai_speaking_since = 0.0
+        self._barge_in_block_until = 0.0
+
+        self.ECHO_GUARD_SEC = 0.8
+        self._ignore_input_until = 0.0
+        self.SEND_SILENCE_WHEN_SPEAKING = True
+        self.SPEAKING_ENERGY_GATE = 0.85
+        self._silence_pcm = b"\x00" * (CHUNK_SIZE * 2)
+        self._photo_phrases_file = photo_phrases_file
+        self._photo_command_map = None
+        self.audio_gate_open = bool(int(os.environ.get("AUDIO_GATE_OPEN_ON_START", "1")))
+        self.passive_listen_only = False
+        self._cmd_last_ts = {}
+        self.command_cooldown_sec = float(os.environ.get("VOICE_COMMAND_COOLDOWN_SEC", "1.2"))
+        self.device_restart_delay_sec = float(os.environ.get("AUDIO_DEVICE_RESTART_DELAY_SEC", "1.0"))
+        self.require_final_command = bool(int(os.environ.get("VOICE_CMDS_REQUIRE_FINAL", "1")))
+        self.context_silent_default = bool(config.read_vision_gemini_context_silent())
+        self.context_suppress_window_sec = float(os.environ.get("GEMINI_CONTEXT_SUPPRESS_WINDOW_SEC", "1.2"))
+        self.prompt_audio_allow_sec = float(os.environ.get("GEMINI_PROMPT_AUDIO_ALLOW_SEC", "15.0"))
+        self.user_turn_audio_allow_sec = float(os.environ.get("GEMINI_USER_TURN_ALLOW_SEC", "8.0"))
+        self._vision_context_seq = 0
+        self._context_suppress_until = 0.0
+        self._prompt_audio_allow_until = 0.0
+        self._last_user_transcript_ts = 0.0
+        self._last_context_drop_log_ts = 0.0
+        self._last_audio_drop_log_ts = 0.0
+        self._last_transcript_log_text = ""
+        self._last_transcript_log_ts = 0.0
+        self._speaker_queue_drop_count = 0
+        self._ws = None
+        self._ws_seq = 0
+        self._ws_event = asyncio.Event()
+        self._prompt_play_lock = asyncio.Lock()
+        self._health = {
+            "ws_connected": False,
+            "ws_state": "detached",
+            "ws_restarts": 0,
+            "ws_last_error": "",
+            "ws_last_event_ts": 0.0,
+            "ws_last_reason": "",
+            "mic_state": "idle",
+            "mic_restarts": 0,
+            "mic_last_error": "",
+            "mic_last_event_ts": 0.0,
+            "speaker_state": "idle",
+            "speaker_restarts": 0,
+            "speaker_last_error": "",
+            "speaker_last_event_ts": 0.0,
+            "speaker_queue_drops": 0,
+            "speaker_queue_max": 0,
+        }
+        self._component_restart_delay_sec = float(config.read_watchdog_component_restart_delay_sec())
+        self._log_audio_device_summary()
+
+    def _log_user_transcript(self, text: str, is_final: bool, mode: str):
+        txt = str(text or "").strip()
+        if not txt:
+            return
+        now = time.time()
+        if is_final and txt == self._last_transcript_log_text and (now - self._last_transcript_log_ts) < 1.0:
+            return
+        self._last_transcript_log_text = txt
+        self._last_transcript_log_ts = now
+        state = "final" if is_final else "partial"
+        self.sanad_logger.print_and_log(
+            f"🎤 Heard ({state}, mode={mode}): {txt}",
+            message_type="info",
+        )
+
+    def _log_audio_device_summary(self):
+        try:
+            in_info = self.pya.get_default_input_device_info()
+        except Exception:
+            in_info = None
+        try:
+            out_info = self.pya.get_default_output_device_info()
+        except Exception:
+            out_info = None
+
+        def _fmt(info: dict | None) -> str:
+            if not info:
+                return "unavailable"
+            name = str(info.get("name", "unknown"))
+            idx = info.get("index", "?")
+            rate = info.get("defaultSampleRate", "?")
+            return f"{name} (index={idx}, rate={rate})"
+
+        self.sanad_logger.print_and_log(f"🎤 PortAudio input: {_fmt(in_info)}", message_type="info")
+        self.sanad_logger.print_and_log(f"🔈 PortAudio output: {_fmt(out_info)}", message_type="info")
+
+    def set_audio_gate(self, enabled: bool, reason: str = ""):
+        self.audio_gate_open = bool(enabled)
+        state = "OPEN" if self.audio_gate_open else "CLOSED"
+        suffix = f" ({reason})" if reason else ""
+        self.sanad_logger.print_and_log(f"🎧 Audio gate {state}{suffix}", message_type="info")
+
+    def set_passive_listen(self, enabled: bool, reason: str = ""):
+        self.passive_listen_only = bool(enabled)
+        state = "ON" if self.passive_listen_only else "OFF"
+        suffix = f" ({reason})" if reason else ""
+        self.sanad_logger.print_and_log(f"🦻 Passive listen {state}{suffix}", message_type="info")
+
+    def attach_ws(self, ws):
+        if ws is None:
+            return
+        self._ws = ws
+        self._ws_seq += 1
+        self._ws_event.set()
+        self._health["ws_connected"] = True
+        self._health["ws_state"] = "connected"
+        self._health["ws_last_event_ts"] = time.time()
+        self._health["ws_last_reason"] = "attach"
+        if self._ws_seq > 1:
+            self._health["ws_restarts"] = int(self._health.get("ws_restarts", 0)) + 1
+
+    def detach_ws(self, reason: str = ""):
+        old_ws = self._ws
+        self._ws = None
+        self._ws_event.clear()
+        self._health["ws_connected"] = False
+        self._health["ws_state"] = "detached"
+        self._health["ws_last_event_ts"] = time.time()
+        self._health["ws_last_reason"] = str(reason or "")
+        if reason:
+            self._health["ws_last_error"] = str(reason)
+        try:
+            if old_ws is not None:
+                asyncio.create_task(old_ws.close())
+        except Exception:
+            pass
+
+    def is_ws_connected(self) -> bool:
+        ws = self._ws
+        return ws is not None
+
+    async def _wait_for_ws(self, timeout_sec: float | None = None):
+        ws = self._ws
+        if ws is not None:
+            return ws
+        if timeout_sec is None:
+            await self._ws_event.wait()
+            return self._ws
+        if timeout_sec <= 0:
+            return None
+        try:
+            await asyncio.wait_for(self._ws_event.wait(), timeout=timeout_sec)
+        except asyncio.TimeoutError:
+            return None
+        return self._ws
+
+    def get_runtime_health(self) -> dict:
+        out = dict(self._health)
+        out["mic_enabled"] = bool(config.read_gemini_mic_enabled())
+        out["audio_gate_open"] = bool(self.audio_gate_open)
+        out["passive_listen_only"] = bool(self.passive_listen_only)
+        out["speaking"] = bool(self.speaking)
+        out["interrupted"] = bool(self.interrupted)
+        out["speaker_queue_size"] = int(self.audio_q.qsize())
+        out["time"] = time.time()
+        return out
+
+    def _queue_model_audio(self, audio_bytes: bytes):
+        if not audio_bytes:
+            return
+        self.audio_q.put_nowait(audio_bytes)
+
+    def _load_prompt_pcm(self, prompt_path: Path) -> tuple[bytes, float]:
+        with wave.open(str(prompt_path), "rb") as wav_file:
+            channels = int(wav_file.getnchannels())
+            sample_width = int(wav_file.getsampwidth())
+            frame_rate = int(wav_file.getframerate())
+            raw = wav_file.readframes(wav_file.getnframes())
+
+        if channels < 1 or channels > 2:
+            raise ValueError(f"unsupported WAV channel count: {channels}")
+
+        if sample_width != 2:
+            raw = audioop.lin2lin(raw, sample_width, 2)
+            sample_width = 2
+
+        if channels == 2:
+            raw = audioop.tomono(raw, sample_width, 0.5, 0.5)
+            channels = 1
+
+        if frame_rate != RECEIVE_SAMPLE_RATE:
+            raw, _ = audioop.ratecv(raw, sample_width, channels, frame_rate, RECEIVE_SAMPLE_RATE, None)
+
+        duration_sec = len(raw) / float(sample_width * channels * RECEIVE_SAMPLE_RATE) if raw else 0.0
+        return raw, max(0.0, duration_sec)
+
+    async def _play_local_prompt_file(self, prompt_path: Path) -> bool:
+        async with self._prompt_play_lock:
+            try:
+                pcm, duration_sec = await asyncio.to_thread(self._load_prompt_pcm, prompt_path)
+            except Exception as e:
+                self.sanad_logger.print_and_log(
+                    f"⚠️ Prompt audio failed for {prompt_path.name}: {e}",
+                    message_type="warning",
+                )
+                return False
+
+            if not pcm:
+                return False
+
+            now = time.time()
+            self.interrupted = False
+            self.speaking = True
+            self._ai_speaking_since = now
+            self._last_ai_audio_time = now
+            self._ignore_input_until = now + duration_sec + self.ECHO_GUARD_SEC
+            self._prompt_audio_allow_until = max(self._prompt_audio_allow_until, now + duration_sec + 1.0)
+            self.sanad_logger.print_and_log(
+                f"🔊 Prompt audio: {prompt_path.name}",
+                message_type="info",
+            )
+
+            chunk_bytes = max(self.speaker_frames_per_buffer * 2, 4096)
+            for i in range(0, len(pcm), chunk_bytes):
+                self._queue_model_audio(pcm[i:i + chunk_bytes])
+
+            deadline = time.time() + max(2.0, duration_sec + 2.0)
+            while time.time() < deadline:
+                if self.audio_q.empty() and not self.speaking:
+                    break
+                await asyncio.sleep(0.05)
+            return True
+
+    async def play_prompt_key(
+        self,
+        key: str,
+        fallback_text: str = "",
+        allow_gemini_fallback: bool | None = None,
+        wait_timeout_sec: float = 0.0,
+        mode_override: str | None = None,
+    ) -> bool:
+        prompt_mode = str(mode_override or config.read_audio_prompt_mode()).strip().lower()
+        if prompt_mode not in ("audio", "gemini"):
+            prompt_mode = "audio"
+        allow_fallback = (
+            config.read_audio_prompts_fallback_to_gemini()
+            if allow_gemini_fallback is None
+            else bool(allow_gemini_fallback)
+        )
+        try:
+            prompt_path = audio_prompts.prompt_path(key)
+        except Exception as e:
+            self.sanad_logger.print_and_log(f"⚠️ Unknown prompt key {key}: {e}", message_type="warning")
+            prompt_path = None
+
+        if prompt_mode == "gemini" and fallback_text:
+            return await self.send_text_prompt_live(fallback_text, wait_timeout_sec=wait_timeout_sec)
+
+        if prompt_path is not None and prompt_path.exists():
+            played = await self._play_local_prompt_file(prompt_path)
+            if played:
+                return True
+
+        if fallback_text and allow_fallback:
+            return await self.send_text_prompt_live(fallback_text, wait_timeout_sec=wait_timeout_sec)
+        return False
+
+    async def trigger_wake_sequence(self, ws=None, wake_text: str | None = None, prompt_key: str | None = None):
+        """
+        Open mic gate and inject a context prompt so Gemini speaks first.
+        """
+        self.set_audio_gate(True, reason="interaction triggered")
+        prompt = (
+            wake_text
+            or "A tourist has just approached you. Warmly greet them and ask if they would like to take a photo."
+        )
+        if prompt_key:
+            played = await self.play_prompt_key(prompt_key, fallback_text=prompt)
+            if played:
+                return
+        if ws is not None:
+            await self.send_text_prompt(ws, prompt)
+        else:
+            await self.send_text_prompt_live(prompt)
+
+    def _should_suppress_model_audio(self, now_ts: float) -> bool:
+        if self.passive_listen_only:
+            return True
+        if now_ts <= self._prompt_audio_allow_until:
+            return False
+        if (now_ts - self._last_user_transcript_ts) <= self.user_turn_audio_allow_sec:
+            return False
+        return now_ts <= self._context_suppress_until
+
+    def _command_allowed_now(self, cmd: str) -> bool:
+        now = time.time()
+        last = float(self._cmd_last_ts.get(cmd, 0.0))
+        if (now - last) < self.command_cooldown_sec:
+            return False
+        self._cmd_last_ts[cmd] = now
+        return True
+
+    def _write_flag(self, flag_name: str, label: str):
+        try:
+            p = config.SCRIPTS_DIR / flag_name
+            p.write_text(str(time.time()))
+            self.sanad_logger.print_and_log(f"📩 {label} flag written", message_type="info")
+        except Exception as e:
+            self.sanad_logger.print_and_log(f"❌ Failed to write {label} flag: {e}", message_type="error")
+
+    def _mode_value(self) -> str:
+        try:
+            mode = str(config.read_runtime_mode()).strip().lower()
+        except Exception:
+            mode = "manual"
+        if mode not in ("manual", "ai"):
+            mode = "manual"
+        return mode
+
+    def _match_in_mapping(self, text: str, mapping: dict | None):
+        norm = _norm_ar(str(text or ""))
+        if not norm or not mapping:
+            return None
+
+        # Exact phrase first.
+        cmd = mapping.get(norm)
+        if cmd:
+            return cmd
+
+        norm_padded = f" {norm} "
+        norm_nospace = norm.replace(" ", "")
+        # Longest aliases first to avoid matching short words prematurely.
+        for phrase, mapped in sorted(mapping.items(), key=lambda kv: len(kv[0]), reverse=True):
+            p = str(phrase or "").strip()
+            if not p:
+                continue
+            if f" {p} " in norm_padded:
+                return mapped
+            # Arabic/compact forms fallback.
+            p_nospace = p.replace(" ", "")
+            if p_nospace and p_nospace in norm_nospace:
+                return mapped
+            try:
+                if " " in p and re.search(rf"\b{re.escape(p)}\b", norm):
+                    return mapped
+            except Exception:
+                pass
+        return None
+
+    def _match_photo_command_from_text(self, text: str):
+        if self._photo_command_map is None:
+            self._photo_command_map = load_phrase_map(self._photo_phrases_file)
+        return self._match_in_mapping(text, self._photo_command_map)
+
+    def _extract_user_transcripts(self, response: dict, server_content: dict):
+        out = []
+        candidates = [
+            response.get("inputAudioTranscription"),
+            response.get("inputTranscription"),
+            server_content.get("inputAudioTranscription"),
+            server_content.get("inputTranscription"),
+        ]
+        for item in candidates:
+            if item is None:
+                continue
+            if isinstance(item, str):
+                out.append((item, True))
+                continue
+            if isinstance(item, dict):
+                txt = item.get("text") or item.get("transcript") or item.get("content")
+                is_final = item.get("isFinal")
+                if is_final is None:
+                    is_final = item.get("final")
+                if is_final is None:
+                    is_final = item.get("done")
+                if txt:
+                    out.append((str(txt), True if is_final is None else bool(is_final)))
+                parts = item.get("parts")
+                if isinstance(parts, list):
+                    for p in parts:
+                        if isinstance(p, dict):
+                            t = p.get("text")
+                            if t:
+                                out.append((str(t), True))
+            elif isinstance(item, list):
+                for it in item:
+                    if isinstance(it, str):
+                        out.append((it, True))
+                    elif isinstance(it, dict):
+                        t = it.get("text") or it.get("transcript")
+                        if t:
+                            out.append((str(t), bool(it.get("isFinal", True))))
+        return out
+
+    async def _handle_user_transcript(self, text: str, is_final: bool):
+        now = time.time()
+        self._last_user_transcript_ts = now
+        self._prompt_audio_allow_until = max(self._prompt_audio_allow_until, now + self.user_turn_audio_allow_sec)
+
+        mode = self._mode_value()
+        self._log_user_transcript(text, is_final=bool(is_final), mode=mode)
+
+        if self.require_final_command and (not is_final):
+            return
+
+        if mode == "manual":
+            return
+
+        photo_cmd = self._match_photo_command_from_text(text)
+        if photo_cmd:
+            self.sanad_logger.print_and_log(
+                f"🧠 Command match: {photo_cmd}",
+                message_type="info",
+            )
+            if not self._command_allowed_now(photo_cmd):
+                return
+
+            if photo_cmd == "no_photo":
+                self._write_flag("confirm_no.flag", "No photo")
+            else:
+                self._write_flag(
+                    "confirm_yes.flag",
+                    "Yes photo" if photo_cmd == "yes_photo" else "Photo request",
+                )
+                if photo_cmd == "request_photo":
+                    self._write_flag("request_photo.flag", "Photo request")
+            return
+
+    def audio_energy(self, pcm):
+        try:
+            samples = array.array("h", pcm)
+            if not samples:
+                return 0
+            return sum(abs(s) for s in samples) // len(samples)
+        except Exception:
+            return 0
+
+    def calibrate_mic(self):
+        self.sanad_logger.print_and_log("\n🤫 Calibrating Microphone... (Please remain silent)", message_type="info")
+        try:
+            stream = self.pya.open(
+                format=FORMAT,
+                channels=CHANNELS,
+                rate=SEND_SAMPLE_RATE,
+                input=True,
+                frames_per_buffer=self.mic_frames_per_buffer,
+            )
+            values = []
+            for _ in range(40):
+                data = stream.read(CHUNK_SIZE, exception_on_overflow=False)
+                values.append(self.audio_energy(data))
+
+            stream.stop_stream()
+            stream.close()
+
+            avg_noise = sum(values) / len(values)
+            self.barge_in_threshold = max(self.MIN_THRESHOLD, avg_noise * 3.0)
+
+            self.sanad_logger.print_and_log(f"✅ Baseline Noise: {avg_noise:.1f}", message_type="info")
+            self.sanad_logger.print_and_log(f"✅ Interruption Threshold: {self.barge_in_threshold:.1f}", message_type="info")
+        except Exception as e:
+            self.sanad_logger.print_and_log(f"⚠️ Calibration failed: {e}. Using default threshold.", message_type="warning")
+
+    def _ws_connect_kwargs(self):
+        kwargs = {"max_size": None}
+        try:
+            sig = inspect.signature(websockets.connect)
+            if "extra_headers" in sig.parameters:
+                kwargs["extra_headers"] = {"Content-Type": "application/json"}
+            else:
+                kwargs["additional_headers"] = {"Content-Type": "application/json"}
+        except Exception:
+            kwargs["extra_headers"] = {"Content-Type": "application/json"}
+        return kwargs
+
+    async def send_text_prompt(self, ws, text: str, allow_speech: bool = True):
+        msg = {
+            "clientContent": {
+                "turns": [{"role": "user", "parts": [{"text": text}]}],
+                "turnComplete": True
+            }
+        }
+        await ws.send(json.dumps(msg))
+        if allow_speech:
+            self._prompt_audio_allow_until = max(self._prompt_audio_allow_until, time.time() + self.prompt_audio_allow_sec)
+
+    async def send_text_prompt_live(self, text: str, allow_speech: bool = True, wait_timeout_sec: float = 0.0) -> bool:
+        ws = await self._wait_for_ws(timeout_sec=wait_timeout_sec)
+        if ws is None:
+            return False
+        try:
+            await self.send_text_prompt(ws, text, allow_speech=allow_speech)
+            return True
+        except Exception as e:
+            self.detach_ws(reason=f"send_text_prompt_live failed: {e}")
+            return False
+
+    async def send_vision_context(self, ws, context: dict, silent: bool | None = None):
+        if silent is None:
+            silent = bool(self.context_silent_default)
+        self._vision_context_seq += 1
+        seq = self._vision_context_seq
+        payload = dict(context or {})
+        payload["context_seq"] = seq
+        payload["context_type"] = "vision"
+
+        if silent:
+            text = (
+                "SILENT_VISION_CONTEXT. Internal grounding update only; do not speak and do not produce audio. "
+                f"Use this context silently. Payload JSON: {json.dumps(payload, ensure_ascii=False)}"
+            )
+        else:
+            text = f"VISION_CONTEXT_UPDATE: {json.dumps(payload, ensure_ascii=False)}"
+
+        await self.send_text_prompt(ws, text, allow_speech=not silent)
+        if silent:
+            self._context_suppress_until = max(
+                self._context_suppress_until,
+                time.time() + max(0.2, self.context_suppress_window_sec),
+            )
+
+    async def send_vision_context_live(self, context: dict, silent: bool | None = None, wait_timeout_sec: float = 0.0) -> bool:
+        ws = await self._wait_for_ws(timeout_sec=wait_timeout_sec)
+        if ws is None:
+            return False
+        try:
+            await self.send_vision_context(ws, context=context, silent=silent)
+            return True
+        except Exception as e:
+            self.detach_ws(reason=f"send_vision_context_live failed: {e}")
+            return False
+
+    async def keepalive(self, ws=None, every_sec: float = 20.0):
+        """
+        Prevent idle disconnects: periodically send a websocket ping.
+        """
+        while True:
+            try:
+                await asyncio.sleep(every_sec)
+                active_ws = self._ws
+                if active_ws is None:
+                    continue
+                await active_ws.ping()
+            except asyncio.CancelledError:
+                raise
+            except Exception as e:
+                self.detach_ws(reason=f"keepalive ping failed: {e}")
+                await asyncio.sleep(self._component_restart_delay_sec)
+
+    async def capture_mic(self, ws=None):
+        loud_chunks = 0
+        while True:
+            stream = None
+            try:
+                while not self.audio_gate_open:
+                    self._health["mic_state"] = "idle"
+                    self._health["mic_last_event_ts"] = time.time()
+                    await asyncio.sleep(0.1)
+
+                self._health["mic_state"] = "starting"
+                self._health["mic_last_event_ts"] = time.time()
+                stream = await asyncio.to_thread(
+                    self.pya.open,
+                    format=FORMAT,
+                    channels=CHANNELS,
+                    rate=SEND_SAMPLE_RATE,
+                    input=True,
+                    frames_per_buffer=self.mic_frames_per_buffer,
+                )
+                self._health["mic_state"] = "running"
+                self._health["mic_last_event_ts"] = time.time()
+
+                while True:
+                    data = await asyncio.to_thread(stream.read, CHUNK_SIZE, exception_on_overflow=False)
+                    energy = self.audio_energy(data)
+                    now = time.time()
+
+                    if not self.audio_gate_open:
+                        continue
+
+                    if self.speaking and (now >= self._barge_in_block_until):
+                        if (now - self._ai_speaking_since) >= self.AI_SPEAK_GRACE:
+                            loud_chunks = loud_chunks + 1 if energy > self.barge_in_threshold else 0
+                            if loud_chunks > self.REQUIRED_LOUD_CHUNKS:
+                                self.sanad_logger.print_and_log(f"🛑 Interruption! (Energy: {energy})", message_type="warning")
+                                self.interrupted = True
+                                self.speaking = False
+                                loud_chunks = 0
+                                self._barge_in_block_until = now + self.BARGE_IN_COOLDOWN
+                                while not self.audio_q.empty():
+                                    try:
+                                        self.audio_q.get_nowait()
+                                    except asyncio.QueueEmpty:
+                                        break
+
+                    data_to_send = data
+                    if self.SEND_SILENCE_WHEN_SPEAKING and self.speaking:
+                        gate = self.barge_in_threshold * self.SPEAKING_ENERGY_GATE
+                        if energy < gate:
+                            data_to_send = self._silence_pcm
+
+                    b64_audio = base64.b64encode(data_to_send).decode("utf-8")
+                    msg = {
+                        "realtime_input": {
+                            "media_chunks": [{
+                                "data": b64_audio,
+                                "mime_type": f"audio/pcm;rate={SEND_SAMPLE_RATE}",
+                            }]
+                        }
+                    }
+                    active_ws = self._ws
+                    if active_ws is None:
+                        continue
+                    try:
+                        await active_ws.send(json.dumps(msg))
+                    except websockets.exceptions.ConnectionClosed as e:
+                        self.detach_ws(reason=f"mic send ws closed: {e}")
+                        await asyncio.sleep(self._component_restart_delay_sec)
+                    except Exception as e:
+                        self.detach_ws(reason=f"mic send ws error: {e}")
+                        await asyncio.sleep(self._component_restart_delay_sec)
+
+            except asyncio.CancelledError:
+                raise
+            except Exception as e:
+                self.sanad_logger.print_and_log(f"❌ Mic Error: {e} (restarting mic)", message_type="warning")
+                self._health["mic_state"] = "error"
+                self._health["mic_restarts"] = int(self._health.get("mic_restarts", 0)) + 1
+                self._health["mic_last_error"] = str(e)
+                self._health["mic_last_event_ts"] = time.time()
+                await asyncio.sleep(max(self.device_restart_delay_sec, self._component_restart_delay_sec))
+            finally:
+                if stream is not None:
+                    try:
+                        await asyncio.to_thread(stream.stop_stream)
+                    except Exception:
+                        pass
+                    try:
+                        await asyncio.to_thread(stream.close)
+                    except Exception:
+                        pass
+                if self._health.get("mic_state") != "error":
+                    self._health["mic_state"] = "restarting"
+                    self._health["mic_last_event_ts"] = time.time()
+
+    async def receive_audio(self, ws=None):
+        while True:
+            active_ws = self._ws
+            if active_ws is None:
+                await asyncio.sleep(0.05)
+                continue
+            try:
+                msg = await active_ws.recv()
+            except asyncio.CancelledError:
+                raise
+            except websockets.exceptions.ConnectionClosed as e:
+                self.detach_ws(reason=f"receive ws closed: {e}")
+                await asyncio.sleep(self._component_restart_delay_sec)
+                continue
+            except Exception as e:
+                self.detach_ws(reason=f"receive ws error: {e}")
+                await asyncio.sleep(self._component_restart_delay_sec)
+                continue
+
+            try:
+                response = json.loads(msg)
+                server_content = response.get("serverContent", {})
+
+                if server_content.get("interrupted"):
+                    self.interrupted = False
+
+                if self.interrupted:
+                    continue
+
+                # Safety: map commands from USER transcription events (not model text).
+                try:
+                    transcripts = self._extract_user_transcripts(response, server_content)
+                    for txt, is_final in transcripts:
+                        await self._handle_user_transcript(txt, is_final=bool(is_final))
+                except Exception as e:
+                    self.sanad_logger.print_and_log(f"⚠️ Transcript parse warning: {e}", message_type="warning")
+
+                model_turn = server_content.get("modelTurn")
+                if model_turn:
+                    for part in model_turn.get("parts", []):
+                        inline_data = part.get("inlineData")
+                        if inline_data and inline_data.get("data"):
+                            now = time.time()
+                            if self._should_suppress_model_audio(now):
+                                if (now - self._last_context_drop_log_ts) >= 5.0:
+                                    self._last_context_drop_log_ts = now
+                                    self.sanad_logger.print_and_log(
+                                        "🤫 Suppressed unsolicited model audio from context-only turn.",
+                                        message_type="info",
+                                    )
+                                continue
+                            if not self.speaking:
+                                self._ai_speaking_since = now
+                                self.sanad_logger.print_and_log("🔊 Gemini audio response started.", message_type="info")
+                            self.speaking = True
+                            self._last_ai_audio_time = now
+                            self._ignore_input_until = now + self.ECHO_GUARD_SEC
+
+                            audio_bytes = base64.b64decode(inline_data["data"])
+                            self._queue_model_audio(audio_bytes)
+
+            except Exception as e:
+                self.sanad_logger.print_and_log(f"❌ Parse Error: {e}", message_type="error")
+
+    async def play_audio(self):
+        while True:
+            stream = None
+            buffered = False
+            try:
+                self._health["speaker_state"] = "starting"
+                self._health["speaker_last_event_ts"] = time.time()
+                stream = await asyncio.to_thread(
+                    self.pya.open,
+                    format=FORMAT,
+                    channels=CHANNELS,
+                    rate=RECEIVE_SAMPLE_RATE,
+                    output=True,
+                    frames_per_buffer=self.speaker_frames_per_buffer,
+                )
+                self._health["speaker_state"] = "running"
+                self._health["speaker_last_event_ts"] = time.time()
+
+                while True:
+                    if self.interrupted:
+                        await asyncio.sleep(0.01)
+                        continue
+
+                    if self.speaking and not buffered:
+                        while self.audio_q.qsize() < self.PREBUFFER_CHUNKS and self.speaking and not self.interrupted:
+                            await asyncio.sleep(0.01)
+                        buffered = True
+
+                    try:
+                        data = await asyncio.wait_for(self.audio_q.get(), timeout=self.PLAYBACK_TIMEOUT)
+                    except asyncio.TimeoutError:
+                        if self.audio_q.empty() and (time.time() - self._last_ai_audio_time) > 0.25:
+                            self.speaking = False
+                            buffered = False
+                        continue
+
+                    if data:
+                        await asyncio.to_thread(stream.write, data)
+
+                    if self.audio_q.empty() and (time.time() - self._last_ai_audio_time) > 0.25:
+                        self.speaking = False
+                        buffered = False
+
+            except asyncio.CancelledError:
+                raise
+            except Exception as e:
+                self.sanad_logger.print_and_log(f"❌ Speaker Error: {e} (restarting speaker)", message_type="warning")
+                self._health["speaker_state"] = "error"
+                self._health["speaker_restarts"] = int(self._health.get("speaker_restarts", 0)) + 1
+                self._health["speaker_last_error"] = str(e)
+                self._health["speaker_last_event_ts"] = time.time()
+                await asyncio.sleep(max(self.device_restart_delay_sec, self._component_restart_delay_sec))
+            finally:
+                if stream is not None:
+                    try:
+                        await asyncio.to_thread(stream.stop_stream)
+                    except Exception:
+                        pass
+                    try:
+                        await asyncio.to_thread(stream.close)
+                    except Exception:
+                        pass
+                if self._health.get("speaker_state") != "error":
+                    self._health["speaker_state"] = "restarting"
+                    self._health["speaker_last_event_ts"] = time.time()
diff --git a/Gemini/sanad_text_utils.py b/Gemini/sanad_text_utils.py
new file mode 100644
index 0000000..cf63633
--- /dev/null
+++ b/Gemini/sanad_text_utils.py
@@ -0,0 +1,372 @@
+import ast
+import os
+import re
+import time
+import asyncio
+
+from Core import settings as config
+
+# ==================================================
+# 🔤 Arabic & English normalization
+# ==================================================
+
+def _norm_ar(s: str) -> str:
+    s = (s or "").strip().lower()
+    if not s:
+        return ""
+
+    # Arabic punctuation: ؟ ، ؛
+    s = re.sub(r"[\u061F\u060C\u061B]", " ", s)
+
+    # ✅ Keep Arabic, English letters, word chars, and spaces
+    s = re.sub(r"[^\w\s\u0600-\u06FFa-zA-Z]", " ", s)
+
+    # collapse spaces
+    s = re.sub(r"\s+", " ", s).strip()
+
+    # normalize hamza/alif variants
+    s = s.replace("أ", "ا").replace("إ", "ا").replace("آ", "ا")
+
+    # ta marbuta -> ha, alif maqsoora -> ya
+    s = s.replace("ة", "ه").replace("ى", "ي")
+
+    # tatweel
+    s = s.replace("ـ", "")
+
+    # common nickname normalization
+    s = s.replace("ابو", "بو")
+
+    return s.strip()
+
+
+# ==================================================
+# 📂 Load wake phrases from a python file (sanad_arm.txt)
+# Modified to search the local Scripts folder if not found next to module
+# ==================================================
+
+def load_arm_phrases(filename: str = "sanad_arm.txt", *, var_name: str = "WAKE_PHRASES") -> set[str]:
+    base_dir = os.path.dirname(os.path.abspath(__file__))
+
+    # Candidate locations (module dir, module dir / Scripts, parent / Scripts)
+    candidates = [
+        os.path.join(base_dir, filename),
+        os.path.join(base_dir, "Scripts", filename),
+        os.path.join(base_dir, "..", "Scripts", filename),
+    ]
+
+    arm_path = None
+    for c in candidates:
+        if os.path.exists(c):
+            arm_path = c
+            break
+
+    if arm_path is None:
+        raise FileNotFoundError(f"Arm phrases file not found in candidates: {candidates}")
+
+    print(f"📂 Loading arm phrases from: {arm_path} (var={var_name})")
+
+    with open(arm_path, "r", encoding="utf-8-sig") as f:
+        raw = f.read()
+
+    # Try to parse as python file (legacy format with WAKE_PHRASES variables).
+    # Uses ast.parse + ast.literal_eval instead of exec() for safety.
+    try:
+        tree = ast.parse(raw)
+        for node in ast.walk(tree):
+            if isinstance(node, ast.Assign):
+                for target in node.targets:
+                    if isinstance(target, ast.Name) and target.id == var_name:
+                        phrases = ast.literal_eval(node.value)
+                        if isinstance(phrases, (set, list, tuple)):
+                            out = {_norm_ar(str(p)) for p in phrases if str(p).strip()}
+                            out = {p for p in out if p}
+                            print(f"✅ Loaded {len(out)} wake phrases from file variable: {var_name}")
+                            return out
+    except Exception:
+        # fall through to plain text parsing
+        pass
+
+    # Plain-text newline-separated phrases fallback
+    lines = [ln.strip() for ln in raw.splitlines()]
+    cand = [ln for ln in lines if ln and not ln.startswith("#")]
+    out = {_norm_ar(ln) for ln in cand}
+    out = {p for p in out if p}
+    print(f"✅ Loaded {len(out)} wake phrases from plain text file: {arm_path}")
+    return out
+
+
+# ==================================================
+# 🧠 Wake phrase matching + scheduling
+# ==================================================
+
+def _is_valid_text(s: str) -> bool:
+    # Allow Arabic OR English letters
+    has_ar = bool(re.search(r"[\u0600-\u06FF]", s or ""))
+    has_en = bool(re.search(r"[a-zA-Z]", s or ""))
+    return has_ar or has_en
+
+
+def _strip_ya_prefix(s: str) -> str:
+    s = (s or "").strip()
+    if not s:
+        return ""
+    if s.startswith("يا "):
+        return s[3:].strip()
+    if s.startswith("يا"):
+        return s[2:].strip()
+    return s
+
+
+def _remove_al_prefix_words(text: str) -> str:
+    if not text:
+        return ""
+    parts = text.split()
+    out = []
+    for w in parts:
+        if w.startswith("ال") and len(w) > 2:
+            out.append(w[2:])
+        else:
+            out.append(w)
+    return " ".join(out).strip()
+
+
+def _maybe_trigger_arm(
+    obj,
+    transcript_text: str,
+    wake_phrases: set[str],
+    *,
+    fire_on_wake_match: bool = False,
+    arm_trigger_fn=None,
+) -> bool:
+    if not transcript_text or not wake_phrases:
+        return False
+
+    # initialization of state variables (copied from original logic)
+    if not hasattr(obj, "_asr_buf"):
+        obj._asr_buf = ""
+    if not hasattr(obj, "_asr_last_time"):
+        obj._asr_last_time = 0.0
+    if not hasattr(obj, "ASR_WINDOW_SEC"):
+        obj.ASR_WINDOW_SEC = 2.0
+    if not hasattr(obj, "ASR_SHORT_TOKEN_BONUS_SEC"):
+        obj.ASR_SHORT_TOKEN_BONUS_SEC = 1.0
+    if not hasattr(obj, "ASR_JOIN_NO_SPACE_MAXLEN"):
+        obj.ASR_JOIN_NO_SPACE_MAXLEN = 2
+    if not hasattr(obj, "ASR_MAX_CHARS"):
+        obj.ASR_MAX_CHARS = 120
+
+    if not hasattr(obj, "_last_trigger_norm"):
+        obj._last_trigger_norm = ""
+    if not hasattr(obj, "_last_trigger_time"):
+        obj._last_trigger_time = 0.0
+    if not hasattr(obj, "TRIGGER_DEDUP_WINDOW"):
+        obj.TRIGGER_DEDUP_WINDOW = 2.0
+
+    if not hasattr(obj, "_pending_arm_wave"):
+        obj._pending_arm_wave = False
+    if not hasattr(obj, "_pending_arm_wave_fired"):
+        obj._pending_arm_wave_fired = False
+    if not hasattr(obj, "_pending_arm_wave_set_time"):
+        obj._pending_arm_wave_set_time = 0.0
+    if not hasattr(obj, "PENDING_ARM_TTL"):
+        obj.PENDING_ARM_TTL = 6.0
+
+    if not hasattr(obj, "_pending_arm_trigger_fn"):
+        obj._pending_arm_trigger_fn = None
+    if not hasattr(obj, "_pending_arm_fallback_time"):
+        obj._pending_arm_fallback_time = 0.0
+
+    if not hasattr(obj, "_last_piece_call_norm"):
+        obj._last_piece_call_norm = ""
+    if not hasattr(obj, "_last_piece_call_time"):
+        obj._last_piece_call_time = 0.0
+
+    if not hasattr(obj, "_asr_stream"):
+        obj._asr_stream = ""
+    if not hasattr(obj, "ASR_STREAM_MAX_CHARS"):
+        obj.ASR_STREAM_MAX_CHARS = 80
+
+    dup_call_window = float(getattr(obj, "DUP_CALL_WINDOW_SEC", 0.25))
+    dup_asr_repeat_window = float(getattr(obj, "DUP_ASR_REPEAT_WINDOW_SEC", 0.9))
+    pending_fallback_sec = float(getattr(obj, "PENDING_ARM_FALLBACK_SEC", 0.65))
+
+    piece_raw = (transcript_text or "").strip()
+    if not piece_raw:
+        return False
+
+    piece_norm = _norm_ar(piece_raw)
+    if not piece_norm:
+        return False
+
+    now = time.time()
+
+    if not _is_valid_text(piece_norm):
+        return False
+
+    duplicate_call = (
+        (piece_norm == obj._last_piece_call_norm)
+        and ((now - obj._last_piece_call_time) < dup_call_window)
+    )
+
+    repeated_asr = (
+        (piece_norm == obj._last_piece_call_norm)
+        and ((now - obj._last_piece_call_time) < dup_asr_repeat_window)
+    )
+
+    obj._last_piece_call_norm = piece_norm
+    obj._last_piece_call_time = now
+
+    if not duplicate_call and not repeated_asr:
+        print(f"📝 USER SAID (raw): {piece_raw}")
+        print(f"📝 USER SAID (norm): {piece_norm}")
+
+    if not duplicate_call and not repeated_asr:
+        if obj._asr_last_time:
+            gap = now - obj._asr_last_time
+            window = obj.ASR_WINDOW_SEC
+            if len(piece_norm) <= obj.ASR_JOIN_NO_SPACE_MAXLEN:
+                window += obj.ASR_SHORT_TOKEN_BONUS_SEC
+            if gap > window:
+                obj._asr_buf = ""
+                obj._asr_stream = ""
+
+        obj._asr_last_time = now
+
+        if obj._asr_buf:
+            if len(piece_norm) <= obj.ASR_JOIN_NO_SPACE_MAXLEN:
+                obj._asr_buf = (obj._asr_buf + piece_norm).strip()
+            else:
+                obj._asr_buf = (obj._asr_buf + " " + piece_norm).strip()
+        else:
+            obj._asr_buf = piece_norm
+
+        compact = piece_norm.replace(" ", "")
+        obj._asr_stream = (obj._asr_stream + compact)[-obj.ASR_STREAM_MAX_CHARS :]
+
+        if len(obj._asr_buf) > obj.ASR_MAX_CHARS:
+            obj._asr_buf = obj._asr_buf[-obj.ASR_MAX_CHARS :]
+
+    buf_norm = _norm_ar(obj._asr_buf)
+    buf_nospace = buf_norm.replace(" ", "")
+    buf_noal = _remove_al_prefix_words(buf_norm)
+    buf_noal_nospace = buf_noal.replace(" ", "")
+    stream = _norm_ar(obj._asr_stream).replace(" ", "")
+    stream_noal = _remove_al_prefix_words(stream)
+
+    if not duplicate_call and not repeated_asr:
+        print(f"🧩 ASR BUFFER: {buf_norm}")
+
+    if (
+        buf_norm == obj._last_trigger_norm
+        and (now - obj._last_trigger_time) < obj.TRIGGER_DEDUP_WINDOW
+    ):
+        return False
+
+    for phrase in wake_phrases:
+        p_norm = _strip_ya_prefix(_norm_ar(str(phrase)))
+        if not p_norm:
+            continue
+
+        p_nospace = p_norm.replace(" ", "")
+        p_noal = _remove_al_prefix_words(p_norm)
+        p_noal_nospace = p_noal.replace(" ", "")
+
+        pattern = r'\b' + re.escape(p_norm) + r'\b'
+        hit_buf = bool(re.search(pattern, buf_norm)) or (p_nospace and p_nospace == buf_nospace)
+        hit_buf = hit_buf or (p_noal and (p_noal in buf_noal or (p_noal_nospace and p_noal_nospace in buf_noal_nospace)))
+
+        hit_stream = False
+        if p_nospace and p_nospace in stream:
+            hit_stream = True
+        elif p_noal_nospace and p_noal_nospace in stream_noal:
+            hit_stream = True
+
+        if hit_buf or hit_stream:
+            if hit_stream and not hit_buf:
+                print(f"⚡ FAST MATCH: '{phrase}' (recent tokens)")
+            else:
+                print(f"✅ MATCH: '{phrase}'  in  BUFFER='{obj._asr_buf}'")
+
+            obj._last_trigger_norm = buf_norm
+            obj._last_trigger_time = now
+
+            obj._asr_buf = ""
+            obj._asr_last_time = 0.0
+            obj._asr_stream = ""
+
+            if fire_on_wake_match:
+                if arm_trigger_fn:
+                    asyncio.create_task(asyncio.to_thread(arm_trigger_fn))
+                obj._pending_arm_wave = False
+                obj._pending_arm_wave_fired = False
+                obj._pending_arm_wave_set_time = 0.0
+                obj._pending_arm_trigger_fn = None
+                obj._pending_arm_fallback_time = 0.0
+            else:
+                obj._pending_arm_wave = True
+                obj._pending_arm_wave_fired = False
+                obj._pending_arm_wave_set_time = now
+                obj._pending_arm_trigger_fn = arm_trigger_fn
+                obj._pending_arm_fallback_time = now + pending_fallback_sec
+
+            return True
+
+    return False
+
+
+# ==================================================
+# 🔁 Phrase map loader (plain-text grouped format)
+# Format: groups separated by blank lines. First line = canonical command,
+# following lines = aliases.
+_phrase_map_cache = {}
+
+def load_phrase_map(filename: str = "photo_command_ai.txt") -> dict:
+    base_dir = os.path.dirname(os.path.abspath(__file__))
+    candidates = [
+        str(config.PHOTO_PHRASES_FILE),
+        os.path.join(base_dir, filename),
+        os.path.join(base_dir, "Scripts", filename),
+        os.path.join(base_dir, "Data", filename),
+        os.path.join(base_dir, "..", "Data", "Scripts", filename),
+        os.path.join(base_dir, "..", "Scripts", filename),
+        os.path.join(base_dir, "..", "Data", filename),
+    ]
+    path = None
+    for c in candidates:
+        if os.path.exists(c):
+            path = c
+            break
+    if path is None:
+        return {}
+
+    if path in _phrase_map_cache:
+        return _phrase_map_cache[path]
+
+    with open(path, 'r', encoding='utf-8-sig') as f:
+        lines = [ln.rstrip() for ln in f.readlines()]
+
+    groups = []
+    cur = []
+    for ln in lines:
+        s = ln.strip()
+        if not s:
+            if cur:
+                groups.append(cur)
+                cur = []
+            continue
+        if s.startswith("#"):
+            continue
+        cur.append(s)
+    if cur:
+        groups.append(cur)
+
+    mapping = {}
+    for g in groups:
+        cmd = g[0]
+        aliases = g
+        for a in aliases:
+            mapping[_norm_ar(a)] = cmd
+
+    _phrase_map_cache[path] = mapping
+    print(f"✅ Loaded phrase mapping from {path}: {len(mapping)} aliases")
+    return mapping
diff --git a/Gemini/voice_sanad.py b/Gemini/voice_sanad.py
new file mode 100644
index 0000000..903c4e6
--- /dev/null
+++ b/Gemini/voice_sanad.py
@@ -0,0 +1,463 @@
+#!/usr/bin/env python3
+"""
+voice_sanad.py (PRODUCTION)
+- Starts photo server ONCE and keeps it alive.
+- Initializes DDS ONCE.
+- Keeps core components alive (mic/speaker/receive/trigger/autonomous).
+- Uses a dedicated WS supervisor loop that reconnects only the Gemini channel.
+"""
+
+import asyncio
+import json
+import os
+import random
+import time
+from pathlib import Path
+
+import websockets
+
+from Core.Logger import Logs
+
+from Core import settings as config
+from Core.settings import (
+    PHOTOS_DIR,
+    PHOTO_SERVER_PORT,
+    MODEL,
+    VOICE_NAME,
+    GEMINI_API_KEY,
+    PHOTO_TOTAL_SEC,
+    PHOTO_DELAY_SEC,
+    load_system_prompt,
+)
+
+from Server.photo_server import start_photo_server
+from Gemini.gemini_voice import HamadGeminiVoice
+
+
+sanad_logger = Logs()
+sanad_logger.LogEngine("G1_Logs", "voice_sanad")
+
+API_KEY = GEMINI_API_KEY.strip()
+if not API_KEY:
+    raise RuntimeError(f"Gemini API key is empty. Set gemini.api_key in {config.CONFIG_JSON}.")
+
+URI = (
+    "wss://generativelanguage.googleapis.com/ws/"
+    "google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent"
+    f"?key={API_KEY}"
+)
+
+RUNTIME_HEALTH_FILE = Path(config.RUNTIME_HEALTH_FILE)
+INTERACTION_FLAG_FILE = Path(config.SCRIPTS_DIR) / "interaction_triggered.flag"
+
+
+def _build_setup_message() -> dict:
+    system_prompt = load_system_prompt()
+    return {
+        "setup": {
+            "model": MODEL,
+            "generationConfig": {
+                "responseModalities": ["AUDIO"],
+                "speechConfig": {
+                    "voiceConfig": {"prebuiltVoiceConfig": {"voiceName": VOICE_NAME}}
+                },
+            },
+            "inputAudioTranscription": {},
+            "systemInstruction": {"parts": [{"text": system_prompt}]},
+        }
+    }
+
+
+def _read_runtime_mode_safe() -> str:
+    try:
+        mode = str(config.read_runtime_mode()).strip().lower()
+    except Exception:
+        mode = "manual"
+    return mode if mode in ("manual", "ai") else "manual"
+
+
+def _interaction_active_now() -> bool:
+    try:
+        return INTERACTION_FLAG_FILE.exists()
+    except Exception:
+        return False
+
+
+def _apply_idle_audio_policy(voice: HamadGeminiVoice, autonomous_enabled: bool):
+    runtime_mode = _read_runtime_mode_safe()
+    idle_voice_listen_enabled = bool(config.read_vision_idle_voice_listen_enabled())
+    mic_enabled = bool(config.read_gemini_mic_enabled())
+
+    if not mic_enabled:
+        voice.set_passive_listen(False, reason="mic disabled")
+        voice.set_audio_gate(False, reason="mic disabled")
+        return
+
+    if runtime_mode != "ai":
+        voice.set_passive_listen(False, reason=f"{runtime_mode} mode")
+        voice.set_audio_gate(True, reason=f"{runtime_mode} mode")
+        return
+
+    if autonomous_enabled:
+        if idle_voice_listen_enabled:
+            voice.set_passive_listen(True, reason="autonomous idle")
+            voice.set_audio_gate(True, reason="autonomous idle listen")
+        else:
+            voice.set_passive_listen(False, reason="autonomous idle")
+            voice.set_audio_gate(False, reason="autonomous idle")
+        return
+
+    voice.set_passive_listen(False, reason="ai mode")
+    voice.set_audio_gate(True, reason="ai mode")
+
+
+async def _write_runtime_health_loop(voice: HamadGeminiVoice, interval_sec: float = 1.0):
+    while True:
+        try:
+            payload = voice.get_runtime_health() if hasattr(voice, "get_runtime_health") else {}
+            payload = dict(payload or {})
+            payload["model"] = MODEL
+            payload["time"] = payload.get("time") or time.time()
+            RUNTIME_HEALTH_FILE.parent.mkdir(parents=True, exist_ok=True)
+            RUNTIME_HEALTH_FILE.write_text(json.dumps(payload, ensure_ascii=False), encoding="utf-8")
+        except Exception as e:
+            sanad_logger.print_and_log(f"Runtime health write failed: {e}", "warning")
+        await asyncio.sleep(max(0.2, float(interval_sec)))
+
+
+async def _run_component_forever(name: str, coro_factory, restart_delay_sec: float):
+    while True:
+        try:
+            await coro_factory()
+            sanad_logger.print_and_log(f"⚠️ {name} loop ended; restarting.", "warning")
+        except asyncio.CancelledError:
+            raise
+        except Exception as e:
+            sanad_logger.print_and_log(f"❌ {name} loop error: {e}. Restarting.", "warning")
+        await asyncio.sleep(max(0.1, float(restart_delay_sec)))
+
+
+async def _run_mode_policy_sync(voice: HamadGeminiVoice, autonomous_enabled: bool, interval_sec: float = 0.5):
+    last_signature = None
+    while True:
+        try:
+            await asyncio.sleep(max(0.2, float(interval_sec)))
+            if not voice.is_ws_connected():
+                continue
+            runtime_mode = _read_runtime_mode_safe()
+            mic_enabled = bool(config.read_gemini_mic_enabled())
+            idle_voice_listen_enabled = bool(config.read_vision_idle_voice_listen_enabled())
+            signature = (runtime_mode, mic_enabled, idle_voice_listen_enabled, bool(autonomous_enabled))
+            if not mic_enabled:
+                if signature != last_signature:
+                    _apply_idle_audio_policy(voice, autonomous_enabled=autonomous_enabled)
+                    last_signature = signature
+                continue
+            if _interaction_active_now():
+                last_signature = signature
+                continue
+            if signature != last_signature:
+                _apply_idle_audio_policy(voice, autonomous_enabled=autonomous_enabled)
+                last_signature = signature
+        except asyncio.CancelledError:
+            raise
+        except Exception as e:
+            sanad_logger.print_and_log(f"⚠️ Mode policy sync error: {e}", "warning")
+
+
+async def _run_autonomous_forever(hub, replay, voice, restart_delay_sec: float):
+    from Modes.AI.autonomous_manager import AutonomousManager
+
+    while True:
+        am = AutonomousManager()
+        try:
+            await am.run(hub=hub, replay=replay, voice=voice, ws=None)
+            sanad_logger.print_and_log("⚠️ Autonomous manager exited; restarting.", "warning")
+        except asyncio.CancelledError:
+            try:
+                am.stop()
+            except Exception:
+                pass
+            raise
+        except Exception as e:
+            sanad_logger.print_and_log(f"❌ Autonomous manager error: {e}. Restarting.", "warning")
+        await asyncio.sleep(max(0.2, float(restart_delay_sec)))
+
+
+async def _run_ws_supervisor(
+    voice: HamadGeminiVoice,
+    autonomous_enabled: bool,
+    dashboard_url: str | None = None,
+    manual_lean_runtime: bool = False,
+):
+    backoff = float(config.read_watchdog_ws_initial_backoff_sec())
+    max_backoff = float(config.read_watchdog_ws_max_backoff_sec())
+
+    while True:
+        sanad_logger.print_and_log(f"\n🚀 Connecting to Gemini ({MODEL})...", message_type="info")
+        ws = None
+        try:
+            async with websockets.connect(URI, **voice._ws_connect_kwargs()) as ws:
+                setup_msg = _build_setup_message()
+                await ws.send(json.dumps(setup_msg))
+                await ws.recv()
+
+                voice.attach_ws(ws)
+                backoff = float(config.read_watchdog_ws_initial_backoff_sec())
+                _apply_idle_audio_policy(voice, autonomous_enabled=autonomous_enabled)
+
+                sanad_logger.print_and_log("🎙️ Connected! Sanad ready.", message_type="info")
+                if dashboard_url:
+                    base_url = dashboard_url.rstrip("/")
+                    sanad_logger.print_and_log(f"🌐 Dashboard: {base_url}/", "info")
+                    sanad_logger.print_and_log(f"📊 Runtime Health API: {base_url}/api/runtime_health", "info")
+                    sanad_logger.print_and_log("🖼️ Live Preview: OFF by default. Enable it from the dashboard when needed.", "info")
+                sanad_logger.print_and_log("🛡️ Idle behavior: no auto-shutdown on silence. Gemini WS keepalive is active.", "info")
+                if manual_lean_runtime:
+                    sanad_logger.print_and_log("🎮 Manual lean runtime: voice conversation only. Restart in AI mode for replay/capture/autonomous services.", "info")
+                else:
+                    sanad_logger.print_and_log("🎮 Controls:", "info")
+                    sanad_logger.print_and_log("   - R2+X : Replay + Photographer Talk + Take Photo", "info")
+                    sanad_logger.print_and_log("   - R2+L1: HARD CANCEL safety combo (AI/manual) -> cancel session/replay", "info")
+
+                await ws.wait_closed()
+        except asyncio.CancelledError:
+            if ws is not None:
+                try:
+                    await ws.close()
+                except Exception:
+                    pass
+            raise
+        except websockets.exceptions.ConnectionClosed as e:
+            sanad_logger.print_and_log(f"⚠️ WebSocket closed: {e}", message_type="warning")
+        except Exception as e:
+            sanad_logger.print_and_log(f"❌ WS supervisor error: {e}", message_type="error")
+        finally:
+            voice.detach_ws(reason="ws supervisor disconnect")
+
+        sleep_s = backoff + random.uniform(0.0, 0.8)
+        sanad_logger.print_and_log(f"🔁 Reconnecting in {sleep_s:.1f}s...", message_type="warning")
+        await asyncio.sleep(max(0.1, sleep_s))
+        backoff = min(max_backoff, backoff * 1.7)
+
+
+def _manual_lean_runtime_enabled(startup_mode: str) -> bool:
+    if startup_mode != "manual":
+        return False
+    raw = os.environ.get("MANUAL_LEAN_RUNTIME")
+    if raw is None or raw == "":
+        return False
+    return str(raw).strip().lower() in ("1", "true", "yes", "on", "y")
+
+
+async def _run_autonomous_mode_supervisor(hub, replay, voice, restart_delay_sec: float, poll_sec: float = 0.5):
+    task = None
+    last_should_run = None
+    try:
+        while True:
+            should_run = _read_runtime_mode_safe() == "ai"
+            if should_run != last_should_run:
+                if should_run:
+                    sanad_logger.print_and_log("🤖 AI mode active: starting autonomous manager.", "info")
+                else:
+                    sanad_logger.print_and_log("🤖 Manual mode active: autonomous manager paused.", "info")
+                last_should_run = should_run
+
+            if should_run:
+                if task is None or task.done():
+                    task = asyncio.create_task(
+                        _run_autonomous_forever(hub=hub, replay=replay, voice=voice, restart_delay_sec=restart_delay_sec)
+                    )
+            elif task is not None:
+                task.cancel()
+                await asyncio.gather(task, return_exceptions=True)
+                task = None
+
+            await asyncio.sleep(max(0.2, float(poll_sec)))
+    finally:
+        if task is not None:
+            task.cancel()
+            await asyncio.gather(task, return_exceptions=True)
+
+
+async def main():
+    startup_mode = _read_runtime_mode_safe()
+    autonomous_enabled = bool(int(os.environ.get("AUTONOMOUS_ENABLE", "0")))
+    manual_lean_runtime = _manual_lean_runtime_enabled(startup_mode)
+
+    hub = None
+    replay = None
+    dashboard_capture_func = None
+    dashboard_replay_test_func = None
+
+    if manual_lean_runtime:
+        sanad_logger.print_and_log(
+            "🪶 Manual lean runtime active: Gemini + dashboard only. DDS, replay, uploader, and teleimager-dependent startup are skipped.",
+            "info",
+        )
+
+        def _manual_capture_unavailable() -> str:
+            return "[ERR] Capture unavailable in manual lean runtime. Restart in AI mode for camera/replay services."
+
+        dashboard_capture_func = _manual_capture_unavailable
+    else:
+        from unitree_sdk2py.core.channel import ChannelSubscriber, ChannelFactoryInitialize
+        from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowState_
+        from Modes.Manual.controller import auto_pick_iface, LowStateHub
+        from Modes.Manual.replay_engine import ReplayWithHome
+        from Server.capture_service import capture_with_replay_sync, ensure_replay_integrity
+
+        iface = auto_pick_iface()
+        sanad_logger.print_and_log(f"🌐 DDS iface: {iface}", "info")
+        ChannelFactoryInitialize(0, iface)
+
+        hub = LowStateHub(watchdog_timeout=0.25)
+        sub = ChannelSubscriber("rt/lowstate", LowState_)
+        sub.Init(hub.handler, 10)
+
+        replay = ReplayWithHome(hub, watchdog_disable_after=1.0)
+
+        startup_replay = config.read_selected_replay_path()
+        fallback_replay = config.DATA_DIR / "photo_G3.jsonl"
+        selected_replay, replay_report = ensure_replay_integrity(startup_replay, fallback_replay)
+        if not replay_report.get("active", {}).get("ok", False):
+            sanad_logger.print_and_log(
+                f"⚠️ Active replay invalid: {replay_report.get('active', {}).get('error', 'unknown')}",
+                "warning",
+            )
+        elif not replay_report.get("active", {}).get("trigger_ok", False):
+            sanad_logger.print_and_log(
+                "⚠️ Active replay has no trigger markers. Timed fallback capture will be used.",
+                "warning",
+            )
+        if replay_report.get("fallback_used"):
+            sanad_logger.print_and_log(
+                f"⚠️ Using fallback replay: {selected_replay.name}",
+                "warning",
+            )
+        if replay_report.get("degraded_no_trigger"):
+            sanad_logger.print_and_log(
+                "⚠️ No replay with trigger markers found. Running in degraded triggerless mode.",
+                "warning",
+            )
+        config.REPLAY_FILE = selected_replay
+        try:
+            rel_name = str(selected_replay.resolve().relative_to(config.DATA_DIR)).replace("\\", "/")
+            config.write_selected_replay_name(rel_name)
+        except Exception:
+            pass
+
+        def _capture_from_dashboard() -> str:
+            base_prefix = os.environ.get("PHOTO_PREFIX", "photo").strip() or "photo"
+            delay = max(0.0, min(PHOTO_DELAY_SEC, PHOTO_TOTAL_SEC))
+            return capture_with_replay_sync(
+                replay_runner=replay,
+                replay_file=config.REPLAY_FILE,
+                home_file=config.HOME_FILE,
+                delay_sec=delay,
+                prefix=base_prefix,
+                speed=1.0,
+            )
+
+        dashboard_capture_func = _capture_from_dashboard
+
+        def _test_replay_from_dashboard(replay_name: str) -> str:
+            try:
+                candidate = config.resolve_replay_path(replay_name)
+            except Exception as e:
+                return f"[ERR] invalid replay path: {e}"
+            if not candidate.exists():
+                return "[ERR] replay not found"
+            if replay.is_playing:
+                return "[ERR] replay already in progress"
+            replay.run(candidate, config.HOME_FILE, speed=1.0)
+            return str(candidate)
+
+        dashboard_replay_test_func = _test_replay_from_dashboard
+
+    url = start_photo_server(
+        PHOTOS_DIR,
+        port=PHOTO_SERVER_PORT,
+        capture_func=dashboard_capture_func,
+        replay_test_func=dashboard_replay_test_func,
+    )
+    sanad_logger.print_and_log(f"🖼️ Phone gallery: {url}", message_type="info")
+
+    if not manual_lean_runtime:
+        from Server.uploader import start_uploader
+
+        try:
+            start_uploader(PHOTOS_DIR)
+        except Exception as e:
+            sanad_logger.print_and_log(f"Failed to start uploader: {e}", message_type="warning")
+
+    voice = HamadGeminiVoice(
+        photo_phrases_file=str(config.PHOTO_PHRASES_FILE),
+    )
+
+    if startup_mode == "ai" or autonomous_enabled:
+        voice.calibrate_mic()
+    else:
+        sanad_logger.print_and_log("🎙️ Mic calibration skipped at startup (manual mode).", "info")
+        sanad_logger.print_and_log("ℹ️ Manual mode: mic follows dashboard toggle, but AI photo commands and AI detection stay disabled until AI mode.", "info")
+    restart_delay = float(config.read_watchdog_component_restart_delay_sec())
+
+    tasks = [
+        asyncio.create_task(_run_component_forever("capture_mic", lambda: voice.capture_mic(), restart_delay)),
+        asyncio.create_task(_run_component_forever("receive_audio", lambda: voice.receive_audio(), restart_delay)),
+        asyncio.create_task(_run_component_forever("play_audio", lambda: voice.play_audio(), restart_delay)),
+        asyncio.create_task(_run_component_forever("keepalive", lambda: voice.keepalive(every_sec=20.0), restart_delay)),
+        asyncio.create_task(_run_component_forever("runtime_health", lambda: _write_runtime_health_loop(voice, 1.0), restart_delay)),
+        asyncio.create_task(
+            _run_ws_supervisor(
+                voice,
+                autonomous_enabled=autonomous_enabled,
+                dashboard_url=url,
+                manual_lean_runtime=manual_lean_runtime,
+            )
+        ),
+        asyncio.create_task(_run_mode_policy_sync(voice, autonomous_enabled=autonomous_enabled)),
+    ]
+
+    if not manual_lean_runtime:
+        from Modes.Manual.trigger_loop import trigger_loop
+
+        tasks.append(
+            asyncio.create_task(
+                _run_component_forever(
+                    "trigger_loop",
+                    lambda: trigger_loop(hub=hub, replay=replay, voice=voice, take_photo_sync_callable=None, ws=None),
+                    restart_delay,
+                )
+            )
+        )
+
+    if autonomous_enabled and not manual_lean_runtime:
+        tasks.append(
+            asyncio.create_task(
+                _run_autonomous_mode_supervisor(
+                    hub=hub,
+                    replay=replay,
+                    voice=voice,
+                    restart_delay_sec=restart_delay,
+                )
+            )
+        )
+        sanad_logger.print_and_log("🤖 Autonomous services armed (AUTONOMOUS_ENABLE=1). AI mode can start without restart.", "info")
+
+    try:
+        await asyncio.gather(*tasks)
+    finally:
+        for t in tasks:
+            if not t.done():
+                t.cancel()
+        await asyncio.gather(*tasks, return_exceptions=True)
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        sanad_logger.print_and_log("\n👋 Ma'a Salama (Goodbye)!", message_type="info")
+    except Exception as e:
+        sanad_logger.print_and_log(f"\n❌ Fatal Error: {e}", message_type="error")
diff --git a/Models/person.pt b/Models/person.pt
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diff --git a/Modes/AI/__init__.py b/Modes/AI/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Modes/AI/autonomous_manager.py b/Modes/AI/autonomous_manager.py
new file mode 100644
index 0000000..69eb33e
--- /dev/null
+++ b/Modes/AI/autonomous_manager.py
@@ -0,0 +1,1457 @@
+import asyncio
+import json
+import os
+import threading
+import time
+from pathlib import Path
+from threading import Thread
+
+import cv2
+
+from Modes.AI.vision_detector import VisionDetector
+from Core import settings as config
+from Core.error_events import record_error
+from Core.Logger import Logs
+from Core import people_registry
+from Server.capture_service import capture_with_replay_sync, replay_timing_profile
+
+sanad_logger = Logs()
+sanad_logger.LogEngine("G1_Logs", "autonomous_manager")
+
+
+class AutonomousManager:
+    """
+    Autonomous flow:
+      IDLE -> WAIT_CONFIRM -> FRAMING -> COUNTDOWN -> COMPLETE -> IDLE
+    """
+
+    def __init__(
+        self,
+        zmq_host: str = "127.0.0.1",
+        zmq_port: int = 55555,
+        stability_frames: int = 3,
+        poll_hz: int = 8,
+        video_source: str | None = None,
+    ):
+        self.detector = VisionDetector(
+            zmq_host=zmq_host,
+            zmq_port=zmq_port,
+            poll_hz=poll_hz,
+            video_source=video_source,
+        )
+        self.stability_frames = int(stability_frames)
+        self.cooldown_until = 0.0
+        self.session_id = 0
+        self._running = False
+
+        self._capture_done = False
+        self._capture_result = None
+        self._capture_lock = threading.Lock()
+        self._capture_cancel_event: threading.Event | None = None
+
+        self.interaction_active = False
+        self.interaction_flag = Path(config.SCRIPTS_DIR) / "interaction_triggered.flag"
+        self.request_photo_flag = Path(config.SCRIPTS_DIR) / "request_photo.flag"
+        self.confirm_yes_flag = Path(config.SCRIPTS_DIR) / "confirm_yes.flag"
+        self.confirm_no_flag = Path(config.SCRIPTS_DIR) / "confirm_no.flag"
+        self.state_file = Path(config.AUTONOMOUS_STATE_FILE)
+
+        self.confirm_timeout_sec = float(os.environ.get("CONFIRM_TIMEOUT_SEC", "15.0"))
+        self.confirm_reminder_sec = float(os.environ.get("CONFIRM_REMINDER_SEC", "5.0"))
+        self.confirm_guard_sec = float(os.environ.get("CONFIRM_GUARD_SEC", "1.2"))
+        self.session_cooldown_sec = float(os.environ.get("SESSION_COOLDOWN_SEC", "10.0"))
+        self.leave_timeout_sec = float(os.environ.get("VISITOR_LEAVE_TIMEOUT_SEC", "2.5"))
+        self.countdown_lose_subject_sec = float(os.environ.get("COUNTDOWN_LOSE_SUBJECT_SEC", "1.4"))
+        self.capture_finalize_grace_sec = float(os.environ.get("CAPTURE_FINALIZE_GRACE_SEC", "3.0"))
+
+        self.framing_timeout_sec = float(os.environ.get("FRAMING_TIMEOUT_SEC", "20.0"))
+        self.framing_feedback_interval_sec = float(os.environ.get("FRAMING_FEEDBACK_INTERVAL_SEC", "2.0"))
+        self.framing_good_frames_required = int(os.environ.get("FRAMING_GOOD_FRAMES_REQUIRED", "2"))
+
+        # Framing thresholds
+        self.center_tolerance = float(os.environ.get("FRAMING_CENTER_TOLERANCE", "0.18"))
+        self.subject_min_area_ratio = float(os.environ.get("FRAMING_MIN_AREA_RATIO", "0.06"))
+        self.subject_max_area_ratio = float(os.environ.get("FRAMING_MAX_AREA_RATIO", "0.55"))
+        self.min_blur_var = float(os.environ.get("FRAMING_MIN_BLUR_VAR", "80.0"))
+        self.min_exposure = float(os.environ.get("FRAMING_MIN_EXPOSURE", "55.0"))
+        self.max_exposure = float(os.environ.get("FRAMING_MAX_EXPOSURE", "200.0"))
+        self.headroom_min_ratio = float(config.read_vision_framing_headroom_min_ratio())
+        self.headroom_max_ratio = float(config.read_vision_framing_headroom_max_ratio())
+        self.eye_line_min_ratio = float(config.read_vision_framing_eye_line_min_ratio())
+        self.eye_line_max_ratio = float(config.read_vision_framing_eye_line_max_ratio())
+        self.retake_score_threshold = float(config.read_vision_framing_retake_score_threshold())
+        self.retake_prompt_enabled = bool(config.read_vision_retake_prompt_enabled())
+        self.retake_limit = int(config.read_vision_retake_max_per_session())
+        self.hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled())
+        self.autonomous_greeting_replay_enabled = bool(config.read_vision_autonomous_greeting_replay_enabled())
+        self.autonomous_greeting_replay_file = self._resolve_replay_path(
+            config.read_vision_autonomous_greeting_replay_file()
+        )
+        self.autonomous_capture_replay_enabled = bool(config.read_vision_autonomous_capture_replay_enabled())
+        self.retake_confirm_timeout_sec = float(os.environ.get("RETAKE_CONFIRM_TIMEOUT_SEC", "8.0"))
+
+        self.yolo_strict_required = bool(config.read_vision_yolo_strict_required())
+        self.gemini_context_hz = float(config.read_vision_gemini_context_hz())
+        self.gemini_context_silent = bool(config.read_vision_gemini_context_silent())
+        self._context_interval_sec = 1.0 / max(0.5, self.gemini_context_hz)
+        self._next_context_ts = 0.0
+
+        self.ai_blocked = False
+        self.ai_block_reason = ""
+        self._last_vision_log_signature = None
+        self._last_vision_log_ts = 0.0
+        self.face_recognition_enabled = bool(config.read_vision_face_recognition_enabled())
+        self.face_recognition_threshold = float(config.read_vision_face_recognition_threshold())
+        self.current_person: dict | None = None
+
+    async def _say(self, voice, text: str):
+        if voice is None:
+            return
+        try:
+            ok = await voice.send_text_prompt_live(text)
+            if not ok:
+                sanad_logger.print_and_log("Voice prompt skipped: Gemini WS not connected.", "warning")
+        except Exception as e:
+            sanad_logger.print_and_log(f"Voice prompt failed: {e}", "warning")
+
+    async def _say_prompt(
+        self,
+        voice,
+        prompt_key: str,
+        fallback_text: str,
+        *,
+        mode_override: str | None = None,
+        allow_gemini_fallback: bool | None = None,
+    ):
+        if voice is None:
+            return
+        try:
+            if hasattr(voice, "play_prompt_key"):
+                ok = await voice.play_prompt_key(
+                    prompt_key,
+                    fallback_text=fallback_text,
+                    allow_gemini_fallback=allow_gemini_fallback,
+                    mode_override=mode_override,
+                )
+            else:
+                ok = await voice.send_text_prompt_live(fallback_text)
+            if not ok:
+                sanad_logger.print_and_log(f"Voice prompt skipped for {prompt_key}: output unavailable.", "warning")
+        except Exception as e:
+            sanad_logger.print_and_log(f"Voice prompt failed for {prompt_key}: {e}", "warning")
+
+    async def _say_capture_prompt(self, voice, prompt_key: str, fallback_text: str):
+        await self._say_prompt(
+            voice,
+            prompt_key,
+            fallback_text,
+            mode_override="audio",
+            allow_gemini_fallback=False,
+        )
+
+    def _maybe_log_vision_snapshot(self, snapshot: dict, now_ts: float):
+        try:
+            person_count = int(snapshot.get("person_count", 0))
+            face_count = int(snapshot.get("face_count", 0))
+            group_detected = bool(snapshot.get("group_detected", False))
+            group_size = int(snapshot.get("group_size", 0))
+            subject_visible = bool(snapshot.get("subject_visible", False))
+            intent_detected = bool(snapshot.get("intent_detected", False))
+            max_area = int(float(snapshot.get("max_area", 0.0) or 0.0))
+            depth_m = snapshot.get("depth_m", None)
+            if depth_m is not None:
+                depth_m = round(float(depth_m), 2)
+
+            sig = (
+                person_count,
+                face_count,
+                group_detected,
+                group_size,
+                subject_visible,
+                intent_detected,
+                max_area,
+                depth_m,
+            )
+            active = bool(person_count or face_count or subject_visible or group_detected or intent_detected)
+            if (not active) and self._last_vision_log_signature in (None, sig):
+                return
+            if sig == self._last_vision_log_signature and (now_ts - self._last_vision_log_ts) < 1.0:
+                return
+
+            self._last_vision_log_signature = sig
+            self._last_vision_log_ts = now_ts
+            sanad_logger.print_and_log(
+                "👁️ Vision: "
+                f"people={person_count} faces={face_count} group={group_detected}({group_size}) "
+                f"visible={subject_visible} intent={intent_detected} area={max_area} depth={depth_m if depth_m is not None else '-'}",
+                "info",
+            )
+        except Exception as e:
+            record_error("autonomous_manager", "vision_snapshot_log", e)
+
+    def _set_interaction_active(self, active: bool, voice=None, reason: str = ""):
+        active = bool(active)
+        self.interaction_active = active
+        try:
+            self.interaction_flag.parent.mkdir(parents=True, exist_ok=True)
+            if active:
+                self.interaction_flag.write_text(f"{time.time():.3f} {reason}".strip(), encoding="utf-8")
+            elif self.interaction_flag.exists():
+                self.interaction_flag.unlink()
+        except Exception as e:
+            record_error("autonomous_manager", "set_interaction_active_file", e, {"active": bool(active)})
+
+        if voice is not None and hasattr(voice, "set_audio_gate"):
+            try:
+                idle_voice_listen_enabled = bool(config.read_vision_idle_voice_listen_enabled())
+                mic_enabled = bool(config.read_gemini_mic_enabled())
+                runtime_mode = str(config.read_runtime_mode()).strip().lower()
+                if runtime_mode not in ("manual", "ai"):
+                    runtime_mode = "manual"
+                if active:
+                    if hasattr(voice, "set_passive_listen"):
+                        voice.set_passive_listen(False, reason=reason or "interaction active")
+                    voice.set_audio_gate(True, reason=reason)
+                else:
+                    if runtime_mode != "ai":
+                        if hasattr(voice, "set_passive_listen"):
+                            voice.set_passive_listen(False, reason=reason or "manual mode")
+                        voice.set_audio_gate(mic_enabled, reason=reason or "manual mode")
+                    else:
+                        if hasattr(voice, "set_passive_listen"):
+                            voice.set_passive_listen(mic_enabled and idle_voice_listen_enabled, reason=reason or "idle")
+                        voice.set_audio_gate(mic_enabled and idle_voice_listen_enabled, reason=reason or "idle")
+            except Exception as e:
+                record_error("autonomous_manager", "set_interaction_active_audio_gate", e, {"active": bool(active)})
+
+    @staticmethod
+    def _clear_flag(path: Path):
+        try:
+            if path.exists():
+                path.unlink()
+        except Exception as e:
+            record_error("autonomous_manager", "clear_flag", e, {"path": str(path)})
+
+    @staticmethod
+    def _consume_flag(path: Path) -> bool:
+        try:
+            if path.exists():
+                path.unlink()
+                return True
+        except Exception as e:
+            record_error("autonomous_manager", "consume_flag", e, {"path": str(path)})
+        return False
+
+    def _consume_request_photo_flag(self) -> bool:
+        return self._consume_flag(self.request_photo_flag) or self._consume_flag(self.confirm_yes_flag)
+
+    def _consume_direct_request_flag(self) -> bool:
+        return self._consume_flag(self.request_photo_flag)
+
+    def _consume_no_photo_flag(self) -> bool:
+        return self._consume_flag(self.confirm_no_flag)
+
+    def _clear_confirmation_flags(self):
+        self._clear_flag(self.request_photo_flag)
+        self._clear_flag(self.confirm_yes_flag)
+        self._clear_flag(self.confirm_no_flag)
+
+    def _cancel_capture_pipeline(self, reason: str = ""):
+        try:
+            ev = self._capture_cancel_event
+            if ev is not None:
+                ev.set()
+            self._capture_cancel_event = None
+            if reason:
+                sanad_logger.print_and_log(f"Capture pipeline cancelled: {reason}", "warning")
+        except Exception as e:
+            record_error("autonomous_manager", "cancel_capture_pipeline", e, {"reason": reason})
+
+    @staticmethod
+    def _resolve_replay_path(path_value: str) -> Path:
+        return config.resolve_replay_path(path_value)
+
+    def _start_greeting_replay(self, replay):
+        if replay is None or not bool(self.autonomous_greeting_replay_enabled):
+            return
+        replay_file = Path(self.autonomous_greeting_replay_file).resolve()
+        if not replay_file.exists():
+            sanad_logger.print_and_log(f"⚠️ Greeting replay missing: {replay_file}", "warning")
+            return
+        if bool(getattr(replay, "is_playing", False)):
+            sanad_logger.print_and_log("⚠️ Greeting replay skipped: replay already busy.", "warning")
+            return
+
+        def _run_greeting():
+            try:
+                sanad_logger.print_and_log(f"👋 Greeting replay: {replay_file.name}", "info")
+                replay.run(replay_file, config.HOME_FILE, 1.0)
+            except Exception as e:
+                record_error("autonomous_manager", "greeting_replay", e, {"replay_file": str(replay_file)})
+
+        Thread(target=_run_greeting, daemon=True).start()
+
+    def _reset_current_person(self):
+        self.current_person = None
+
+    def _session_person_label(self) -> str:
+        if not isinstance(self.current_person, dict):
+            return ""
+        return str(
+            self.current_person.get("display_label")
+            or self.current_person.get("display_name")
+            or self.current_person.get("person_id")
+            or ""
+        ).strip()
+
+    def _current_person_extras(self) -> dict:
+        person = self.current_person if isinstance(self.current_person, dict) else {}
+        return {
+            "recognized_person_id": str(person.get("person_id") or ""),
+            "recognized_person_known": bool(person.get("known_person", False)),
+            "recognized_person_new": bool(person.get("new_person", False)),
+            "recognized_person_label": str(
+                person.get("display_label") or person.get("display_name") or person.get("person_id") or ""
+            ),
+            "recognized_person_match_score": float(person.get("match_score", 0.0) or 0.0),
+            "recognized_person_created_date": str(person.get("created_date") or ""),
+        }
+
+    def _select_face_box(self, snapshot: dict) -> dict | None:
+        faces = snapshot.get("face_boxes") or []
+        if not isinstance(faces, list) or not faces:
+            return None
+        subject_box = self._find_subject_box(snapshot)
+        if not isinstance(subject_box, dict):
+            try:
+                return max(faces, key=lambda f: float(f.get("w", 0.0)) * float(f.get("h", 0.0)))
+            except Exception:
+                return faces[0] if faces else None
+
+        try:
+            sx1 = float(subject_box.get("x", 0.0))
+            sy1 = float(subject_box.get("y", 0.0))
+            sx2 = sx1 + max(1.0, float(subject_box.get("w", 1.0)))
+            sy2 = sy1 + max(1.0, float(subject_box.get("h", 1.0)))
+        except Exception:
+            sx1 = sy1 = 0.0
+            sx2 = sy2 = 0.0
+
+        best = None
+        best_overlap = -1.0
+        for face in faces:
+            try:
+                fx1 = float(face.get("x", 0.0))
+                fy1 = float(face.get("y", 0.0))
+                fx2 = fx1 + max(1.0, float(face.get("w", 1.0)))
+                fy2 = fy1 + max(1.0, float(face.get("h", 1.0)))
+                ix1 = max(sx1, fx1)
+                iy1 = max(sy1, fy1)
+                ix2 = min(sx2, fx2)
+                iy2 = min(sy2, fy2)
+                overlap = max(0.0, ix2 - ix1) * max(0.0, iy2 - iy1)
+                if overlap > best_overlap:
+                    best_overlap = overlap
+                    best = face
+            except Exception:
+                continue
+        if best is not None:
+            return best
+        try:
+            return max(faces, key=lambda f: float(f.get("w", 0.0)) * float(f.get("h", 0.0)))
+        except Exception:
+            return faces[0] if faces else None
+
+    def _identify_person_for_session(self, snapshot: dict, source: str = "vision") -> dict | None:
+        if not bool(self.face_recognition_enabled):
+            self._reset_current_person()
+            return None
+        frame = snapshot.get("frame")
+        if frame is None:
+            self._reset_current_person()
+            return None
+        if bool(snapshot.get("group_detected", False)) or int(snapshot.get("face_count", 0) or 0) > 1:
+            self._reset_current_person()
+            return None
+
+        face_box = self._select_face_box(snapshot)
+        if face_box is None:
+            self._reset_current_person()
+            return None
+        subject_box = self._find_subject_box(snapshot)
+        try:
+            result = people_registry.recognize_or_enroll(
+                frame,
+                face_box,
+                subject_box=subject_box,
+                threshold=self.face_recognition_threshold,
+                source=source,
+            )
+        except Exception as e:
+            record_error("autonomous_manager", "identify_person_for_session", e)
+            self._reset_current_person()
+            return None
+        if not isinstance(result, dict) or not bool(result.get("ok", False)):
+            self._reset_current_person()
+            return None
+        self.current_person = result
+        label = self._session_person_label()
+        if bool(result.get("known_person", False)):
+            sanad_logger.print_and_log(
+                f"🧑 Returning guest recognized: {label} (score={float(result.get('match_score', 0.0) or 0.0):.2f})",
+                "info",
+            )
+        else:
+            sanad_logger.print_and_log(f"🧑 New guest enrolled: {label}", "info")
+        return result
+
+    def _welcome_prompt_text(self, group_detected: bool) -> str:
+        if group_detected:
+            return (
+                "Hello everyone, welcome. We will take a photo together. "
+                "Would your group like a photo? Please say yes photo or no photo."
+            )
+        label = self._session_person_label()
+        if label and bool(self.current_person and self.current_person.get("known_person")):
+            return (
+                f"Welcome back, {label}. Would you like another photo? "
+                "Please say yes photo or no photo."
+            )
+        return (
+            "Hello, welcome. We will take a photo together. "
+            "Would you like a photo? Please say yes photo or no photo."
+        )
+
+    def _welcome_prompt_key(self, group_detected: bool) -> str:
+        if group_detected:
+            return "welcome_group"
+        if self._session_person_label() and bool(self.current_person and self.current_person.get("known_person")):
+            return "welcome_returning"
+        return "welcome_single"
+
+    def _framing_prompt_text(self, group_detected: bool) -> str:
+        if group_detected:
+            return "Great. Please stand with me in front of the camera, stay together in the center, and look at the camera."
+        return "Great. Please stand with me in front of the camera, stay in the center, and look at the camera."
+
+    @staticmethod
+    def _framing_prompt_key(group_detected: bool) -> str:
+        return "frame_group" if group_detected else "frame_single"
+
+    @staticmethod
+    def _find_subject_box(snapshot: dict) -> dict | None:
+        subj = snapshot.get("subject_box")
+        if isinstance(subj, dict):
+            return subj
+        boxes = snapshot.get("boxes") or []
+        if not boxes:
+            return None
+        try:
+            return max(boxes, key=lambda b: float(b.get("w", 0.0)) * float(b.get("h", 0.0)))
+        except Exception:
+            return boxes[0] if boxes else None
+
+    def _evaluate_framing_quality(self, snapshot: dict) -> tuple[bool, list[str], dict]:
+        frame = snapshot.get("frame")
+        box = self._find_subject_box(snapshot)
+        if frame is None or box is None:
+            return False, ["step into view"], {"reason": "no_frame_or_subject"}
+
+        try:
+            h, w = frame.shape[:2]
+            x = float(box.get("x", 0.0))
+            y = float(box.get("y", 0.0))
+            bw = max(1.0, float(box.get("w", 1.0)))
+            bh = max(1.0, float(box.get("h", 1.0)))
+            area_ratio = (bw * bh) / max(1.0, float(w * h))
+            cx = x + (bw / 2.0)
+            dx = (cx - (w / 2.0)) / max(1.0, float(w))
+            centered = abs(dx) <= self.center_tolerance
+            size_ok = self.subject_min_area_ratio <= area_ratio <= self.subject_max_area_ratio
+
+            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+            blur_var = float(cv2.Laplacian(gray, cv2.CV_64F).var())
+            exposure = float(gray.mean())
+            blur_ok = blur_var >= self.min_blur_var
+            exposure_ok = self.min_exposure <= exposure <= self.max_exposure
+
+            faces = snapshot.get("face_boxes") or []
+            face_box = None
+            best_overlap = -1.0
+            for f in faces:
+                try:
+                    fx = float(f.get("x", 0.0))
+                    fy = float(f.get("y", 0.0))
+                    fw = max(1.0, float(f.get("w", 1.0)))
+                    fh = max(1.0, float(f.get("h", 1.0)))
+                    ix1 = max(x, fx)
+                    iy1 = max(y, fy)
+                    ix2 = min(x + bw, fx + fw)
+                    iy2 = min(y + bh, fy + fh)
+                    iw = max(0.0, ix2 - ix1)
+                    ih = max(0.0, iy2 - iy1)
+                    overlap = iw * ih
+                    if overlap > best_overlap:
+                        best_overlap = overlap
+                        face_box = {"x": fx, "y": fy, "w": fw, "h": fh}
+                except Exception:
+                    continue
+
+            if face_box is not None:
+                headroom_ratio = float(face_box["y"]) / max(1.0, float(h))
+                eye_y = float(face_box["y"]) + (0.38 * float(face_box["h"]))
+                eye_line_ratio = eye_y / max(1.0, float(h))
+            else:
+                headroom_ratio = y / max(1.0, float(h))
+                eye_line_ratio = (y + (0.25 * bh)) / max(1.0, float(h))
+            headroom_ok = self.headroom_min_ratio <= headroom_ratio <= self.headroom_max_ratio
+            eye_line_ok = self.eye_line_min_ratio <= eye_line_ratio <= self.eye_line_max_ratio
+
+            mid = int(max(1, w // 2))
+            left_mean = float(gray[:, :mid].mean()) if mid > 0 else exposure
+            right_mean = float(gray[:, mid:].mean()) if (w - mid) > 0 else exposure
+            lr_delta = right_mean - left_mean
+
+            reasons: list[str] = []
+            if not centered:
+                reasons.append("move a bit to the center")
+            if not size_ok:
+                reasons.append("come a little closer" if area_ratio < self.subject_min_area_ratio else "step slightly back")
+            if not headroom_ok:
+                if headroom_ratio < self.headroom_min_ratio:
+                    reasons.append("lower your chin a little")
+                else:
+                    reasons.append("raise your chin a little")
+            if not eye_line_ok:
+                reasons.append("keep your eyes around the middle of the frame")
+            if not blur_ok:
+                reasons.append("hold still for a second")
+            if not exposure_ok:
+                if exposure < self.min_exposure:
+                    if abs(lr_delta) > 12.0:
+                        reasons.append(
+                            "turn slightly toward the brighter side"
+                        )
+                    else:
+                        reasons.append("face the light")
+                else:
+                    reasons.append("avoid strong direct light")
+
+            metrics = {
+                "area_ratio": area_ratio,
+                "blur_var": blur_var,
+                "exposure": exposure,
+                "center_dx": dx,
+                "centered": centered,
+                "size_ok": size_ok,
+                "blur_ok": blur_ok,
+                "exposure_ok": exposure_ok,
+                "headroom_ratio": headroom_ratio,
+                "eye_line_ratio": eye_line_ratio,
+                "headroom_ok": headroom_ok,
+                "eye_line_ok": eye_line_ok,
+                "left_exposure": left_mean,
+                "right_exposure": right_mean,
+                "lr_exposure_delta": lr_delta,
+            }
+            return len(reasons) == 0, reasons, metrics
+        except Exception as e:
+            return False, ["hold still and face the camera"], {"reason": str(e)}
+
+    @staticmethod
+    def _framing_guidance_text(reasons: list[str]) -> str:
+        if not reasons:
+            return "Great framing. Hold still."
+        uniq = []
+        for r in reasons:
+            if r not in uniq:
+                uniq.append(r)
+        joined = ", and ".join(uniq[:2])
+        return f"Almost ready. Please {joined}."
+
+    @staticmethod
+    def _quality_score_from_metrics(metrics: dict) -> float:
+        checks = [
+            bool(metrics.get("centered", False)),
+            bool(metrics.get("size_ok", False)),
+            bool(metrics.get("blur_ok", False)),
+            bool(metrics.get("exposure_ok", False)),
+            bool(metrics.get("headroom_ok", False)),
+            bool(metrics.get("eye_line_ok", False)),
+        ]
+        if not checks:
+            return 0.0
+        return float(sum(1 for x in checks if x)) / float(len(checks))
+
+    def _retake_assessment(self, snapshot: dict, previous_metrics: dict | None = None) -> tuple[bool, str, float, dict]:
+        good, reasons, metrics = self._evaluate_framing_quality(snapshot)
+        if previous_metrics and isinstance(previous_metrics, dict):
+            merged = dict(previous_metrics)
+            merged.update(metrics)
+            metrics = merged
+        score = self._quality_score_from_metrics(metrics)
+        if good and score >= self.retake_score_threshold:
+            return False, "", score, metrics
+        if reasons:
+            reason = reasons[0]
+        else:
+            reason = "framing quality is not optimal"
+        return True, str(reason), score, metrics
+
+    def _lock_target_on_session_start(self, snapshot: dict):
+        try:
+            if hasattr(self.detector, "set_hard_lock"):
+                self.detector.set_hard_lock(bool(self.hard_target_lock_enabled))
+            if hasattr(self.detector, "lock_target_from_snapshot"):
+                self.detector.lock_target_from_snapshot(
+                    snapshot,
+                    lock_group=bool(self.hard_target_lock_enabled and snapshot.get("group_detected", False)),
+                )
+            elif hasattr(self.detector, "lock_subject_from_snapshot"):
+                self.detector.lock_subject_from_snapshot(snapshot)
+        except Exception as e:
+            record_error("autonomous_manager", "lock_target_on_session_start", e)
+
+    def _unlock_target(self):
+        try:
+            if hasattr(self.detector, "unlock_target"):
+                self.detector.unlock_target()
+            elif hasattr(self.detector, "unlock_subject"):
+                self.detector.unlock_subject()
+        except Exception as e:
+            record_error("autonomous_manager", "unlock_target", e)
+
+    def _detector_readiness(self) -> dict:
+        try:
+            return self.detector.readiness(strict_required=self.yolo_strict_required)
+        except Exception as e:
+            record_error("autonomous_manager", "detector_readiness", e)
+            return {
+                "ok": False,
+                "strict_required": bool(self.yolo_strict_required),
+                "configured_backend": "normal",
+                "effective_backend": "normal",
+                "yolo_loaded": False,
+                "person_model_ok": False,
+                "face_model_ok": False,
+                "person_model_path": "",
+                "face_model_path": "",
+                "person_model_error": str(e),
+                "face_model_error": "",
+                "block_reason": f"Detector readiness failed: {e}",
+            }
+
+    async def _push_vision_context(self, voice, state_name: str, snapshot: dict):
+        if voice is None:
+            return
+        if not hasattr(voice, "send_vision_context_live"):
+            return
+        now = time.time()
+        if now < self._next_context_ts:
+            return
+        self._next_context_ts = now + self._context_interval_sec
+
+        payload = {
+            "person_count": int(snapshot.get("person_count", 0)),
+            "group_count": int(snapshot.get("group_count", 0)),
+            "group_size": int(snapshot.get("group_size", 0)),
+            "subject_visible": bool(snapshot.get("subject_visible", False)),
+            "depth_m": snapshot.get("depth_m"),
+            "approach_speed_mps": float(snapshot.get("approach_speed_mps", 0.0) or 0.0),
+            "state": str(state_name),
+            "intent_detected": bool(snapshot.get("intent_detected", False)),
+        }
+        try:
+            await voice.send_vision_context_live(payload, silent=bool(self.gemini_context_silent))
+        except Exception as e:
+            record_error("autonomous_manager", "push_vision_context", e, {"state": state_name})
+
+    def _write_runtime_state(self, state_name: str, snapshot: dict, voice=None, extras: dict | None = None):
+        payload = {
+            "state": state_name,
+            "session_id": self.session_id,
+            "interaction_active": bool(self.interaction_active),
+            "intent_detected": bool(snapshot.get("intent_detected", False)),
+            "detector_backend": str(snapshot.get("detector_backend", "normal")),
+            "yolo_runtime": str(snapshot.get("yolo_runtime", "")),
+            "ai_blocked": bool(self.ai_blocked),
+            "ai_block_reason": str(self.ai_block_reason or ""),
+            "person_count": int(snapshot.get("person_count", 0)),
+            "face_count": int(snapshot.get("face_count", 0)),
+            "group_count": int(snapshot.get("group_count", 0)),
+            "group_size": int(snapshot.get("group_size", 0)),
+            "group_detected": bool(snapshot.get("group_detected", False)),
+            "is_close": bool(snapshot.get("is_close", False)),
+            "is_approaching": bool(snapshot.get("is_approaching", False)),
+            "max_area": float(snapshot.get("max_area", 0.0)),
+            "depth_m": snapshot.get("depth_m"),
+            "approach_speed_mps": snapshot.get("approach_speed_mps"),
+            "subject_id": snapshot.get("subject_id"),
+            "subject_visible": bool(snapshot.get("subject_visible", False)),
+            "target_lock_active": bool(snapshot.get("target_lock_active", False)),
+            "target_lock_type": str(snapshot.get("target_lock_type", "") or ""),
+            "target_lock_id": snapshot.get("target_lock_id"),
+            "target_switch_blocked_count": int(snapshot.get("target_switch_blocked_count", 0)),
+            "camera_ok": bool(snapshot.get("camera_ok", False)),
+            "depth_ok": bool(snapshot.get("depth_ok", False)),
+            "camera_restarts": int(snapshot.get("camera_restarts", 0)),
+            "depth_restarts": int(snapshot.get("depth_restarts", 0)),
+            "audio_gate_open": bool(getattr(voice, "audio_gate_open", False)) if voice is not None else None,
+            "ws_connected": bool(getattr(voice, "is_ws_connected", lambda: False)()) if voice is not None else False,
+            "mic_state": "",
+            "speaker_state": "",
+            "cooldown_remaining": max(0.0, self.cooldown_until - time.time()),
+            "time": time.time(),
+        }
+        try:
+            if voice is not None and hasattr(voice, "get_runtime_health"):
+                vh = voice.get_runtime_health() or {}
+                payload["ws_connected"] = bool(vh.get("ws_connected", payload["ws_connected"]))
+                payload["mic_state"] = str(vh.get("mic_state", "") or "")
+                payload["speaker_state"] = str(vh.get("speaker_state", "") or "")
+        except Exception as e:
+            record_error("autonomous_manager", "write_runtime_state_voice_health", e)
+        if extras:
+            payload.update(extras)
+        try:
+            self.state_file.parent.mkdir(parents=True, exist_ok=True)
+            self.state_file.write_text(json.dumps(payload, ensure_ascii=False), encoding="utf-8")
+        except Exception as e:
+            record_error("autonomous_manager", "write_runtime_state", e, {"state": state_name})
+
+    def _start_capture_pipeline(self, replay, timing_info: dict | None = None):
+        self._cancel_capture_pipeline(reason="restart")
+        with self._capture_lock:
+            self._capture_done = False
+            self._capture_result = None
+
+        timing_info = timing_info or self._resolve_capture_timing(use_replay=bool(self.autonomous_capture_replay_enabled))
+        default_delay_sec = max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC))
+        delay_sec = float(timing_info.get("capture_offset_sec") or default_delay_sec)
+        cancel_event = threading.Event()
+        self._capture_cancel_event = cancel_event
+
+        def _run_pipeline():
+            try:
+                base_prefix = os.environ.get("PHOTO_PREFIX", "photo")
+                prefix = f"session{self.session_id}_{base_prefix}"
+                run_delay_sec = delay_sec
+                capture_replay_runner = replay if bool(self.autonomous_capture_replay_enabled) else None
+                if capture_replay_runner is not None:
+                    replay_wait_deadline = time.time() + 4.0
+                    while (
+                        bool(getattr(capture_replay_runner, "is_playing", False))
+                        and time.time() < replay_wait_deadline
+                        and not cancel_event.is_set()
+                    ):
+                        time.sleep(0.05)
+                    if bool(getattr(capture_replay_runner, "is_playing", False)):
+                        sanad_logger.print_and_log(
+                            "⚠️ AI capture replay still busy; falling back to still photo for this shot.",
+                            "warning",
+                        )
+                        capture_replay_runner = None
+                        run_delay_sec = default_delay_sec
+                if capture_replay_runner is None:
+                    sanad_logger.print_and_log("📷 AI capture: still photo mode (no replay during photo).", "info")
+                else:
+                    sanad_logger.print_and_log(
+                        f"📷 AI capture: replaying {Path(config.REPLAY_FILE).name} during the shot. "
+                        f"duration={float(timing_info.get('duration_sec') or 0.0):.3f}s "
+                        f"shot_at={run_delay_sec:.3f}s "
+                        f"source={timing_info.get('capture_source', 'config_fallback')}",
+                        "info",
+                    )
+                res = capture_with_replay_sync(
+                    replay_runner=capture_replay_runner,
+                    replay_file=config.REPLAY_FILE,
+                    home_file=config.HOME_FILE,
+                    delay_sec=run_delay_sec,
+                    prefix=prefix,
+                    speed=1.0,
+                    cancel_event=cancel_event,
+                )
+                with self._capture_lock:
+                    self._capture_result = str(res)
+                    self._capture_done = True
+                if str(res).startswith("[ERR]"):
+                    sanad_logger.print_and_log(f"Capture pipeline failed: {res}", "error")
+                else:
+                    sanad_logger.print_and_log(f"Saved photo (pipeline): {res}", "info")
+            except Exception as e:
+                record_error("autonomous_manager", "start_capture_pipeline", e, {"session_id": self.session_id})
+                with self._capture_lock:
+                    self._capture_result = f"[ERR] capture pipeline exception: {e}"
+                    self._capture_done = True
+
+        Thread(target=_run_pipeline, daemon=True).start()
+
+    def _resolve_capture_timing(self, use_replay: bool) -> dict:
+        default_delay = max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC))
+        timing_info = {
+            "capture_offset_sec": default_delay,
+            "duration_sec": 0.0,
+            "capture_source": "config_fallback",
+        }
+        if not use_replay:
+            return timing_info
+        try:
+            profile = replay_timing_profile(config.REPLAY_FILE)
+            if bool(profile.get("ok")):
+                return profile
+            if profile.get("capture_offset_sec") is not None:
+                timing_info["capture_offset_sec"] = float(profile.get("capture_offset_sec") or default_delay)
+        except Exception as e:
+            record_error("autonomous_manager", "resolve_capture_timing", e, {"replay_file": str(config.REPLAY_FILE)})
+        return timing_info
+
+    async def run(self, hub, replay, voice, ws=None):
+        self.detector.start()
+        self.hub = hub
+        self._running = True
+        self._set_interaction_active(False, voice=voice, reason="idle")
+
+        state = "IDLE"
+        state_enter_ts = time.time()
+        stable_count = 0
+
+        confirm_deadline = 0.0
+        confirm_last_prompt_ts = 0.0
+        confirm_ignore_until = 0.0
+        leave_since = 0.0
+
+        framing_deadline = 0.0
+        framing_last_feedback_ts = 0.0
+        framing_good_streak = 0
+        framing_metrics: dict = {}
+
+        countdown_deadline = 0.0
+        countdown_announced: set[int] = set()
+        countdown_lost_since = 0.0
+
+        retake_count = 0
+        retake_deadline = 0.0
+        retake_recommended = False
+        retake_reason = ""
+        retake_score = 1.0
+
+        sanad_logger.print_and_log("🤖 Autonomous mode enabled.", "info")
+
+        try:
+            while self._running:
+                await asyncio.sleep(1.0 / max(1, self.detector.poll_hz))
+                now = time.time()
+                runtime_mode = "manual"
+                try:
+                    runtime_mode = str(config.read_runtime_mode()).strip().lower()
+                except Exception:
+                    runtime_mode = "manual"
+                if runtime_mode not in ("manual", "ai"):
+                    runtime_mode = "manual"
+
+                # Runtime-refresh operator toggles from config.json.
+                try:
+                    self.hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled())
+                    self.retake_prompt_enabled = bool(config.read_vision_retake_prompt_enabled())
+                    self.retake_limit = int(config.read_vision_retake_max_per_session())
+                    self.retake_score_threshold = float(config.read_vision_framing_retake_score_threshold())
+                    self.autonomous_greeting_replay_enabled = bool(config.read_vision_autonomous_greeting_replay_enabled())
+                    self.autonomous_greeting_replay_file = self._resolve_replay_path(
+                        config.read_vision_autonomous_greeting_replay_file()
+                    )
+                    self.autonomous_capture_replay_enabled = bool(config.read_vision_autonomous_capture_replay_enabled())
+                    self.face_recognition_enabled = bool(config.read_vision_face_recognition_enabled())
+                    self.face_recognition_threshold = float(config.read_vision_face_recognition_threshold())
+                except Exception as e:
+                    record_error("autonomous_manager", "runtime_option_refresh", e)
+
+                if hasattr(self.detector, "set_hard_lock"):
+                    try:
+                        self.detector.set_hard_lock(bool(self.hard_target_lock_enabled))
+                    except Exception as e:
+                        record_error("autonomous_manager", "detector_set_hard_lock", e)
+
+                snap = self.detector.latest()
+                face_count = int(snap.get("face_count", 0))
+                subject_visible = bool(snap.get("subject_visible", face_count > 0))
+                intent_detected = bool(snap.get("intent_detected", False))
+                max_area = float(snap.get("max_area", 0.0))
+                group_detected = bool(snap.get("group_detected", False))
+                self._maybe_log_vision_snapshot(snap, now)
+
+                if runtime_mode != "ai":
+                    stable_count = 0
+                    if state != "IDLE":
+                        sanad_logger.print_and_log("🛑 Autonomous flow paused: runtime mode is MANUAL.", "info")
+                    state = "IDLE"
+                    state_enter_ts = now
+                    self._clear_confirmation_flags()
+                    self._set_interaction_active(False, voice=voice, reason="manual mode")
+                    self._cancel_capture_pipeline(reason="manual mode")
+                    self._unlock_target()
+                    self._reset_current_person()
+                    self._write_runtime_state(
+                        "IDLE",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "stable_count": 0,
+                            "runtime_mode": runtime_mode,
+                            "autonomous_paused": True,
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_count": int(retake_count),
+                            **self._current_person_extras(),
+                        },
+                    )
+                    continue
+
+                readiness = self._detector_readiness()
+                if self.yolo_strict_required and (not bool(readiness.get("ok", False))):
+                    block_reason = str(readiness.get("block_reason") or "AI blocked by strict YOLO policy.")
+                    if (not self.ai_blocked) or (self.ai_block_reason != block_reason):
+                        sanad_logger.print_and_log(f"⛔ AI blocked: {block_reason}", "error")
+                        self._set_interaction_active(False, voice=voice, reason="strict yolo blocked")
+                        self._clear_confirmation_flags()
+                        self._cancel_capture_pipeline(reason="strict yolo blocked")
+                        self._unlock_target()
+                        self._reset_current_person()
+                    self.ai_blocked = True
+                    self.ai_block_reason = block_reason
+                    state = "IDLE_BLOCKED"
+                    stable_count = 0
+                    self._write_runtime_state(
+                        "IDLE_BLOCKED",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "yolo_loaded": bool(readiness.get("yolo_loaded", False)),
+                            "person_model_ok": bool(readiness.get("person_model_ok", False)),
+                            "face_model_ok": bool(readiness.get("face_model_ok", False)),
+                            "detector_backend": str(readiness.get("effective_backend", "normal")),
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_count": int(retake_count),
+                            **self._current_person_extras(),
+                        },
+                    )
+                    await self._push_vision_context(voice, "IDLE_BLOCKED", snap)
+                    continue
+
+                if self.ai_blocked:
+                    sanad_logger.print_and_log("✅ AI readiness restored. Leaving blocked state.", "info")
+                    self.ai_blocked = False
+                    self.ai_block_reason = ""
+                    state = "IDLE"
+                    state_enter_ts = now
+                    stable_count = 0
+
+                await self._push_vision_context(voice, state, snap)
+
+                try:
+                    hard_cancel = False
+                    if hub is not None:
+                        if getattr(hub, "hard_cancel_combo", None):
+                            hard_cancel = bool(hub.hard_cancel_combo())
+                        elif getattr(hub, "combo_r2l1", None):
+                            hard_cancel = bool(hub.combo_r2l1())
+                    if hard_cancel:
+                        sanad_logger.print_and_log("🛑 HARD CANCEL detected (R2+L1).", "warning")
+                        state = "IDLE"
+                        state_enter_ts = now
+                        self.cooldown_until = now + self.session_cooldown_sec
+                        self._clear_confirmation_flags()
+                        self._set_interaction_active(False, voice=voice, reason="hard cancel")
+                        self._cancel_capture_pipeline(reason="hard cancel")
+                        self._unlock_target()
+                        self._reset_current_person()
+                except Exception as e:
+                    record_error("autonomous_manager", "remote_cancel_check", e)
+
+                if state == "IDLE":
+                    self._write_runtime_state(
+                        "IDLE",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "stable_count": stable_count,
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_count": int(retake_count),
+                            **self._current_person_extras(),
+                        },
+                    )
+
+                    # Allow visitor-initiated photo request from IDLE.
+                    # Only explicit request_photo should start a new session from idle.
+                    if self._consume_direct_request_flag():
+                        self.session_id += 1
+                        state = "FRAMING"
+                        state_enter_ts = now
+                        framing_deadline = now + self.framing_timeout_sec
+                        framing_last_feedback_ts = 0.0
+                        framing_good_streak = 0
+                        framing_metrics = {}
+                        retake_count = 0
+                        retake_recommended = False
+                        retake_reason = ""
+                        retake_score = 1.0
+                        self._clear_confirmation_flags()
+                        self._set_interaction_active(True, voice=voice, reason="voice request from idle")
+                        self._lock_target_on_session_start(snap)
+                        self._identify_person_for_session(snap, source="voice_request")
+                        sanad_logger.print_and_log(
+                            f"🗣️ Voice photo request from IDLE -> session {self.session_id}",
+                            "info",
+                        )
+                        await self._say_prompt(
+                            voice,
+                            self._framing_prompt_key(group_detected),
+                            self._framing_prompt_text(group_detected),
+                        )
+                        continue
+
+                    if now < self.cooldown_until:
+                        continue
+
+                    if intent_detected:
+                        stable_count += 1
+                    else:
+                        stable_count = 0
+
+                    if stable_count < self.stability_frames:
+                        continue
+
+                    stable_count = 0
+                    self.session_id += 1
+                    state = "WAIT_CONFIRM"
+                    state_enter_ts = now
+                    confirm_deadline = now + self.confirm_timeout_sec
+                    confirm_ignore_until = now + self.confirm_guard_sec
+                    confirm_last_prompt_ts = now
+                    leave_since = 0.0
+                    framing_metrics = {}
+                    retake_count = 0
+                    retake_recommended = False
+                    retake_reason = ""
+                    retake_score = 1.0
+                    self._clear_confirmation_flags()
+                    self._set_interaction_active(True, voice=voice, reason=f"intent max_area={max_area:.0f}")
+                    self._lock_target_on_session_start(snap)
+                    self._identify_person_for_session(snap, source="intent")
+
+                    sanad_logger.print_and_log(
+                        f"🔔 Intent detected (area={max_area:.0f}) -> session {self.session_id}",
+                        "info",
+                    )
+                    self._start_greeting_replay(replay)
+                    try:
+                        wake_text = self._welcome_prompt_text(group_detected)
+                        await voice.trigger_wake_sequence(
+                            wake_text=wake_text,
+                            prompt_key=self._welcome_prompt_key(group_detected),
+                        )
+                    except Exception as e:
+                        record_error("autonomous_manager", "wake_sequence", e)
+                        sanad_logger.print_and_log(f"Wake sequence failed: {e}", "warning")
+                    continue
+
+                if state == "WAIT_CONFIRM":
+                    confirm_remaining = max(0.0, confirm_deadline - now)
+                    self._write_runtime_state(
+                        "WAIT_CONFIRM",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "confirm_timeout_remaining": confirm_remaining,
+                            "confirm_guard_remaining": max(0.0, confirm_ignore_until - now),
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_count": int(retake_count),
+                            **self._current_person_extras(),
+                        },
+                    )
+
+                    if not subject_visible:
+                        if leave_since <= 0.0:
+                            leave_since = now
+                        elif (now - leave_since) >= self.leave_timeout_sec:
+                            sanad_logger.print_and_log("🙈 Visitor left before confirmation.", "warning")
+                            await self._say_prompt(
+                                voice,
+                                "visitor_left",
+                                "No worries. I will wait here for the next visitor.",
+                            )
+                            state = "IDLE"
+                            state_enter_ts = now
+                            self.cooldown_until = now + self.session_cooldown_sec
+                            self._clear_confirmation_flags()
+                            self._set_interaction_active(False, voice=voice, reason="left before confirm")
+                            self._cancel_capture_pipeline(reason="left before confirm")
+                            self._unlock_target()
+                            self._reset_current_person()
+                            continue
+                    else:
+                        leave_since = 0.0
+
+                    if now >= confirm_ignore_until:
+                        if self._consume_no_photo_flag():
+                            await self._say_prompt(voice, "declined", "No problem. We can do it anytime.")
+                            state = "IDLE"
+                            state_enter_ts = now
+                            self.cooldown_until = now + self.session_cooldown_sec
+                            self._clear_confirmation_flags()
+                            self._set_interaction_active(False, voice=voice, reason="visitor declined")
+                            self._cancel_capture_pipeline(reason="visitor declined")
+                            self._unlock_target()
+                            self._reset_current_person()
+                            continue
+
+                        if self._consume_request_photo_flag():
+                            sanad_logger.print_and_log("✅ Confirmation received. Entering framing check.", "info")
+                            await self._say_prompt(
+                                voice,
+                                self._framing_prompt_key(group_detected),
+                                self._framing_prompt_text(group_detected),
+                            )
+                            state = "FRAMING"
+                            state_enter_ts = now
+                            framing_deadline = now + self.framing_timeout_sec
+                            framing_last_feedback_ts = 0.0
+                            framing_good_streak = 0
+                            continue
+
+                    if (now - confirm_last_prompt_ts) >= self.confirm_reminder_sec:
+                        confirm_last_prompt_ts = now
+                        await self._say_prompt(
+                            voice,
+                            "confirm_reminder",
+                            "Say yes photo to continue, or no photo to cancel.",
+                        )
+
+                    if now >= confirm_deadline:
+                        sanad_logger.print_and_log("⌛ Confirmation timeout.", "warning")
+                        await self._say_prompt(
+                            voice,
+                            "confirm_timeout",
+                            "No problem. I will wait here. Come back anytime for a photo.",
+                        )
+                        state = "IDLE"
+                        state_enter_ts = now
+                        self.cooldown_until = now + self.session_cooldown_sec
+                        self._clear_confirmation_flags()
+                        self._set_interaction_active(False, voice=voice, reason="confirm timeout")
+                        self._cancel_capture_pipeline(reason="confirm timeout")
+                        self._unlock_target()
+                        self._reset_current_person()
+                        continue
+
+                elif state == "FRAMING":
+                    if self._consume_no_photo_flag():
+                        await self._say_prompt(voice, "session_cancelled", "Okay. Session cancelled.")
+                        state = "IDLE"
+                        state_enter_ts = now
+                        self.cooldown_until = now + self.session_cooldown_sec
+                        self._clear_confirmation_flags()
+                        self._set_interaction_active(False, voice=voice, reason="cancelled during framing")
+                        self._cancel_capture_pipeline(reason="cancelled during framing")
+                        self._unlock_target()
+                        self._reset_current_person()
+                        continue
+
+                    good, reasons, framing_metrics = self._evaluate_framing_quality(snap)
+                    framing_remaining = max(0.0, framing_deadline - now)
+                    self._write_runtime_state(
+                        "FRAMING",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "framing_ok": bool(good),
+                            "framing_reasons": reasons,
+                            "framing_timeout_remaining": framing_remaining,
+                            "framing_good_streak": framing_good_streak,
+                            "framing_metrics": framing_metrics,
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_count": int(retake_count),
+                            **self._current_person_extras(),
+                        },
+                    )
+
+                    if good:
+                        framing_good_streak += 1
+                    else:
+                        framing_good_streak = 0
+                        if (now - framing_last_feedback_ts) >= self.framing_feedback_interval_sec:
+                            framing_last_feedback_ts = now
+                            await self._say(voice, self._framing_guidance_text(reasons))
+
+                    if framing_good_streak >= self.framing_good_frames_required:
+                        capture_timing = self._resolve_capture_timing(
+                            use_replay=bool(self.autonomous_capture_replay_enabled)
+                        )
+                        capture_start_ts = time.time()
+                        self._start_capture_pipeline(replay, timing_info=capture_timing)
+                        await self._say_capture_prompt(
+                            voice,
+                            "countdown_intro",
+                            "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.",
+                        )
+                        state = "COUNTDOWN"
+                        state_enter_ts = now
+                        countdown_deadline = capture_start_ts + float(
+                            capture_timing.get("capture_offset_sec")
+                            or max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC))
+                        )
+                        countdown_announced = set()
+                        countdown_lost_since = 0.0
+                        continue
+
+                    if now >= framing_deadline:
+                        sanad_logger.print_and_log("⌛ Framing timeout.", "warning")
+                        await self._say_prompt(
+                            voice,
+                            "framing_timeout",
+                            "I still need a better frame. Please step in front of me and say yes photo when ready.",
+                        )
+                        state = "WAIT_CONFIRM"
+                        state_enter_ts = now
+                        confirm_deadline = now + self.confirm_timeout_sec
+                        confirm_ignore_until = now + self.confirm_guard_sec
+                        confirm_last_prompt_ts = now
+                        leave_since = 0.0
+                        continue
+
+                elif state == "COUNTDOWN":
+                    countdown_remaining = max(0.0, countdown_deadline - now)
+                    self._write_runtime_state(
+                        "COUNTDOWN",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "countdown_remaining": countdown_remaining,
+                            "framing_metrics": framing_metrics,
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_count": int(retake_count),
+                            **self._current_person_extras(),
+                        },
+                    )
+
+                    if self._consume_no_photo_flag():
+                        await self._say_prompt(voice, "countdown_cancelled", "Countdown cancelled.")
+                        state = "IDLE"
+                        state_enter_ts = now
+                        self.cooldown_until = now + self.session_cooldown_sec
+                        self._clear_confirmation_flags()
+                        self._set_interaction_active(False, voice=voice, reason="cancelled during countdown")
+                        self._cancel_capture_pipeline(reason="cancelled during countdown")
+                        self._unlock_target()
+                        self._reset_current_person()
+                        continue
+
+                    if not subject_visible:
+                        if countdown_lost_since <= 0.0:
+                            countdown_lost_since = now
+                        elif (now - countdown_lost_since) >= self.countdown_lose_subject_sec:
+                            await self._say_prompt(
+                                voice,
+                                "lost_from_frame",
+                                "I lost you from frame. Let us try again.",
+                            )
+                            state = "FRAMING"
+                            state_enter_ts = now
+                            framing_deadline = now + self.framing_timeout_sec
+                            framing_last_feedback_ts = 0.0
+                            framing_good_streak = 0
+                            continue
+                    else:
+                        countdown_lost_since = 0.0
+
+                    sec_left = int(round(countdown_remaining))
+                    if sec_left in (3, 2, 1) and sec_left not in countdown_announced:
+                        countdown_announced.add(sec_left)
+                        await self._say_capture_prompt(voice, f"count_{sec_left}", f"{sec_left}...")
+                    elif sec_left <= 0 and 0 not in countdown_announced:
+                        countdown_announced.add(0)
+                        await self._say_capture_prompt(voice, "smile", "Smile.")
+
+                    with self._capture_lock:
+                        capture_done = bool(self._capture_done)
+                        capture_result = self._capture_result
+
+                    if capture_done:
+                        if isinstance(capture_result, str) and capture_result.startswith("[ERR]"):
+                            sanad_logger.print_and_log(f"Capture failed: {capture_result}", "error")
+                            state = "IDLE"
+                            state_enter_ts = now
+                            self.cooldown_until = now + self.session_cooldown_sec
+                            self._set_interaction_active(False, voice=voice, reason="capture failed")
+                            self._cancel_capture_pipeline(reason="capture failed")
+                            self._unlock_target()
+                            self._reset_current_person()
+                        else:
+                            try:
+                                person_id = str((self.current_person or {}).get("person_id") or "").strip()
+                                if person_id:
+                                    people_registry.attach_captured_photo(person_id, str(capture_result))
+                            except Exception as e:
+                                record_error("autonomous_manager", "attach_captured_photo", e)
+                            retake_recommended, retake_reason, retake_score, framing_metrics = self._retake_assessment(
+                                snap,
+                                previous_metrics=framing_metrics,
+                            )
+                            if (
+                                bool(self.retake_prompt_enabled)
+                                and bool(retake_recommended)
+                                and int(retake_count) < int(self.retake_limit)
+                            ):
+                                state = "RETAKE_CONFIRM"
+                                state_enter_ts = now
+                                retake_deadline = now + self.retake_confirm_timeout_sec
+                                reason_txt = retake_reason or "the framing is not optimal"
+                                await self._say_prompt(
+                                    voice,
+                                    "retake_recommended",
+                                    f"Photo captured. I recommend a retake because {reason_txt}. "
+                                    "Say yes photo to retake, or no photo to keep this one.",
+                                )
+                            else:
+                                state = "COMPLETE"
+                                state_enter_ts = now
+                        continue
+
+                    if now >= (countdown_deadline + self.capture_finalize_grace_sec):
+                        record_error(
+                            "autonomous_manager",
+                            "countdown_capture_timeout",
+                            context={"session_id": self.session_id, "grace_sec": self.capture_finalize_grace_sec},
+                        )
+                        sanad_logger.print_and_log("Capture timeout after countdown. Resetting session.", "error")
+                        state = "IDLE"
+                        state_enter_ts = now
+                        self.cooldown_until = now + self.session_cooldown_sec
+                        self._set_interaction_active(False, voice=voice, reason="capture timeout")
+                        self._cancel_capture_pipeline(reason="capture timeout")
+                        self._unlock_target()
+                        self._reset_current_person()
+                        continue
+
+                elif state == "RETAKE_CONFIRM":
+                    rem = max(0.0, retake_deadline - now)
+                    self._write_runtime_state(
+                        "RETAKE_CONFIRM",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_recommended": bool(retake_recommended),
+                            "retake_reason": str(retake_reason or ""),
+                            "retake_score": float(retake_score),
+                            "retake_count": int(retake_count),
+                            "retake_limit": int(self.retake_limit),
+                            "retake_timeout_remaining": rem,
+                            "framing_metrics": framing_metrics,
+                            **self._current_person_extras(),
+                        },
+                    )
+                    if self._consume_no_photo_flag():
+                        state = "COMPLETE"
+                        state_enter_ts = now
+                        continue
+                    if self._consume_request_photo_flag():
+                        if int(retake_count) < int(self.retake_limit):
+                            retake_count += 1
+                            await self._say_prompt(
+                                voice,
+                                "retake_yes",
+                                "Great, let us retake. Hold your pose.",
+                            )
+                            state = "FRAMING"
+                            state_enter_ts = now
+                            framing_deadline = now + self.framing_timeout_sec
+                            framing_last_feedback_ts = 0.0
+                            framing_good_streak = 0
+                        else:
+                            await self._say_prompt(
+                                voice,
+                                "retake_limit",
+                                "Retake limit reached. Keeping the current photo.",
+                            )
+                            state = "COMPLETE"
+                            state_enter_ts = now
+                        continue
+                    if now >= retake_deadline:
+                        state = "COMPLETE"
+                        state_enter_ts = now
+                        continue
+
+                elif state == "COMPLETE":
+                    self._write_runtime_state(
+                        "COMPLETE",
+                        snap,
+                        voice=voice,
+                        extras={
+                            "capture_result": self._capture_result,
+                            "retake_prompt_enabled": bool(self.retake_prompt_enabled),
+                            "retake_recommended": bool(retake_recommended),
+                            "retake_reason": str(retake_reason or ""),
+                            "retake_score": float(retake_score),
+                            "retake_count": int(retake_count),
+                            "retake_limit": int(self.retake_limit),
+                            "framing_metrics": framing_metrics,
+                            **self._current_person_extras(),
+                        },
+                    )
+                    await self._say_capture_prompt(
+                        voice,
+                        "photo_saved_thanks",
+                        "Thank you. Photo saved. Don't forget to check your photos.",
+                    )
+                    sanad_logger.print_and_log(f"✅ Session {self.session_id} complete.", "info")
+                    await asyncio.sleep(1.0)
+                    state = "IDLE"
+                    state_enter_ts = now
+                    self.cooldown_until = time.time() + self.session_cooldown_sec
+                    self._clear_confirmation_flags()
+                    self._set_interaction_active(False, voice=voice, reason="session complete")
+                    self._cancel_capture_pipeline(reason="session complete")
+                    self._unlock_target()
+                    self._reset_current_person()
+                    continue
+
+                if (time.time() - state_enter_ts) > 120.0:
+                    sanad_logger.print_and_log("Autonomous state timed out, forcing IDLE reset.", "warning")
+                    state = "IDLE"
+                    state_enter_ts = time.time()
+                    self.cooldown_until = time.time() + self.session_cooldown_sec
+                    self._clear_confirmation_flags()
+                    self._set_interaction_active(False, voice=voice, reason="state watchdog reset")
+                    self._cancel_capture_pipeline(reason="state watchdog reset")
+                    self._unlock_target()
+                    self._reset_current_person()
+
+        finally:
+            self._set_interaction_active(False, voice=voice, reason="autonomous stop")
+            self._cancel_capture_pipeline(reason="autonomous stop")
+            self._unlock_target()
+            self._reset_current_person()
+            self.detector.stop()
+    def stop(self):
+        self._running = False
+        self.detector.stop()
+
+
+if __name__ == "__main__":
+    async def main():
+        am = AutonomousManager()
+
+        class Stub:
+            pass
+
+        await am.run(Stub(), Stub(), Stub(), None)
+
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        pass
diff --git a/Modes/AI/camera_module.py b/Modes/AI/camera_module.py
new file mode 100644
index 0000000..381acde
--- /dev/null
+++ b/Modes/AI/camera_module.py
@@ -0,0 +1,333 @@
+"""
+Camera capture module for Unitree G1 robot
+Handles OpenCV camera interface and image processing for AI analysis
+"""
+
+import cv2
+import numpy as np
+import base64
+import io
+import os
+import time
+from pathlib import Path
+from PIL import Image
+from typing import Optional, Union, List
+import logging
+from Core.settings import CAMERA_INDEX, FRAME_WIDTH, FRAME_HEIGHT, FPS
+
+class CameraCapture:
+    """
+    Camera capture class for Unitree G1 robot
+    Provides methods to capture frames and prepare them for AI analysis
+    """
+    
+    def __init__(self, camera_index: Optional[Union[int, str]] = None):
+        """
+        Initialize camera capture
+        
+        Args:
+            camera_index: int index, /dev/videoX path, "auto", or None
+        """
+        self.camera_source = self._resolve_camera_source(camera_index)
+        # Keep legacy field name for backward compatibility with older modules/tests
+        self.camera_index = self.camera_source
+        self.cap = None
+        self.is_initialized = False
+        self.logger = logging.getLogger(__name__)
+        self._last_read_warn_ts = 0.0
+
+    def _resolve_camera_source(self, camera_source: Optional[Union[int, str]]) -> Union[int, str]:
+        """
+        Resolve requested camera source from argument/env/defaults.
+        Priority:
+          1) explicit argument
+          2) CAMERA_DEVICE env (supports /dev/videoX or "auto")
+          3) CAMERA_INDEX env/config int
+        """
+        if camera_source is None:
+            env_device = os.environ.get("CAMERA_DEVICE", "").strip()
+            if env_device:
+                camera_source = env_device
+            else:
+                camera_source = os.environ.get("CAMERA_INDEX", str(CAMERA_INDEX))
+
+        if isinstance(camera_source, str):
+            s = camera_source.strip()
+            if not s:
+                return int(CAMERA_INDEX)
+            if s.lower() == "auto":
+                return "auto"
+            try:
+                return int(s)
+            except ValueError:
+                return s
+
+        return int(camera_source)
+
+    def _candidate_sources(self) -> List[Union[int, str]]:
+        """
+        Build candidate capture sources. When CAMERA_FALLBACK_SCAN=1 (default),
+        we also try available /dev/video* nodes if the primary source fails.
+        """
+        src = self.camera_source
+        candidates: List[Union[int, str]] = [src]
+
+        # If primary source is /dev/videoX, also try numeric index X.
+        if isinstance(src, str) and src.startswith("/dev/video"):
+            try:
+                idx = int(src.replace("/dev/video", ""))
+                candidates.append(idx)
+            except Exception:
+                pass
+
+        do_scan = os.environ.get("CAMERA_FALLBACK_SCAN", "1").strip().lower() not in (
+            "0", "false", "no", "off"
+        )
+        if src == "auto" or do_scan:
+            for p in sorted(Path("/dev").glob("video*")):
+                sp = str(p)
+                if sp not in candidates:
+                    candidates.append(sp)
+                try:
+                    idx = int(sp.replace("/dev/video", ""))
+                    if idx not in candidates:
+                        candidates.append(idx)
+                except Exception:
+                    pass
+
+        return candidates
+
+    def _open_capture(self, source: Union[int, str]):
+        if isinstance(source, str) and source.startswith("/dev/video"):
+            # V4L2 backend is more reliable for /dev/videoX on Linux.
+            return cv2.VideoCapture(source, cv2.CAP_V4L2)
+        return cv2.VideoCapture(source)
+        
+    def initialize(self) -> bool:
+        """
+        Initialize camera connection
+        
+        Returns:
+            bool: True if successful, False otherwise
+        """
+        try:
+            self.release()
+            tried: List[str] = []
+
+            for source in self._candidate_sources():
+                tried.append(str(source))
+                cap = None
+                try:
+                    cap = self._open_capture(source)
+                except Exception:
+                    cap = None
+
+                if cap is None or not cap.isOpened():
+                    try:
+                        if cap is not None:
+                            cap.release()
+                    except Exception:
+                        pass
+                    continue
+
+                # Set camera properties
+                cap.set(cv2.CAP_PROP_FRAME_WIDTH, FRAME_WIDTH)
+                cap.set(cv2.CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT)
+                cap.set(cv2.CAP_PROP_FPS, FPS)
+
+                # Test capture
+                ret, _frame = cap.read()
+                if not ret:
+                    cap.release()
+                    continue
+
+                self.cap = cap
+                self.camera_source = source
+                self.camera_index = source
+                self.is_initialized = True
+                self.logger.info(f"Camera initialized successfully: {source}")
+                return True
+
+            self.is_initialized = False
+            self.cap = None
+            self.logger.error(f"Failed to open camera. Tried sources: {', '.join(tried)}")
+            return False
+            
+        except Exception as e:
+            self.logger.error(f"Camera initialization failed: {e}")
+            return False
+    
+    def capture_frame(self) -> Optional[np.ndarray]:
+        """
+        Capture a single frame from camera
+        
+        Returns:
+            numpy.ndarray: Captured frame or None if failed
+        """
+        if not self.is_initialized or self.cap is None:
+            return None
+            
+        try:
+            ret, frame = self.cap.read()
+            if not ret:
+                now = time.time()
+                # Throttle noisy warnings when camera stream is unstable/unavailable.
+                if now - self._last_read_warn_ts >= 5.0:
+                    self.logger.warning("Failed to capture frame from camera")
+                    self._last_read_warn_ts = now
+                return None
+                
+            return frame
+            
+        except Exception as e:
+            self.logger.error(f"Frame capture failed: {e}")
+            return None
+    
+    def frame_to_base64(self, frame: np.ndarray, format: str = 'JPEG') -> Optional[str]:
+        """
+        Convert OpenCV frame to base64 string for API transmission
+        
+        Args:
+            frame: OpenCV frame (BGR format)
+            format: Image format ('JPEG' or 'PNG')
+            
+        Returns:
+            str: Base64 encoded image or None if failed
+        """
+        try:
+            # Convert BGR to RGB
+            rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            
+            # Convert to PIL Image
+            pil_image = Image.fromarray(rgb_frame)
+            
+            # Convert to bytes
+            buffer = io.BytesIO()
+            pil_image.save(buffer, format=format, quality=85)
+            buffer.seek(0)
+            
+            # Encode to base64
+            img_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8')
+            
+            return img_base64
+            
+        except Exception as e:
+            self.logger.error(f"Base64 conversion failed: {e}")
+            return None
+    
+    def frame_to_pil(self, frame: np.ndarray) -> Optional[Image.Image]:
+        """
+        Convert OpenCV frame to PIL Image for Gemini API
+        
+        Args:
+            frame: OpenCV frame (BGR format)
+            
+        Returns:
+            PIL.Image: Converted image or None if failed
+        """
+        try:
+            # Convert BGR to RGB
+            rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            
+            # Convert to PIL Image
+            pil_image = Image.fromarray(rgb_frame)
+            
+            return pil_image
+            
+        except Exception as e:
+            self.logger.error(f"PIL conversion failed: {e}")
+            return None
+    
+    def get_frame_info(self) -> dict:
+        """
+        Get current camera frame information
+        
+        Returns:
+            dict: Frame information including resolution, FPS
+        """
+        if not self.is_initialized or self.cap is None:
+            return {}
+            
+        try:
+            info = {
+                'width': int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
+                'height': int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT)),
+                'fps': self.cap.get(cv2.CAP_PROP_FPS),
+                'format': int(self.cap.get(cv2.CAP_PROP_FORMAT)),
+                'brightness': self.cap.get(cv2.CAP_PROP_BRIGHTNESS),
+                'contrast': self.cap.get(cv2.CAP_PROP_CONTRAST),
+                'saturation': self.cap.get(cv2.CAP_PROP_SATURATION)
+            }
+            return info
+            
+        except Exception as e:
+            self.logger.error(f"Failed to get frame info: {e}")
+            return {}
+    
+    def release(self):
+        """
+        Release camera resources
+        """
+        try:
+            if self.cap is not None:
+                self.cap.release()
+                self.cap = None
+                self.logger.info("Camera released successfully")
+                
+            self.is_initialized = False
+            
+        except Exception as e:
+            self.logger.error(f"Camera release failed: {e}")
+        finally:
+            # Headless systems often ship OpenCV without HighGUI window backends.
+            # Do not fail camera lifecycle because window teardown is unavailable.
+            try:
+                import cv2
+                cv2.destroyAllWindows()
+            except Exception:
+                pass
+    
+    def __enter__(self):
+        """Context manager entry"""
+        self.initialize()
+        return self
+    
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """Context manager exit"""
+        self.release()
+        return False  # Don't suppress exceptions
+
+# Utility functions for camera testing
+def test_camera_capture():
+    """
+    Test camera capture functionality
+    """
+    logging.basicConfig(level=logging.INFO)
+    
+    with CameraCapture() as camera:
+        if not camera.is_initialized:
+            print("Failed to initialize camera")
+            return
+            
+        print("Camera info:", camera.get_frame_info())
+        
+        # Capture test frame
+        frame = camera.capture_frame()
+        if frame is not None:
+            print(f"Captured frame shape: {frame.shape}")
+            
+            # Test base64 conversion
+            base64_str = camera.frame_to_base64(frame)
+            if base64_str:
+                print(f"Base64 conversion successful, length: {len(base64_str)}")
+            
+            # Test PIL conversion
+            pil_img = camera.frame_to_pil(frame)
+            if pil_img:
+                print(f"PIL conversion successful, size: {pil_img.size}")
+                
+            # Save test image
+            cv2.imwrite('test_capture.jpg', frame)
+            print("Test image saved as test_capture.jpg")
+        else:
+            print("Failed to capture frame")
diff --git a/Modes/AI/vision_detector.py b/Modes/AI/vision_detector.py
new file mode 100644
index 0000000..c5ea902
--- /dev/null
+++ b/Modes/AI/vision_detector.py
@@ -0,0 +1,1480 @@
+"""vision_detector.py
+
+YOLO detector + tracker + intent:
+- YOLO ONNX person detector for subject tracking/intent.
+- YOLO ONNX face detector (optional) for face metrics.
+- Group detection from person clusters.
+- Intent uses RealSense depth first; bbox area fallback.
+"""
+
+from collections import deque
+from threading import Event, Lock, Thread
+import logging
+import os
+import time
+from pathlib import Path
+
+import cv2
+import numpy as np
+
+from Modes.AI.camera_module import CameraCapture
+from Core import settings as config
+from Core.error_events import record_error
+from Server import direct_camera_client
+
+try:
+    import pyrealsense2 as rs  # type: ignore
+
+    _HAS_RS = True
+except Exception:
+    _HAS_RS = False
+
+try:
+    from ultralytics import YOLO  # type: ignore
+
+    _HAS_ULTRALYTICS = True
+except Exception:
+    YOLO = None  # type: ignore
+    _HAS_ULTRALYTICS = False
+
+logger = logging.getLogger(__name__)
+
+
+def _coerce_backend_name(value: str | None) -> str:
+    v = str(value or "").strip().lower()
+    if v in ("yolo", "normal"):
+        return v
+    return "normal"
+
+
+def _coerce_yolo_runtime(value: str | None) -> str:
+    v = str(value or "").strip().lower()
+    if v in ("ultralytics", "opencv"):
+        return v
+    return "ultralytics"
+
+
+def _resolve_model_path(path_value: str | None) -> Path | None:
+    if not path_value:
+        return None
+    p = Path(str(path_value)).expanduser()
+    if not p.is_absolute():
+        p = (config.PROJECT_ROOT / p).resolve()
+    return p
+
+
+def _probe_onnx_model(path_value: str | None) -> dict:
+    out = {"path": "", "exists": False, "loadable": False, "error": ""}
+    p = _resolve_model_path(path_value)
+    if p is None:
+        return out
+
+    out["path"] = str(p)
+    if not p.exists() or (not p.is_file()):
+        out["error"] = "model file missing"
+        return out
+
+    out["exists"] = True
+    try:
+        cv2.dnn.readNetFromONNX(str(p))
+        out["loadable"] = True
+    except Exception as e:
+        out["error"] = str(e)
+    return out
+
+
+def _probe_ultralytics_model(path_value: str | None) -> dict:
+    out = {"path": "", "exists": False, "loadable": False, "error": ""}
+    p = _resolve_model_path(path_value)
+    if p is None:
+        return out
+
+    out["path"] = str(p)
+    if not p.exists() or (not p.is_file()):
+        out["error"] = "model file missing"
+        return out
+    out["exists"] = True
+
+    if not _HAS_ULTRALYTICS:
+        out["error"] = "ultralytics not installed"
+        return out
+
+    try:
+        YOLO(str(p))
+        out["loadable"] = True
+    except Exception as e:
+        out["error"] = str(e)
+    return out
+
+
+def probe_ai_readiness(backend: str | None = None, strict_required: bool | None = None) -> dict:
+    configured_backend = _coerce_backend_name(
+        backend if backend is not None else config.read_vision_detector_backend()
+    )
+    yolo_runtime = _coerce_yolo_runtime(config.read_vision_yolo_runtime())
+    strict = bool(config.read_vision_yolo_strict_required() if strict_required is None else strict_required)
+
+    person_path = (
+        os.environ.get("DETECTOR_PERSON_YOLO_ONNX", "").strip()
+        or os.environ.get("DETECTOR_ONNX_PATH", "").strip()
+        or str(getattr(config, "VISION_PERSON_YOLO_ONNX", "")).strip()
+    )
+    face_path = (
+        os.environ.get("DETECTOR_FACE_YOLO_ONNX", "").strip()
+        or str(getattr(config, "VISION_FACE_YOLO_ONNX", "")).strip()
+    )
+
+    if yolo_runtime == "ultralytics":
+        person = _probe_ultralytics_model(person_path)
+        face = _probe_ultralytics_model(face_path)
+    else:
+        person = _probe_onnx_model(person_path)
+        face = _probe_onnx_model(face_path)
+    person_ok = bool(person.get("loadable"))
+    face_ok = bool(face.get("loadable"))
+    yolo_loaded = bool(configured_backend == "yolo" and person_ok)
+
+    block_reason = ""
+    if strict and configured_backend != "yolo":
+        block_reason = "Strict AI mode requires detection_backend=yolo."
+    elif strict and yolo_runtime == "ultralytics" and not _HAS_ULTRALYTICS:
+        block_reason = "Ultralytics runtime selected but package is not installed."
+    elif strict and not person_ok:
+        block_reason = "Person YOLO model is missing/invalid. Fix vision.person_yolo_onnx."
+
+    ok = not bool(block_reason)
+    return {
+        "ok": bool(ok),
+        "strict_required": bool(strict),
+        "configured_backend": configured_backend,
+        "yolo_runtime": yolo_runtime,
+        "effective_backend": "yolo" if yolo_loaded else "normal",
+        "yolo_loaded": bool(yolo_loaded),
+        "person_model_ok": bool(person_ok),
+        "face_model_ok": bool(face_ok),
+        "person_model_path": str(person.get("path") or ""),
+        "face_model_path": str(face.get("path") or ""),
+        "person_model_error": str(person.get("error") or ""),
+        "face_model_error": str(face.get("error") or ""),
+        "block_reason": block_reason,
+    }
+
+
+class VisionDetector:
+    def __init__(self, zmq_host="127.0.0.1", zmq_port=55555, poll_hz=10, video_source: str | None = None):
+        self.zmq_host = zmq_host
+        self.zmq_port = int(zmq_port)
+        self.poll_hz = float(poll_hz)
+        self.video_source = video_source
+
+        self._stop = Event()
+        self._thread = None
+        self._latest_lock = Lock()
+        self._latest = {
+            "frame_time": 0.0,
+            "detector_backend": "normal",
+            "yolo_runtime": "ultralytics",
+            "face_count": 0,
+            "person_count": 0,
+            "group_count": 0,
+            "group_size": 0,
+            "group_detected": False,
+            "boxes": [],
+            "face_boxes": [],
+            "group_boxes": [],
+            "frame": None,
+            "intent_detected": False,
+            "max_area": 0.0,
+            "is_close": False,
+            "is_approaching": False,
+            "depth_m": None,
+            "approach_speed_mps": 0.0,
+            "subject_id": None,
+            "subject_box": None,
+            "subject_visible": False,
+            "subject_locked": False,
+            "target_lock_active": False,
+            "target_lock_type": "",
+            "target_lock_id": None,
+            "target_switch_blocked_count": 0,
+            "camera_ok": False,
+            "depth_ok": False,
+            "camera_restarts": 0,
+            "depth_restarts": 0,
+        }
+
+        # Runtime-selectable detector backend
+        self._detector_backend = self._coerce_backend(
+            os.environ.get("DETECTOR_BACKEND", "").strip() or config.read_vision_detector_backend()
+        )
+        self._last_backend_check_ts = 0.0
+
+        # YOLO detection config
+        self._yolo_runtime = _coerce_yolo_runtime(
+            os.environ.get("DETECTOR_YOLO_RUNTIME", "").strip() or config.read_vision_yolo_runtime()
+        )
+        self._ultralytics_device = (
+            os.environ.get("DETECTOR_YOLO_DEVICE", "").strip() or config.read_vision_yolo_ultralytics_device()
+        )
+        self._person_model_path = str(
+            _resolve_model_path(
+                os.environ.get("DETECTOR_PERSON_YOLO_ONNX", "").strip()
+                or os.environ.get("DETECTOR_ONNX_PATH", "").strip()
+                or str(getattr(config, "VISION_PERSON_YOLO_ONNX", "")).strip()
+                or ""
+            )
+            or ""
+        ).strip()
+        self._face_model_path = str(
+            _resolve_model_path(
+                os.environ.get("DETECTOR_FACE_YOLO_ONNX", "").strip()
+                or str(getattr(config, "VISION_FACE_YOLO_ONNX", "")).strip()
+                or ""
+            )
+            or ""
+        ).strip()
+        input_size = int(max(320, getattr(config, "VISION_INPUT_SIZE", 640)))
+        self._dnn_input_size = (input_size, input_size)
+        self._person_score_thresh = float(getattr(config, "VISION_PERSON_SCORE_THRESH", 0.35))
+        self._face_score_thresh = float(getattr(config, "VISION_FACE_SCORE_THRESH", 0.35))
+        self._nms_iou_thresh = float(getattr(config, "VISION_NMS_IOU_THRESH", 0.45))
+        self._person_class_id = int(getattr(config, "VISION_PERSON_CLASS_ID", 0))
+        self._group_min_people = max(2, int(getattr(config, "VISION_GROUP_MIN_PEOPLE", 3)))
+        self._group_link_distance_px = float(getattr(config, "VISION_GROUP_LINK_DISTANCE_PX", 220.0))
+
+        self._person_net = None
+        self._face_net = None
+        self._warned_person_fallback = False
+        self._warned_yolo_unavailable = False
+        self._warned_ultralytics_missing = False
+        self._last_model_retry_ts = 0.0
+        self._model_retry_sec = float(os.environ.get("YOLO_MODEL_RETRY_SEC", "2.0"))
+
+        # Area-based fallback intent
+        self._proximity_threshold = float(os.environ.get("PROXIMITY_THRESHOLD", "50000"))
+        self._approach_delta = float(os.environ.get("APPROACH_DELTA", "12000"))
+        self._history_len = max(2, int(os.environ.get("INTENT_HISTORY_LEN", "5")))
+        self._area_history = deque(maxlen=self._history_len)
+
+        # Depth-first intent
+        self._min_depth_m = float(os.environ.get("MIN_DEPTH_M", "1.7"))
+        self._min_approach_speed_mps = float(os.environ.get("MIN_APPROACH_SPEED_MPS", "0.08"))
+        self._depth_history_len = max(2, int(os.environ.get("DEPTH_HISTORY_LEN", "6")))
+        self._depth_history = deque(maxlen=self._depth_history_len)
+
+        # Subject lock
+        self._hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled())
+        self._locked_target_type = ""
+        self._locked_subject_id = None
+        self._locked_group_id = None
+        self._target_switch_blocked_count = 0
+        self._subject_lock_lost_frames = max(1, int(os.environ.get("SUBJECT_LOCK_LOST_FRAMES", "20")))
+        self._subject_lost_count = 0
+
+        # Camera/depth watchdog
+        self._no_frame_count = 0
+        self._recover_after_no_frame = max(3, int(os.environ.get("CAMERA_RECOVER_AFTER_FRAMES", "10")))
+        self._camera_ok = False
+        self._depth_ok = False
+        self._camera_restarts = 0
+        self._depth_restarts = 0
+        self._depth_enabled = os.environ.get("DETECTOR_USE_REALSENSE_DEPTH", "1").strip().lower() not in (
+            "0",
+            "false",
+            "no",
+            "off",
+        )
+        self._rs_pipeline = None
+        self._rs_profile = None
+        self._last_rs_restart = 0.0
+
+        self._apply_detector_backend(self._detector_backend, reason="init")
+        self._latest["detector_backend"] = self._effective_backend()
+        self._latest["yolo_runtime"] = self._yolo_runtime
+        self._face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
+
+        self._camera = CameraCapture()
+        try:
+            self._camera.initialize()
+        except Exception:
+            logger.warning("VisionDetector: could not init CameraCapture fallback")
+
+        self._video_cap = None
+        if self.video_source:
+            try:
+                self._video_cap = cv2.VideoCapture(self.video_source)
+                if not self._video_cap.isOpened():
+                    logger.warning(f"VisionDetector: could not open video source {self.video_source}")
+                    self._video_cap = None
+                else:
+                    logger.info(f"VisionDetector: using video source {self.video_source} for simulation")
+            except Exception as e:
+                logger.warning(f"VisionDetector: video source init failed: {e}")
+
+        self._ensure_depth_pipeline(force=False)
+
+    @staticmethod
+    def _coerce_backend(value: str | None) -> str:
+        return _coerce_backend_name(value)
+
+    def _effective_backend(self) -> str:
+        if self._detector_backend == "yolo" and self._person_net is not None:
+            return "yolo"
+        return "normal"
+
+    def _build_readiness(self, strict_required: bool | None = None) -> dict:
+        strict = bool(config.read_vision_yolo_strict_required() if strict_required is None else strict_required)
+        configured_backend = self._coerce_backend(self._detector_backend)
+        yolo_runtime = _coerce_yolo_runtime(self._yolo_runtime)
+        if yolo_runtime == "ultralytics":
+            person_model_ok = bool(self._person_net is not None and hasattr(self._person_net, "predict"))
+            face_model_ok = bool(self._face_net is not None and hasattr(self._face_net, "predict")) if self._face_model_path else False
+        else:
+            person_model_ok = bool(self._person_net is not None and hasattr(self._person_net, "setInput"))
+            face_model_ok = bool(self._face_net is not None and hasattr(self._face_net, "setInput")) if self._face_model_path else False
+        yolo_loaded = bool(configured_backend == "yolo" and person_model_ok)
+
+        block_reason = ""
+        if strict and configured_backend != "yolo":
+            block_reason = "Strict AI mode requires detection_backend=yolo."
+        elif strict and yolo_runtime == "ultralytics" and not _HAS_ULTRALYTICS:
+            block_reason = "Ultralytics runtime selected but package is not installed."
+        elif strict and not person_model_ok:
+            block_reason = "Person YOLO model is missing/invalid. Fix vision.person_yolo_onnx."
+
+        return {
+            "ok": not bool(block_reason),
+            "strict_required": bool(strict),
+            "configured_backend": configured_backend,
+            "yolo_runtime": yolo_runtime,
+            "effective_backend": self._effective_backend(),
+            "yolo_loaded": bool(yolo_loaded),
+            "person_model_ok": bool(person_model_ok),
+            "face_model_ok": bool(face_model_ok),
+            "person_model_path": str(self._person_model_path or ""),
+            "face_model_path": str(self._face_model_path or ""),
+            "person_model_error": "" if person_model_ok else "model not loaded",
+            "face_model_error": "" if (face_model_ok or (not self._face_model_path)) else "model not loaded",
+            "block_reason": block_reason,
+        }
+
+    def readiness(self, strict_required: bool | None = None) -> dict:
+        return self._build_readiness(strict_required=strict_required)
+
+    @classmethod
+    def probe_readiness(cls, backend: str | None = None, strict_required: bool | None = None) -> dict:
+        return probe_ai_readiness(backend=backend, strict_required=strict_required)
+
+    def _maybe_retry_yolo_models(self, now_ts: float):
+        if self._detector_backend != "yolo":
+            return
+        if self._person_net is not None and (self._face_net is not None or not self._face_model_path):
+            return
+        if (now_ts - self._last_model_retry_ts) < max(0.5, self._model_retry_sec):
+            return
+        self._last_model_retry_ts = now_ts
+        if self._yolo_runtime == "ultralytics":
+            if self._person_net is None:
+                self._person_net = self._load_ultralytics_model(self._person_model_path, label="person")
+            if self._face_net is None and self._face_model_path:
+                self._face_net = self._load_ultralytics_model(self._face_model_path, label="face")
+        else:
+            if self._person_net is None:
+                self._person_net = self._load_onnx_model(self._person_model_path, label="person")
+            if self._face_net is None and self._face_model_path:
+                self._face_net = self._load_onnx_model(self._face_model_path, label="face")
+
+    def _apply_detector_backend(self, backend: str, reason: str = ""):
+        backend = self._coerce_backend(backend)
+        prev_runtime = self._yolo_runtime
+        self._detector_backend = backend
+        self._warned_person_fallback = False
+        self._warned_yolo_unavailable = False
+        self._warned_ultralytics_missing = False
+
+        try:
+            self._yolo_runtime = _coerce_yolo_runtime(config.read_vision_yolo_runtime())
+        except Exception:
+            self._yolo_runtime = _coerce_yolo_runtime(self._yolo_runtime)
+        self._yolo_runtime = _coerce_yolo_runtime(
+            os.environ.get("DETECTOR_YOLO_RUNTIME", "").strip() or self._yolo_runtime
+        )
+        if self._yolo_runtime != prev_runtime:
+            self._person_net = None
+            self._face_net = None
+
+        if backend == "yolo":
+            if self._yolo_runtime == "ultralytics":
+                if self._person_net is None:
+                    self._person_net = self._load_ultralytics_model(self._person_model_path, label="person")
+                if self._face_net is None and self._face_model_path:
+                    self._face_net = self._load_ultralytics_model(self._face_model_path, label="face")
+            else:
+                if self._person_net is None:
+                    self._person_net = self._load_onnx_model(self._person_model_path, label="person")
+                if self._face_net is None and self._face_model_path:
+                    self._face_net = self._load_onnx_model(self._face_model_path, label="face")
+
+            if self._person_net is None:
+                logger.warning(
+                    f"VisionDetector: YOLO backend selected ({self._yolo_runtime}) but person model unavailable. Falling back to normal."
+                )
+            elif self._face_net is None and self._face_model_path:
+                logger.info("VisionDetector: YOLO person active, face model missing -> Haar face fallback.")
+        else:
+            # Force non-AI normal mode.
+            self._person_net = None
+            self._face_net = None
+
+        suffix = f" ({reason})" if reason else ""
+        logger.info(f"VisionDetector: detector backend set to {self._effective_backend()} [runtime={self._yolo_runtime}]{suffix}")
+
+    def _refresh_detector_backend(self, now_ts: float):
+        if (now_ts - self._last_backend_check_ts) < 1.0:
+            self._maybe_retry_yolo_models(now_ts)
+            return
+        self._last_backend_check_ts = now_ts
+        try:
+            self._hard_target_lock_enabled = bool(config.read_vision_hard_target_lock_enabled())
+        except Exception:
+            pass
+        try:
+            cfg_backend = self._coerce_backend(config.read_vision_detector_backend())
+        except Exception:
+            cfg_backend = self._detector_backend
+        try:
+            cfg_runtime = _coerce_yolo_runtime(config.read_vision_yolo_runtime())
+        except Exception:
+            cfg_runtime = self._yolo_runtime
+        if cfg_backend != self._detector_backend or cfg_runtime != self._yolo_runtime:
+            self._apply_detector_backend(cfg_backend, reason="runtime switch")
+        else:
+            self._maybe_retry_yolo_models(now_ts)
+
+    @staticmethod
+    def _load_onnx_model(path: str | None, label: str):
+        if not path:
+            return None
+        try:
+            net = cv2.dnn.readNetFromONNX(str(path))
+            net.setPreferableBackend(cv2.dnn.DNN_BACKEND_DEFAULT)
+            net.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)
+            logger.info(f"VisionDetector: loaded {label} YOLO ONNX model: {path}")
+            return net
+        except Exception as e:
+            logger.warning(f"VisionDetector: failed to load {label} model {path}: {e}")
+            return None
+
+    def _load_ultralytics_model(self, path: str | None, label: str):
+        if not path:
+            return None
+        if not _HAS_ULTRALYTICS:
+            if not self._warned_ultralytics_missing:
+                self._warned_ultralytics_missing = True
+                logger.warning("VisionDetector: ultralytics package not installed; cannot use ultralytics runtime.")
+            return None
+        try:
+            model = YOLO(str(path))
+            logger.info(f"VisionDetector: loaded {label} Ultralytics model: {path}")
+            return model
+        except Exception as e:
+            logger.warning(f"VisionDetector: failed to load {label} ultralytics model {path}: {e}")
+            return None
+
+    def _run_yolo_ultralytics(self, model, frame, conf_thresh: float, class_filter: int | None = None):
+        if model is None or frame is None:
+            return []
+        try:
+            results = model.predict(
+                source=frame,
+                conf=float(conf_thresh),
+                iou=float(self._nms_iou_thresh),
+                imgsz=int(self._dnn_input_size[0]),
+                device=str(self._ultralytics_device),
+                verbose=False,
+            )
+            if not results:
+                return []
+            res = results[0]
+            boxes_obj = getattr(res, "boxes", None)
+            if boxes_obj is None:
+                return []
+            xyxy = boxes_obj.xyxy
+            confs = boxes_obj.conf
+            classes = boxes_obj.cls
+            if xyxy is None or confs is None or classes is None:
+                return []
+
+            try:
+                xyxy_np = xyxy.cpu().numpy()
+                conf_np = confs.cpu().numpy()
+                cls_np = classes.cpu().numpy()
+            except Exception:
+                xyxy_np = np.asarray(xyxy)
+                conf_np = np.asarray(confs)
+                cls_np = np.asarray(classes)
+
+            out = []
+            for i in range(len(xyxy_np)):
+                cls_id = int(round(float(cls_np[i])))
+                if class_filter is not None and cls_id != int(class_filter):
+                    continue
+                x1, y1, x2, y2 = [float(v) for v in xyxy_np[i][:4]]
+                x = int(round(max(0.0, x1)))
+                y = int(round(max(0.0, y1)))
+                w = int(round(max(0.0, x2 - x1)))
+                h = int(round(max(0.0, y2 - y1)))
+                if w < 4 or h < 4:
+                    continue
+                out.append(
+                    {
+                        "x": x,
+                        "y": y,
+                        "w": w,
+                        "h": h,
+                        "conf": float(conf_np[i]),
+                        "class_id": cls_id,
+                    }
+                )
+            return out
+        except Exception as e:
+            record_error("vision_detector", "run_yolo_ultralytics", e)
+            return []
+
+    @staticmethod
+    def _prepare_output_rows(output) -> np.ndarray:
+        if isinstance(output, (list, tuple)):
+            chunks = []
+            for out in output:
+                rows = VisionDetector._prepare_output_rows(out)
+                if rows.size > 0:
+                    chunks.append(rows)
+            if not chunks:
+                return np.empty((0, 0), dtype=np.float32)
+            try:
+                return np.concatenate(chunks, axis=0)
+            except Exception:
+                return chunks[0]
+
+        arr = np.asarray(output)
+        if arr.size == 0:
+            return np.empty((0, 0), dtype=np.float32)
+
+        if arr.ndim >= 4:
+            arr = arr.reshape(arr.shape[0], -1, arr.shape[-1])
+
+        if arr.ndim == 3:
+            if arr.shape[0] == 1:
+                arr = arr[0]
+            else:
+                arr = arr.reshape(-1, arr.shape[-1])
+        elif arr.ndim == 2:
+            pass
+        elif arr.ndim == 1:
+            arr = arr.reshape(1, -1)
+        else:
+            arr = arr.reshape(-1, 1)
+
+        if arr.ndim != 2:
+            return np.empty((0, 0), dtype=np.float32)
+
+        # Typical YOLO ONNX output can be [84, 8400], transpose to [8400, 84].
+        if arr.shape[0] < arr.shape[1] and arr.shape[1] > 64 and arr.shape[0] <= 256:
+            arr = arr.T
+
+        return arr.astype(np.float32, copy=False)
+
+    @staticmethod
+    def _decode_conf_and_class(row: np.ndarray) -> tuple[float, int] | None:
+        n = int(row.shape[0])
+        if n < 5:
+            return None
+
+        # End-to-end format: [x1, y1, x2, y2, conf, class_id]
+        if (
+            n == 6
+            and row[2] > row[0]
+            and row[3] > row[1]
+            and (row[2] > 2.0 or row[3] > 2.0 or row[0] < 0.0 or row[1] < 0.0)
+            and 0.0 <= float(row[4]) <= 1.0
+            and abs(float(row[5]) - round(float(row[5]))) <= 1e-3
+        ):
+            return float(row[4]), int(round(float(row[5])))
+
+        obj = max(0.0, float(row[4]))
+        if n <= 5:
+            return obj, 0
+
+        class_scores = row[5:]
+        cls_id = int(np.argmax(class_scores))
+        cls_score = max(0.0, float(class_scores[cls_id]))
+
+        if obj <= 1.5:
+            conf = obj * cls_score
+        else:
+            conf = cls_score
+        return float(conf), cls_id
+
+    @staticmethod
+    def _coords_to_xywh(coords: np.ndarray, frame_w: int, frame_h: int) -> tuple[int, int, int, int] | None:
+        if coords.shape[0] < 4:
+            return None
+
+        a, b, c, d = (float(coords[0]), float(coords[1]), float(coords[2]), float(coords[3]))
+        max_abs = max(abs(a), abs(b), abs(c), abs(d))
+
+        # xyxy-style
+        if c > a and d > b:
+            if max_abs <= 2.0:
+                x1, y1 = a * frame_w, b * frame_h
+                x2, y2 = c * frame_w, d * frame_h
+            else:
+                x1, y1, x2, y2 = a, b, c, d
+        else:
+            # cx, cy, w, h style (YOLO default)
+            if max_abs <= 2.0:
+                cx, cy = a * frame_w, b * frame_h
+                bw, bh = c * frame_w, d * frame_h
+            else:
+                cx, cy = a, b
+                bw, bh = c, d
+            x1 = cx - (bw / 2.0)
+            y1 = cy - (bh / 2.0)
+            x2 = cx + (bw / 2.0)
+            y2 = cy + (bh / 2.0)
+
+        x1_i = max(0, min(frame_w - 1, int(round(x1))))
+        y1_i = max(0, min(frame_h - 1, int(round(y1))))
+        x2_i = max(0, min(frame_w, int(round(x2))))
+        y2_i = max(0, min(frame_h, int(round(y2))))
+
+        w_i = max(0, x2_i - x1_i)
+        h_i = max(0, y2_i - y1_i)
+        if w_i < 4 or h_i < 4:
+            return None
+        return x1_i, y1_i, w_i, h_i
+
+    def _decode_yolo_output(self, output, frame_w: int, frame_h: int, conf_thresh: float, class_filter: int | None):
+        rows = self._prepare_output_rows(output)
+        if rows.size == 0:
+            return []
+
+        candidates = []
+        rects = []
+        confs = []
+        for row in rows:
+            conf_and_class = self._decode_conf_and_class(row)
+            if conf_and_class is None:
+                continue
+            conf, class_id = conf_and_class
+            if conf < conf_thresh:
+                continue
+            if class_filter is not None and int(class_id) != int(class_filter):
+                continue
+            xywh = self._coords_to_xywh(row[:4], frame_w=frame_w, frame_h=frame_h)
+            if xywh is None:
+                continue
+            x, y, w, h = xywh
+            candidates.append({"x": x, "y": y, "w": w, "h": h, "conf": float(conf), "class_id": int(class_id)})
+            rects.append([int(x), int(y), int(w), int(h)])
+            confs.append(float(conf))
+
+        if not candidates:
+            return []
+
+        try:
+            idxs = cv2.dnn.NMSBoxes(rects, confs, conf_thresh, self._nms_iou_thresh)
+        except Exception:
+            idxs = None
+
+        if idxs is None or len(idxs) == 0:
+            return candidates
+
+        if isinstance(idxs, np.ndarray):
+            keep = [int(i) for i in idxs.flatten().tolist()]
+        else:
+            keep = []
+            for i in idxs:
+                if isinstance(i, (list, tuple, np.ndarray)):
+                    keep.append(int(i[0]))
+                else:
+                    keep.append(int(i))
+
+        filtered = []
+        for idx in keep:
+            if 0 <= idx < len(candidates):
+                filtered.append(candidates[idx])
+        return filtered
+
+    def _run_yolo_onnx(self, net, frame, conf_thresh: float, class_filter: int | None = None):
+        if net is None or frame is None:
+            return []
+        try:
+            blob = cv2.dnn.blobFromImage(frame, 1.0 / 255.0, self._dnn_input_size, swapRB=True, crop=False)
+            net.setInput(blob)
+            output = None
+            try:
+                names = net.getUnconnectedOutLayersNames()
+                if names:
+                    output = net.forward(names)
+            except Exception:
+                output = None
+            if output is None:
+                output = net.forward()
+            h, w = frame.shape[:2]
+            return self._decode_yolo_output(output, frame_w=w, frame_h=h, conf_thresh=conf_thresh, class_filter=class_filter)
+        except Exception as e:
+            record_error("vision_detector", "run_yolo_onnx", e)
+            return []
+
+    @staticmethod
+    def _bbox_iou(a: tuple[int, int, int, int], b: tuple[int, int, int, int]) -> float:
+        ax, ay, aw, ah = a
+        bx, by, bw, bh = b
+        ax2, ay2 = ax + aw, ay + ah
+        bx2, by2 = bx + bw, by + bh
+
+        ix1 = max(ax, bx)
+        iy1 = max(ay, by)
+        ix2 = min(ax2, bx2)
+        iy2 = min(ay2, by2)
+        iw = max(0, ix2 - ix1)
+        ih = max(0, iy2 - iy1)
+        inter = float(iw * ih)
+        if inter <= 0.0:
+            return 0.0
+        union = float(aw * ah + bw * bh) - inter
+        if union <= 0.0:
+            return 0.0
+        return inter / union
+
+    def _detect_person_boxes(self, frame, tracker):
+        if self._detector_backend == "yolo" and self._person_net is not None:
+            if self._yolo_runtime == "ultralytics":
+                raw = self._run_yolo_ultralytics(
+                    self._person_net,
+                    frame,
+                    conf_thresh=self._person_score_thresh,
+                    class_filter=self._person_class_id,
+                )
+            else:
+                raw = self._run_yolo_onnx(
+                    self._person_net,
+                    frame,
+                    conf_thresh=self._person_score_thresh,
+                    class_filter=self._person_class_id,
+                )
+            boxes_raw = [(int(d["x"]), int(d["y"]), int(d["w"]), int(d["h"])) for d in raw]
+            assigned = tracker.update(boxes_raw)
+
+            boxes = []
+            for (cid, box) in assigned:
+                best_conf = 0.0
+                for det in raw:
+                    dbox = (int(det["x"]), int(det["y"]), int(det["w"]), int(det["h"]))
+                    iou = self._bbox_iou(tuple(box), dbox)
+                    if iou > 0.5:
+                        best_conf = max(best_conf, float(det.get("conf", 0.0)))
+                boxes.append(
+                    {
+                        "x": int(box[0]),
+                        "y": int(box[1]),
+                        "w": int(box[2]),
+                        "h": int(box[3]),
+                        "id": int(cid),
+                        "conf": float(best_conf),
+                    }
+                )
+            return boxes
+
+        if self._detector_backend == "yolo" and self._person_net is None and not self._warned_yolo_unavailable:
+            self._warned_yolo_unavailable = True
+            logger.warning("VisionDetector: YOLO person model unavailable at runtime; using normal detector.")
+
+        if not self._warned_person_fallback:
+            self._warned_person_fallback = True
+            logger.warning("VisionDetector: person fallback enabled (Haar face boxes used as person proxies).")
+
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        faces = self._face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4, minSize=(30, 30))
+        boxes_raw = [tuple(map(int, f)) for f in faces]
+        assigned = tracker.update(boxes_raw)
+        return [
+            {"x": int(b[0]), "y": int(b[1]), "w": int(b[2]), "h": int(b[3]), "id": int(i), "conf": 1.0}
+            for (i, b) in assigned
+        ]
+
+    def _detect_face_boxes(self, frame):
+        if self._detector_backend == "yolo" and self._face_net is not None:
+            if self._yolo_runtime == "ultralytics":
+                raw = self._run_yolo_ultralytics(
+                    self._face_net,
+                    frame,
+                    conf_thresh=self._face_score_thresh,
+                    class_filter=None,
+                )
+            else:
+                raw = self._run_yolo_onnx(self._face_net, frame, conf_thresh=self._face_score_thresh, class_filter=None)
+            return [
+                {
+                    "x": int(d["x"]),
+                    "y": int(d["y"]),
+                    "w": int(d["w"]),
+                    "h": int(d["h"]),
+                    "conf": float(d.get("conf", 0.0)),
+                }
+                for d in raw
+            ]
+
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        faces = self._face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4, minSize=(30, 30))
+        return [{"x": int(x), "y": int(y), "w": int(w), "h": int(h), "conf": 1.0} for (x, y, w, h) in faces]
+
+    def _detect_groups(self, person_boxes):
+        if len(person_boxes) < self._group_min_people:
+            return []
+
+        centers = []
+        for b in person_boxes:
+            cx = float(b.get("x", 0.0)) + (float(b.get("w", 0.0)) / 2.0)
+            cy = float(b.get("y", 0.0)) + (float(b.get("h", 0.0)) / 2.0)
+            centers.append((cx, cy))
+
+        n = len(person_boxes)
+        visited = set()
+        components = []
+        link_dist_sq = float(self._group_link_distance_px) * float(self._group_link_distance_px)
+
+        for i in range(n):
+            if i in visited:
+                continue
+            stack = [i]
+            comp = []
+            while stack:
+                cur = stack.pop()
+                if cur in visited:
+                    continue
+                visited.add(cur)
+                comp.append(cur)
+                cx, cy = centers[cur]
+                for j in range(n):
+                    if j in visited:
+                        continue
+                    dx = cx - centers[j][0]
+                    dy = cy - centers[j][1]
+                    if (dx * dx + dy * dy) <= link_dist_sq:
+                        stack.append(j)
+            components.append(comp)
+
+        groups = []
+        gid = 1
+        for comp in components:
+            if len(comp) < self._group_min_people:
+                continue
+            xs = [int(person_boxes[k]["x"]) for k in comp]
+            ys = [int(person_boxes[k]["y"]) for k in comp]
+            x2s = [int(person_boxes[k]["x"] + person_boxes[k]["w"]) for k in comp]
+            y2s = [int(person_boxes[k]["y"] + person_boxes[k]["h"]) for k in comp]
+            x1 = min(xs)
+            y1 = min(ys)
+            x2 = max(x2s)
+            y2 = max(y2s)
+            groups.append(
+                {
+                    "id": gid,
+                    "size": int(len(comp)),
+                    "members": [int(person_boxes[k].get("id", 0)) for k in comp],
+                    "x": int(x1),
+                    "y": int(y1),
+                    "w": int(max(0, x2 - x1)),
+                    "h": int(max(0, y2 - y1)),
+                }
+            )
+            gid += 1
+
+        groups.sort(key=lambda g: (-int(g.get("size", 0)), int(g.get("id", 0))))
+        return groups
+
+    def start(self):
+        if self._thread and self._thread.is_alive():
+            return
+        self._stop.clear()
+        self._thread = Thread(target=self._run, daemon=True)
+        self._thread.start()
+
+    def stop(self):
+        self._stop.set()
+        if self._thread:
+            self._thread.join(timeout=1.0)
+        self._close_depth_pipeline()
+        try:
+            if self._video_cap is not None:
+                self._video_cap.release()
+        except Exception as e:
+            record_error("vision_detector", "stop_release_video", e)
+
+    def latest(self):
+        with self._latest_lock:
+            return dict(self._latest)
+
+    def set_hard_lock(self, enabled: bool):
+        self._hard_target_lock_enabled = bool(enabled)
+
+    def lock_target_from_snapshot(self, snapshot: dict | None = None, lock_group: bool = False):
+        s = snapshot or self.latest()
+        self._locked_target_type = ""
+        self._locked_group_id = None
+        self._locked_subject_id = None
+
+        if lock_group:
+            groups = s.get("group_boxes") or []
+            if groups:
+                try:
+                    g = max(
+                        groups,
+                        key=lambda x: (int(x.get("size", 0)), float(x.get("w", 0.0)) * float(x.get("h", 0.0))),
+                    )
+                except Exception:
+                    g = groups[0]
+                gid = g.get("id")
+                members = g.get("members") or []
+                try:
+                    self._locked_group_id = int(gid) if gid is not None else None
+                except Exception:
+                    self._locked_group_id = None
+                try:
+                    self._locked_subject_id = int(members[0]) if members else None
+                except Exception:
+                    self._locked_subject_id = None
+                if self._locked_group_id is not None:
+                    self._locked_target_type = "group"
+
+        if self._locked_target_type != "group":
+            sid = s.get("subject_id")
+            if sid is None:
+                boxes = s.get("boxes") or []
+                if boxes:
+                    try:
+                        sid = max(boxes, key=lambda x: float(x.get("w", 0.0)) * float(x.get("h", 0.0))).get("id")
+                    except Exception:
+                        sid = boxes[0].get("id")
+            try:
+                self._locked_subject_id = int(sid) if sid is not None else None
+            except Exception:
+                self._locked_subject_id = None
+            if self._locked_subject_id is not None:
+                self._locked_target_type = "subject"
+
+        self._subject_lost_count = 0
+
+    def unlock_target(self):
+        self._locked_target_type = ""
+        self._locked_group_id = None
+        self._locked_subject_id = None
+        self._subject_lost_count = 0
+
+    def lock_subject(self, subject_id: int | None = None):
+        if subject_id is None:
+            snap = self.latest()
+            subject_id = snap.get("subject_id")
+        try:
+            self._locked_subject_id = int(subject_id) if subject_id is not None else None
+        except Exception:
+            self._locked_subject_id = None
+        self._locked_group_id = None
+        self._locked_target_type = "subject" if self._locked_subject_id is not None else ""
+        self._subject_lost_count = 0
+
+    def lock_subject_from_snapshot(self, snapshot: dict | None = None):
+        s = snapshot or self.latest()
+        sid = s.get("subject_id")
+        if sid is None:
+            boxes = s.get("boxes") or []
+            if boxes:
+                b = max(boxes, key=lambda x: float(x.get("w", 0.0)) * float(x.get("h", 0.0)))
+                sid = b.get("id")
+        self.lock_subject(sid)
+
+    def unlock_subject(self):
+        self.unlock_target()
+
+    def _close_depth_pipeline(self):
+        if self._rs_pipeline is not None:
+            try:
+                self._rs_pipeline.stop()
+            except Exception:
+                pass
+        self._rs_pipeline = None
+        self._rs_profile = None
+        self._depth_ok = False
+
+    def _ensure_depth_pipeline(self, force: bool = False):
+        if not self._depth_enabled or not _HAS_RS:
+            self._depth_ok = False
+            return False
+        if self._rs_pipeline is not None and not force:
+            self._depth_ok = True
+            return True
+        now = time.time()
+        if (not force) and (now - self._last_rs_restart) < 2.0:
+            return self._rs_pipeline is not None
+        self._last_rs_restart = now
+        self._close_depth_pipeline()
+        try:
+            pipe = rs.pipeline()
+            cfg = rs.config()
+            cfg.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
+            self._rs_profile = pipe.start(cfg)
+            self._rs_pipeline = pipe
+            self._depth_ok = True
+            if force:
+                self._depth_restarts += 1
+            logger.info("VisionDetector: RealSense depth pipeline started")
+            return True
+        except Exception as e:
+            self._rs_pipeline = None
+            self._rs_profile = None
+            self._depth_ok = False
+            logger.warning(f"VisionDetector: depth pipeline unavailable: {e}")
+            return False
+
+    def _recover_inputs(self):
+        logger.warning("VisionDetector: recovering camera/depth inputs")
+        self._camera_restarts += 1
+        try:
+            self._camera.release()
+        except Exception as e:
+            record_error("vision_detector", "recover_inputs_release", e)
+        try:
+            self._camera.initialize()
+        except Exception as e:
+            record_error("vision_detector", "recover_inputs_initialize", e)
+        self._ensure_depth_pipeline(force=True)
+        self._no_frame_count = 0
+
+    @staticmethod
+    def _coerce_depth_payload(depth_payload, subject_box=None):
+        if depth_payload is None:
+            return None
+        if isinstance(depth_payload, (int, float)):
+            d = float(depth_payload)
+            return d if d > 0.0 else None
+
+        if isinstance(depth_payload, np.ndarray):
+            arr = depth_payload
+            h, w = arr.shape[:2]
+            if subject_box:
+                x = max(0, int(subject_box.get("x", 0)))
+                y = max(0, int(subject_box.get("y", 0)))
+                bw = max(1, int(subject_box.get("w", 1)))
+                bh = max(1, int(subject_box.get("h", 1)))
+                x2 = min(w, x + bw)
+                y2 = min(h, y + bh)
+                roi = arr[y:y2, x:x2]
+            else:
+                roi = arr
+            if roi.size <= 0:
+                return None
+            vals = roi[roi > 0]
+            if vals.size <= 0:
+                return None
+            med = float(np.median(vals))
+            if arr.dtype in (np.uint16, np.int16, np.uint32, np.int32):
+                med *= 0.001  # mm -> m
+            return med if med > 0.0 else None
+        return None
+
+    def _estimate_depth_m(self, subject_box=None, depth_payload=None):
+        d = self._coerce_depth_payload(depth_payload, subject_box=subject_box)
+        if d is not None:
+            self._depth_ok = True
+            return d
+
+        if not self._ensure_depth_pipeline(force=False):
+            self._depth_ok = False
+            return None
+        try:
+            frames = self._rs_pipeline.poll_for_frames()
+            if not frames:
+                return None
+            depth_frame = frames.get_depth_frame()
+            if not depth_frame:
+                return None
+            w = depth_frame.get_width()
+            h = depth_frame.get_height()
+            if subject_box:
+                cx = int(subject_box.get("x", 0) + (subject_box.get("w", 0) / 2))
+                cy = int(subject_box.get("y", 0) + (subject_box.get("h", 0) / 2))
+            else:
+                cx, cy = int(w / 2), int(h / 2)
+            cx = max(0, min(w - 1, cx))
+            cy = max(0, min(h - 1, cy))
+            d = float(depth_frame.get_distance(cx, cy))
+            if d <= 0.0:
+                self._depth_ok = False
+                return None
+            self._depth_ok = True
+            return d
+        except Exception:
+            self._depth_ok = False
+            return None
+
+    def _extract_frame_and_depth(self):
+        if self._video_cap is not None:
+            try:
+                ret, frame = self._video_cap.read()
+                if not ret:
+                    self._video_cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
+                    ret, frame = self._video_cap.read()
+                self._camera_ok = bool(ret and frame is not None)
+                return frame, None
+            except Exception:
+                self._camera_ok = False
+                return None, None
+
+        if direct_camera_client.is_enabled():
+            try:
+                frame = direct_camera_client.frame_bgr(timeout=1.5)
+                if frame is not None:
+                    self._camera_ok = True
+                    return frame, None
+            except Exception:
+                pass
+
+        try:
+            frame = self._camera.capture_frame()
+            self._camera_ok = frame is not None
+            return frame, None
+        except Exception:
+            self._camera_ok = False
+            return None, None
+
+    def _select_subject(self, boxes, groups=None):
+        groups = groups or []
+        if not boxes:
+            self._subject_lost_count += 1
+            if (not self._hard_target_lock_enabled) and self._subject_lost_count > self._subject_lock_lost_frames:
+                self._locked_subject_id = None
+                self._locked_group_id = None
+                self._locked_target_type = ""
+            return None, False
+
+        self._subject_lost_count = 0
+        if self._hard_target_lock_enabled and self._locked_group_id is not None:
+            locked_group = None
+            for g in groups:
+                try:
+                    if int(g.get("id", -1)) == int(self._locked_group_id):
+                        locked_group = g
+                        break
+                except Exception:
+                    continue
+            if locked_group is None:
+                self._target_switch_blocked_count += 1
+                return None, False
+            members = set()
+            try:
+                members = {int(x) for x in (locked_group.get("members") or [])}
+            except Exception:
+                members = set()
+            cands = [b for b in boxes if int(b.get("id", -1)) in members]
+            if not cands:
+                self._target_switch_blocked_count += 1
+                return None, False
+            best = max(cands, key=lambda b: float(b.get("w", 0.0)) * float(b.get("h", 0.0)))
+            try:
+                self._locked_subject_id = int(best.get("id"))
+            except Exception:
+                pass
+            return best, True
+
+        if self._locked_subject_id is not None:
+            for b in boxes:
+                if int(b.get("id", -1)) == int(self._locked_subject_id):
+                    return b, True
+            if self._hard_target_lock_enabled:
+                self._target_switch_blocked_count += 1
+            return None, False
+
+        # No lock: select largest target.
+        best = max(boxes, key=lambda b: float(b.get("w", 0.0)) * float(b.get("h", 0.0)))
+        return best, True
+
+    def _check_interaction_intent(self, boxes, subject_box, depth_m, now):
+        max_area = 0.0
+        for b in boxes:
+            try:
+                area = max(0.0, float(b.get("w", 0.0))) * max(0.0, float(b.get("h", 0.0)))
+                if area > max_area:
+                    max_area = area
+            except Exception:
+                continue
+
+        self._area_history.append(max_area)
+        area_first = self._area_history[0] if self._area_history else 0.0
+        is_close_area = max_area >= self._proximity_threshold
+        is_approach_area = len(self._area_history) >= self._history_len and (max_area - area_first) >= self._approach_delta
+
+        approach_speed = 0.0
+        is_close_depth = False
+        is_approach_depth = False
+        if depth_m is not None:
+            self._depth_history.append((now, float(depth_m)))
+            if len(self._depth_history) >= 2:
+                t0, d0 = self._depth_history[0]
+                dt = max(1e-3, now - float(t0))
+                approach_speed = max(0.0, (float(d0) - float(depth_m)) / dt)
+            is_close_depth = float(depth_m) <= self._min_depth_m
+            is_approach_depth = approach_speed >= self._min_approach_speed_mps
+        else:
+            self._depth_history.clear()
+
+        if depth_m is not None:
+            is_close = is_close_depth
+            is_approaching = is_approach_depth
+        else:
+            is_close = is_close_area
+            is_approaching = is_approach_area
+
+        subject_visible = subject_box is not None
+        intent_detected = bool(subject_visible and (is_close or is_approaching))
+        return {
+            "intent_detected": intent_detected,
+            "max_area": float(max_area),
+            "is_close": bool(is_close),
+            "is_approaching": bool(is_approaching),
+            "depth_m": float(depth_m) if depth_m is not None else None,
+            "approach_speed_mps": float(approach_speed),
+        }
+
+    def _run(self):
+        interval = max(0.01, 1.0 / max(1.0, self.poll_hz))
+        tracker = CentroidTracker()
+
+        while not self._stop.is_set():
+            t0 = time.time()
+            now = time.time()
+            self._refresh_detector_backend(now)
+            frame, depth_payload = self._extract_frame_and_depth()
+            if frame is None:
+                self._no_frame_count += 1
+                if self._no_frame_count >= self._recover_after_no_frame:
+                    self._recover_inputs()
+                intent = self._check_interaction_intent([], None, None, now)
+                with self._latest_lock:
+                    self._latest.update(
+                        {
+                            "frame_time": now,
+                            "detector_backend": self._effective_backend(),
+                            "yolo_runtime": self._yolo_runtime,
+                            "face_count": 0,
+                            "person_count": 0,
+                            "group_count": 0,
+                            "group_size": 0,
+                            "group_detected": False,
+                            "boxes": [],
+                            "face_boxes": [],
+                            "group_boxes": [],
+                            "frame": None,
+                            "subject_id": self._locked_subject_id,
+                            "subject_box": None,
+                            "subject_visible": False,
+                            "subject_locked": self._locked_subject_id is not None,
+                            "target_lock_active": bool(self._locked_subject_id is not None or self._locked_group_id is not None),
+                            "target_lock_type": str(self._locked_target_type or ""),
+                            "target_lock_id": self._locked_group_id if self._locked_group_id is not None else self._locked_subject_id,
+                            "target_switch_blocked_count": int(self._target_switch_blocked_count),
+                            "camera_ok": bool(self._camera_ok),
+                            "depth_ok": bool(self._depth_ok),
+                            "camera_restarts": int(self._camera_restarts),
+                            "depth_restarts": int(self._depth_restarts),
+                            **intent,
+                        }
+                    )
+                time.sleep(interval)
+                continue
+
+            self._no_frame_count = 0
+            try:
+                person_boxes = self._detect_person_boxes(frame, tracker)
+                face_boxes = self._detect_face_boxes(frame)
+                groups = self._detect_groups(person_boxes)
+                group_size = max((int(g.get("size", 0)) for g in groups), default=0)
+
+                subject_box, subject_visible = self._select_subject(person_boxes, groups=groups)
+                depth_m = self._estimate_depth_m(subject_box=subject_box, depth_payload=depth_payload)
+                intent = self._check_interaction_intent(person_boxes, subject_box, depth_m, now)
+
+                with self._latest_lock:
+                    self._latest.update(
+                        {
+                            "frame_time": now,
+                            "detector_backend": self._effective_backend(),
+                            "yolo_runtime": self._yolo_runtime,
+                            "face_count": len(face_boxes),
+                            "person_count": len(person_boxes),
+                            "group_count": len(groups),
+                            "group_size": int(group_size),
+                            "group_detected": bool(group_size >= self._group_min_people),
+                            "boxes": person_boxes,
+                            "face_boxes": face_boxes,
+                            "group_boxes": groups,
+                            "frame": frame.copy() if frame is not None else None,
+                            "subject_id": subject_box.get("id") if subject_box else self._locked_subject_id,
+                            "subject_box": dict(subject_box) if isinstance(subject_box, dict) else None,
+                            "subject_visible": bool(subject_visible),
+                            "subject_locked": self._locked_subject_id is not None,
+                            "target_lock_active": bool(self._locked_subject_id is not None or self._locked_group_id is not None),
+                            "target_lock_type": str(self._locked_target_type or ""),
+                            "target_lock_id": self._locked_group_id if self._locked_group_id is not None else self._locked_subject_id,
+                            "target_switch_blocked_count": int(self._target_switch_blocked_count),
+                            "camera_ok": bool(self._camera_ok),
+                            "depth_ok": bool(self._depth_ok),
+                            "camera_restarts": int(self._camera_restarts),
+                            "depth_restarts": int(self._depth_restarts),
+                            **intent,
+                        }
+                    )
+            except Exception as e:
+                record_error("vision_detector", "run_loop_detect", e)
+                logger.warning(f"VisionDetector: detect failed: {e}")
+                intent = self._check_interaction_intent([], None, None, now)
+                with self._latest_lock:
+                    self._latest.update(
+                        {
+                            "frame_time": now,
+                            "detector_backend": self._effective_backend(),
+                            "yolo_runtime": self._yolo_runtime,
+                            "face_count": 0,
+                            "person_count": 0,
+                            "group_count": 0,
+                            "group_size": 0,
+                            "group_detected": False,
+                            "boxes": [],
+                            "face_boxes": [],
+                            "group_boxes": [],
+                            "frame": frame.copy() if frame is not None else None,
+                            "subject_id": self._locked_subject_id,
+                            "subject_box": None,
+                            "subject_visible": False,
+                            "subject_locked": self._locked_subject_id is not None,
+                            "target_lock_active": bool(self._locked_subject_id is not None or self._locked_group_id is not None),
+                            "target_lock_type": str(self._locked_target_type or ""),
+                            "target_lock_id": self._locked_group_id if self._locked_group_id is not None else self._locked_subject_id,
+                            "target_switch_blocked_count": int(self._target_switch_blocked_count),
+                            "camera_ok": bool(self._camera_ok),
+                            "depth_ok": bool(self._depth_ok),
+                            "camera_restarts": int(self._camera_restarts),
+                            "depth_restarts": int(self._depth_restarts),
+                            **intent,
+                        }
+                    )
+
+            dt = time.time() - t0
+            time.sleep(max(0.0, interval - dt))
+
+
+class CentroidTracker:
+    """Small centroid tracker assigning incremental IDs to objects."""
+
+    def __init__(self, max_disappeared: int = 10, max_distance: int = 80):
+        self.next_id = 1
+        self.objects = {}  # id -> centroid
+        self.disappeared = {}  # id -> frames disappeared
+        self.max_disappeared = max_disappeared
+        self.max_distance = max_distance
+
+    def _centroid(self, box):
+        x, y, w, h = box
+        return (int(x + w / 2), int(y + h / 2))
+
+    def register(self, box):
+        cid = self.next_id
+        self.next_id += 1
+        cent = self._centroid(box)
+        self.objects[cid] = cent
+        self.disappeared[cid] = 0
+        return cid
+
+    def deregister(self, cid):
+        del self.objects[cid]
+        del self.disappeared[cid]
+
+    def update(self, boxes):
+        """boxes: list of (x, y, w, h), returns list of (id, box)."""
+        if len(boxes) == 0:
+            remove = []
+            for cid in list(self.disappeared.keys()):
+                self.disappeared[cid] += 1
+                if self.disappeared[cid] > self.max_disappeared:
+                    remove.append(cid)
+            for cid in remove:
+                self.deregister(cid)
+            return []
+
+        input_centroids = [self._centroid(b) for b in boxes]
+
+        if len(self.objects) == 0:
+            assigned = []
+            for b in boxes:
+                cid = self.register(b)
+                assigned.append((cid, b))
+            return assigned
+
+        object_ids = list(self.objects.keys())
+        object_centroids = list(self.objects.values())
+
+        D = np.linalg.norm(np.array(object_centroids)[:, None, :] - np.array(input_centroids)[None, :, :], axis=2)
+        rows = D.min(axis=1).argsort()
+        cols = D.argmin(axis=1)[rows]
+
+        used_rows = set()
+        used_cols = set()
+        assigned = []
+
+        for r, c in zip(rows, cols):
+            if r in used_rows or c in used_cols:
+                continue
+            if D[r, c] > self.max_distance:
+                continue
+            cid = object_ids[r]
+            self.objects[cid] = input_centroids[c]
+            self.disappeared[cid] = 0
+            assigned.append((cid, boxes[c]))
+            used_rows.add(r)
+            used_cols.add(c)
+
+        for i, b in enumerate(boxes):
+            if i in used_cols:
+                continue
+            cid = self.register(b)
+            assigned.append((cid, b))
+
+        for i, cid in enumerate(object_ids):
+            if i in used_rows:
+                continue
+            self.disappeared[cid] += 1
+            if self.disappeared[cid] > self.max_disappeared:
+                self.deregister(cid)
+
+        return assigned
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    v = VisionDetector()
+    v.start()
+    try:
+        for _ in range(30):
+            s = v.latest()
+            logger.info(
+                "people=%s faces=%s groups=%s intent=%s time=%s",
+                s.get("person_count", 0),
+                s.get("face_count", 0),
+                s.get("group_count", 0),
+                s.get("intent_detected", False),
+                s.get("frame_time", 0.0),
+            )
+            time.sleep(0.5)
+    finally:
+        v.stop()
diff --git a/Modes/Manual/__init__.py b/Modes/Manual/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Modes/Manual/controller.py b/Modes/Manual/controller.py
new file mode 100644
index 0000000..0b99240
--- /dev/null
+++ b/Modes/Manual/controller.py
@@ -0,0 +1,96 @@
+# controller.py
+import time
+import struct
+from pathlib import Path
+
+from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowState_
+
+
+def auto_pick_iface() -> str:
+    try:
+        net_dir = Path("/sys/class/net")
+        if not net_dir.exists():
+            return "lo"
+        names = [p.name for p in net_dir.iterdir() if p.is_dir()]
+        for pref in ("en", "eth", "wl"):
+            for n in names:
+                if n != "lo" and n.startswith(pref):
+                    return n
+        for n in names:
+            if n != "lo":
+                return n
+        return "lo"
+    except Exception:
+        return "lo"
+
+
+class unitreeRemoteController:
+    def __init__(self):
+        self.Lx = 0; self.Rx = 0; self.Ry = 0; self.Ly = 0
+        self.L1 = 0; self.L2 = 0; self.R1 = 0; self.R2 = 0
+        self.A = 0; self.B = 0; self.X = 0; self.Y = 0
+        self.Up = 0; self.Down = 0; self.Left = 0; self.Right = 0
+        self.Select = 0; self.F1 = 0; self.F3 = 0; self.Start = 0
+
+    def parse_botton(self, data1, data2):
+        self.R1 = (data1 >> 0) & 1; self.L1 = (data1 >> 1) & 1
+        self.Start = (data1 >> 2) & 1; self.Select = (data1 >> 3) & 1
+        self.R2 = (data1 >> 4) & 1; self.L2 = (data1 >> 5) & 1
+        self.F1 = (data1 >> 6) & 1; self.F3 = (data1 >> 7) & 1
+        self.A = (data2 >> 0) & 1; self.B = (data2 >> 1) & 1
+        self.X = (data2 >> 2) & 1; self.Y = (data2 >> 3) & 1
+        self.Up = (data2 >> 4) & 1; self.Right = (data2 >> 5) & 1
+        self.Down = (data2 >> 6) & 1; self.Left = (data2 >> 7) & 1
+
+    def parse_key(self, data):
+        offsets = [4, 8, 12, 20]  # Lx, Rx, Ry, Ly
+        self.Lx, self.Rx, self.Ry, self.Ly = [struct.unpack('<f', data[o:o+4])[0] for o in offsets]
+
+    def parse(self, remoteData):
+        if len(remoteData) < 24:
+            return
+        self.parse_key(remoteData)
+        self.parse_botton(remoteData[2], remoteData[3])
+
+    def get_state(self):
+        return self.__dict__.copy()
+
+
+class LowStateHub:
+    def __init__(self, watchdog_timeout=0.25):
+        self.low_state = None
+        self.first_state = False
+        self.last_state_time = 0.0
+        self.watchdog_timeout = float(watchdog_timeout)
+
+        self.remote = unitreeRemoteController()
+        self.controller_state = self.remote.get_state()
+
+    def handler(self, msg: LowState_):
+        self.low_state = msg
+        self.first_state = True
+        self.last_state_time = time.time()
+        try:
+            self.remote.parse(msg.wireless_remote)
+            self.controller_state = self.remote.get_state()
+        except Exception:
+            pass
+
+    def fresh(self) -> bool:
+        return (time.time() - self.last_state_time) < self.watchdog_timeout
+
+    def combo_r2x(self) -> bool:
+        s = self.controller_state
+        return bool(s.get("R2", 0) and s.get("X", 0))
+
+    def combo_r2l1(self) -> bool:
+        s = self.controller_state
+        return bool(s.get("R2", 0) and s.get("L1", 0))
+
+    def hard_cancel_combo(self) -> bool:
+        """
+        Global safety cancel combo.
+        Keep this as the single mapping point so all runtimes (manual/AI)
+        can share the same hard-cancel behavior.
+        """
+        return self.combo_r2l1()
diff --git a/Modes/Manual/replay_engine.py b/Modes/Manual/replay_engine.py
new file mode 100644
index 0000000..c3570c5
--- /dev/null
+++ b/Modes/Manual/replay_engine.py
@@ -0,0 +1,243 @@
+# replay_engine.py
+import json
+import time
+from pathlib import Path
+
+from unitree_sdk2py.core.channel import ChannelPublisher
+from unitree_sdk2py.idl.default import unitree_hg_msg_dds__LowCmd_
+from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowCmd_
+from unitree_sdk2py.utils.crc import CRC
+from Core.Logger import Logs
+
+G1_NUM_MOTOR = 29
+ENABLE_ARM_SDK_INDEX = 29
+REPLAY_HZ = 60.0
+
+KP_HIGH = 300.0
+KD_HIGH = 3.0
+KP_LOW  = 80.0
+KD_LOW  = 3.0
+KP_WRIST = 40.0
+KD_WRIST = 1.5
+
+WEAK_MOTORS  = [4, 10, 15, 16, 17, 18, 22, 23, 24, 25]
+WRIST_MOTORS = [19, 20, 21, 26, 27, 28]
+
+sanad_logger = Logs()
+sanad_logger.LogEngine("G1_Logs", "replay_engine")
+
+def load_home_pose(home_path: Path):
+    try:
+        last_valid_q = None
+        with open(home_path, "r") as f:
+            for line in f:
+                d = json.loads(line)
+                if "q" in d and len(d["q"]) == G1_NUM_MOTOR:
+                    last_valid_q = d["q"]
+        if last_valid_q:
+            sanad_logger.print_and_log(f"✅ Loaded Home Pose from {home_path}", "info")
+            return last_valid_q
+        sanad_logger.print_and_log(f"⚠️ Home file has no valid q: {home_path}", "warning")
+    except FileNotFoundError:
+        sanad_logger.print_and_log(f"⚠️ Home file not found: {home_path}", "warning")
+
+    sanad_logger.print_and_log("⚠️ Using Default Home (Arms at 0.0)", "warning")
+    return [0.0] * G1_NUM_MOTOR
+
+
+class ReplayWithHome:
+    def __init__(self, hub, watchdog_disable_after=1.0):
+        self.hub = hub
+
+        self.low_cmd = unitree_hg_msg_dds__LowCmd_()
+        self.crc = CRC()
+
+        self.arm_pub = ChannelPublisher("rt/arm_sdk", LowCmd_)
+        self.arm_pub.Init()
+
+        self.watchdog_disable_after = float(watchdog_disable_after)
+        self.is_playing = False
+
+    def _cancel(self) -> bool:
+        if hasattr(self.hub, "hard_cancel_combo"):
+            return bool(self.hub.hard_cancel_combo())
+        return bool(self.hub.combo_r2l1())
+
+    def _send_frame(self, arm_target_q, body_lock_q):
+        self.low_cmd.motor_cmd[ENABLE_ARM_SDK_INDEX].q = 1.0
+
+        for i in range(G1_NUM_MOTOR):
+            self.low_cmd.motor_cmd[i].mode = 1
+            self.low_cmd.motor_cmd[i].dq = 0
+            self.low_cmd.motor_cmd[i].tau = 0
+
+            self.low_cmd.motor_cmd[i].q = arm_target_q[i] if i >= 15 else body_lock_q[i]
+
+            if i in WEAK_MOTORS:
+                self.low_cmd.motor_cmd[i].kp = KP_LOW
+                self.low_cmd.motor_cmd[i].kd = KD_LOW
+            elif i in WRIST_MOTORS:
+                self.low_cmd.motor_cmd[i].kp = KP_WRIST
+                self.low_cmd.motor_cmd[i].kd = KD_WRIST
+            else:
+                self.low_cmd.motor_cmd[i].kp = KP_HIGH
+                self.low_cmd.motor_cmd[i].kd = KD_HIGH
+
+        self.low_cmd.crc = self.crc.Crc(self.low_cmd)
+        self.arm_pub.Write(self.low_cmd)
+
+    def _disable_sdk(self):
+        sanad_logger.print_and_log("🔌 Disabling SDK...", "info")
+        self.low_cmd.motor_cmd[ENABLE_ARM_SDK_INDEX].q = 0.0
+        self.low_cmd.crc = self.crc.Crc(self.low_cmd)
+        for _ in range(10):
+            self.arm_pub.Write(self.low_cmd)
+            time.sleep(0.02)
+
+    def _return_home(self, last_q, body_lock_q, home_q, steps=180):
+        sanad_logger.print_and_log("🏡 Returning arms to HOME...", "info")
+        for k in range(steps):
+            stale_for = time.time() - self.hub.last_state_time
+            if stale_for > self.watchdog_disable_after:
+                sanad_logger.print_and_log("🛑 WATCHDOG: lost during home. Disable SDK.", "error")
+                self._disable_sdk()
+                return
+
+            if not self.hub.fresh():
+                self._send_frame(last_q, body_lock_q)
+                time.sleep(1.0 / REPLAY_HZ)
+                continue
+
+            alpha = k / steps
+            interp_q = list(last_q)
+            for j in range(15, 29):
+                interp_q[j] = (1 - alpha) * last_q[j] + alpha * home_q[j]
+            self._send_frame(interp_q, body_lock_q)
+            time.sleep(1.0 / REPLAY_HZ)
+
+        sanad_logger.print_and_log("✅ Home Reached.", "info")
+
+    def run(self, replay_file: Path, home_file: Path, speed: float, trigger_callback=None):
+        self.is_playing = True
+        cancel = False
+
+        try:
+            sanad_logger.print_and_log(f"🎬 Replay: {replay_file}", "info")
+            while not self.hub.first_state:
+                time.sleep(0.05)
+
+            home_q = load_home_pose(home_file)
+            body_lock_q = [self.hub.low_state.motor_state[i].q for i in range(G1_NUM_MOTOR)]
+
+            frames = []
+            with open(replay_file, "r") as f:
+                for line in f:
+                    line = line.strip()
+                    if not line:
+                        continue
+                    try:
+                        d = json.loads(line)
+                    except Exception:
+                        continue
+                    if "q" in d and "t" in d:
+                        frames.append(d)
+
+            if not frames:
+                sanad_logger.print_and_log("❌ No frames found.", "error")
+                return
+
+            file_start_q = frames[0]["q"]
+            last_played_q = file_start_q
+
+            # Move to start
+            for k in range(60):
+                if self._cancel():
+                    cancel = True
+                    sanad_logger.print_and_log("🛑 CANCEL during move-to-start.", "warning")
+                    break
+
+                if not self.hub.fresh():
+                    self._send_frame(last_played_q, body_lock_q)
+                    time.sleep(1.0 / REPLAY_HZ)
+                    continue
+
+                alpha = k / 60
+                interp_q = list(body_lock_q)
+                for j in range(15, 29):
+                    interp_q[j] = (1 - alpha) * body_lock_q[j] + alpha * file_start_q[j]
+                self._send_frame(interp_q, body_lock_q)
+                last_played_q = interp_q
+                time.sleep(1.0 / REPLAY_HZ)
+
+            # Play
+            if not cancel:
+                sanad_logger.print_and_log("▶️ Playing...", "info")
+                play_elapsed = 0.0
+                last_real = time.time()
+
+                while True:
+                    if self._cancel():
+                        cancel = True
+                        sanad_logger.print_and_log("🛑 CANCEL during replay.", "warning")
+                        break
+
+                    stale_for = time.time() - self.hub.last_state_time
+                    if stale_for > self.watchdog_disable_after:
+                        sanad_logger.print_and_log("🛑 WATCHDOG: lost. Disable SDK.", "error")
+                        self._disable_sdk()
+                        return
+
+                    if not self.hub.fresh():
+                        self._send_frame(last_played_q, body_lock_q)
+                        time.sleep(1.0 / REPLAY_HZ)
+                        continue
+
+                    now = time.time()
+                    dt = now - last_real
+                    last_real = now
+                    play_elapsed += dt * speed
+
+                    target = None
+                    for fr in frames:
+                        if fr["t"] - frames[0]["t"] >= play_elapsed:
+                            target = fr
+                            break
+                    if target is None:
+                        break
+
+                    # If this frame contains a trigger marker, call the callback (non-blocking)
+                    try:
+                        meta = target.get("meta") if isinstance(target, dict) else None
+                        if trigger_callback and meta:
+                            # support meta: "trigger" or meta: {"trigger": true}
+                            call_cb = False
+                            if isinstance(meta, str) and "trigger" in meta.lower():
+                                call_cb = True
+                            elif isinstance(meta, dict) and meta.get("trigger"):
+                                call_cb = True
+                            if call_cb:
+                                try:
+                                    from threading import Thread as _Thread
+                                    _Thread(target=lambda: trigger_callback(target), daemon=True).start()
+                                    sanad_logger.print_and_log("🔔 Trigger callback invoked (replay).", "info")
+                                except Exception as _e:
+                                    sanad_logger.print_and_log(f"Trigger callback error: {_e}", "warning")
+                    except Exception:
+                        pass
+
+                    self._send_frame(target["q"], body_lock_q)
+                    last_played_q = target["q"]
+                    time.sleep(1.0 / REPLAY_HZ)
+
+            # Always home
+            self._return_home(last_played_q, body_lock_q, home_q, steps=180)
+            self._disable_sdk()
+
+        except Exception as e:
+            sanad_logger.print_and_log(f"❌ Replay exception: {e}", "error")
+            try:
+                self._disable_sdk()
+            except Exception:
+                pass
+        finally:
+            self.is_playing = False
diff --git a/Modes/Manual/trigger_loop.py b/Modes/Manual/trigger_loop.py
new file mode 100644
index 0000000..3e87f00
--- /dev/null
+++ b/Modes/Manual/trigger_loop.py
@@ -0,0 +1,183 @@
+# trigger_loop.py
+import asyncio
+import threading
+import time
+from pathlib import Path
+
+from Core import settings as config
+from Core.Logger import Logs
+from Server.capture_service import capture_with_replay_sync, replay_timing_profile
+
+
+sanad_logger = Logs()
+sanad_logger.LogEngine("G1_Logs", "trigger_loop")
+
+async def _play_prompt(voice, prompt_key: str, fallback_text: str) -> bool:
+    try:
+        return bool(await voice.play_prompt_key(prompt_key, fallback_text))
+    except Exception as e:
+        sanad_logger.print_and_log(f"⚠️ Prompt playback failed for {prompt_key}: {e}", message_type="warning")
+        return False
+
+
+async def _play_capture_prompt(voice, prompt_key: str, fallback_text: str) -> bool:
+    try:
+        return bool(
+            await voice.play_prompt_key(
+                prompt_key,
+                fallback_text="",
+                allow_gemini_fallback=False,
+                mode_override="audio",
+            )
+        )
+    except Exception as e:
+        sanad_logger.print_and_log(f"⚠️ Capture prompt playback failed for {prompt_key}: {e}", message_type="warning")
+        return False
+
+
+async def _play_manual_capture_prompt_sequence(
+    voice,
+    shot_delay_sec: float,
+    cancel_event: threading.Event,
+):
+    start_ts = time.time()
+    await _play_capture_prompt(
+        voice,
+        "countdown_intro",
+        "Look at the camera, stay ready, hold your pose with me, keep still, keep your smile soft, and in a moment I will count down for the photo.",
+    )
+    announced = set()
+
+    while True:
+        if cancel_event.is_set():
+            raise asyncio.CancelledError
+
+        remaining = max(0.0, shot_delay_sec - (time.time() - start_ts))
+        sec_left = int(round(remaining))
+
+        if sec_left in (3, 2, 1) and sec_left not in announced:
+            announced.add(sec_left)
+            await _play_capture_prompt(voice, f"count_{sec_left}", f"{sec_left}...")
+        elif sec_left <= 0 and 0 not in announced:
+            announced.add(0)
+            await _play_capture_prompt(voice, "smile", "Smile.")
+            return
+
+        await asyncio.sleep(0.05)
+
+
+async def trigger_loop(
+    hub,
+    replay,
+    voice,
+    take_photo_sync_callable=None,
+    ws=None,
+):
+    """
+    R2+X:
+      - play the fixed capture prompt sequence (recorded audio by default)
+      - run unified capture pipeline (replay + timed capture/upload)
+    R2+L1:
+      - cancels pending delayed photo (replay cancel handled in replay engine)
+    Debounce:
+      - must release R2+X to re-trigger
+      - blocks retrigger for PHOTO_TOTAL_SEC window
+    """
+    r2x_prev = False
+    waiting_release = False
+    photo_busy_until = 0.0
+
+    pending_photo_task: asyncio.Task | None = None
+    pending_audio_task: asyncio.Task | None = None
+    pending_capture_cancel: threading.Event | None = None
+
+    def _hard_cancel_pressed() -> bool:
+        if hasattr(hub, "hard_cancel_combo"):
+            return bool(hub.hard_cancel_combo())
+        return bool(hub.combo_r2l1())
+
+    async def delayed_photo(delay_sec: float, cancel_event: threading.Event):
+        # Unified pipeline: replay + trigger/fallback capture + upload touch.
+        base_prefix = None  # keep existing default naming behavior
+        photo_result = await asyncio.to_thread(
+            capture_with_replay_sync,
+            replay_runner=replay,
+            replay_file=config.REPLAY_FILE,
+            home_file=config.HOME_FILE,
+            delay_sec=delay_sec,
+            prefix=base_prefix,
+            speed=1.0,
+            cancel_event=cancel_event,
+        )
+        sanad_logger.print_and_log(f"📸 Capture pipeline result: {photo_result}", message_type="info")
+        if cancel_event.is_set():
+            return
+        if isinstance(photo_result, str) and not photo_result.startswith("[ERR]"):
+            await _play_capture_prompt(
+                voice,
+                "photo_saved_thanks",
+                "Thank you. Photo saved. Do not forget to check your photos.",
+            )
+
+    while True:
+        await asyncio.sleep(0.02)
+        if not hub.first_state:
+            continue
+
+        # Cancel combo: cancel pending photo
+        if _hard_cancel_pressed():
+            if pending_capture_cancel is not None:
+                pending_capture_cancel.set()
+            if pending_photo_task and not pending_photo_task.done():
+                pending_photo_task.cancel()
+            if pending_audio_task and not pending_audio_task.done():
+                pending_audio_task.cancel()
+            sanad_logger.print_and_log("🛑 HARD CANCEL: pending photo cancelled (R2+L1).", message_type="warning")
+
+        r2x_now = hub.combo_r2x()
+
+        # Require release before next trigger
+        if waiting_release:
+            if not r2x_now:
+                waiting_release = False
+            r2x_prev = r2x_now
+            continue
+
+        # Do not retrigger while replay is playing
+        if replay.is_playing:
+            r2x_prev = r2x_now
+            continue
+
+        now = time.time()
+
+        # Rising edge trigger + not inside busy window
+        if r2x_now and (not r2x_prev) and (now >= photo_busy_until):
+            waiting_release = True
+
+            # 1) schedule manual countdown speech using the same prompt keys as AI mode
+            if pending_photo_task and not pending_photo_task.done():
+                if pending_capture_cancel is not None:
+                    pending_capture_cancel.set()
+                pending_photo_task.cancel()
+            if pending_audio_task and not pending_audio_task.done():
+                pending_audio_task.cancel()
+
+            timing = replay_timing_profile(config.REPLAY_FILE)
+            delay = float(timing.get("capture_offset_sec") or max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC)))
+            replay_duration = float(timing.get("duration_sec") or 0.0)
+            photo_busy_until = now + max(config.PHOTO_TOTAL_SEC, replay_duration + 3.2, delay + config.PHOTO_THANKS_SEC)
+            sanad_logger.print_and_log(
+                "🎯 Manual capture timing: "
+                f"replay={Path(config.REPLAY_FILE).name} "
+                f"duration={replay_duration:.3f}s "
+                f"shot_at={delay:.3f}s "
+                f"source={timing.get('capture_source', 'config_fallback')}",
+                message_type="info",
+            )
+            pending_capture_cancel = threading.Event()
+            pending_audio_task = asyncio.create_task(
+                _play_manual_capture_prompt_sequence(voice, delay, pending_capture_cancel)
+            )
+            pending_photo_task = asyncio.create_task(delayed_photo(delay, pending_capture_cancel))
+
+        r2x_prev = r2x_now
diff --git a/Modes/__init__.py b/Modes/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..c840f6d
--- /dev/null
+++ b/README.md
@@ -0,0 +1,268 @@
+# AI Photographer
+
+Production-oriented robot photographer stack for Unitree G1.
+
+## Quick Start
+
+1. Set API key in config:
+   - edit `Data/Settings/config.json` -> `gemini.api_key`
+2. Run launcher:
+   - `cd Scripts && ./photo_sanad.sh`
+
+Launcher behavior:
+- resets `mode.current_mode` to the configured `mode.default_mode` on each launch,
+- resolves the active PulseAudio speaker/microphone and exports them for the runtime,
+- starts the direct camera service (`Core/direct_camera_service.py` in the `teleimager` conda env) for the full runtime path,
+- starts Gemini runtime (`gemini` conda env),
+- runs `Gemini/voice_sanad.py` as the main process,
+- keeps `manual` as the default startup mode unless changed in `Data/Settings/config.json`,
+- keeps `Gemini/voice_sanad.py`, the dashboard server, the direct camera server, and replay/trigger services running in the full runtime path across mode switches,
+- arms autonomous services in the full runtime path so switching dashboard mode from `manual` to `ai` works without a restart.
+
+Optional startup profile:
+- `MANUAL_LEAN_RUNTIME=1`
+  - manual-mode voice + dashboard only
+  - skips direct camera, DDS, replay, uploader, and autonomous startup
+  - capture/replay services are unavailable in that profile
+  - this is an explicit reduced profile, not the normal production mode
+
+## Project Layout
+
+- `Scripts/`
+  - startup and ops shell entrypoints
+  - `photo_sanad.sh`, `fix_realsense_usb.sh`
+  - `direct_camera_samples_server.py` remains as a compatibility wrapper
+  - `fix_realsense_usb.sh` supports `--check`, `--fix`, and `--serials`
+- `Data/`
+  - categorized runtime assets and state
+  - `Settings/config.json`
+  - `Scripts/photo_command_ai.txt`, `Scripts/sanad_script.txt`
+  - `Runtime/upload_db.json`, generated runtime JSON state files
+  - `Settings/config.json -> camera.preferred_realsense_serial` selects the preferred default RealSense by serial
+  - generated runtime JSON files are created on demand during execution
+- `Data/Audio/`
+  - fixed prerecorded AI situation prompts (`*.wav`)
+  - matching raw Gemini captures (`*_raw.wav`)
+- `Data/Settings/audio_prompt_records.json`
+  - prompt recording metadata for files in `Data/Audio/`
+- `photos/people/`
+  - AI face-recognition registry
+  - each returning guest gets a folder with face/scene references, metadata, and captured-photo links
+- `photos/Captures/`
+  - final saved runtime captures from dashboard, manual trigger, and AI capture flow
+- `photos/samples/`
+  - standalone direct-camera sample captures
+- `Logs/`
+  - one stable log file per runtime component
+  - examples: `voice_sanad.log`, `gemini_voice.log`, `photo_server.log`, `direct_camera.log`
+- `Web/`
+  - operator dashboard frontend (`gallery.html`, `gallery.js`, `style.css`)
+  - direct camera service frontend (`direct_camera.html`, `direct_camera.js`, `direct_camera.css`)
+- `Data/G1/`
+  - replay/gesture motion files (`*.jsonl`)
+  - dashboard-recorded replay captures are saved directly here
+- `Core/`
+  - shared runtime foundations (`settings.py`, `Logger.py`, `error_events.py`, `direct_camera_service.py`)
+  - `direct_camera_service.py` handles camera backend/API and serves its UI from `Web/`
+- `Gemini/`
+  - voice orchestration (`voice_sanad.py`, `gemini_voice.py`, `sanad_text_utils.py`)
+- `Server/`
+  - dashboard/API/capture/upload (`photo_server.py`, `capture_service.py`, `direct_camera_client.py`, `uploader.py`)
+- `Modes/AI/`
+  - autonomous vision/intent/session manager (`autonomous_manager.py`, `vision_detector.py`, `camera_module.py`)
+- `Modes/Manual/`
+  - controller + replay + trigger loop (`controller.py`, `replay_engine.py`, `trigger_loop.py`)
+
+## Runtime Modes
+
+Mode is persisted in `Data/Settings/config.json` under `mode.current_mode`:
+- `manual`
+  - Gemini conversation stays available when `gemini.mic_enabled=true`
+  - voice `request_photo / yes_photo / no_photo` disabled
+  - `R2+X` replay/capture path stays available in the full runtime path
+  - `Gemini/voice_sanad.py`, dashboard server, direct camera server, and replay services stay running
+  - autonomous services can be armed in the background, but autonomous flow stays paused until mode becomes `ai`
+- `ai`
+  - voice `request_photo / yes_photo / no_photo` enabled
+  - `R2+X` replay/capture path still works
+  - `Gemini/voice_sanad.py`, dashboard server, direct camera server, and replay services continue running without restart
+  - autonomous flow runs live when `AUTONOMOUS_ENABLE=1`
+  - on stable visual intent, AI identifies or enrolls a single guest, optionally greets with a short hand replay, asks for photo confirmation, guides guests into frame, then captures using the active replay during the shot when AI capture replay is enabled
+  - returning guests are recognized from `photos/people/` and can be greeted as returning visitors
+
+Command-mode functionality was extracted from this project and moved to:
+- `G1_Lootah/AI_Command`
+
+## Remote Controls
+
+- `R2+X`
+  - replay + photographer talk + capture pipeline
+- `R2+L1`
+  - global hard cancel safety combo
+  - active in runtime loops to cancel pending capture/replay and reset active interaction
+
+Mode APIs:
+- `GET /api/mode`
+- `GET /api/set_mode?mode=manual|ai`
+- `GET /api/mode_policy`
+- `GET /api/mic`
+- `GET /api/set_mic?enabled=0|1`
+- `GET /api/detector_backend`
+- `GET /api/set_detector_backend?backend=normal|yolo`
+- `GET /api/ai_readiness`
+- `GET /api/ai_options`
+- `GET /api/set_ai_options?hard_target_lock_enabled=0|1&retake_prompt_enabled=0|1&autonomous_greeting_replay_enabled=0|1&autonomous_greeting_replay_file=...&autonomous_capture_replay_enabled=0|1&face_recognition_enabled=0|1&face_recognition_threshold=...`
+- `GET /api/autonomous_state`
+- `GET /api/runtime_health`
+
+## Autonomous Flow
+
+Autonomous services are armed by environment:
+- `AUTONOMOUS_ENABLE=1`
+  - allows `Modes/AI/autonomous_manager.py` to run inside `voice_sanad.py`
+  - in `manual` mode it stays paused
+  - core services still remain up in `manual` (`voice_sanad.py`, dashboard, direct camera server, replay/trigger)
+  - switching dashboard mode to `ai` starts autonomous flow live without a restart
+- `AUTONOMOUS_ENABLE=0`
+  - disables autonomous manager entirely
+  - manual trigger loop + voice runtime still work
+
+Session state machine:
+- `IDLE -> WAIT_CONFIRM -> FRAMING -> COUNTDOWN -> RETAKE_CONFIRM (optional) -> COMPLETE -> IDLE`
+- strict readiness block state: `IDLE_BLOCKED` when required YOLO readiness is not met
+
+## Dashboard / API Highlights
+
+- `GET /` gallery dashboard
+- `GET /preview.mjpg` live preview
+  - preview is off by default and starts only when requested from the dashboard
+  - preview camera/OpenCV is loaded lazily when preview is requested
+- Camera control APIs:
+  - `GET /api/camera_health`
+  - `GET /api/camera_sources`
+  - `GET /api/set_camera_source?source=...`
+  - `GET /api/set_camera_resolution?width=...&height=...&fps=...`
+  - `GET /api/set_preferred_camera?serial=...`
+  - dashboard can switch camera source, show active camera info, change resolution live, and save a preferred RealSense serial into `Data/Settings/config.json`
+- Audio prompt APIs:
+  - `GET /api/audio_prompts`
+  - `GET /api/set_audio_prompt_mode?mode=audio|gemini`
+  - `GET /api/set_audio_prompt_fallback?enabled=0|1`
+  - `GET /api/audio_prompt_record_status`
+  - `GET /api/download_audio_prompt?key=...`
+  - `GET /api/delete_audio_prompt?key=...`
+  - `POST /api/upload_audio_prompt`
+  - `POST /api/audio_prompt_record`
+  - dashboard can upload, replace, download, delete, inspect, and record prerecorded AI prompt clips stored in `Data/Audio/`
+  - dashboard can switch fixed AI situation speech between recorded audio and Gemini without restart
+- `GET /api/autonomous_state` runtime autonomous state panel data (lock/retake/health fields)
+- `GET /api/runtime_health` component health (WS/mic/speaker/gate/restarts)
+- `GET /api/mic` and `GET /api/set_mic`
+  - microphone ON/OFF toggle for both modes
+- `GET /api/ai_readiness` strict AI readiness + block reason
+- `GET /api/ai_options` and `GET /api/set_ai_options` for hard lock/retake toggles
+- Replay APIs:
+  - `GET /api/replays`
+  - `GET /api/get_replay`
+  - `GET /api/set_replay?name=...`
+  - `GET /api/delete_replay?name=...`
+  - `GET /api/rename_replay?old=...&new=...`
+  - `GET /api/download_replay?name=...`
+  - `GET /api/replay_record_status`
+  - `GET /api/replay_record_start?name=...&seconds=...`
+  - `GET /api/replay_test_status`
+  - `GET /api/test_replay?name=...`
+  - `POST /api/upload_replay`
+  - dashboard can record new replays into `Data/G1`, replay-test them, rename them, download them, delete them, upload new `.jsonl` replays, and set the active replay
+  - replay recording and replay test are allowed only while runtime mode is `manual`
+- People APIs:
+  - `GET /api/people`
+  - `GET /api/person_image?id=...&kind=face|scene`
+  - `GET /api/download_person?id=...`
+  - `GET /api/delete_person?id=...`
+  - `GET /api/reset_people`
+  - `POST /api/upload_person`
+  - dashboard can upload face photos for future recognition, download a saved guest package, delete one guest, or reset the full registry
+- `GET /api/capture` capture via unified pipeline
+- `GET /api/photos`, `GET /api/sessions`, `GET /api/delete`, `GET /api/reupload`
+- `GET /api/errors` structured error counters
+
+## Configuration
+
+Source of truth:
+- `Data/Settings/config.json` loaded by `Core/settings.py`
+
+Environment overrides are supported (timing, ports, upload settings, camera, etc.).
+
+Direct camera serial selection precedence:
+- `REALSENSE_SERIAL`
+- `PREFERRED_REALSENSE_SERIAL`
+- `Data/Settings/config.json -> camera.preferred_realsense_serial`
+- teleimager camera config serial
+- any other detected RealSense
+
+Dashboard camera behavior:
+- main production dashboard can switch between available camera sources without restarting the runtime
+- camera status panel shows requested source, active source, backend, active profile, preferred serial, and active RealSense serial
+- resolution changes are applied live through the direct camera service
+- `Save As Default` stores the preferred RealSense serial into `Data/Settings/config.json`
+
+AI prerecorded prompt behavior:
+- `Data/Audio/` stores fixed WAV clips by prompt key
+- `Data/Settings/audio_prompt_records.json` stores prompt recording metadata and raw-output file references
+- `audio_prompts.files` in `Data/Settings/config.json` maps each key to its filename
+- `audio_prompts.mode` controls fixed AI situation speech:
+  - `audio`: use recorded clips first for AI situation prompts
+  - `gemini`: use Gemini speech instead for those same fixed prompts
+- `audio_prompts.fallback_to_gemini` controls whether missing prompt clips fall back to Gemini text
+- dashboard prompt library manages upload/download/delete, text-to-record generation, speech mode, and fallback state
+- imported prerecorded prompts currently cover 18 situation keys; missing keys continue through Gemini fallback until recorded
+
+AI replay behavior:
+- `vision.autonomous_greeting_replay_enabled` controls the short greeting gesture when intent stabilizes
+- `vision.autonomous_greeting_replay_file` selects the greeting replay file
+- `vision.autonomous_capture_replay_enabled` controls whether AI photo capture uses the active replay during the shot
+- `replay.active_file` in `Data/Settings/config.json` is the single persisted active-replay setting
+- the active replay is shared between manual `R2+X`, dashboard capture choreography, and AI capture when AI capture replay is enabled
+- replay inventory is shared across the full `Data/G1` tree
+
+Face recognition behavior:
+- `vision.face_recognition_enabled` enables single-guest recognition/enrollment in AI mode
+- `vision.face_recognition_threshold` controls the similarity threshold for matching a returning guest
+- new guests are enrolled into `photos/people/`
+- successful AI captures are linked back into the guest folder for future reference
+
+Vision model configuration (`Data/Settings/config.json` -> `vision`):
+- `detection_backend`: `normal` or `yolo` (runtime switchable from dashboard in AI mode)
+- `yolo_runtime`: `ultralytics` (production) or `opencv` (legacy ONNX parser)
+- `yolo_ultralytics_device`: inference device for ultralytics (`cpu`, `0`, `0,1`, ...)
+- `person_yolo_onnx`: path to YOLO ONNX person model
+- `face_yolo_onnx`: path to YOLO ONNX face model
+- `group_min_people`: minimum people count to mark a group
+- `group_link_distance_px`: max centroid-link distance for group clustering
+
+## Documentation
+
+- `Current_runtime.md`: detailed current runtime behavior and script chain.
+
+## Data Layout
+
+- `Data/Settings/`
+  - `config.json`
+- `Data/Scripts/`
+  - `photo_command_ai.txt`
+  - `sanad_script.txt`
+- `Data/Runtime/`
+  - runtime health/state/error JSON files
+- `Data/Audio/`
+  - prerecorded AI prompt WAV files
+  - matching `_raw.wav` Gemini output captures
+- `Data/Settings/audio_prompt_records.json`
+  - prompt recording metadata for files in `Data/Audio/`
+
+## Notes
+
+- `config.py` is intentionally removed; runtime config is JSON + env overrides.
+- legacy AI mover/autonomous prototype scripts were removed from the production tree.
+- Generated artifacts (`__pycache__`, runtime logs) should not be committed.
+- Generated runtime files such as `Data/Runtime/runtime_health.json`, `Data/Runtime/autonomous_state.json`, `Data/Runtime/error_counters.json`, `Data/Runtime/error_events.jsonl`, and `Logs/*.log` may be absent in a clean checkout until the runtime starts.
diff --git a/Scripts/direct_camera_samples_server.py b/Scripts/direct_camera_samples_server.py
new file mode 100644
index 0000000..9f0328a
--- /dev/null
+++ b/Scripts/direct_camera_samples_server.py
@@ -0,0 +1,20 @@
+#!/usr/bin/env python3
+"""
+Compatibility wrapper for the direct camera service.
+
+The main camera service now lives in Core/direct_camera_service.py.
+This wrapper is kept so older commands and scripts still work.
+"""
+
+from pathlib import Path
+import sys
+
+PROJECT_ROOT = Path(__file__).resolve().parent.parent
+if str(PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(PROJECT_ROOT))
+
+from Core.direct_camera_service import main
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Scripts/fix_realsense_usb.sh b/Scripts/fix_realsense_usb.sh
new file mode 100755
index 0000000..496249a
--- /dev/null
+++ b/Scripts/fix_realsense_usb.sh
@@ -0,0 +1,122 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+need_cmd() {
+  command -v "$1" >/dev/null 2>&1 || { echo "[ERR] Missing command: $1" >&2; exit 1; }
+}
+
+need_cmd rs-enumerate-devices
+need_cmd awk
+need_cmd sed
+need_cmd grep
+
+realsense_output() {
+  rs-enumerate-devices 2>/dev/null || true
+}
+
+is_realsense_present() {
+  local out
+  out="$(realsense_output)"
+  echo "$out" | grep -qi "Intel RealSense"
+}
+
+print_bool() {
+  if is_realsense_present; then
+    echo "true"
+  else
+    echo "false"
+  fi
+}
+
+list_serials() {
+  local out
+  out="$(realsense_output)"
+  if ! echo "$out" | grep -qi "Intel RealSense"; then
+    return 0
+  fi
+
+  echo "$out" \
+    | awk -F':' '/Serial Number/ {print $2}' \
+    | sed 's/^[[:space:]]*//; s/[[:space:]]*$//' \
+    | grep -v '^$' \
+    | awk '!seen[$0]++'
+}
+
+# Apply USB power settings to the RealSense sysfs path + its parent hub
+apply_fix() {
+  local RS_OUT SERIAL PHY USB_NODE PARENT_HUB DEV_SYS HUB_SYS
+
+  RS_OUT="$(realsense_output)"
+  if ! echo "$RS_OUT" | grep -qi "Intel RealSense"; then
+    # No device: just print false
+    echo "false"
+    return 0
+  fi
+
+  SERIAL="$(echo "$RS_OUT" | awk -F':' '/Serial Number/ {gsub(/[ \t]/,"",$2); print $2; exit}')"
+  PHY="$(echo "$RS_OUT" | awk -F':' '/Physical Port/ {print $2; exit}' | sed 's/^[ \t]*//')"
+
+  # Extract USB node like "2-2.3" from Physical Port
+  USB_NODE="$(echo "$PHY" | grep -oE '/usb[0-9]+/[^ ]+' | sed -E 's#.*/usb[0-9]+/##' | cut -d'/' -f2 | head -n1 || true)"
+  if [[ -z "${USB_NODE:-}" ]]; then
+    USB_NODE="$(echo "$PHY" | grep -oE 'usb[0-9]+/[0-9]+-[0-9]+(\.[0-9]+)?' | sed 's#usb[0-9]+/##' | head -n1 || true)"
+  fi
+
+  if [[ -z "${USB_NODE:-}" ]]; then
+    # Can't map sysfs; still detected though
+    echo "true"
+    return 0
+  fi
+
+  PARENT_HUB="${USB_NODE%%.*}"
+  DEV_SYS="/sys/bus/usb/devices/${USB_NODE}"
+  HUB_SYS="/sys/bus/usb/devices/${PARENT_HUB}"
+
+  # Disable autosuspend globally (optional)
+  echo -1 | sudo tee /sys/module/usbcore/parameters/autosuspend >/dev/null || true
+
+  apply_power_fix() {
+    local path="$1"
+    [[ -d "$path" ]] || return 0
+    [[ -e "$path/power/control" ]] && echo on | sudo tee "$path/power/control" >/dev/null || true
+    [[ -e "$path/power/autosuspend" ]] && echo -1 | sudo tee "$path/power/autosuspend" >/dev/null || true
+    [[ -e "$path/power/autosuspend_delay_ms" ]] && echo 0 | sudo tee "$path/power/autosuspend_delay_ms" >/dev/null || true
+  }
+
+  apply_power_fix "$HUB_SYS"
+  apply_power_fix "$DEV_SYS"
+
+  # Final verification
+  print_bool
+}
+
+usage() {
+  cat <<'EOF'
+Usage:
+  bash fix_realsense_usb.sh --check   # prints true/false only
+  bash fix_realsense_usb.sh --fix     # applies fix then prints true/false
+  bash fix_realsense_usb.sh --serials # prints available RealSense serials, one per line
+Default: --fix
+EOF
+}
+
+mode="${1:---fix}"
+
+case "$mode" in
+  --check)
+    print_bool
+    ;;
+  --fix)
+    apply_fix
+    ;;
+  --serials|--list-serials)
+    list_serials
+    ;;
+  -h|--help)
+    usage
+    ;;
+  *)
+    usage >&2
+    exit 1
+    ;;
+esac
diff --git a/Scripts/photo_sanad.sh b/Scripts/photo_sanad.sh
new file mode 100755
index 0000000..dc3782f
--- /dev/null
+++ b/Scripts/photo_sanad.sh
@@ -0,0 +1,568 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+# ============================================================
+# photo_sanad.sh
+# ------------------------------------------------------------
+# ONE command to run everything:
+#   ./photo_sanad.sh
+#
+# What it does:
+# 1) Activates the camera env (py3.10) and starts the Core direct camera service in background
+# 2) Activates gemini (py3.11) and runs Gemini/voice_sanad.py in foreground
+# 3) Sets PulseAudio default sink/source (optional)
+# 4) Sets PYTHONPATH for unitree_sdk2_python (so unitree_sdk2py imports work)
+# 5) On exit, stops the direct camera server
+# ============================================================
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+DEFAULT_BASE_DIR="$(cd -- "$SCRIPT_DIR/.." && pwd)"
+BASE_DIR="${BASE_DIR:-$DEFAULT_BASE_DIR}"
+PY_FILE="$BASE_DIR/Gemini/voice_sanad.py"
+RUN_USER="${SUDO_USER:-${USER:-$(id -un)}}"
+RUN_USER_HOME="$(getent passwd "$RUN_USER" 2>/dev/null | cut -d: -f6 || true)"
+if [[ -z "${RUN_USER_HOME:-}" ]]; then
+  RUN_USER_HOME="$HOME"
+fi
+RUN_USER_ID="$(id -u "$RUN_USER" 2>/dev/null || true)"
+export HOME="$RUN_USER_HOME"
+if [[ -n "${RUN_USER_ID:-}" ]] && [[ -d "/run/user/$RUN_USER_ID" ]]; then
+  export XDG_RUNTIME_DIR="/run/user/$RUN_USER_ID"
+  if [[ -S "$XDG_RUNTIME_DIR/pulse/native" ]]; then
+    export PULSE_SERVER="unix:$XDG_RUNTIME_DIR/pulse/native"
+  fi
+fi
+
+# conda
+CONDA_SH="${CONDA_SH:-$RUN_USER_HOME/miniconda3/etc/profile.d/conda.sh}"
+ENV_TELE="teleimager"   # Python 3.10 camera env (pyrealsense2)
+ENV_GEM="gemini"        # Python 3.11
+SDK_PY_PATH="${SDK_PY_PATH:-$RUN_USER_HOME/unitree_sdk2_python}"
+DIRECT_CAMERA_PORT="${DIRECT_CAMERA_PORT:-8091}"
+DIRECT_CAMERA_HOST="${DIRECT_CAMERA_HOST:-127.0.0.1}"
+DIRECT_CAMERA_SOURCE="${DIRECT_CAMERA_SOURCE:-realsense}"
+DIRECT_CAMERA_SCRIPT="${DIRECT_CAMERA_SCRIPT:-$BASE_DIR/Core/direct_camera_service.py}"
+LEGACY_DIRECT_CAMERA_SCRIPT="$BASE_DIR/Scripts/direct_camera_samples_server.py"
+
+# Optional: choose your camera (if needed)
+# export CAMERA_DEVICE=/dev/video2
+# export PHOTO_PREFIX=photo
+export CAMERA_DEVICE="${CAMERA_DEVICE:-/dev/video0}"
+export PHOTO_PREFIX="${PHOTO_PREFIX:-photo}"
+
+# RealSense fix/sudo behavior
+SUDO_ENABLE_FIX="${SUDO_ENABLE_FIX:-1}"          # 1=cache sudo so /api/fix can run
+SUDO_PROMPT_ON_START="${SUDO_PROMPT_ON_START:-0}"  # 1=allow interactive sudo prompt at startup
+AUTO_FIX_ON_START="${AUTO_FIX_ON_START:-0}"      # 1=run fix script once on startup
+SUDO_KEEPALIVE_INTERVAL="${SUDO_KEEPALIVE_INTERVAL:-60}"
+FIX_SCRIPT="${FIX_SCRIPT:-$BASE_DIR/Scripts/fix_realsense_usb.sh}"
+SUDO_KEEPALIVE_PID=""
+LOG_DIR="${LOG_DIR:-$BASE_DIR/Logs}"
+PHOTO_SERVER_PORT="${PHOTO_SERVER_PORT:-8080}"
+PRE_KILL_OLD="${PRE_KILL_OLD:-1}"   # 1=stop stale sanad/camera services from previous runs
+FREE_PORT_BEFORE_START="${FREE_PORT_BEFORE_START:-1}"  # 1=kill listeners on PHOTO_SERVER_PORT
+ALLOW_EXISTING_PORT_SERVER="${ALLOW_EXISTING_PORT_SERVER:-0}"  # 1=allow attaching to an already-running gallery server
+
+# PulseAudio device names (change if needed)
+SINK="${SINK:-alsa_output.usb-Anker_PowerConf_A3321-DEV-SN1-01.analog-stereo}"
+SOURCE="${SOURCE:-alsa_input.usb-Anker_PowerConf_A3321-DEV-SN1-01.mono-fallback}"
+
+# ALSA plugin fix (helps conda envs stop spamming ALSA errors)
+if [[ -d "/usr/lib/aarch64-linux-gnu/alsa-lib" ]]; then
+  export ALSA_PLUGIN_DIR="/usr/lib/aarch64-linux-gnu/alsa-lib"
+elif [[ -d "/usr/lib/alsa-lib" ]]; then
+  export ALSA_PLUGIN_DIR="/usr/lib/alsa-lib"
+fi
+if [[ -f "/usr/share/alsa/alsa.conf" ]]; then
+  export ALSA_CONFIG_PATH="/usr/share/alsa/alsa.conf"
+fi
+export ALSA_LOG_LEVEL=0
+
+echo "📁 Base dir: $BASE_DIR"
+echo "👤 Runtime user: $RUN_USER"
+echo "🏠 Runtime home: $RUN_USER_HOME"
+cd "$BASE_DIR"
+
+# ---------- logging dir ----------
+if ! mkdir -p "$LOG_DIR" >/dev/null 2>&1; then
+  LOG_DIR="$HOME/.ai_photographer_logs"
+  mkdir -p "$LOG_DIR"
+fi
+if ! touch "$LOG_DIR/.write_test" >/dev/null 2>&1; then
+  LOG_DIR="$HOME/.ai_photographer_logs"
+  mkdir -p "$LOG_DIR"
+  touch "$LOG_DIR/.write_test" >/dev/null 2>&1 || true
+fi
+rm -f "$LOG_DIR/.write_test" >/dev/null 2>&1 || true
+export AI_PHOTOGRAPHER_LOG_DIR="$LOG_DIR"
+
+# ---------- stale-process cleanup ----------
+show_port_owner() {
+  local port="$1"
+  if command -v ss >/dev/null 2>&1; then
+    # shellcheck disable=SC2016
+    ss -ltnp 2>/dev/null | awk -v p=":$port" '$4 ~ p {print $0}' || true
+  fi
+}
+
+start_sudo_keepalive() {
+  (
+    while true; do
+      sleep "$SUDO_KEEPALIVE_INTERVAL"
+      sudo -n true >/dev/null 2>&1 || exit 0
+    done
+  ) &
+  SUDO_KEEPALIVE_PID=$!
+  echo "✅ sudo cached (keepalive PID=$SUDO_KEEPALIVE_PID)"
+}
+
+setup_sudo_cache() {
+  if [[ "$SUDO_ENABLE_FIX" != "1" ]]; then
+    return 0
+  fi
+
+  if ! command -v sudo >/dev/null 2>&1; then
+    echo "⚠️ sudo not found; /api/fix cannot run privileged fixes."
+    return 0
+  fi
+
+  if sudo -n true >/dev/null 2>&1; then
+    echo "🔐 sudo credentials already cached."
+    start_sudo_keepalive
+    return 0
+  fi
+
+  if [[ "$SUDO_PROMPT_ON_START" == "1" && -t 0 ]]; then
+    echo "🔐 Preparing sudo for RealSense fix endpoint..."
+    if sudo -v; then
+      start_sudo_keepalive
+    else
+      echo "⚠️ sudo auth failed; /api/fix may require manual terminal command."
+    fi
+  else
+    echo "⚠️ sudo not cached. Use SUDO_PROMPT_ON_START=1 to allow startup prompt."
+  fi
+}
+
+get_port_pids() {
+  local port="$1"
+  {
+    if command -v lsof >/dev/null 2>&1; then
+      lsof -t -iTCP:"$port" -sTCP:LISTEN -Pn 2>/dev/null || true
+    fi
+    if command -v ss >/dev/null 2>&1; then
+      ss -ltnp 2>/dev/null \
+        | awk -v p=":$port" '$4 ~ p {print $0}' \
+        | sed -n 's/.*pid=\([0-9][0-9]*\).*/\1/p' || true
+    fi
+    if command -v fuser >/dev/null 2>&1; then
+      fuser -n tcp "$port" 2>/dev/null | tr ' ' '\n' || true
+    fi
+  } | sed '/^[[:space:]]*$/d' | sort -u
+}
+
+get_pid_cmdline() {
+  local pid="$1"
+  ps -o args= -p "$pid" 2>/dev/null || true
+}
+
+kill_one_pid() {
+  local pid="$1"
+  local signal="${2:-TERM}"
+  local pgid=""
+  [[ -z "${pid:-}" ]] && return 0
+
+  if ! kill "-$signal" "$pid" >/dev/null 2>&1; then
+    sudo -n kill "-$signal" "$pid" >/dev/null 2>&1 || true
+  fi
+
+  pgid="$(ps -o pgid= -p "$pid" 2>/dev/null | tr -d ' ' || true)"
+  if [[ -n "${pgid:-}" ]]; then
+    if ! kill "-$signal" "--" "-$pgid" >/dev/null 2>&1; then
+      sudo -n kill "-$signal" "--" "-$pgid" >/dev/null 2>&1 || true
+    fi
+  fi
+}
+
+kill_port_owner() {
+  local port="$1"
+  local pids pid attempt
+  pids="$(get_port_pids "$port" || true)"
+  [[ -z "${pids:-}" ]] && return 0
+
+  echo "🛑 Attempting to free port $port (PID(s): $(echo "$pids" | tr '\n' ' '))"
+  for attempt in 1 2 3; do
+    while IFS= read -r pid; do
+      [[ -z "${pid:-}" ]] && continue
+      if [[ "$attempt" -lt 3 ]]; then
+        kill_one_pid "$pid" TERM
+      else
+        kill_one_pid "$pid" KILL
+      fi
+    done <<< "$pids"
+    sleep 1
+    pids="$(get_port_pids "$port" || true)"
+    [[ -z "${pids:-}" ]] && return 0
+    if [[ "$attempt" -eq 2 ]]; then
+      echo "⚠️ Port $port still busy, sending SIGKILL..."
+    fi
+  done
+}
+
+report_port_owners() {
+  local port="$1"
+  local pids pid cmd
+  pids="$(get_port_pids "$port" || true)"
+  [[ -z "${pids:-}" ]] && return 0
+  while IFS= read -r pid; do
+    [[ -z "${pid:-}" ]] && continue
+    cmd="$(get_pid_cmdline "$pid")"
+    echo "   - PID $pid: ${cmd:-<unknown>}"
+  done <<< "$pids"
+}
+
+stop_stale_processes() {
+  echo "🧽 Checking stale processes..."
+  local stopped=0
+
+  # Previous Sanad app instances from same project copy
+  if pgrep -f "$BASE_DIR/Gemini/voice_sanad.py" >/dev/null 2>&1; then
+    echo "🛑 Stopping previous voice_sanad.py processes..."
+    pkill -f "$BASE_DIR/Gemini/voice_sanad.py" >/dev/null 2>&1 || sudo -n pkill -f "$BASE_DIR/Gemini/voice_sanad.py" >/dev/null 2>&1 || true
+    stopped=1
+  fi
+  # Legacy pre-restructure path support
+  if pgrep -f "$BASE_DIR/voice_sanad.py" >/dev/null 2>&1; then
+    echo "🛑 Stopping previous legacy voice_sanad.py processes..."
+    pkill -f "$BASE_DIR/voice_sanad.py" >/dev/null 2>&1 || sudo -n pkill -f "$BASE_DIR/voice_sanad.py" >/dev/null 2>&1 || true
+    stopped=1
+  fi
+
+# Previous direct camera servers
+  if pgrep -f "$DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1; then
+    echo "🛑 Stopping previous direct camera service processes..."
+    pkill -f "$DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || sudo -n pkill -f "$DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || true
+    stopped=1
+  fi
+  if [[ "$DIRECT_CAMERA_SCRIPT" != "$LEGACY_DIRECT_CAMERA_SCRIPT" ]] && pgrep -f "$LEGACY_DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1; then
+    echo "🛑 Stopping previous legacy direct_camera_samples_server.py processes..."
+    pkill -f "$LEGACY_DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || sudo -n pkill -f "$LEGACY_DIRECT_CAMERA_SCRIPT" >/dev/null 2>&1 || true
+    stopped=1
+  fi
+
+  # Give OS a moment to release sockets/resources.
+  if [[ "$stopped" -eq 1 ]]; then
+    sleep 1
+  fi
+}
+
+# Try to cache sudo early so stale cleanup can stop root-owned leftovers.
+setup_sudo_cache
+
+if [[ "$PRE_KILL_OLD" == "1" ]]; then
+  stop_stale_processes
+fi
+
+PORT_OWNER="$(show_port_owner "$PHOTO_SERVER_PORT" || true)"
+if [[ -n "${PORT_OWNER:-}" ]]; then
+  echo "⚠️ Port $PHOTO_SERVER_PORT currently in use:"
+  echo "$PORT_OWNER"
+fi
+
+# ---------- conda init ----------
+if [[ ! -f "$CONDA_SH" ]]; then
+  echo "❌ conda.sh not found: $CONDA_SH"
+  exit 1
+fi
+# shellcheck disable=SC1090
+source "$CONDA_SH"
+
+# ---------- time sync wait ----------
+echo "⏰ Checking system time..."
+while [ "$(date +%Y)" -lt 2025 ]; do
+  echo "⏳ Waiting for time sync... $(date)"
+  sleep 2
+done
+echo "✅ Time synced: $(date)"
+
+# ---------- PulseAudio defaults (optional) ----------
+pick_pactl_device() {
+  local kind="$1"
+  local requested="$2"
+  local current=""
+  local names=""
+  local chosen=""
+
+  if [[ "$kind" == "sink" ]]; then
+    current="$(pactl info 2>/dev/null | sed -n 's/^Default Sink: //p' | head -n1)"
+    names="$(pactl list short sinks 2>/dev/null | awk '{print $2}')"
+  else
+    current="$(pactl info 2>/dev/null | sed -n 's/^Default Source: //p' | head -n1)"
+    names="$(pactl list short sources 2>/dev/null | awk '{print $2}')"
+  fi
+
+  if [[ -n "${requested:-}" ]] && echo "$names" | grep -Fxq "$requested"; then
+    chosen="$requested"
+  elif [[ -n "${current:-}" ]] && echo "$names" | grep -Fxq "$current"; then
+    chosen="$current"
+  else
+    chosen="$(echo "$names" | grep -Ei 'anker|powerconf|usb' | head -n1 || true)"
+    if [[ -z "${chosen:-}" ]]; then
+      chosen="$(echo "$names" | head -n1 || true)"
+    fi
+  fi
+
+  printf '%s' "$chosen"
+}
+
+if command -v pactl >/dev/null 2>&1; then
+  echo "🔊 Checking audio server..."
+  READY=0
+  for _ in {1..20}; do
+    if timeout 0.3s pactl info >/dev/null 2>&1; then
+      READY=1
+      break
+    fi
+    sleep 0.3
+  done
+
+  if [[ "$READY" -eq 1 ]]; then
+    RESOLVED_SINK="$(pick_pactl_device sink "$SINK")"
+    RESOLVED_SOURCE="$(pick_pactl_device source "$SOURCE")"
+
+    if [[ -n "${RESOLVED_SINK:-}" ]]; then
+      if [[ "$RESOLVED_SINK" != "$SINK" ]]; then
+        echo "⚠️ Requested speaker not found. Using → $RESOLVED_SINK"
+      else
+        echo "🎧 Setting default speaker → $RESOLVED_SINK"
+      fi
+      pactl set-default-sink "$RESOLVED_SINK" || true
+    else
+      echo "⚠️ No PulseAudio sink found. Continuing without speaker selection."
+    fi
+
+    if [[ -n "${RESOLVED_SOURCE:-}" ]]; then
+      if [[ "$RESOLVED_SOURCE" != "$SOURCE" ]]; then
+        echo "⚠️ Requested microphone not found. Using → $RESOLVED_SOURCE"
+      else
+        echo "🎤 Setting default microphone → $RESOLVED_SOURCE"
+      fi
+      pactl set-default-source "$RESOLVED_SOURCE" || true
+    else
+      echo "⚠️ No PulseAudio source found. Continuing without microphone selection."
+    fi
+
+    ACTIVE_SINK="$(pactl info 2>/dev/null | sed -n 's/^Default Sink: //p' | head -n1 || true)"
+    ACTIVE_SOURCE="$(pactl info 2>/dev/null | sed -n 's/^Default Source: //p' | head -n1 || true)"
+    [[ -n "${ACTIVE_SINK:-}" ]] && echo "🔈 Active speaker default: $ACTIVE_SINK"
+    [[ -n "${ACTIVE_SOURCE:-}" ]] && echo "🎙️ Active microphone default: $ACTIVE_SOURCE"
+  else
+    echo "⚠️ PulseAudio/PipeWire not ready. Continuing anyway."
+  fi
+else
+  echo "⚠️ pactl not found. Skipping audio defaults."
+fi
+
+# ---------- paths check ----------
+if [[ ! -f "$PY_FILE" ]]; then
+  echo "❌ voice_sanad.py not found: $PY_FILE"
+  exit 1
+fi
+
+# ---------- startup mode / runtime profile ----------
+# Primary config lives in Data/Settings/config.json. Keep legacy Data/config.json
+# and Scripts/config.json fallbacks so older robot copies can still boot during migrations.
+MODE_FROM_CFG="$(python - <<'PY'
+import json
+from pathlib import Path
+p = Path("Data/Settings/config.json")
+legacy_candidates = [Path("Data/config.json"), Path("Scripts/config.json")]
+if not p.exists():
+    for legacy in legacy_candidates:
+        if legacy.exists():
+            p = legacy
+            break
+mode = "manual"
+try:
+    if p.exists():
+        d = json.loads(p.read_text(encoding="utf-8"))
+        mode_block = d.get("mode") or {}
+        mode = str(mode_block.get("default_mode", mode_block.get("current_mode", "manual"))).strip().lower()
+except Exception:
+    mode = "manual"
+if mode == "command":
+    mode = "ai"
+try:
+    if p.exists():
+        d = json.loads(p.read_text(encoding="utf-8"))
+        mode_block = d.get("mode") or {}
+        mode_block["current_mode"] = mode
+        d["mode"] = mode_block
+        p.write_text(json.dumps(d, indent=2), encoding="utf-8")
+except Exception:
+    pass
+print(mode if mode in ("manual", "ai") else "manual")
+PY
+)"
+echo "✅ Runtime mode reset to default: $MODE_FROM_CFG"
+
+PHOTO_OUTPUT_DIR="$(python - <<'PY'
+import json
+from pathlib import Path
+base = Path(".").resolve()
+p = Path("Data/Settings/config.json")
+legacy_candidates = [Path("Data/config.json"), Path("Scripts/config.json")]
+if not p.exists():
+    for legacy in legacy_candidates:
+        if legacy.exists():
+            p = legacy
+            break
+value = "AI_Photographer/photos/Captures"
+try:
+    if p.exists():
+        d = json.loads(p.read_text(encoding="utf-8"))
+        paths = d.get("paths") or {}
+        value = str(paths.get("photos_dir", value) or value).strip()
+except Exception:
+    pass
+target = Path(value).expanduser()
+if not target.is_absolute():
+    parts = target.parts
+    if parts and parts[0] == base.name:
+        target = (base.parent / target).resolve()
+    else:
+        target = (base / target).resolve()
+print(target)
+PY
+)"
+echo "🗂️ Capture output dir: $PHOTO_OUTPUT_DIR"
+
+if [[ -z "${MANUAL_LEAN_RUNTIME:-}" ]]; then
+  if [[ "$MODE_FROM_CFG" == "manual" ]]; then
+    export MANUAL_LEAN_RUNTIME=0
+  else
+    export MANUAL_LEAN_RUNTIME=0
+  fi
+fi
+if [[ "$MODE_FROM_CFG" == "manual" && "${MANUAL_LEAN_RUNTIME}" == "1" ]]; then
+  echo "🪶 Manual lean runtime enabled: direct camera/DDS/replay startup will be skipped."
+fi
+
+# ---------- start direct camera server (py3.10) ----------
+TELE_PID=""
+TELE_LOG="$LOG_DIR/direct_camera.log"
+if [[ "$MODE_FROM_CFG" == "manual" && "${MANUAL_LEAN_RUNTIME}" == "1" ]]; then
+  echo "📷 Skipping direct camera startup for lean manual runtime."
+else
+  kill_port_owner "$DIRECT_CAMERA_PORT"
+  echo "🐍 Activating camera env: $ENV_TELE"
+  conda activate "$ENV_TELE"
+
+  echo "🐍 camera env python: $(which python)"
+  python -c "import sys; print('✅ camera env sys.executable:', sys.executable); print('✅ camera env sys.version:', sys.version.split()[0])"
+
+  echo "📷 Starting direct camera server in background..."
+  python "$DIRECT_CAMERA_SCRIPT" \
+    --camera "$DIRECT_CAMERA_SOURCE" \
+    --host "$DIRECT_CAMERA_HOST" \
+    --port "$DIRECT_CAMERA_PORT" \
+    --samples-dir "$PHOTO_OUTPUT_DIR" \
+    --capture-prefix "$PHOTO_PREFIX" \
+    --capture-ext jpg >"$TELE_LOG" 2>&1 &
+  TELE_PID=$!
+  echo "✅ direct camera PID=$TELE_PID  log=$TELE_LOG"
+fi
+
+cleanup() {
+  echo ""
+  echo "🧹 Cleaning up..."
+  if [[ -n "${SUDO_KEEPALIVE_PID:-}" ]] && kill -0 "$SUDO_KEEPALIVE_PID" >/dev/null 2>&1; then
+    echo "🛑 Stopping sudo keepalive PID=$SUDO_KEEPALIVE_PID"
+    kill "$SUDO_KEEPALIVE_PID" >/dev/null 2>&1 || true
+    wait "$SUDO_KEEPALIVE_PID" >/dev/null 2>&1 || true
+  fi
+  if [[ -n "${TELE_PID:-}" ]] && kill -0 "$TELE_PID" >/dev/null 2>&1; then
+    echo "🛑 Stopping direct camera server PID=$TELE_PID"
+    kill "$TELE_PID" >/dev/null 2>&1 || true
+    wait "$TELE_PID" >/dev/null 2>&1 || true
+  fi
+  echo "✅ Done."
+}
+trap cleanup EXIT INT TERM
+
+# Give server time to start
+if [[ -n "${TELE_PID:-}" ]]; then
+  sleep 2
+fi
+
+# ---------- run sanad (py3.11) ----------
+echo "🐍 Activating gemini env: $ENV_GEM"
+conda activate "$ENV_GEM"
+
+echo "🐍 gemini python: $(which python)"
+python -c "import sys; print('✅ gemini sys.executable:', sys.executable); print('✅ gemini sys.version:', sys.version.split()[0])"
+
+# ---------- autonomous enable policy ----------
+# If AUTONOMOUS_ENABLE is not explicitly provided, derive from startup default mode:
+# - full runtime -> arm autonomous services so AI mode can start live without restart
+# - lean manual runtime -> keep disabled
+if [[ -z "${AUTONOMOUS_ENABLE:-}" ]]; then
+  if [[ "$MODE_FROM_CFG" == "manual" && "${MANUAL_LEAN_RUNTIME}" == "1" ]]; then
+    export AUTONOMOUS_ENABLE=0
+  else
+    export AUTONOMOUS_ENABLE=1
+  fi
+  echo "🤖 AUTONOMOUS_ENABLE auto-set to $AUTONOMOUS_ENABLE (mode=$MODE_FROM_CFG, lean_manual=${MANUAL_LEAN_RUNTIME})"
+else
+  echo "🤖 AUTONOMOUS_ENABLE preset to $AUTONOMOUS_ENABLE"
+fi
+
+# Ensure unitree_sdk2py can import using the local project modules.
+export PYTHONPATH="$SDK_PY_PATH:${BASE_DIR}:${PYTHONPATH:-}"
+echo "🔧 Using local AI_Photographer modules"
+export DIRECT_CAMERA_ENABLED="${DIRECT_CAMERA_ENABLED:-1}"
+export DIRECT_CAMERA_SERVER_URL="${DIRECT_CAMERA_SERVER_URL:-http://$DIRECT_CAMERA_HOST:$DIRECT_CAMERA_PORT}"
+
+echo "🔧 PYTHONPATH=$PYTHONPATH"
+echo "📷 DIRECT_CAMERA_SERVER_URL=$DIRECT_CAMERA_SERVER_URL"
+echo "🔧 ALSA_PLUGIN_DIR=${ALSA_PLUGIN_DIR:-"(not set)"}"
+echo "🔧 ALSA_CONFIG_PATH=${ALSA_CONFIG_PATH:-"(not set)"}"
+echo "🎥 CAMERA_DEVICE=$CAMERA_DEVICE"
+echo "🖼️ PHOTO_PREFIX=$PHOTO_PREFIX"
+echo "🔧 FIX_SCRIPT=$FIX_SCRIPT"
+echo "🪵 LOG_DIR=$LOG_DIR"
+
+# sudo cache is handled earlier by setup_sudo_cache.
+
+if [[ "$AUTO_FIX_ON_START" == "1" ]]; then
+  if [[ -f "$FIX_SCRIPT" ]]; then
+    echo "🛠️ Running RealSense fix on startup..."
+    if sudo bash "$FIX_SCRIPT" --fix; then
+      echo "✅ RealSense fix completed."
+    else
+      echo "⚠️ RealSense fix failed; continuing startup."
+    fi
+  else
+    echo "⚠️ AUTO_FIX_ON_START=1 but fix script not found: $FIX_SCRIPT"
+  fi
+fi
+
+# Final port cleanup right before launching main app (after sudo caching)
+if [[ "$FREE_PORT_BEFORE_START" == "1" ]]; then
+  kill_port_owner "$PHOTO_SERVER_PORT"
+fi
+PORT_OWNER="$(show_port_owner "$PHOTO_SERVER_PORT" || true)"
+if [[ -n "${PORT_OWNER:-}" ]]; then
+  echo "⚠️ Port $PHOTO_SERVER_PORT remains in use:"
+  echo "$PORT_OWNER"
+  report_port_owners "$PHOTO_SERVER_PORT"
+  if [[ "$ALLOW_EXISTING_PORT_SERVER" != "1" ]]; then
+    echo "❌ Refusing to continue while a stale server still owns port $PHOTO_SERVER_PORT."
+    echo "   Set ALLOW_EXISTING_PORT_SERVER=1 only if you intentionally want to attach to the existing server."
+    exit 1
+  fi
+fi
+
+echo "🚀 Starting Sanad AI_Photographer..."
+# Run in foreground (so trap cleanup runs when process exits)
+python "$PY_FILE"
diff --git a/Server/__init__.py b/Server/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Server/capture_service.py b/Server/capture_service.py
new file mode 100644
index 0000000..671e854
--- /dev/null
+++ b/Server/capture_service.py
@@ -0,0 +1,396 @@
+# capture_service.py
+import os
+import subprocess
+import threading
+import time
+from pathlib import Path
+
+from Core.error_events import record_error
+from Core import settings as config
+from Server import direct_camera_client
+
+SERVER_DIR = Path(__file__).resolve().parent
+PROJECT_ROOT = SERVER_DIR.parent
+
+FIX_SCRIPT = str((PROJECT_ROOT / "Scripts" / "fix_realsense_usb.sh").resolve())
+UPLOAD_NOW_FLAG = (PROJECT_ROOT / "Scripts" / "upload_now.flag").resolve()
+
+
+def _touch_upload_now_flag():
+    try:
+        UPLOAD_NOW_FLAG.parent.mkdir(parents=True, exist_ok=True)
+        UPLOAD_NOW_FLAG.write_text(str(time.time()), encoding="utf-8")
+    except Exception as e:
+        record_error("capture_service", "touch_upload_now_flag", e)
+
+
+def _next_photo_name(out_dir: Path, prefix: str, ext: str) -> Path:
+    base = out_dir / f"{prefix}.{ext}"
+    if not base.exists():
+        return base
+    i = 1
+    while True:
+        p = out_dir / f"{prefix}({i}).{ext}"
+        if not p.exists():
+            return p
+        i += 1
+
+
+def take_photo_sync(prefix: str | None = None) -> str:
+    """
+    Captures one photo and returns the saved path or a compact error.
+    Production runtime uses the direct camera service only.
+    """
+    retry_count = max(0, int(config.read_watchdog_camera_capture_retry_count()))
+    retry_delay = max(0.0, float(config.read_watchdog_camera_capture_retry_delay_sec()))
+    total_attempts = max(1, retry_count + 1)
+    last_err = "[ERR] take_photo unknown error"
+
+    for attempt in range(1, total_attempts + 1):
+        try:
+            env = os.environ.copy()
+            env.setdefault("PHOTOS_DIR", str(Path(config.PHOTOS_DIR).resolve()))
+            if prefix:
+                env["PHOTO_PREFIX"] = prefix
+            else:
+                env.setdefault("PHOTO_PREFIX", "photo")
+            if not direct_camera_client.is_enabled():
+                last_err = "[ERR] direct camera service is disabled"
+                record_error(
+                    "capture_service",
+                    "take_photo_sync_attempt_failed",
+                    context={"attempt": attempt, "total_attempts": total_attempts, "reason": "direct_camera_disabled"},
+                )
+                continue
+
+            saved = direct_camera_client.capture(
+                prefix=env.get("PHOTO_PREFIX", "photo"),
+                ext=env.get("PHOTO_EXT", "jpg").strip().lstrip(".") or "jpg",
+                timeout=10.0,
+            )
+            _touch_upload_now_flag()
+            return saved
+        except Exception as e:
+            last_err = f"[ERR] take_photo exception: {e}"
+            record_error(
+                "capture_service",
+                "take_photo_sync_exception",
+                e,
+                {"attempt": attempt, "total_attempts": total_attempts},
+            )
+
+        if attempt < total_attempts and retry_delay > 0.0:
+            time.sleep(retry_delay)
+
+    return last_err
+
+
+def take_photo_test_sync() -> str:
+    """
+    Takes a photo and deletes it immediately. Good as a camera health test.
+    Returns "OK" or an error string.
+    """
+    result = take_photo_sync()
+    if result.startswith("/"):
+        try:
+            p = Path(result)
+            if p.exists():
+                p.unlink()
+            return "OK"
+        except Exception as e:
+            return f"[WARN] captured but delete failed: {e}"
+    return result
+
+
+def run_fix_realsense_sync() -> str:
+    """
+    Runs fix_realsense_usb.sh. NOTE: script uses sudo tee -> needs passwordless sudo to fully work.
+    """
+    try:
+        if not Path(FIX_SCRIPT).exists():
+            return f"[ERR] fix script not found: {FIX_SCRIPT}"
+
+        p = subprocess.run(
+            ["bash", FIX_SCRIPT],
+            capture_output=True,
+            text=True,
+            timeout=20,
+        )
+        out = (p.stdout or "").strip()
+        err = (p.stderr or "").strip()
+        if p.returncode == 0:
+            return out or "OK"
+        return f"[ERR] fix script rc={p.returncode}\n{out}\n{err}".strip()
+    except Exception as e:
+        record_error("capture_service", "run_fix_realsense_sync_exception", e)
+        return f"[ERR] fix exception: {e}"
+
+
+def replay_file_integrity(path: Path) -> dict:
+    """
+    Checks:
+    - file exists
+    - has at least one frame with 'q'
+    - has at least one trigger marker (meta contains trigger)
+    """
+    p = Path(path).resolve()
+    out = {
+        "ok": False,          # usable replay (has frames)
+        "trigger_ok": False,  # has explicit trigger markers
+        "path": str(p),
+        "exists": False,
+        "frames": 0,
+        "triggers": 0,
+        "error": "",
+    }
+    if not p.exists() or not p.is_file():
+        out["error"] = "missing replay file"
+        return out
+    out["exists"] = True
+
+    import json
+
+    try:
+        with p.open("r", encoding="utf-8") as f:
+            for line in f:
+                line = line.strip()
+                if not line:
+                    continue
+                try:
+                    d = json.loads(line)
+                except Exception:
+                    continue
+                if isinstance(d, dict) and isinstance(d.get("q"), list):
+                    out["frames"] += 1
+                    meta = d.get("meta")
+                    trig = False
+                    if isinstance(meta, str) and ("trigger" in meta.lower()):
+                        trig = True
+                    elif isinstance(meta, dict) and bool(meta.get("trigger")):
+                        trig = True
+                    if trig:
+                        out["triggers"] += 1
+        out["ok"] = out["frames"] > 0
+        out["trigger_ok"] = out["triggers"] > 0
+        if out["frames"] <= 0:
+            out["error"] = "replay has no valid frames"
+        elif out["triggers"] <= 0:
+            out["warning"] = "replay has no trigger markers; timed fallback capture will be used"
+        return out
+    except Exception as e:
+        out["error"] = str(e)
+        record_error("capture_service", "replay_file_integrity", e, {"path": str(p)})
+        return out
+
+
+def replay_timing_profile(path: Path, end_margin_sec: float | None = None) -> dict:
+    """
+    Returns replay timing information used to align countdown audio and fallback capture.
+
+    If the replay contains explicit trigger markers, the first trigger offset is treated as the
+    desired shot time. Otherwise the shot is scheduled slightly before the replay ends so capture
+    happens before the arm starts returning home.
+    """
+    p = Path(path).resolve()
+    margin = max(0.0, float(end_margin_sec if end_margin_sec is not None else config.REPLAY_CAPTURE_END_MARGIN_SEC))
+    out = {
+        "ok": False,
+        "path": str(p),
+        "exists": False,
+        "frames": 0,
+        "timed_frames": 0,
+        "duration_sec": 0.0,
+        "trigger_offsets_sec": [],
+        "trigger_count": 0,
+        "capture_offset_sec": max(0.0, min(config.PHOTO_DELAY_SEC, config.PHOTO_TOTAL_SEC)),
+        "capture_source": "config_fallback",
+        "end_margin_sec": margin,
+        "error": "",
+    }
+    if not p.exists() or not p.is_file():
+        out["error"] = "missing replay file"
+        return out
+    out["exists"] = True
+
+    import json
+
+    timed_offsets: list[float] = []
+    trigger_offsets: list[float] = []
+    first_t: float | None = None
+
+    try:
+        with p.open("r", encoding="utf-8") as f:
+            for line in f:
+                line = line.strip()
+                if not line:
+                    continue
+                try:
+                    d = json.loads(line)
+                except Exception:
+                    continue
+                if not (isinstance(d, dict) and isinstance(d.get("q"), list)):
+                    continue
+
+                out["frames"] += 1
+                try:
+                    t_val = float(d.get("t"))
+                except Exception:
+                    continue
+
+                if first_t is None:
+                    first_t = t_val
+                rel_t = max(0.0, t_val - first_t)
+                timed_offsets.append(rel_t)
+                out["timed_frames"] += 1
+
+                meta = d.get("meta")
+                if isinstance(meta, str) and ("trigger" in meta.lower()):
+                    trigger_offsets.append(rel_t)
+                elif isinstance(meta, dict) and bool(meta.get("trigger")):
+                    trigger_offsets.append(rel_t)
+
+        out["ok"] = out["frames"] > 0
+        if not out["ok"]:
+            out["error"] = "replay has no valid frames"
+            return out
+
+        if timed_offsets:
+            duration_sec = max(0.0, timed_offsets[-1])
+            out["duration_sec"] = duration_sec
+            out["trigger_offsets_sec"] = [round(x, 3) for x in trigger_offsets]
+            out["trigger_count"] = len(trigger_offsets)
+
+            if trigger_offsets:
+                out["capture_offset_sec"] = max(0.0, min(duration_sec, trigger_offsets[0]))
+                out["capture_source"] = "trigger"
+            elif duration_sec > 0.0:
+                out["capture_offset_sec"] = max(0.0, duration_sec - margin)
+                out["capture_source"] = "timed_end"
+            else:
+                out["capture_source"] = "config_fallback"
+        else:
+            out["error"] = "replay has no timestamped frames; config fallback timing will be used"
+
+        return out
+    except Exception as e:
+        out["error"] = str(e)
+        record_error("capture_service", "replay_timing_profile", e, {"path": str(p)})
+        return out
+
+
+def ensure_replay_integrity(active_replay: Path, fallback_replay: Path) -> tuple[Path, dict]:
+    """
+    Returns a valid replay path. If active invalid, tries fallback.
+    """
+    active = Path(active_replay).resolve()
+    fallback = Path(fallback_replay).resolve()
+    active_report = replay_file_integrity(active)
+    if active_report.get("ok") and active_report.get("trigger_ok"):
+        return active, {"selected": str(active), "active": active_report, "fallback_used": False}
+
+    fallback_report = replay_file_integrity(fallback)
+    if fallback_report.get("ok") and fallback_report.get("trigger_ok"):
+        return fallback, {
+            "selected": str(fallback),
+            "active": active_report,
+            "fallback": fallback_report,
+            "fallback_used": True,
+            "reason": "active replay missing trigger markers",
+        }
+
+    # Degraded mode: no trigger-marked file found, keep active if it has frames.
+    if active_report.get("ok"):
+        return active, {
+            "selected": str(active),
+            "active": active_report,
+            "fallback": fallback_report,
+            "fallback_used": False,
+            "degraded_no_trigger": True,
+        }
+
+    # If both invalid, keep active and report both failures.
+    return active, {
+        "selected": str(active),
+        "active": active_report,
+        "fallback": fallback_report,
+        "fallback_used": False,
+    }
+
+
+def capture_with_replay_sync(
+    replay_runner,
+    replay_file: Path,
+    home_file: Path,
+    delay_sec: float,
+    prefix: str | None = None,
+    speed: float = 1.0,
+    finalize_timeout_sec: float = 4.0,
+    cancel_event: threading.Event | None = None,
+) -> str:
+    """
+    Unified capture pipeline:
+      replay + trigger callback capture + fallback timed capture + upload flag.
+    """
+    delay_sec = max(0.0, float(delay_sec))
+    done = threading.Event()
+    lock = threading.Lock()
+    result = {"value": None}
+    capture_started = {"value": False}
+
+    def _is_cancelled() -> bool:
+        return bool(cancel_event is not None and cancel_event.is_set())
+
+    def _capture_once(reason: str):
+        if _is_cancelled():
+            return
+        with lock:
+            if capture_started["value"]:
+                return
+            capture_started["value"] = True
+        try:
+            result["value"] = take_photo_sync(prefix=prefix)
+        except Exception as e:
+            record_error("capture_service", "capture_with_replay_capture_once", e, {"reason": reason})
+            result["value"] = f"[ERR] capture failed ({reason}): {e}"
+        finally:
+            done.set()
+
+    if replay_runner is not None and bool(getattr(replay_runner, "is_playing", False)):
+        return "[ERR] replay busy"
+    if _is_cancelled():
+        return "[ERR] capture cancelled"
+
+    try:
+        if replay_runner is not None:
+            def _trigger_cb(_frame):
+                threading.Thread(target=lambda: _capture_once("trigger"), daemon=True).start()
+
+            threading.Thread(
+                target=lambda: replay_runner.run(replay_file, home_file, speed, trigger_callback=_trigger_cb),
+                daemon=True,
+            ).start()
+    except Exception as e:
+        record_error("capture_service", "capture_with_replay_start_replay", e)
+        return f"[ERR] replay start failed: {e}"
+
+    deadline = time.time() + delay_sec
+    while (not done.is_set()) and (time.time() < deadline):
+        if _is_cancelled():
+            return "[ERR] capture cancelled"
+        time.sleep(0.02)
+
+    if (not done.is_set()) and (not _is_cancelled()):
+        _capture_once("fallback")
+
+    finalize_deadline = time.time() + max(0.1, finalize_timeout_sec)
+    while not done.is_set():
+        if _is_cancelled():
+            return "[ERR] capture cancelled"
+        if time.time() >= finalize_deadline:
+            break
+        time.sleep(0.02)
+    if not done.is_set():
+        record_error("capture_service", "capture_with_replay_timeout", context={"delay_sec": delay_sec})
+        return "[ERR] capture pipeline timeout"
+
+    return str(result["value"] or "[ERR] capture pipeline no result")
diff --git a/Server/direct_camera_client.py b/Server/direct_camera_client.py
new file mode 100644
index 0000000..49f8ada
--- /dev/null
+++ b/Server/direct_camera_client.py
@@ -0,0 +1,103 @@
+from __future__ import annotations
+
+import json
+import os
+import urllib.error
+import urllib.parse
+import urllib.request
+from typing import Any, Optional
+
+import cv2
+import numpy as np
+
+
+def is_enabled() -> bool:
+    return os.environ.get("DIRECT_CAMERA_ENABLED", "1").strip().lower() not in ("0", "false", "no", "off")
+
+
+def base_url() -> str:
+    return (
+        os.environ.get("DIRECT_CAMERA_SERVER_URL", "").strip()
+        or f"http://127.0.0.1:{int(os.environ.get('DIRECT_CAMERA_PORT', '8091'))}"
+    ).rstrip("/")
+
+
+def _open(path: str, timeout: float = 3.0):
+    url = base_url() + path
+    req = urllib.request.Request(url, method="GET")
+    return urllib.request.urlopen(req, timeout=timeout)
+
+
+def get_json(path: str, timeout: float = 3.0) -> dict[str, Any]:
+    with _open(path, timeout=timeout) as resp:
+        raw = resp.read()
+    data = json.loads(raw.decode("utf-8"))
+    if isinstance(data, dict):
+        return data
+    raise RuntimeError("direct camera server returned non-object JSON")
+
+
+def get_bytes(path: str, timeout: float = 3.0) -> bytes:
+    with _open(path, timeout=timeout) as resp:
+        return resp.read()
+
+
+def health(timeout: float = 2.0) -> dict[str, Any]:
+    return get_json("/api/health", timeout=timeout)
+
+
+def cameras(timeout: float = 2.0) -> dict[str, Any]:
+    return get_json("/api/cameras", timeout=timeout)
+
+
+def capture(prefix: str = "photo", ext: str = "jpg", timeout: float = 10.0) -> str:
+    q = urllib.parse.urlencode({"prefix": prefix, "ext": ext})
+    data = get_json(f"/api/capture?{q}", timeout=timeout)
+    if not data.get("ok"):
+        raise RuntimeError(str(data.get("error") or "capture failed"))
+    path = str(data.get("path") or "").strip()
+    if not path:
+        raise RuntimeError("capture response missing saved path")
+    return path
+
+
+def set_source(source: str, timeout: float = 8.0) -> dict[str, Any]:
+    q = urllib.parse.urlencode({"source": source})
+    data = get_json(f"/api/set_camera?{q}", timeout=timeout)
+    if not data.get("ok"):
+        raise RuntimeError(str(data.get("error") or "camera switch failed"))
+    return data
+
+
+def set_preferred_camera(serial: str, timeout: float = 8.0) -> dict[str, Any]:
+    q = urllib.parse.urlencode({"serial": serial})
+    data = get_json(f"/api/set_preferred_camera?{q}", timeout=timeout)
+    if not data.get("ok"):
+        raise RuntimeError(str(data.get("error") or "preferred camera update failed"))
+    return data
+
+
+def set_resolution(width: int, height: int, fps: int, timeout: float = 8.0) -> dict[str, Any]:
+    q = urllib.parse.urlencode({"width": int(width), "height": int(height), "fps": int(fps)})
+    data = get_json(f"/api/set_resolution?{q}", timeout=timeout)
+    if not data.get("ok"):
+        raise RuntimeError(str(data.get("error") or "resolution change failed"))
+    return data
+
+
+def frame_jpeg(timeout: float = 2.0) -> bytes:
+    return get_bytes("/api/frame.jpg", timeout=timeout)
+
+
+def frame_bgr(timeout: float = 2.0) -> Optional[np.ndarray]:
+    try:
+        raw = frame_jpeg(timeout=timeout)
+    except urllib.error.URLError:
+        return None
+    except Exception:
+        return None
+    arr = np.frombuffer(raw, dtype=np.uint8)
+    if arr.size <= 0:
+        return None
+    frame = cv2.imdecode(arr, cv2.IMREAD_COLOR)
+    return frame
diff --git a/Server/photo_server.py b/Server/photo_server.py
new file mode 100644
index 0000000..ab437fe
--- /dev/null
+++ b/Server/photo_server.py
@@ -0,0 +1,2195 @@
+#!/usr/bin/env python3
+"""
+photo_server.py
+---------------
+HTTP photo gallery server for the configured AI_Photographer photos directory.
+
+✅ Features:
+- Phone/Laptop gallery UI: GET /
+- Serves photos directly (open/download): GET /<filename>
+- Delete photo: GET /api/delete?name=<filename>
+- Capture via unified replay pipeline: GET /api/capture
+- Camera status: GET /api/status
+- Camera test (RealSense enumerate via camera env python): GET /api/test
+- Run RealSense USB fix script: GET /api/fix
+- CSS/HTML split:
+    Web/gallery.html
+    Web/style.css
+  Served as:
+    / -> gallery.html template (photo list injected)
+    /static/style.css -> style.css file
+
+⚠️ Security note:
+- This is an open LAN server (anyone on same WiFi can view/download/delete).
+  Use only on trusted networks.
+
+Works well with your structure (no new folders).
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import socket
+import sys
+import threading
+import tempfile
+import time
+import urllib.parse
+import subprocess
+import cgi
+from pathlib import Path
+from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer
+from typing import Optional, Callable, Dict, Any, List
+from Core import settings as config
+from Core import audio_prompts
+from Core import audio_prompt_recorder
+from Core.error_events import get_error_counters, record_error
+from Core import people_registry
+from Server.capture_service import replay_file_integrity, take_photo_sync
+from Server import direct_camera_client
+
+try:
+    from Core.Logger import Logs
+except Exception:
+    Logs = None  # type: ignore
+
+
+# ============================================================
+# Defaults / Paths
+# ============================================================
+SERVER_DIR = Path(__file__).resolve().parent
+PROJECT_ROOT = SERVER_DIR.parent
+SCRIPTS_DIR = (PROJECT_ROOT / "Scripts").resolve()
+APP_DATA_DIR = Path(getattr(config, "APP_DATA_DIR", PROJECT_ROOT / "Data")).resolve()
+DATA_SCRIPTS_DIR = Path(getattr(config, "APP_SCRIPTS_DIR", APP_DATA_DIR / "Scripts")).resolve()
+AUTONOMOUS_STATE_FILE = Path(getattr(config, "AUTONOMOUS_STATE_FILE", APP_DATA_DIR / "Runtime" / "autonomous_state.json")).resolve()
+RUNTIME_HEALTH_FILE = Path(getattr(config, "RUNTIME_HEALTH_FILE", APP_DATA_DIR / "Runtime" / "runtime_health.json")).resolve()
+DEFAULT_PHOTOS_DIR = Path(getattr(config, "PHOTOS_DIR", PROJECT_ROOT / "photos" / "Captures")).resolve()
+WEB_DIR = (PROJECT_ROOT / "Web").resolve()
+
+GALLERY_HTML = WEB_DIR / "gallery.html"
+STYLE_CSS = WEB_DIR / "style.css"
+GALLERY_JS = WEB_DIR / "gallery.js"
+
+FIX_SCRIPT_ENV = os.environ.get("FIX_SCRIPT_PATH", "").strip()
+_DEFAULT_RUNTIME_HOME = Path(os.environ.get("HOME", "~")).expanduser()
+CAMERA_ENV_PY = os.environ.get(
+    "TELEIMAGER_PY",
+    str((_DEFAULT_RUNTIME_HOME / "miniconda3" / "envs" / "teleimager" / "bin" / "python").resolve()),
+)
+
+# Preview fallback controls
+PREVIEW_USE_OPENCV_FALLBACK = os.environ.get("PREVIEW_USE_OPENCV_FALLBACK", "1").strip().lower() not in (
+    "0", "false", "no", "off"
+)
+PREVIEW_RETRY_SEC = float(os.environ.get("PREVIEW_RETRY_SEC", "2.0"))
+
+# Shared preview camera state to avoid reopening camera on every frame
+_PREVIEW_CAM_LOCK = threading.Lock()
+_PREVIEW_CAM: Optional[Any] = None
+_PREVIEW_LAST_OPEN_TRY = 0.0
+_CV2_MODULE = None
+_CAMERA_CAPTURE_CLS = None
+
+_RECORDER_LOCK = threading.Lock()
+_RECORDER_STATE: Dict[str, Any] = {
+    "running": False,
+    "name": "",
+    "seconds": 0.0,
+    "output": "",
+    "returncode": None,
+    "ok": False,
+    "error": "",
+    "started_at": 0.0,
+    "finished_at": 0.0,
+    "stdout_tail": [],
+}
+
+_REPLAY_TEST_LOCK = threading.Lock()
+_REPLAY_TEST_STATE: Dict[str, Any] = {
+    "running": False,
+    "name": "",
+    "ok": False,
+    "error": "",
+    "result": "",
+    "started_at": 0.0,
+    "finished_at": 0.0,
+}
+
+_AUDIO_PROMPT_RECORD_LOCK = threading.Lock()
+_AUDIO_PROMPT_RECORD_STATE: Dict[str, Any] = {
+    "running": False,
+    "key": "",
+    "filename": "",
+    "text": "",
+    "ok": False,
+    "error": "",
+    "started_at": 0.0,
+    "finished_at": 0.0,
+    "result": {},
+}
+
+
+# ============================================================
+# Logging helpers
+# ============================================================
+def _make_logger(log_name: str = "photo_server"):
+    if Logs is None:
+        return None
+    lg = Logs()
+    try:
+        lg.LogEngine("G1_Logs", log_name)
+    except Exception:
+        pass
+    return lg
+
+
+def _log(lg, msg: str, level: str = "info"):
+    # level: info / warning / error
+    if lg is not None:
+        try:
+            lg.print_and_log(msg, message_type=level)
+            return
+        except Exception:
+            pass
+    print(msg)
+
+
+# ============================================================
+# Utilities
+# ============================================================
+def _get_local_ip() -> str:
+    """
+    Best-effort IP that phones can reach (same WiFi).
+    """
+    try:
+        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+        s.connect(("8.8.8.8", 80))
+        ip = s.getsockname()[0]
+        s.close()
+        return ip
+    except Exception:
+        return "127.0.0.1"
+
+
+def _safe_name(name: str) -> str:
+    """
+    Prevent path traversal: keep only filename (no dirs).
+    """
+    name = name.strip().replace("\\", "/")
+    name = name.split("/")[-1]
+    return name
+
+
+def _fix_script_candidates() -> List[Path]:
+    cands: List[Path] = []
+    if FIX_SCRIPT_ENV:
+        p = Path(FIX_SCRIPT_ENV).expanduser()
+        if not p.is_absolute():
+            p = (PROJECT_ROOT / p).resolve()
+        cands.append(p)
+    cands.append((SCRIPTS_DIR / "fix_realsense_usb.sh").resolve())
+    cands.append((PROJECT_ROOT / "fix_realsense_usb.sh").resolve())
+    return cands
+
+
+def _resolve_fix_script() -> Optional[Path]:
+    for p in _fix_script_candidates():
+        if p.exists() and p.is_file():
+            return p
+    return None
+
+
+def _get_cv2():
+    global _CV2_MODULE
+    if _CV2_MODULE is None:
+        import cv2
+
+        _CV2_MODULE = cv2
+    return _CV2_MODULE
+
+
+def _get_camera_capture_cls():
+    global _CAMERA_CAPTURE_CLS
+    if _CAMERA_CAPTURE_CLS is None:
+        from Modes.AI.camera_module import CameraCapture
+
+        _CAMERA_CAPTURE_CLS = CameraCapture
+    return _CAMERA_CAPTURE_CLS
+
+
+def _is_photo_file(p: Path) -> bool:
+    if not p.is_file():
+        return False
+    ext = p.suffix.lower()
+    return ext in (".jpg", ".jpeg", ".png", ".webp")
+
+
+def _list_photos(folder: Path) -> List[Dict[str, Any]]:
+    items: List[Dict[str, Any]] = []
+    folder.mkdir(parents=True, exist_ok=True)
+
+    for p in sorted(folder.iterdir(), key=lambda x: x.stat().st_mtime, reverse=True):
+        if not _is_photo_file(p):
+            continue
+        st = p.stat()
+        items.append(
+            {
+                "name": p.name,
+                "size": st.st_size,
+                "mtime": st.st_mtime,
+            }
+        )
+    return items
+
+
+def _group_sessions(items: List[Dict[str, Any]], gap_sec: int = 120) -> List[Dict[str, Any]]:
+    """Group photos into sessions when gaps between photos exceed gap_sec."""
+    sessions = []
+    cur = None
+    for it in sorted(items, key=lambda x: x["mtime"]):
+        t = it["mtime"]
+        if cur is None:
+            cur = {"id": len(sessions) + 1, "start": t, "end": t, "photos": [it["name"]]}
+            continue
+        if t - cur["end"] > gap_sec:
+            sessions.append(cur)
+            cur = {"id": len(sessions) + 1, "start": t, "end": t, "photos": [it["name"]]}
+        else:
+            cur["photos"].append(it["name"])
+            cur["end"] = t
+
+    if cur is not None:
+        sessions.append(cur)
+    return sessions
+
+
+def _read_text_file(path: Path) -> Optional[str]:
+    try:
+        return path.read_text(encoding="utf-8")
+    except Exception:
+        return None
+
+
+def _read_bytes_file(path: Path) -> Optional[bytes]:
+    try:
+        return path.read_bytes()
+    except Exception:
+        return None
+
+
+def _read_mode() -> str:
+    try:
+        m = str(config.read_runtime_mode()).strip().lower()
+    except Exception:
+        m = "manual"
+    if m == "command":
+        return "ai"
+    if m not in ("manual", "ai"):
+        return "manual"
+    return m
+
+
+def _read_detector_backend() -> str:
+    try:
+        b = str(config.read_vision_detector_backend()).strip().lower()
+    except Exception:
+        b = "normal"
+    if b not in ("yolo", "normal"):
+        return "normal"
+    return b
+
+
+def _strict_yolo_required() -> bool:
+    try:
+        return bool(config.read_vision_yolo_strict_required())
+    except Exception:
+        return bool(getattr(config, "VISION_YOLO_STRICT_REQUIRED", False))
+
+
+def _read_ai_readiness() -> Dict[str, Any]:
+    from Modes.AI.vision_detector import probe_ai_readiness
+
+    backend = _read_detector_backend()
+    strict_required = _strict_yolo_required()
+    readiness = probe_ai_readiness(backend=backend, strict_required=strict_required)
+    state = _read_autonomous_state()
+
+    ai_blocked = bool(state.get("ai_blocked", False))
+    ai_block_reason = str(state.get("ai_block_reason", "") or "").strip()
+    if ai_blocked and ai_block_reason:
+        readiness["ok"] = False
+        readiness["block_reason"] = ai_block_reason
+
+    return {
+        "ok": bool(readiness.get("ok", False)),
+        "strict_required": bool(strict_required),
+        "backend": backend,
+        "yolo_runtime": str(readiness.get("yolo_runtime", "") or ""),
+        "yolo_loaded": bool(readiness.get("yolo_loaded", False)),
+        "person_model_ok": bool(readiness.get("person_model_ok", False)),
+        "face_model_ok": bool(readiness.get("face_model_ok", False)),
+        "block_reason": str(readiness.get("block_reason", "") or ""),
+        "person_model_path": str(readiness.get("person_model_path", "") or ""),
+        "face_model_path": str(readiness.get("face_model_path", "") or ""),
+    }
+
+
+def _read_runtime_health() -> Dict[str, Any]:
+    default = {
+        "ws_connected": False,
+        "ws_state": "detached",
+        "ws_restarts": 0,
+        "ws_last_error": "",
+        "mic_enabled": True,
+        "mic_state": "idle",
+        "mic_restarts": 0,
+        "mic_last_error": "",
+        "speaker_state": "idle",
+        "speaker_restarts": 0,
+        "speaker_last_error": "",
+        "audio_gate_open": False,
+        "time": 0.0,
+    }
+    try:
+        if not RUNTIME_HEALTH_FILE.exists():
+            return default
+        raw = json.loads(RUNTIME_HEALTH_FILE.read_text(encoding="utf-8"))
+        if not isinstance(raw, dict):
+            return default
+        out = dict(default)
+        out.update(raw)
+        return out
+    except Exception:
+        return default
+
+
+def _read_ai_options() -> Dict[str, Any]:
+    try:
+        hard = bool(config.read_vision_hard_target_lock_enabled())
+    except Exception:
+        hard = True
+    try:
+        retake = bool(config.read_vision_retake_prompt_enabled())
+    except Exception:
+        retake = True
+    try:
+        greeting_replay_enabled = bool(config.read_vision_autonomous_greeting_replay_enabled())
+    except Exception:
+        greeting_replay_enabled = True
+    try:
+        greeting_replay_file = str(config.read_vision_autonomous_greeting_replay_file() or "").strip()
+    except Exception:
+        greeting_replay_file = "right_hand_up.jsonl"
+    try:
+        capture_replay_enabled = bool(config.read_vision_autonomous_capture_replay_enabled())
+    except Exception:
+        capture_replay_enabled = True
+    try:
+        face_recognition_enabled = bool(config.read_vision_face_recognition_enabled())
+    except Exception:
+        face_recognition_enabled = True
+    try:
+        face_recognition_threshold = float(config.read_vision_face_recognition_threshold())
+    except Exception:
+        face_recognition_threshold = 0.88
+    return {
+        "hard_target_lock_enabled": hard,
+        "retake_prompt_enabled": retake,
+        "autonomous_greeting_replay_enabled": greeting_replay_enabled,
+        "autonomous_greeting_replay_file": greeting_replay_file,
+        "autonomous_capture_replay_enabled": capture_replay_enabled,
+        "face_recognition_enabled": face_recognition_enabled,
+        "face_recognition_threshold": face_recognition_threshold,
+        "active_replay": _read_active_replay_name(),
+    }
+
+
+def _read_mic_options() -> Dict[str, Any]:
+    try:
+        enabled = bool(config.read_gemini_mic_enabled())
+    except Exception:
+        enabled = True
+    return {"mic_enabled": enabled}
+
+
+def _safe_relative_name(name: str) -> str:
+    raw = str(name or "").strip().replace("\\", "/").lstrip("/")
+    if not raw:
+        return ""
+    p = Path(raw)
+    if p.is_absolute():
+        return ""
+    parts = [part for part in p.parts if part not in ("", ".")]
+    if any(part == ".." for part in parts):
+        return ""
+    return Path(*parts).as_posix() if parts else ""
+
+
+def _normalize_replay_name(name: str, default_parent: str | None = None) -> str:
+    safe = _safe_relative_name(name)
+    if not safe:
+        raise ValueError("invalid replay path")
+
+    p = Path(safe)
+    if len(p.parts) == 1 and default_parent:
+        p = Path(default_parent) / p.name
+    if p.suffix.lower() != ".jsonl":
+        p = p.with_suffix(".jsonl")
+    if p.name == config.HOME_FILE.name:
+        raise ValueError("reserved replay name")
+    return p.as_posix()
+
+
+def _resolve_replay_path(name: str) -> Path:
+    candidate = config.resolve_replay_path(_normalize_replay_name(name))
+    try:
+        candidate.relative_to(config.DATA_DIR)
+    except Exception as e:
+        raise ValueError("invalid replay path") from e
+    return candidate
+
+
+def _is_replay_file(path: Path) -> bool:
+    return path.is_file() and path.suffix.lower() == ".jsonl" and path.name != config.HOME_FILE.name
+
+
+def _read_active_replay_name() -> str:
+    try:
+        return config.read_selected_replay_name()
+    except Exception:
+        return str(config.REPLAY_FILE.name)
+
+
+def _list_replays() -> List[Dict[str, Any]]:
+    items: List[Dict[str, Any]] = []
+    root = config.DATA_DIR.resolve()
+    root.mkdir(parents=True, exist_ok=True)
+    active_name = _read_active_replay_name()
+    greeting_name = str(config.read_vision_autonomous_greeting_replay_file() or "").strip().replace("\\", "/")
+    for path in sorted(root.rglob("*.jsonl")):
+        if not _is_replay_file(path):
+            continue
+        try:
+            rel = str(path.resolve().relative_to(root)).replace("\\", "/")
+        except Exception:
+            rel = path.name
+        st = path.stat()
+        integrity = replay_file_integrity(path)
+        items.append(
+            {
+                "name": rel,
+                "label": path.name,
+                "size": st.st_size,
+                "mtime": st.st_mtime,
+                "active": rel == active_name,
+                "greeting": rel == greeting_name or path.name == greeting_name,
+                "trigger_ok": bool(integrity.get("trigger_ok", False)),
+                "ok": bool(integrity.get("ok", False)),
+            }
+        )
+    return items
+
+
+def _replay_recorder_candidates() -> List[Path]:
+    candidates = []
+    env_path = os.environ.get("REPLAY_RECORDER_SCRIPT", "").strip()
+    if env_path:
+        candidates.append(Path(env_path).expanduser())
+    cfg_raw = str(getattr(config, "REPLAY_RECORDER_SCRIPT", "") or "").strip()
+    if cfg_raw:
+        cfg_path = Path(cfg_raw).expanduser()
+        candidates.append(cfg_path)
+    candidates.append((PROJECT_ROOT.parent / "G1_Lootah" / "Manual_Recorder" / "g1_teach_v4_stable.py").resolve())
+    candidates.append((PROJECT_ROOT.parents[1] / "G1_Lootah" / "Manual_Recorder" / "g1_teach_v4_stable.py").resolve())
+    candidates.append((Path.home() / "G1_Lootah" / "Manual_Recorder" / "g1_teach_v4_stable.py").resolve())
+    return [p if p.is_absolute() else p.resolve() for p in candidates]
+
+
+def _resolve_replay_recorder_script() -> Optional[Path]:
+    for candidate in _replay_recorder_candidates():
+        try:
+            if candidate.exists() and candidate.is_file():
+                return candidate
+        except Exception:
+            continue
+    return None
+
+
+def _read_recorder_state() -> Dict[str, Any]:
+    with _RECORDER_LOCK:
+        return dict(_RECORDER_STATE)
+
+
+def _set_recorder_state(**kwargs):
+    with _RECORDER_LOCK:
+        _RECORDER_STATE.update(kwargs)
+
+
+def _read_replay_test_state() -> Dict[str, Any]:
+    with _REPLAY_TEST_LOCK:
+        return dict(_REPLAY_TEST_STATE)
+
+
+def _set_replay_test_state(**kwargs):
+    with _REPLAY_TEST_LOCK:
+        _REPLAY_TEST_STATE.update(kwargs)
+
+
+def _read_audio_prompt_record_state() -> Dict[str, Any]:
+    with _AUDIO_PROMPT_RECORD_LOCK:
+        return dict(_AUDIO_PROMPT_RECORD_STATE)
+
+
+def _set_audio_prompt_record_state(**kwargs):
+    with _AUDIO_PROMPT_RECORD_LOCK:
+        _AUDIO_PROMPT_RECORD_STATE.update(kwargs)
+
+
+def _run_audio_prompt_record(key: str, text: str, filename: str):
+    try:
+        result = audio_prompt_recorder.record_prompt_from_text(key, text, filename=filename)
+        _set_audio_prompt_record_state(
+            running=False,
+            ok=True,
+            error="",
+            finished_at=time.time(),
+            result=result,
+        )
+    except Exception as e:
+        _set_audio_prompt_record_state(
+            running=False,
+            ok=False,
+            error=str(e),
+            finished_at=time.time(),
+            result={},
+        )
+
+
+def _run_replay_recorder(name: str, seconds: float):
+    script = _resolve_replay_recorder_script()
+    if script is None:
+        _set_recorder_state(
+            running=False,
+            ok=False,
+            error="recorder script not found",
+            finished_at=time.time(),
+        )
+        return
+    try:
+        from Modes.Manual.controller import auto_pick_iface
+
+        iface = auto_pick_iface()
+    except Exception as e:
+        _set_recorder_state(
+            running=False,
+            ok=False,
+            error=f"failed to resolve DDS interface: {e}",
+            finished_at=time.time(),
+        )
+        return
+
+    output_path = _resolve_replay_path(name)
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    cmd = [
+        sys.executable,
+        str(script),
+        iface,
+        "--output",
+        str(output_path),
+        "--seconds",
+        str(seconds),
+        "--home",
+        str(config.HOME_FILE),
+    ]
+    try:
+        proc = subprocess.run(
+            cmd,
+            input="y\nn\n",
+            capture_output=True,
+            text=True,
+            timeout=max(30.0, seconds + 45.0),
+            cwd=str(PROJECT_ROOT),
+        )
+        combined = ((proc.stdout or "") + "\n" + (proc.stderr or "")).strip()
+        tail = [line for line in combined.splitlines() if line.strip()][-25:]
+        saved_path = ""
+        for line in tail:
+            marker = "💾 Saved "
+            if marker in line and " to " in line:
+                saved_path = line.split(" to ", 1)[1].strip()
+        ok = proc.returncode == 0 and bool(saved_path)
+        _set_recorder_state(
+            running=False,
+            ok=ok,
+            error="" if ok else (tail[-1] if tail else f"recorder failed rc={proc.returncode}"),
+            returncode=proc.returncode,
+            finished_at=time.time(),
+            output=saved_path,
+            stdout_tail=tail,
+        )
+    except Exception as e:
+        _set_recorder_state(
+            running=False,
+            ok=False,
+            error=str(e),
+            finished_at=time.time(),
+            stdout_tail=[],
+        )
+
+
+def _run_replay_test(name: str, replay_test_func: Callable[[str], str]):
+    try:
+        result = replay_test_func(name)
+        ok = not str(result or "").startswith("[ERR]")
+        _set_replay_test_state(
+            running=False,
+            ok=ok,
+            error="" if ok else str(result or "").replace("[ERR] ", "").replace("[ERR]", "").strip(),
+            result=str(result or ""),
+            finished_at=time.time(),
+        )
+    except Exception as e:
+        _set_replay_test_state(
+            running=False,
+            ok=False,
+            error=str(e),
+            result="",
+            finished_at=time.time(),
+        )
+
+
+def _update_replay_references_after_rename(old_rel: str, new_rel: str, new_path: Path):
+    if _read_active_replay_name() == old_rel:
+        config.write_selected_replay_name(new_rel)
+        config.REPLAY_FILE = new_path
+    greeting_name = str(config.read_vision_autonomous_greeting_replay_file() or "").strip().replace("\\", "/")
+    if greeting_name == old_rel:
+        config.write_vision_autonomous_greeting_replay_file(new_rel)
+
+
+def _is_greeting_replay(rel_name: str) -> bool:
+    greeting_name = str(config.read_vision_autonomous_greeting_replay_file() or "").strip().replace("\\", "/")
+    return rel_name == greeting_name
+
+
+def _mode_policy(mode: str) -> Dict[str, Any]:
+    mode = mode if mode in ("manual", "ai") else "manual"
+    if mode == "manual":
+        return {
+            "voice_request_photo": False,
+            "description": "Manual mode: Gemini mic can stay on, but mapped photo commands and AI detection are disabled.",
+        }
+    if mode == "ai":
+        return {
+            "voice_request_photo": True,
+            "description": "AI mode: mapped voice can request photo.",
+        }
+    return {
+        "voice_request_photo": False,
+        "description": "Unknown mode.",
+    }
+
+
+def _read_autonomous_state() -> Dict[str, Any]:
+    default: Dict[str, Any] = {
+        "state": "IDLE",
+        "session_id": 0,
+        "interaction_active": False,
+        "intent_detected": False,
+        "detector_backend": "normal",
+        "ai_blocked": False,
+        "ai_block_reason": "",
+        "person_count": 0,
+        "face_count": 0,
+        "group_count": 0,
+        "group_size": 0,
+        "group_detected": False,
+        "max_area": 0.0,
+        "audio_gate_open": False,
+        "subject_id": None,
+        "subject_visible": False,
+        "target_lock_active": False,
+        "target_lock_type": "",
+        "target_lock_id": None,
+        "target_switch_blocked_count": 0,
+        "depth_m": None,
+        "approach_speed_mps": 0.0,
+        "camera_ok": False,
+        "depth_ok": False,
+        "camera_restarts": 0,
+        "depth_restarts": 0,
+        "ws_connected": False,
+        "mic_state": "",
+        "speaker_state": "",
+        "cooldown_remaining": 0.0,
+        "confirm_timeout_remaining": 0.0,
+        "framing_timeout_remaining": 0.0,
+        "countdown_remaining": 0.0,
+        "retake_prompt_enabled": False,
+        "retake_recommended": False,
+        "retake_reason": "",
+        "retake_count": 0,
+        "retake_limit": 0,
+        "recognized_person_id": "",
+        "recognized_person_known": False,
+        "recognized_person_new": False,
+        "recognized_person_label": "",
+        "recognized_person_match_score": 0.0,
+        "recognized_person_created_date": "",
+        "time": 0.0,
+    }
+    try:
+        if not AUTONOMOUS_STATE_FILE.exists():
+            return default
+        data = json.loads(AUTONOMOUS_STATE_FILE.read_text(encoding="utf-8"))
+        if not isinstance(data, dict):
+            return default
+        merged = dict(default)
+        merged.update(data)
+        return merged
+    except Exception:
+        return default
+
+
+# ============================================================
+# Capture/Test/Fix implementations
+# ============================================================
+def _capture_via_service() -> str:
+    """
+    Capture a photo using the shared capture service.
+    """
+    try:
+        return take_photo_sync(prefix="photo")
+    except Exception as e:
+        return f"[ERR] capture exception: {e}"
+
+
+def _preview_camera_source() -> Optional[str]:
+    src = os.environ.get("CAMERA_DEVICE", "").strip()
+    if src:
+        return src
+    idx = os.environ.get("CAMERA_INDEX", "").strip()
+    return idx or None
+
+
+def _get_preview_frame(zmq_host: str = "127.0.0.1", zmq_port: int = 55555, video_source: Optional[str] = None):
+    """Best-effort single frame for MJPEG preview.
+    Tries direct camera server, then CameraCapture fallback.
+    Returns BGR frame or None.
+    """
+    global _PREVIEW_CAM, _PREVIEW_LAST_OPEN_TRY
+    try:
+        if direct_camera_client.is_enabled():
+            frame = direct_camera_client.frame_bgr(timeout=2.0)
+            if frame is not None:
+                return frame
+
+        if not PREVIEW_USE_OPENCV_FALLBACK:
+            return None
+
+        now = time.time()
+        with _PREVIEW_CAM_LOCK:
+            if _PREVIEW_CAM is None and (now - _PREVIEW_LAST_OPEN_TRY) >= PREVIEW_RETRY_SEC:
+                _PREVIEW_LAST_OPEN_TRY = now
+                src = video_source if video_source is not None else _preview_camera_source()
+                cam = _get_camera_capture_cls()(src)
+                if cam.initialize():
+                    _PREVIEW_CAM = cam
+                else:
+                    try:
+                        cam.release()
+                    except Exception:
+                        pass
+                    _PREVIEW_CAM = None
+
+            if _PREVIEW_CAM is None:
+                return None
+
+            frame = _PREVIEW_CAM.capture_frame()
+            if frame is None:
+                # If device dropped, close it and retry after cooldown.
+                cap = getattr(_PREVIEW_CAM, "cap", None)
+                if cap is None or not cap.isOpened():
+                    try:
+                        _PREVIEW_CAM.release()
+                    except Exception:
+                        pass
+                    _PREVIEW_CAM = None
+                return None
+
+            return frame
+    except Exception:
+        return None
+
+
+def _realsense_test() -> Dict[str, Any]:
+    """
+    Quick test using the camera env python:
+    - import pyrealsense2
+    - count devices
+    """
+    try:
+        code = (
+            "import pyrealsense2 as rs\n"
+            "ctx = rs.context()\n"
+            "devs = list(ctx.query_devices())\n"
+            "print(len(devs))\n"
+            "print([d.get_info(rs.camera_info.serial_number) for d in devs])\n"
+        )
+        p = subprocess.run(
+            [CAMERA_ENV_PY, "-c", code],
+            capture_output=True,
+            text=True,
+            timeout=10,
+        )
+        out = (p.stdout or "").strip().splitlines()
+        err = (p.stderr or "").strip()
+
+        if p.returncode != 0:
+            return {"ok": False, "rc": p.returncode, "error": err or "realsense test failed", "stdout": out[-20:]}
+
+        count = int(out[0]) if out else 0
+        serials = []
+        if len(out) >= 2:
+            # second line prints python list
+            serials = out[1]
+        return {"ok": True, "devices": count, "serials": serials, "rc": 0}
+
+    except Exception as e:
+        return {"ok": False, "error": str(e)}
+
+
+def _run_fix_script() -> Dict[str, Any]:
+    """
+    Runs fix_realsense_usb.sh in NON-INTERACTIVE mode.
+    If sudo password is required, it fails gracefully (no terminal prompt).
+    """
+    fix_script = _resolve_fix_script()
+    if not fix_script:
+        checked = [str(p) for p in _fix_script_candidates()]
+        return {"ok": False, "error": "fix script not found", "checked": checked}
+
+    try:
+        # IMPORTANT: -n = non-interactive (won't prompt for password)
+        p = subprocess.run(
+            ["sudo", "-n", "bash", str(fix_script)],
+            capture_output=True,
+            text=True,
+            timeout=40,
+        )
+
+        out = (p.stdout or "").strip().splitlines()[-80:]
+        err = (p.stderr or "").strip().splitlines()[-80:]
+
+        if p.returncode == 0:
+            return {"ok": True, "rc": 0, "stdout": out, "stderr": err}
+
+        # Most common case: sudo needs password
+        joined_err = "\n".join(err).lower()
+        if "a password is required" in joined_err or "sudo:" in joined_err:
+            return {
+                "ok": False,
+                "rc": p.returncode,
+                "error": f"sudo password required. Run manually in terminal: sudo bash {fix_script}",
+                "stdout": out,
+                "stderr": err,
+            }
+
+        return {"ok": False, "rc": p.returncode, "stdout": out, "stderr": err}
+
+    except Exception as e:
+        return {"ok": False, "error": str(e)}
+
+
+
+# ============================================================
+# HTML template fallback (if Scripts/gallery.html missing)
+# ============================================================
+# All HTML/CSS/JS files live in WEB_DIR. The server reads them at runtime.
+
+
+# ============================================================
+# Main server factory
+# ============================================================
+def start_photo_server(
+    folder: Path = DEFAULT_PHOTOS_DIR,
+    port: int = 8080,
+    bind: str = "0.0.0.0",
+    capture_func: Optional[Callable[[], str]] = None,
+    replay_test_func: Optional[Callable[[str], str]] = None,
+    logger=None,
+) -> str:
+    """
+    Starts the gallery server in a daemon thread.
+    Returns the URL (best-effort reachable IP).
+
+    If port is already in use, it logs and returns the URL anyway (assumes old server is running).
+    """
+    lg = logger or _make_logger("photo_server.log")
+    folder = folder.resolve()
+    folder.mkdir(parents=True, exist_ok=True)
+
+    ip = _get_local_ip()
+    url = f"http://{ip}:{port}/"
+
+    if capture_func is None:
+        capture_func = _capture_via_service
+
+    class Handler(SimpleHTTPRequestHandler):
+        QUIET_PATHS = {
+            "/api/autonomous_state",
+            "/api/runtime_health",
+            "/api/photos",
+            "/api/people",
+            "/api/audio_prompts",
+            "/api/audio_prompt_record_status",
+            "/api/set_audio_prompt_mode",
+            "/api/set_audio_prompt_fallback",
+            "/api/replays",
+            "/api/get_replay",
+            "/api/replay_record_status",
+            "/api/replay_test_status",
+            "/api/mode",
+            "/api/ai_readiness",
+            "/api/ai_options",
+            "/api/detector_backend",
+            "/api/camera_health",
+            "/api/camera_sources",
+            "/api/person_image",
+            "/preview.mjpg",
+        }
+
+        # Serve files from PHOTOS folder by default
+        def __init__(self, *args, **kwargs):
+            super().__init__(*args, directory=str(folder), **kwargs)
+
+        def log_message(self, fmt, *args):
+            path = urllib.parse.urlparse(getattr(self, "path", "")).path
+            if path.startswith("/static/"):
+                return
+            if path in self.QUIET_PATHS:
+                return
+            if path.endswith(".jpg") or path.endswith(".jpeg") or path.endswith(".png") or path.endswith(".zip"):
+                return
+            status = str(args[1]) if len(args) > 1 else "?"
+            print(f"🌐 HTTP {getattr(self, 'command', '?')} {path} -> {status}")
+
+        def _send_json(self, obj: Dict[str, Any], code: int = 200):
+            data = json.dumps(obj, ensure_ascii=False, indent=2).encode("utf-8")
+            self.send_response(code)
+            self.send_header("Content-Type", "application/json; charset=utf-8")
+            self.send_header("Content-Length", str(len(data)))
+            self.end_headers()
+            self.wfile.write(data)
+
+        def _send_text(self, text: str, code: int = 200, ctype: str = "text/plain; charset=utf-8"):
+            data = text.encode("utf-8")
+            self.send_response(code)
+            self.send_header("Content-Type", ctype)
+            self.send_header("Content-Length", str(len(data)))
+            self.end_headers()
+            self.wfile.write(data)
+
+        def do_GET(self):
+            parsed = urllib.parse.urlparse(self.path)
+            path = parsed.path
+            q = urllib.parse.parse_qs(parsed.query)
+
+            # Ignore favicon noise
+            if path == "/favicon.ico":
+                self.send_response(204)
+                self.end_headers()
+                return
+
+            # Serve static CSS/JS from Web folder
+            if path == "/static/style.css":
+                css = _read_bytes_file(STYLE_CSS)
+                if css is None:
+                    self.send_response(404)
+                    self.end_headers()
+                    return
+                self.send_response(200)
+                self.send_header("Content-Type", "text/css; charset=utf-8")
+                self.send_header("Content-Length", str(len(css)))
+                self.end_headers()
+                self.wfile.write(css)
+                return
+
+            if path == "/static/gallery.js":
+                js = _read_text_file(GALLERY_JS)
+                if js is None:
+                    self.send_response(404)
+                    self.end_headers()
+                    return
+                data = js.encode("utf-8")
+                self.send_response(200)
+                self.send_header("Content-Type", "application/javascript; charset=utf-8")
+                self.send_header("Content-Length", str(len(data)))
+                self.end_headers()
+                self.wfile.write(data)
+                return
+
+            # API endpoints
+            if path == "/api/status":
+                items = _list_photos(folder)
+                res = {
+                    "ok": True,
+                    "photos_dir": str(folder),
+                    "count": len(items),
+                    "latest": items[0]["name"] if items else None,
+                    "url": url,
+                    "time": time.strftime("%Y-%m-%d %H:%M:%S"),
+                }
+                self._send_json(res, 200)
+                return
+
+            if path == "/api/errors":
+                self._send_json({"ok": True, "counters": get_error_counters()})
+                return
+
+            if path == "/api/mode":
+                # return current mode
+                m = _read_mode()
+                self._send_json({"ok": True, "mode": m, "policy": _mode_policy(m)})
+                return
+
+            if path == "/api/detector_backend":
+                b = _read_detector_backend()
+                strict_required = _strict_yolo_required()
+                mode = _read_mode()
+                locked = bool(strict_required and mode == "ai")
+                self._send_json(
+                    {
+                        "ok": True,
+                        "backend": b,
+                        "yolo_runtime": str(config.read_vision_yolo_runtime()),
+                        "options": ["normal", "yolo"],
+                        "strict_required": strict_required,
+                        "locked": locked,
+                    }
+                )
+                return
+
+            if path == "/api/ai_readiness":
+                data = _read_ai_readiness()
+                self._send_json(data, 200 if data.get("ok") else 503)
+                return
+
+            if path == "/api/runtime_health":
+                self._send_json({"ok": True, "health": _read_runtime_health()})
+                return
+
+            if path == "/api/camera_health":
+                try:
+                    self._send_json(direct_camera_client.health(timeout=3.0))
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e), "camera": {}}, 503)
+                return
+
+            if path == "/api/camera_sources":
+                try:
+                    self._send_json(direct_camera_client.cameras(timeout=3.0))
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e), "options": []}, 503)
+                return
+
+            if path == "/api/set_camera_source":
+                source = q.get("source", [""])[0].strip()
+                if not source:
+                    self._send_json({"ok": False, "error": "missing source"}, 400)
+                    return
+                try:
+                    self._send_json(direct_camera_client.set_source(source, timeout=8.0))
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_camera_resolution":
+                try:
+                    width = int((q.get("width") or [""])[0])
+                    height = int((q.get("height") or [""])[0])
+                    fps = int((q.get("fps") or [""])[0])
+                except Exception:
+                    self._send_json({"ok": False, "error": "width, height, and fps are required integers"}, 400)
+                    return
+                try:
+                    self._send_json(direct_camera_client.set_resolution(width, height, fps, timeout=8.0))
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_preferred_camera":
+                serial = q.get("serial", [""])[0].strip()
+                try:
+                    saved = config.write_camera_preferred_realsense_serial(serial)
+                    self._send_json(direct_camera_client.set_preferred_camera(saved, timeout=8.0))
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/mic":
+                self._send_json({"ok": True, "options": _read_mic_options()})
+                return
+
+            if path == "/api/ai_options":
+                self._send_json({"ok": True, "options": _read_ai_options()})
+                return
+
+            if path == "/api/autonomous_state":
+                self._send_json({"ok": True, "state": _read_autonomous_state()})
+                return
+
+            if path == "/api/people":
+                try:
+                    self._send_json({"ok": True, "people": people_registry.list_people()})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e), "people": []}, 500)
+                return
+
+            if path == "/api/audio_prompts":
+                try:
+                    self._send_json(
+                        {
+                            "ok": True,
+                            "dir": str(config.AUDIO_PROMPTS_DIR),
+                            "mode": str(config.read_audio_prompt_mode()),
+                            "fallback_to_gemini": bool(config.read_audio_prompts_fallback_to_gemini()),
+                            "prompts": audio_prompts.list_audio_prompts(),
+                        }
+                    )
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e), "prompts": []}, 500)
+                return
+
+            if path == "/api/audio_prompt_record_status":
+                self._send_json({"ok": True, "status": _read_audio_prompt_record_state()})
+                return
+
+            if path == "/api/set_audio_prompt_mode":
+                mode = q.get("mode", [""])[0]
+                if mode == "":
+                    self._send_json({"ok": False, "error": "missing mode"}, 400)
+                    return
+                try:
+                    value = str(config.write_audio_prompt_mode(mode))
+                    self._send_json({"ok": True, "mode": value})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_audio_prompt_fallback":
+                enabled = q.get("enabled", [""])[0]
+                if enabled == "":
+                    self._send_json({"ok": False, "error": "missing enabled"}, 400)
+                    return
+                try:
+                    value = bool(config.write_audio_prompts_fallback_to_gemini(enabled))
+                    self._send_json({"ok": True, "fallback_to_gemini": value})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/download_audio_prompt":
+                key = q.get("key", [""])[0].strip()
+                if not key:
+                    self._send_json({"ok": False, "error": "missing key"}, 400)
+                    return
+                try:
+                    prompt_path, body = audio_prompts.read_audio_prompt_bytes(key)
+                    self.send_response(200)
+                    self.send_header("Content-Type", "audio/wav")
+                    self.send_header("Content-Length", str(len(body)))
+                    self.send_header("Content-Disposition", f'attachment; filename="{prompt_path.name}"')
+                    self.end_headers()
+                    self.wfile.write(body)
+                except FileNotFoundError:
+                    self._send_json({"ok": False, "error": "audio prompt not found"}, 404)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/delete_audio_prompt":
+                key = q.get("key", [""])[0].strip()
+                if not key:
+                    self._send_json({"ok": False, "error": "missing key"}, 400)
+                    return
+                try:
+                    self._send_json(audio_prompts.delete_audio_prompt(key))
+                except KeyError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/person_image":
+                person_id = q.get("id", [""])[0].strip()
+                kind = q.get("kind", ["face"])[0].strip().lower()
+                if kind not in ("face", "scene"):
+                    kind = "face"
+                data = people_registry.read_person_image(person_id, kind=kind)
+                if data is None:
+                    self._send_json({"ok": False, "error": "person image not found"}, 404)
+                    return
+                body, ctype, filename = data
+                self.send_response(200)
+                self.send_header("Content-Type", ctype)
+                self.send_header("Content-Length", str(len(body)))
+                self.send_header("Content-Disposition", f'inline; filename="{filename}"')
+                self.end_headers()
+                self.wfile.write(body)
+                return
+
+            if path == "/api/delete_person":
+                person_id = q.get("id", [""])[0].strip()
+                if not person_id:
+                    self._send_json({"ok": False, "error": "missing id"}, 400)
+                    return
+                try:
+                    ok = people_registry.delete_person(person_id)
+                    if not ok:
+                        self._send_json({"ok": False, "error": "person not found"}, 404)
+                        return
+                    self._send_json({"ok": True, "deleted": person_id})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/reset_people":
+                try:
+                    count = int(people_registry.reset_people())
+                    self._send_json({"ok": True, "deleted": count})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/download_person":
+                person_id = q.get("id", [""])[0].strip()
+                if not person_id:
+                    self._send_json({"ok": False, "error": "missing id"}, 400)
+                    return
+                try:
+                    with tempfile.NamedTemporaryFile(prefix=f"{person_id}_", suffix=".zip", delete=False) as tmp:
+                        tmp_path = Path(tmp.name)
+                    archive_path = people_registry.export_person_zip(person_id, tmp_path)
+                    if archive_path is None or not archive_path.exists():
+                        try:
+                            tmp_path.unlink()
+                        except Exception:
+                            pass
+                        self._send_json({"ok": False, "error": "person not found"}, 404)
+                        return
+                    body = archive_path.read_bytes()
+                    self.send_response(200)
+                    self.send_header("Content-Type", "application/zip")
+                    self.send_header("Content-Length", str(len(body)))
+                    self.send_header("Content-Disposition", f'attachment; filename="{person_id}.zip"')
+                    self.end_headers()
+                    self.wfile.write(body)
+                    try:
+                        archive_path.unlink()
+                    except Exception:
+                        pass
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_mode":
+                # set mode via ?mode=ai|manual
+                m = q.get("mode", [""])[0]
+                if m == "command":
+                    self._send_json(
+                        {
+                            "ok": False,
+                            "error": "command mode was moved to G1_Lootah/AI_Command",
+                        },
+                        410,
+                    )
+                    return
+                if m not in ("ai", "manual"):
+                    self._send_json({"ok": False, "error": "invalid mode"}, 400)
+                    return
+                try:
+                    m = config.write_runtime_mode(m)
+                    self._send_json({"ok": True, "mode": m, "policy": _mode_policy(m)})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_ai_options":
+                try:
+                    hard_v = q.get("hard_target_lock_enabled", [None])[0]
+                    retake_v = q.get("retake_prompt_enabled", [None])[0]
+                    greet_enabled_v = q.get("autonomous_greeting_replay_enabled", [None])[0]
+                    greet_file_v = q.get("autonomous_greeting_replay_file", [None])[0]
+                    capture_enabled_v = q.get("autonomous_capture_replay_enabled", [None])[0]
+                    face_recognition_v = q.get("face_recognition_enabled", [None])[0]
+                    face_threshold_v = q.get("face_recognition_threshold", [None])[0]
+                    out = _read_ai_options()
+                    if hard_v is not None:
+                        out["hard_target_lock_enabled"] = bool(
+                            config.write_vision_hard_target_lock_enabled(hard_v)
+                        )
+                    if retake_v is not None:
+                        out["retake_prompt_enabled"] = bool(
+                            config.write_vision_retake_prompt_enabled(retake_v)
+                        )
+                    if greet_enabled_v is not None:
+                        out["autonomous_greeting_replay_enabled"] = bool(
+                            config.write_vision_autonomous_greeting_replay_enabled(greet_enabled_v)
+                        )
+                    if greet_file_v is not None:
+                        out["autonomous_greeting_replay_file"] = str(
+                            config.write_vision_autonomous_greeting_replay_file(greet_file_v)
+                        )
+                    if capture_enabled_v is not None:
+                        out["autonomous_capture_replay_enabled"] = bool(
+                            config.write_vision_autonomous_capture_replay_enabled(capture_enabled_v)
+                        )
+                    if face_recognition_v is not None:
+                        out["face_recognition_enabled"] = bool(
+                            config.write_vision_face_recognition_enabled(face_recognition_v)
+                        )
+                    if face_threshold_v is not None:
+                        out["face_recognition_threshold"] = float(
+                            config.write_vision_face_recognition_threshold(face_threshold_v)
+                        )
+                    out["active_replay"] = _read_active_replay_name()
+                    self._send_json({"ok": True, "options": out})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_mic":
+                try:
+                    enabled_v = q.get("enabled", [None])[0]
+                    if enabled_v is None:
+                        self._send_json({"ok": False, "error": "missing enabled"}, 400)
+                        return
+                    enabled = bool(config.write_gemini_mic_enabled(enabled_v))
+                    self._send_json({"ok": True, "options": {"mic_enabled": enabled}})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/mode_policy":
+                m = _read_mode()
+                self._send_json({"ok": True, "mode": m, "policy": _mode_policy(m)})
+                return
+
+            if path == "/api/set_detector_backend":
+                b = q.get("backend", [""])[0]
+                if b not in ("normal", "yolo"):
+                    self._send_json({"ok": False, "error": "invalid backend"}, 400)
+                    return
+                try:
+                    mode = _read_mode()
+                    strict_required = _strict_yolo_required()
+                    if strict_required and mode == "ai" and b != "yolo":
+                        self._send_json(
+                            {
+                                "ok": False,
+                                "error": "Strict AI profile requires YOLO backend while mode=ai.",
+                                "backend": _read_detector_backend(),
+                                "strict_required": True,
+                            },
+                            409,
+                        )
+                        return
+                    b = config.write_vision_detector_backend(b)
+                    self._send_json(
+                        {
+                            "ok": True,
+                            "backend": b,
+                            "yolo_runtime": str(config.read_vision_yolo_runtime()),
+                            "options": ["normal", "yolo"],
+                            "strict_required": strict_required,
+                            "locked": bool(strict_required and mode == "ai"),
+                        }
+                    )
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/command_info":
+                self._send_json(
+                    {
+                        "ok": False,
+                        "error": "command mode moved",
+                        "moved_to": "G1_Lootah/AI_Command",
+                    },
+                    410,
+                )
+                return
+
+            if path == "/api/test":
+                res = _realsense_test()
+                self._send_json(res, 200 if res.get("ok") else 500)
+                return
+
+            if path == "/api/fix":
+                res = _run_fix_script()
+                self._send_json(res, 200 if res.get("ok") else 500)
+                return
+
+            if path == "/api/run_scripts_fix":
+                # Run the Scripts/fix_realsense_usb.sh with optional mode ?mode=check|fix
+                mode = q.get('mode', ['--fix'])[0] or '--fix'
+                try:
+                    scripts_sh = _resolve_fix_script()
+                    if not scripts_sh:
+                        self._send_json(
+                            {"ok": False, "error": "script not found", "checked": [str(p) for p in _fix_script_candidates()]},
+                            404,
+                        )
+                        return
+                    # run non-interactive
+                    p = subprocess.run(["bash", str(scripts_sh), mode], capture_output=True, text=True, timeout=60)
+                    out = (p.stdout or "").strip().splitlines()
+                    err = (p.stderr or "").strip().splitlines()
+                    ok = p.returncode == 0
+                    resp = {"ok": ok, "rc": p.returncode, "stdout": out[-60:], "stderr": err[-60:]}
+                    self._send_json(resp, 200 if ok else 500)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/capture":
+                # Take photo NOW (no remote)
+                result = capture_func()
+                ok = not result.startswith("[ERR]")
+                self._send_json({"ok": ok, "result": result}, 200 if ok else 500)
+                return
+
+            if path == "/api/sessions":
+                items = _list_photos(folder)
+                sessions = _group_sessions(items)
+                self._send_json({"ok": True, "sessions": sessions})
+                return
+
+            if path == "/api/photos":
+                items = _list_photos(folder)
+                self._send_json({"ok": True, "photos": items})
+                return
+
+            # Request a photo from autonomous mover or external monitor
+            if path == "/api/request_photo":
+                try:
+                    # touch a request file for external processes to pick up
+                    reqf = SCRIPTS_DIR / "request_photo.flag"
+                    reqf.write_text(str(time.time()))
+                    self._send_json({"ok": True, "requested": True})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # Clear all photos (DELETE) - destructive
+            if path == "/api/clear_photos":
+                try:
+                    for p in folder.iterdir():
+                        if _is_photo_file(p):
+                            try:
+                                p.unlink()
+                            except Exception:
+                                pass
+                    self._send_json({"ok": True, "cleared": True})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # Create a ZIP archive of all photos and return path
+            if path == "/api/download_zip":
+                try:
+                    import shutil
+                    zip_base = folder / "_archives"
+                    zip_base.mkdir(parents=True, exist_ok=True)
+                    ts = int(time.time())
+                    archive_name = str(zip_base / f"photos_{ts}")
+                    shutil.make_archive(archive_name, 'zip', root_dir=str(folder))
+                    archive_file = archive_name + '.zip'
+                    # serve relative URL
+                    rel = os.path.relpath(archive_file, start=folder)
+                    self._send_json({"ok": True, "archive": rel})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # Trigger uploader now by touching a flag file
+            if path == "/api/upload_now":
+                try:
+                    upf = SCRIPTS_DIR / "upload_now.flag"
+                    upf.write_text(str(time.time()))
+                    self._send_json({"ok": True, "upload_now": True})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/delete":
+                name = _safe_name(q.get("name", [""])[0])
+                if not name:
+                    self._send_json({"ok": False, "error": "missing name"}, 400)
+                    return
+                target = (folder / name).resolve()
+
+                # ensure inside folder
+                try:
+                    target.relative_to(folder)
+                except Exception:
+                    self._send_json({"ok": False, "error": "invalid path"}, 400)
+                    return
+
+                if not target.exists():
+                    self._send_json({"ok": False, "error": "not found"}, 404)
+                    return
+
+                try:
+                    target.unlink()
+                    self._send_json({"ok": True, "deleted": name}, 200)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/retake":
+                # Trigger a capture and return result. Optionally accept session_id to associate.
+                session_id = q.get("session_id", [None])[0]
+                result = capture_func()
+                ok = not result.startswith("[ERR]")
+                self._send_json({"ok": ok, "result": result, "session_id": session_id}, 200 if ok else 500)
+                return
+
+            if path == "/api/reupload":
+                # Allow manual reupload: clears uploaded flag in upload DB so the uploader daemon retries
+                name = _safe_name(q.get("name", [""])[0])
+                if not name:
+                    self._send_json({"ok": False, "error": "missing name"}, 400)
+                    return
+                dbp = Path(config.UPLOAD_DB)
+                if dbp.exists():
+                    try:
+                        d = json.loads(dbp.read_text())
+                    except Exception:
+                        d = {}
+                else:
+                    d = {}
+                # clear uploaded marker
+                entry = d.get(name, {})
+                entry["uploaded"] = False
+                d[name] = entry
+                try:
+                    dbp.write_text(json.dumps(d, indent=2))
+                    self._send_json({"ok": True, "requeued": name})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # Replay management endpoints
+            if path == "/api/replays":
+                try:
+                    items = _list_replays()
+                    self._send_json({"ok": True, "replays": [it["name"] for it in items], "items": items})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/replay_record_status":
+                self._send_json({"ok": True, "status": _read_recorder_state()})
+                return
+
+            if path == "/api/replay_test_status":
+                self._send_json({"ok": True, "status": _read_replay_test_state()})
+                return
+
+            if path == "/api/replay_record_start":
+                try:
+                    if _read_mode() != "manual":
+                        self._send_json({"ok": False, "error": "replay recording is allowed only in manual mode"}, 409)
+                        return
+                    name = _normalize_replay_name(q.get("name", [""])[0])
+                    seconds = float(q.get("seconds", ["15"])[0])
+                    if seconds <= 0:
+                        self._send_json({"ok": False, "error": "seconds must be positive"}, 400)
+                        return
+                    cur = _read_recorder_state()
+                    if cur.get("running"):
+                        self._send_json({"ok": False, "error": "recorder already running", "status": cur}, 409)
+                        return
+                    preview_path = _resolve_replay_path(name)
+                    preview_path.parent.mkdir(parents=True, exist_ok=True)
+                    if preview_path.exists():
+                        self._send_json({"ok": False, "error": "replay already exists"}, 409)
+                        return
+                    preview_output = str(preview_path)
+                    _set_recorder_state(
+                        running=True,
+                        ok=False,
+                        error="",
+                        name=name,
+                        seconds=float(seconds),
+                        output=preview_output,
+                        returncode=None,
+                        started_at=time.time(),
+                        finished_at=0.0,
+                        stdout_tail=[],
+                    )
+                    threading.Thread(target=_run_replay_recorder, args=(name, seconds), daemon=True).start()
+                    self._send_json({"ok": True, "status": _read_recorder_state()})
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/test_replay":
+                try:
+                    if _read_mode() != "manual":
+                        self._send_json({"ok": False, "error": "replay test is allowed only in manual mode"}, 409)
+                        return
+                    if replay_test_func is None:
+                        self._send_json({"ok": False, "error": "replay test is unavailable in this runtime"}, 503)
+                        return
+                    name = _normalize_replay_name(q.get("name", [""])[0])
+                    candidate = _resolve_replay_path(name)
+                    if not candidate.exists():
+                        self._send_json({"ok": False, "error": "replay not found"}, 404)
+                        return
+                    cur = _read_replay_test_state()
+                    if cur.get("running"):
+                        self._send_json({"ok": False, "error": "replay test already running", "status": cur}, 409)
+                        return
+                    _set_replay_test_state(
+                        running=True,
+                        ok=False,
+                        error="",
+                        name=name,
+                        result="",
+                        started_at=time.time(),
+                        finished_at=0.0,
+                    )
+                    threading.Thread(target=_run_replay_test, args=(name, replay_test_func), daemon=True).start()
+                    self._send_json({"ok": True, "status": _read_replay_test_state()})
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/delete_replay":
+                try:
+                    name = q.get("name", [""])[0]
+                    candidate = _resolve_replay_path(name)
+                    if not candidate.exists():
+                        self._send_json({"ok": False, "error": "replay not found"}, 404)
+                        return
+                    active_name = _read_active_replay_name()
+                    rel = str(candidate.resolve().relative_to(config.DATA_DIR)).replace("\\", "/")
+                    if rel == active_name:
+                        self._send_json({"ok": False, "error": "cannot delete the active replay"}, 409)
+                        return
+                    if _is_greeting_replay(rel):
+                        self._send_json({"ok": False, "error": "cannot delete the configured AI greeting replay"}, 409)
+                        return
+                    candidate.unlink()
+                    self._send_json({"ok": True, "deleted": rel})
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/rename_replay":
+                try:
+                    old_name = q.get("old", [""])[0]
+                    new_name = q.get("new", [""])[0]
+                    old_candidate = _resolve_replay_path(old_name)
+                    if not old_candidate.exists():
+                        self._send_json({"ok": False, "error": "replay not found"}, 404)
+                        return
+                    old_rel = str(old_candidate.resolve().relative_to(config.DATA_DIR)).replace("\\", "/")
+                    old_parent = Path(old_rel).parent
+                    default_parent = None if str(old_parent) == "." else old_parent.as_posix()
+                    new_rel = _normalize_replay_name(new_name, default_parent=default_parent)
+                    new_candidate = _resolve_replay_path(new_rel)
+                    if new_candidate.exists():
+                        self._send_json({"ok": False, "error": "target replay already exists"}, 409)
+                        return
+                    new_candidate.parent.mkdir(parents=True, exist_ok=True)
+                    old_candidate.rename(new_candidate)
+                    _update_replay_references_after_rename(old_rel, new_rel, new_candidate)
+                    self._send_json({"ok": True, "old": old_rel, "new": new_rel})
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/download_replay":
+                try:
+                    name = q.get("name", [""])[0]
+                    candidate = _resolve_replay_path(name)
+                    if not candidate.exists():
+                        self._send_json({"ok": False, "error": "replay not found"}, 404)
+                        return
+                    data = candidate.read_bytes()
+                    self.send_response(200)
+                    self.send_header("Content-Type", "application/json; charset=utf-8")
+                    self.send_header("Content-Length", str(len(data)))
+                    self.send_header("Content-Disposition", f'attachment; filename="{candidate.name}"')
+                    self.end_headers()
+                    self.wfile.write(data)
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/scripts":
+                try:
+                    scripts_dir = DATA_SCRIPTS_DIR
+                    scripts_dir.mkdir(parents=True, exist_ok=True)
+                    files = [
+                        p.name
+                        for p in sorted(scripts_dir.iterdir())
+                        if p.is_file() and p.suffix.lower() in (".txt", ".json", ".jsonl")
+                    ]
+                    self._send_json({"ok": True, "scripts": files})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/script_content":
+                # return raw text of a script by name (in Scripts/)
+                name = q.get('name', [None])[0]
+                if not name:
+                    self._send_json({"ok": False, "error": "missing name"}, 400)
+                    return
+                try:
+                    scripts_dir = DATA_SCRIPTS_DIR
+                    candidate = (scripts_dir / _safe_name(name)).resolve()
+                    try:
+                        candidate.relative_to(scripts_dir)
+                    except Exception:
+                        self._send_json({"ok": False, "error": "invalid path"}, 400)
+                        return
+                    if not candidate.exists():
+                        self._send_json({"ok": False, "error": "not found"}, 404)
+                        return
+                    txt = candidate.read_text(encoding='utf-8')
+                    self._send_json({"ok": True, "script": txt})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/get_replay":
+                try:
+                    cur = _read_active_replay_name()
+                    self._send_json({"ok": True, "replay": cur})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/sanad_script":
+                try:
+                    txt = _read_text_file(config.SANAD_SCRIPT_FILE) or ""
+                    self._send_json({"ok": True, "script": txt})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_replay":
+                # set via ?name=filename.jsonl
+                name = q.get("name", [""])[0]
+                if not name:
+                    self._send_json({"ok": False, "error": "missing name"}, 400)
+                    return
+                try:
+                    candidate = _resolve_replay_path(name)
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                    return
+                if not candidate.exists():
+                    self._send_json({"ok": False, "error": "replay not found"}, 404)
+                    return
+                integrity = replay_file_integrity(candidate)
+                if not integrity.get("ok"):
+                    self._send_json(
+                        {"ok": False, "error": "invalid replay file", "integrity": integrity},
+                        400,
+                    )
+                    return
+                try:
+                    rel_name = str(candidate.resolve().relative_to(config.DATA_DIR)).replace("\\", "/")
+                    config.write_selected_replay_name(rel_name)
+                    config.REPLAY_FILE = candidate
+                    resp = {"ok": True, "set": rel_name}
+                    if not integrity.get("trigger_ok", False):
+                        resp["warning"] = "replay has no trigger markers; timed capture fallback will be used"
+                        resp["integrity"] = integrity
+                    self._send_json(resp)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # MJPEG preview stream
+            if path == "/preview.mjpg":
+                self.send_response(200)
+                self.send_header("Content-Type", "multipart/x-mixed-replace; boundary=--frame")
+                self.end_headers()
+                try:
+                    while True:
+                        frame = _get_preview_frame()
+                        if frame is None:
+                            time.sleep(0.1)
+                            continue
+                        cv2 = _get_cv2()
+                        ret, jpg = cv2.imencode('.jpg', frame, [int(cv2.IMWRITE_JPEG_QUALITY), 65])
+                        if not ret:
+                            time.sleep(0.05)
+                            continue
+                        data = jpg.tobytes()
+                        self.wfile.write(b"--frame\r\n")
+                        self.wfile.write(b"Content-Type: image/jpeg\r\n")
+                        self.wfile.write(f"Content-Length: {len(data)}\r\n\r\n".encode('utf-8'))
+                        self.wfile.write(data)
+                        self.wfile.write(b"\r\n")
+                        self.wfile.flush()
+                        # small throttle
+                        time.sleep(0.08)
+                except Exception as e:
+                    record_error(
+                        "photo_server",
+                        "preview_stream",
+                        e,
+                        {"client": self.client_address[0] if self.client_address else "unknown"},
+                    )
+                    return
+
+
+            # Gallery page: serve gallery.html (client JS renders cards)
+            if path == "/":
+                tpl = _read_text_file(GALLERY_HTML)
+                if tpl is None:
+                    self.send_response(404)
+                    self.end_headers()
+                    return
+                html = tpl.replace("{{PHOTOS_DIR}}", str(folder))
+                # leave PHOTO_CARDS and MODE_TOGGLE for client-side JS to populate
+                self._send_text(html, 200, "text/html; charset=utf-8")
+                return
+
+            # Otherwise: serve static files from photos/ (download/open)
+            return super().do_GET()
+
+        def do_POST(self):
+            parsed = urllib.parse.urlparse(self.path)
+            path = parsed.path
+            # Only used to update sanad script content currently
+            if path == "/api/sanad_script":
+                try:
+                    length = int(self.headers.get('Content-Length', '0'))
+                    body = self.rfile.read(length) if length else b""
+                    # accept raw text or JSON {"script": "..."}
+                    try:
+                        payload = json.loads(body.decode('utf-8'))
+                        script = payload.get('script', '')
+                    except Exception:
+                        script = body.decode('utf-8')
+                    # write to SANAD_SCRIPT_FILE
+                    try:
+                        config.SANAD_SCRIPT_FILE.write_text(script, encoding='utf-8')
+                        self._send_json({"ok": True, "written": True})
+                    except Exception as e:
+                        self._send_json({"ok": False, "error": str(e)}, 500)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/audio_prompt_record":
+                try:
+                    length = int(self.headers.get("Content-Length", "0"))
+                    body = self.rfile.read(length) if length else b""
+                    payload = json.loads(body.decode("utf-8")) if body else {}
+                    if not isinstance(payload, dict):
+                        self._send_json({"ok": False, "error": "invalid payload"}, 400)
+                        return
+                    key = str(payload.get("key", "") or "").strip()
+                    text = str(payload.get("text", "") or "").strip()
+                    filename = str(payload.get("filename", "") or "").strip()
+                    if not key:
+                        self._send_json({"ok": False, "error": "missing key"}, 400)
+                        return
+                    if not text:
+                        self._send_json({"ok": False, "error": "missing text"}, 400)
+                        return
+                    cur = _read_audio_prompt_record_state()
+                    if cur.get("running"):
+                        self._send_json({"ok": False, "error": "audio prompt recorder already running", "status": cur}, 409)
+                        return
+                    default_filename = audio_prompts.prompt_filename(key)
+                    _set_audio_prompt_record_state(
+                        running=True,
+                        key=key,
+                        filename=filename or default_filename,
+                        text=text,
+                        ok=False,
+                        error="",
+                        started_at=time.time(),
+                        finished_at=0.0,
+                        result={},
+                    )
+                    threading.Thread(
+                        target=_run_audio_prompt_record,
+                        args=(key, text, filename or default_filename),
+                        daemon=True,
+                    ).start()
+                    self._send_json({"ok": True, "status": _read_audio_prompt_record_state()})
+                except (ValueError, KeyError) as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/upload_person":
+                try:
+                    form = cgi.FieldStorage(
+                        fp=self.rfile,
+                        headers=self.headers,
+                        environ={
+                            "REQUEST_METHOD": "POST",
+                            "CONTENT_TYPE": self.headers.get("Content-Type", ""),
+                        },
+                    )
+                    if "file" not in form:
+                        self._send_json({"ok": False, "error": "missing file"}, 400)
+                        return
+                    file_item = form["file"]
+                    if not getattr(file_item, "file", None):
+                        self._send_json({"ok": False, "error": "missing file payload"}, 400)
+                        return
+                    data = file_item.file.read()
+                    if not data:
+                        self._send_json({"ok": False, "error": "empty upload"}, 400)
+                        return
+                    person_id = str(form.getfirst("person_id", "") or "").strip()
+                    filename = str(getattr(file_item, "filename", "") or "")
+                    result = people_registry.import_person_photo(data, filename=filename, person_id=person_id)
+                    ok = bool(result.get("ok", False))
+                    self._send_json(result, 200 if ok else 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/upload_audio_prompt":
+                try:
+                    form = cgi.FieldStorage(
+                        fp=self.rfile,
+                        headers=self.headers,
+                        environ={
+                            "REQUEST_METHOD": "POST",
+                            "CONTENT_TYPE": self.headers.get("Content-Type", ""),
+                        },
+                    )
+                    key = str(form.getfirst("key", "") or "").strip()
+                    if not key:
+                        self._send_json({"ok": False, "error": "missing key"}, 400)
+                        return
+                    if "file" not in form:
+                        self._send_json({"ok": False, "error": "missing file"}, 400)
+                        return
+                    file_item = form["file"]
+                    if not getattr(file_item, "file", None):
+                        self._send_json({"ok": False, "error": "missing file payload"}, 400)
+                        return
+                    data = file_item.file.read()
+                    if not data:
+                        self._send_json({"ok": False, "error": "empty upload"}, 400)
+                        return
+                    filename = str(form.getfirst("filename", "") or getattr(file_item, "filename", "") or "")
+                    result = audio_prompts.save_audio_prompt(key, data, filename)
+                    self._send_json(result, 200 if bool(result.get("ok")) else 400)
+                except (KeyError, ValueError) as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/upload_replay":
+                try:
+                    form = cgi.FieldStorage(
+                        fp=self.rfile,
+                        headers=self.headers,
+                        environ={
+                            "REQUEST_METHOD": "POST",
+                            "CONTENT_TYPE": self.headers.get("Content-Type", ""),
+                        },
+                    )
+                    if "file" not in form:
+                        self._send_json({"ok": False, "error": "missing file"}, 400)
+                        return
+                    file_item = form["file"]
+                    if not getattr(file_item, "file", None):
+                        self._send_json({"ok": False, "error": "missing file payload"}, 400)
+                        return
+                    raw_name = form.getfirst("name", "") or getattr(file_item, "filename", "") or "uploaded_replay.jsonl"
+                    rel_name = _normalize_replay_name(raw_name)
+                    candidate = _resolve_replay_path(rel_name)
+                    if candidate.exists():
+                        self._send_json({"ok": False, "error": "replay already exists"}, 409)
+                        return
+                    candidate.parent.mkdir(parents=True, exist_ok=True)
+                    data = file_item.file.read()
+                    if not data:
+                        self._send_json({"ok": False, "error": "empty upload"}, 400)
+                        return
+                    candidate.write_bytes(data)
+                    integrity = replay_file_integrity(candidate)
+                    if not integrity.get("ok"):
+                        try:
+                            candidate.unlink()
+                        except Exception:
+                            pass
+                        self._send_json({"ok": False, "error": "invalid replay file", "integrity": integrity}, 400)
+                        return
+                    self._send_json({"ok": True, "saved": rel_name, "integrity": integrity})
+                except ValueError as e:
+                    self._send_json({"ok": False, "error": str(e)}, 400)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # Upload / manage SANAD scripts
+            if path == "/api/upload_script":
+                try:
+                    # Accept JSON {"filename": "name.txt", "script": "..."} or raw text with ?filename=...
+                    length = int(self.headers.get('Content-Length', '0'))
+                    body = self.rfile.read(length) if length else b""
+                    try:
+                        payload = json.loads(body.decode('utf-8'))
+                        filename = payload.get('filename')
+                        script = payload.get('script', '')
+                    except Exception:
+                        filename = urllib.parse.parse_qs(parsed.query).get('filename', [None])[0]
+                        script = body.decode('utf-8')
+                    if not filename:
+                        self._send_json({"ok": False, "error": "missing filename"}, 400)
+                        return
+                    scripts_dir = DATA_SCRIPTS_DIR
+                    scripts_dir.mkdir(parents=True, exist_ok=True)
+                    target = (scripts_dir / _safe_name(filename)).resolve()
+                    try:
+                        target.relative_to(scripts_dir)
+                    except Exception:
+                        self._send_json({"ok": False, "error": "invalid filename"}, 400)
+                        return
+                    target.write_text(script, encoding='utf-8')
+                    self._send_json({"ok": True, "saved": target.name})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/delete_script":
+                try:
+                    length = int(self.headers.get('Content-Length', '0'))
+                    body = self.rfile.read(length) if length else b""
+                    try:
+                        payload = json.loads(body.decode('utf-8'))
+                        name = payload.get('name')
+                    except Exception:
+                        # allow raw name in body
+                        name = body.decode('utf-8').strip()
+                    if not name:
+                        self._send_json({"ok": False, "error": "missing name"}, 400)
+                        return
+                    scripts_dir = DATA_SCRIPTS_DIR
+                    target = (scripts_dir / _safe_name(name)).resolve()
+                    try:
+                        target.relative_to(scripts_dir)
+                    except Exception:
+                        self._send_json({"ok": False, "error": "invalid path"}, 400)
+                        return
+                    if not target.exists():
+                        self._send_json({"ok": False, "error": "not found"}, 404)
+                        return
+                    target.unlink()
+                    self._send_json({"ok": True, "deleted": name})
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            if path == "/api/set_sanad_script":
+                # Accept ?name=filename or JSON {"name":"..."}
+                try:
+                    qs = urllib.parse.parse_qs(parsed.query)
+                    name = qs.get('name', [None])[0]
+                    if not name:
+                        length = int(self.headers.get('Content-Length', '0'))
+                        body = self.rfile.read(length) if length else b""
+                        try:
+                            payload = json.loads(body.decode('utf-8'))
+                            name = payload.get('name')
+                        except Exception:
+                            name = None
+                    if not name:
+                        self._send_json({"ok": False, "error": "missing name"}, 400)
+                        return
+                    scripts_dir = DATA_SCRIPTS_DIR
+                    candidate = (scripts_dir / _safe_name(name)).resolve()
+                    try:
+                        candidate.relative_to(scripts_dir)
+                    except Exception:
+                        self._send_json({"ok": False, "error": "invalid script path"}, 400)
+                        return
+                    if not candidate.exists():
+                        self._send_json({"ok": False, "error": "script not found"}, 404)
+                        return
+                    # copy contents into SANAD_SCRIPT_FILE
+                    try:
+                        txt = candidate.read_text(encoding='utf-8')
+                        config.SANAD_SCRIPT_FILE.write_text(txt, encoding='utf-8')
+                        self._send_json({"ok": True, "set": candidate.name})
+                    except Exception as e:
+                        self._send_json({"ok": False, "error": str(e)}, 500)
+                except Exception as e:
+                    self._send_json({"ok": False, "error": str(e)}, 500)
+                return
+
+            # fallback
+            self.send_response(404)
+            self.end_headers()
+
+    try:
+        ThreadingHTTPServer.allow_reuse_address = True
+        httpd = ThreadingHTTPServer((bind, port), Handler)
+    except OSError as e:
+        _log(lg, f"❌ Photo server failed: {e}", "error")
+        # Assume another server already running
+        _log(lg, f"🖼️ Phone gallery (existing): {url}", "info")
+        return url
+
+    def _serve():
+        try:
+            httpd.serve_forever()
+        except Exception:
+            pass
+
+    t = threading.Thread(target=_serve, daemon=True)
+    t.start()
+
+
+    _log(lg, f"🖼️ Photo server serving {folder} on {url}", "info")
+    return url
+
+
+# ============================================================
+# CLI mode (optional)
+# ============================================================
+if __name__ == "__main__":
+    photos = Path(os.environ.get("PHOTOS_DIR", str(DEFAULT_PHOTOS_DIR))).resolve()
+    port = int(os.environ.get("PHOTO_SERVER_PORT", "8080"))
+    start_photo_server(photos, port=port)
+    print("Server running. Press Ctrl+C to stop.")
+    try:
+        while True:
+            time.sleep(3600)
+    except KeyboardInterrupt:
+        pass
diff --git a/Server/uploader.py b/Server/uploader.py
new file mode 100644
index 0000000..1dca172
--- /dev/null
+++ b/Server/uploader.py
@@ -0,0 +1,167 @@
+"""
+uploader.py
+
+Daemon that watches the photos folder for new files and uploads them
+via HTTP POST (default) or S3 (optional, requires boto3). Implements
+retry with exponential backoff and stores upload state in a small JSON DB.
+"""
+import threading
+import time
+import json
+from pathlib import Path
+from typing import Dict
+import requests
+import logging
+try:
+    import boto3
+    _HAS_BOTO3 = True
+except Exception:
+    _HAS_BOTO3 = False
+
+from Core.Logger import Logs
+from Core import settings as config
+
+sanad_logger = Logs()
+sanad_logger.LogEngine("G1_Logs", "uploader")
+
+
+class UploadDaemon:
+    def __init__(self, photos_dir: Path = config.PHOTOS_DIR, poll_s: float = 2.0):
+        self.photos_dir = Path(photos_dir)
+        self.poll_s = float(poll_s)
+        self._stop = threading.Event()
+        self._thread = None
+        self._db_path = Path(config.UPLOAD_DB)
+        self._state = self._load_db()
+
+    def _load_db(self) -> Dict[str, Dict]:
+        try:
+            if self._db_path.exists():
+                return json.loads(self._db_path.read_text())
+        except Exception:
+            pass
+        return {}
+
+    def _save_db(self):
+        try:
+            self._db_path.write_text(json.dumps(self._state, indent=2))
+        except Exception as e:
+            sanad_logger.print_and_log(f"Failed to write upload db: {e}", "warning")
+
+    def start(self):
+        if self._thread and self._thread.is_alive():
+            return
+        self._stop.clear()
+        self._thread = threading.Thread(target=self._run, daemon=True)
+        self._thread.start()
+        sanad_logger.print_and_log("📤 Upload daemon started.", "info")
+
+    def stop(self):
+        self._stop.set()
+        if self._thread:
+            self._thread.join(timeout=1.0)
+
+    def _should_upload(self, path: Path) -> bool:
+        s = self._state.get(str(path), {})
+        return not s.get("uploaded", False)
+
+    def _mark_uploaded(self, path: Path, info: Dict):
+        self._state[str(path)] = {"uploaded": True, "info": info, "ts": time.time()}
+        self._save_db()
+
+    def _upload_http(self, path: Path) -> Dict:
+        url = config.UPLOAD_URL
+        if not url:
+            raise RuntimeError("UPLOAD_URL is not configured")
+        with open(path, "rb") as f:
+            r = requests.post(url, files={"file": f}, timeout=30)
+            r.raise_for_status()
+            return {"status": "ok", "resp": r.text}
+
+    def _upload_s3(self, path: Path) -> Dict:
+        if not _HAS_BOTO3:
+            raise RuntimeError("boto3 not installed; install it to use S3 uploads")
+        bucket = config.UPLOAD_S3_BUCKET
+        if not bucket:
+            raise RuntimeError("UPLOAD_S3_BUCKET not configured")
+
+        # Build client using provided keys or default env/iam
+        kwargs = {}
+        if config.UPLOAD_S3_KEY and config.UPLOAD_S3_SECRET:
+            kwargs["aws_access_key_id"] = config.UPLOAD_S3_KEY
+            kwargs["aws_secret_access_key"] = config.UPLOAD_S3_SECRET
+        if config.UPLOAD_S3_REGION:
+            kwargs["region_name"] = config.UPLOAD_S3_REGION
+
+        s3 = boto3.client("s3", **kwargs)
+        key = path.name
+        try:
+            s3.upload_file(str(path), bucket, key)
+            return {"status": "ok", "bucket": bucket, "key": key}
+        except Exception:
+            raise
+
+    def _run(self):
+        # If upload destination is not configured, keep daemon alive but idle.
+        if config.UPLOAD_METHOD == "http" and not str(config.UPLOAD_URL or "").strip():
+            sanad_logger.print_and_log("📤 Upload daemon idle: UPLOAD_URL is not configured.", "warning")
+            while not self._stop.is_set():
+                time.sleep(max(2.0, self.poll_s))
+            return
+        if config.UPLOAD_METHOD == "s3" and not str(config.UPLOAD_S3_BUCKET or "").strip():
+            sanad_logger.print_and_log("📤 Upload daemon idle: UPLOAD_S3_BUCKET is not configured.", "warning")
+            while not self._stop.is_set():
+                time.sleep(max(2.0, self.poll_s))
+            return
+
+        while not self._stop.is_set():
+            try:
+                for p in sorted(self.photos_dir.glob("**/*")):
+                    if not p.is_file():
+                        continue
+                    if not self._should_upload(p):
+                        continue
+
+                    # Exponential backoff per-file
+                    attempts = 0
+                    backoff = 1.0
+                    success = False
+                    while attempts < 5 and not success and not self._stop.is_set():
+                        try:
+                            sanad_logger.print_and_log(f"Uploading {p} (attempt {attempts+1})", "info")
+                            if config.UPLOAD_METHOD == "http":
+                                info = self._upload_http(p)
+                            elif config.UPLOAD_METHOD == "s3":
+                                info = self._upload_s3(p)
+                            else:
+                                raise NotImplementedError("UPLOAD_METHOD not implemented by daemon")
+                            self._mark_uploaded(p, info)
+                            sanad_logger.print_and_log(f"Uploaded {p}", "info")
+                            success = True
+                        except Exception as e:
+                            attempts += 1
+                            sanad_logger.print_and_log(f"Upload failed ({e}), backoff {backoff}s", "warning")
+                            time.sleep(backoff)
+                            backoff = min(30.0, backoff * 2)
+
+                time.sleep(self.poll_s)
+            except Exception as e:
+                sanad_logger.print_and_log(f"Upload loop error: {e}", "error")
+                time.sleep(5.0)
+
+
+def start_uploader(photos_dir: Path = config.PHOTOS_DIR) -> UploadDaemon:
+    d = UploadDaemon(photos_dir)
+    d.start()
+    return d
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    d = UploadDaemon()
+    d.start()
+    try:
+        while True:
+            time.sleep(1)
+    except KeyboardInterrupt:
+        d.stop()
diff --git a/Web/direct_camera.css b/Web/direct_camera.css
new file mode 100644
index 0000000..d45c41c
--- /dev/null
+++ b/Web/direct_camera.css
@@ -0,0 +1,162 @@
+:root {
+  --bg: #eef2e9;
+  --panel: #f9fbf6;
+  --ink: #162015;
+  --muted: #5f6f5f;
+  --accent: #205f4a;
+  --line: #c9d4c4;
+  --danger: #8a2d24;
+}
+
+* {
+  box-sizing: border-box;
+}
+
+body {
+  margin: 0;
+  font-family: Georgia, "Times New Roman", serif;
+  background: linear-gradient(180deg, #f4f1e7 0%, var(--bg) 100%);
+  color: var(--ink);
+}
+
+.wrap {
+  max-width: 1280px;
+  margin: 0 auto;
+  padding: 24px;
+}
+
+.top {
+  display: grid;
+  grid-template-columns: 1.1fr 0.9fr;
+  gap: 24px;
+  align-items: start;
+}
+
+.panel {
+  background: rgba(249, 251, 246, 0.94);
+  border: 1px solid var(--line);
+  border-radius: 18px;
+  padding: 18px;
+  box-shadow: 0 12px 30px rgba(22, 32, 21, 0.08);
+}
+
+.panel-space {
+  margin-top: 24px;
+}
+
+h1,
+h2 {
+  margin: 0 0 12px;
+}
+
+.actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+  margin: 12px 0 0;
+}
+
+button,
+.btn {
+  appearance: none;
+  border: 1px solid var(--accent);
+  background: var(--accent);
+  color: white;
+  padding: 10px 14px;
+  border-radius: 999px;
+  cursor: pointer;
+  font: inherit;
+  text-decoration: none;
+  display: inline-block;
+}
+
+button.secondary,
+.btn.secondary {
+  background: white;
+  color: var(--accent);
+}
+
+button.danger,
+.btn.danger {
+  background: white;
+  color: var(--danger);
+  border-color: var(--danger);
+}
+
+select,
+input[type="number"] {
+  appearance: none;
+  border: 1px solid var(--line);
+  background: white;
+  color: var(--ink);
+  padding: 10px 12px;
+  border-radius: 999px;
+  font: inherit;
+  min-width: 100px;
+}
+
+.meta {
+  color: var(--muted);
+  margin: 6px 0;
+}
+
+.preview {
+  width: 100%;
+  aspect-ratio: 4 / 3;
+  object-fit: cover;
+  border-radius: 14px;
+  background: #dbe3d6;
+  border: 1px solid var(--line);
+}
+
+.status {
+  margin-top: 12px;
+  padding: 10px 12px;
+  border-radius: 12px;
+  background: #edf5eb;
+  border: 1px solid var(--line);
+  color: var(--muted);
+  white-space: pre-wrap;
+}
+
+.grid {
+  display: grid;
+  grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));
+  gap: 18px;
+  margin-top: 20px;
+}
+
+.card {
+  background: rgba(255, 255, 255, 0.78);
+  border: 1px solid var(--line);
+  border-radius: 16px;
+  padding: 12px;
+}
+
+.thumb {
+  width: 100%;
+  aspect-ratio: 4 / 3;
+  object-fit: cover;
+  border-radius: 12px;
+  border: 1px solid var(--line);
+  background: #dde6d9;
+}
+
+.name {
+  margin-top: 10px;
+  font-weight: 700;
+  overflow-wrap: anywhere;
+}
+
+.row {
+  display: flex;
+  gap: 8px;
+  flex-wrap: wrap;
+  margin-top: 10px;
+}
+
+@media (max-width: 900px) {
+  .top {
+    grid-template-columns: 1fr;
+  }
+}
diff --git a/Web/direct_camera.html b/Web/direct_camera.html
new file mode 100644
index 0000000..b030957
--- /dev/null
+++ b/Web/direct_camera.html
@@ -0,0 +1,56 @@
+<!doctype html>
+<html lang="en">
+<head>
+  <meta charset="utf-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <title>Direct Camera Service</title>
+  <link rel="stylesheet" href="/static/direct_camera.css">
+</head>
+<body>
+  <div class="wrap">
+    <div class="top">
+      <section class="panel">
+        <h1>Direct Camera Service</h1>
+        <div class="meta">Main camera service. No teleimager. Direct RealSense/OpenCV camera access only.</div>
+        <img id="preview_img" class="preview" src="/preview.mjpg" alt="preview">
+        <div class="actions">
+          <button id="capture_btn">Capture</button>
+          <button id="refresh_btn" class="secondary">Refresh</button>
+          <a class="btn secondary" href="/api/download_all.zip">Download All</a>
+        </div>
+        <div id="status" class="status">Loading...</div>
+      </section>
+
+      <section class="panel">
+        <h2>Camera</h2>
+        <div class="meta">Sample captures are saved in <code>photos/samples/</code>.</div>
+        <div class="actions">
+          <select id="resolution_select">
+            <option value="">Preset</option>
+            <option value="640x480@30">640x480 @ 30</option>
+            <option value="640x480@15">640x480 @ 15</option>
+            <option value="848x480@30">848x480 @ 30</option>
+            <option value="848x480@15">848x480 @ 15</option>
+            <option value="960x540@15">960x540 @ 15</option>
+            <option value="1280x720@30">1280x720 @ 30</option>
+            <option value="1280x720@15">1280x720 @ 15</option>
+          </select>
+          <input id="width_input" type="number" min="1" step="1" placeholder="width">
+          <input id="height_input" type="number" min="1" step="1" placeholder="height">
+          <input id="fps_input" type="number" min="1" step="1" placeholder="fps">
+          <button id="apply_resolution_btn" class="secondary">Apply Resolution</button>
+        </div>
+        <div class="meta">Choose a preset or enter width, height, and fps manually. The stream will reopen with the new settings.</div>
+        <div id="camera_status" class="status">Checking camera...</div>
+      </section>
+    </div>
+
+    <section class="panel panel-space">
+      <h2>Samples</h2>
+      <div id="gallery" class="grid"></div>
+    </section>
+  </div>
+
+  <script src="/static/direct_camera.js"></script>
+</body>
+</html>
diff --git a/Web/direct_camera.js b/Web/direct_camera.js
new file mode 100644
index 0000000..c00f4a8
--- /dev/null
+++ b/Web/direct_camera.js
@@ -0,0 +1,127 @@
+(function () {
+  function restartPreview() {
+    const img = document.getElementById("preview_img");
+    if (!img) {
+      return;
+    }
+    img.src = `/preview.mjpg?t=${Date.now()}`;
+  }
+
+  function setResolutionInputs(width, height, fps) {
+    document.getElementById("width_input").value = String(width || "");
+    document.getElementById("height_input").value = String(height || "");
+    document.getElementById("fps_input").value = String(fps || "");
+    const preset = `${width}x${height}@${fps}`;
+    const sel = document.getElementById("resolution_select");
+    const hasPreset = Array.from(sel.options).some((opt) => opt.value === preset);
+    sel.value = hasPreset ? preset : "";
+  }
+
+  async function api(path) {
+    const response = await fetch(path);
+    if (!response.ok) {
+      throw new Error(await response.text());
+    }
+    return response.json();
+  }
+
+  function fmtBytes(n) {
+    if (n < 1024) {
+      return `${n} B`;
+    }
+    if (n < 1024 * 1024) {
+      return `${(n / 1024).toFixed(1)} KB`;
+    }
+    return `${(n / (1024 * 1024)).toFixed(1)} MB`;
+  }
+
+  async function refreshAll() {
+    const [health, photos] = await Promise.all([api("/api/health"), api("/api/photos")]);
+    const camera = health.camera || {};
+    const widthInput = document.getElementById("width_input");
+    if (widthInput.dataset.initialized !== "1") {
+      setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps);
+      widthInput.dataset.initialized = "1";
+    }
+
+    document.getElementById("status").textContent = camera.ok
+      ? `Camera OK\nSource: ${camera.source}\nBackend: ${camera.backend}\nActive: ${camera.profile || "-"}\nRequested: ${camera.requested_profile}\nPreferred RS Serial: ${camera.preferred_realsense_serial || "-"}\nConfig RS Serial: ${camera.config_realsense_serial || "-"}\nFallback RS Serial: ${camera.configured_realsense_serial || "-"}\nActive RS Serial: ${camera.realsense_serial || "-"}\nSamples: ${photos.items.length}`
+      : `Camera not ready\nSource: ${camera.source}\nRequested: ${camera.requested_profile}\nPreferred RS Serial: ${camera.preferred_realsense_serial || "-"}\nConfig RS Serial: ${camera.config_realsense_serial || "-"}\nFallback RS Serial: ${camera.configured_realsense_serial || "-"}\nActive RS Serial: ${camera.realsense_serial || "-"}\nError: ${camera.last_error || "-"}`;
+
+    document.getElementById("camera_status").textContent = JSON.stringify(health, null, 2);
+
+    const gallery = document.getElementById("gallery");
+    gallery.innerHTML = "";
+    for (const item of photos.items) {
+      const card = document.createElement("article");
+      card.className = "card";
+      card.innerHTML = `
+        <img class="thumb" src="/samples/${encodeURIComponent(item.name)}?t=${Date.now()}" alt="">
+        <div class="name">${item.name}</div>
+        <div class="meta">${fmtBytes(item.size)}</div>
+        <div class="row">
+          <a class="btn secondary" href="/api/download?name=${encodeURIComponent(item.name)}">Download</a>
+          <button class="danger" data-name="${item.name}">Delete</button>
+        </div>
+      `;
+      gallery.appendChild(card);
+    }
+
+    gallery.querySelectorAll("button.danger").forEach((btn) => {
+      btn.addEventListener("click", async () => {
+        const { name } = btn.dataset;
+        await api(`/api/delete?name=${encodeURIComponent(name)}`);
+        await refreshAll();
+      });
+    });
+  }
+
+  document.getElementById("capture_btn").addEventListener("click", async () => {
+    const status = document.getElementById("status");
+    status.textContent = "Capturing...";
+    try {
+      const resp = await api("/api/capture");
+      status.textContent = `Saved: ${resp.name}`;
+      await refreshAll();
+    } catch (e) {
+      status.textContent = `Capture failed\n${e.message}`;
+    }
+  });
+
+  document.getElementById("resolution_select").addEventListener("change", (e) => {
+    const value = e.target.value;
+    const match = value.match(/^(\d+)x(\d+)@(\d+)$/);
+    if (!match) {
+      return;
+    }
+    setResolutionInputs(Number(match[1]), Number(match[2]), Number(match[3]));
+  });
+
+  document.getElementById("apply_resolution_btn").addEventListener("click", async () => {
+    const width = Number(document.getElementById("width_input").value);
+    const height = Number(document.getElementById("height_input").value);
+    const fps = Number(document.getElementById("fps_input").value);
+    const status = document.getElementById("status");
+    status.textContent = `Applying resolution ${width}x${height}@${fps}...`;
+    try {
+      const resp = await api(
+        `/api/set_resolution?width=${encodeURIComponent(width)}&height=${encodeURIComponent(height)}&fps=${encodeURIComponent(fps)}`
+      );
+      const camera = resp.camera || {};
+      setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps);
+      restartPreview();
+      await refreshAll();
+    } catch (e) {
+      status.textContent = `Resolution change failed\n${e.message}`;
+    }
+  });
+
+  document.getElementById("refresh_btn").addEventListener("click", refreshAll);
+
+  refreshAll().catch((e) => {
+    document.getElementById("status").textContent = String(e);
+  });
+  setInterval(() => {
+    refreshAll().catch(() => {});
+  }, 10000);
+})();
diff --git a/Web/gallery.html b/Web/gallery.html
new file mode 100644
index 0000000..de03f8d
--- /dev/null
+++ b/Web/gallery.html
@@ -0,0 +1,98 @@
+<!doctype html>
+<html>
+<head>
+  <meta charset="utf-8"/>
+  <meta name="viewport" content="width=device-width, initial-scale=1"/>
+  <title>Pixibot Photo Console</title>
+  <link rel="stylesheet" href="/static/style.css">
+</head>
+<body>
+  <div class="page-shell">
+    <header class="topbar">
+      <div class="brand-block">
+        <div class="brand-mark">SP</div>
+        <div>
+          <div class="eyebrow">AI Photographer</div>
+          <div class="title">Pixibot Photo Console</div>
+        </div>
+      </div>
+      <div class="top-actions">
+        <button id="top_status" class="btn ghost">Status</button>
+        <button id="top_capture" class="btn primary">Capture</button>
+        <button id="top_test" class="btn ghost">Camera Test</button>
+        <button id="top_fix" class="btn ghost danger">Fix Camera</button>
+      </div>
+    </header>
+
+    <section class="meta-strip">
+      <div class="meta-pill">Photos folder: <code>{{PHOTOS_DIR}}</code></div>
+      <div class="meta-pill">Dashboard and camera controls stay live across mode switches.</div>
+    </section>
+
+    <main class="dashboard-layout">
+      <section class="dashboard-main">
+        <div id="controls"></div>
+      </section>
+
+      <aside class="dashboard-side">
+        <section class="panel gallery-panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Gallery</div>
+              <h2>Recent Photos</h2>
+            </div>
+          </div>
+          <div id="list" class="cards-grid">{{PHOTO_CARDS}}</div>
+        </section>
+
+        <section class="panel people-panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Recognition</div>
+              <h2>People Registry</h2>
+            </div>
+          </div>
+          <div class="action-row">
+            <button id="people_upload_btn" class="btn ghost">Upload Face Photo</button>
+            <button id="people_reset_btn" class="btn ghost danger">Reset Registry</button>
+            <input id="people_upload_file" type="file" accept="image/*" style="display:none;">
+          </div>
+          <div id="people_status_box" class="status-box">People registry loading...</div>
+          <div id="people_list" class="people-grid"></div>
+        </section>
+      </aside>
+    </main>
+  </div>
+
+  <div id="preview_modal" class="modal" style="display:none">
+    <div class="modal-content">
+      <button id="modal_close" class="modal-close">✕</button>
+      <img id="modal_img" src="" alt="photo preview" />
+      <div id="modal_actions" class="modal-actions"></div>
+    </div>
+  </div>
+
+  <div id="scripts_modal" class="modal" style="display:none">
+    <div class="modal-content modal-wide">
+      <button id="scripts_modal_close" class="modal-close">✕</button>
+      <h3>Manage Pixibot Scripts</h3>
+      <div id="scripts_list"></div>
+      <hr/>
+      <div>
+        <label>Upload new script (filename):</label>
+        <input id="script_filename" placeholder="my_script.txt" style="width:40%" />
+        <button id="script_upload" class="btn ghost">Upload</button>
+      </div>
+      <div style="margin-top:8px;">
+        <label>Edit active Pixibot script:</label>
+        <textarea id="script_editor" class="script-editor"></textarea>
+        <div style="text-align:right;margin-top:6px;">
+          <button id="script_save" class="btn primary">Save active script</button>
+        </div>
+      </div>
+    </div>
+  </div>
+
+  <script src="/static/gallery.js"></script>
+</body>
+</html>
diff --git a/Web/gallery.js b/Web/gallery.js
new file mode 100644
index 0000000..02edac8
--- /dev/null
+++ b/Web/gallery.js
@@ -0,0 +1,1654 @@
+window.__previewEnabled = false;
+window.__dashboardPoll = null;
+window.__cameraSourcesCache = null;
+window.__runtimeMode = "manual";
+window.__peoplePollCounter = 0;
+window.__audioPromptLibrary = [];
+
+const RESOLUTION_PRESETS = [
+  [1920, 1080, 30],
+  [1920, 1080, 15],
+  [1280, 720, 30],
+  [1280, 720, 15],
+  [960, 540, 30],
+  [960, 540, 15],
+  [848, 480, 60],
+  [848, 480, 30],
+  [640, 480, 60],
+  [640, 480, 30],
+  [640, 480, 15],
+  [424, 240, 60],
+  [424, 240, 30],
+];
+
+async function apiGet(path) {
+  const response = await fetch(path);
+  const raw = await response.text();
+  let data = null;
+  try {
+    data = raw ? JSON.parse(raw) : null;
+  } catch (_e) {
+    if (!response.ok) {
+      throw new Error(raw || `HTTP ${response.status}`);
+    }
+    return raw;
+  }
+  if (!response.ok) {
+    throw new Error((data && (data.error || data.result)) || raw || `HTTP ${response.status}`);
+  }
+  return data;
+}
+
+async function apiPostFormData(path, formData) {
+  const response = await fetch(path, { method: "POST", body: formData });
+  const raw = await response.text();
+  let data = null;
+  try {
+    data = raw ? JSON.parse(raw) : null;
+  } catch (_e) {
+    if (!response.ok) {
+      throw new Error(raw || `HTTP ${response.status}`);
+    }
+    return raw;
+  }
+  if (!response.ok) {
+    throw new Error((data && (data.error || data.result)) || raw || `HTTP ${response.status}`);
+  }
+  return data;
+}
+
+async function apiPostJson(path, payload) {
+  const response = await fetch(path, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload || {}),
+  });
+  const raw = await response.text();
+  let data = null;
+  try {
+    data = raw ? JSON.parse(raw) : null;
+  } catch (_e) {
+    if (!response.ok) {
+      throw new Error(raw || `HTTP ${response.status}`);
+    }
+    return raw;
+  }
+  if (!response.ok) {
+    throw new Error((data && (data.error || data.result)) || raw || `HTTP ${response.status}`);
+  }
+  return data;
+}
+
+function el(tag, cls, html) {
+  const node = document.createElement(tag);
+  if (cls) node.className = cls;
+  if (html !== undefined) node.innerHTML = html;
+  return node;
+}
+
+function escapeHtml(text) {
+  return String(text || "")
+    .replace(/&/g, "&amp;")
+    .replace(/</g, "&lt;")
+    .replace(/>/g, "&gt;")
+    .replace(/"/g, "&quot;")
+    .replace(/'/g, "&#39;");
+}
+
+function formatSize(n) {
+  if (n < 1024) return `${n} B`;
+  if (n < 1024 * 1024) return `${(n / 1024).toFixed(1)} KB`;
+  return `${(n / (1024 * 1024)).toFixed(1)} MB`;
+}
+
+function fmtNum(v, digits = 2) {
+  const n = Number(v);
+  if (Number.isNaN(n)) return "-";
+  return n.toFixed(digits);
+}
+
+function formatTime(ts) {
+  const n = Number(ts);
+  if (!Number.isFinite(n) || n <= 0) return "-";
+  try {
+    return new Date(n * 1000).toLocaleString();
+  } catch (_e) {
+    return "-";
+  }
+}
+
+function cameraStatusLines(camera) {
+  return [
+    `Camera OK`,
+    `Source: ${camera.source || "-"}`,
+    `Backend: ${camera.backend || "-"}`,
+    `Active: ${camera.profile || "-"}`,
+    `Requested: ${camera.requested_profile || "-"}`,
+    `Preferred RS Serial: ${camera.preferred_realsense_serial || "-"}`,
+    `Active RS Serial: ${camera.realsense_serial || "-"}`,
+  ].join("\n");
+}
+
+function setPreviewEnabled(enabled) {
+  window.__previewEnabled = !!enabled;
+  const btn = document.getElementById("toggle_preview");
+  const img = document.getElementById("live_preview");
+  const placeholder = document.getElementById("preview_placeholder");
+  const hint = document.getElementById("preview_hint");
+  if (btn) btn.textContent = window.__previewEnabled ? "Hide Live Camera" : "Show Live Camera";
+  if (!img) return;
+  if (window.__previewEnabled) {
+    img.style.display = "block";
+    img.src = `/preview.mjpg?t=${Date.now()}`;
+    if (placeholder) placeholder.style.display = "none";
+    if (hint) hint.textContent = "Live preview is running through the shared direct camera service.";
+  } else {
+    img.removeAttribute("src");
+    img.src = "";
+    img.style.display = "none";
+    if (placeholder) placeholder.style.display = "grid";
+    if (hint) hint.textContent = "Live preview is off. Turn it on only when needed.";
+  }
+}
+
+function restartPreview() {
+  if (!window.__previewEnabled) return;
+  const img = document.getElementById("live_preview");
+  if (!img) return;
+  img.src = `/preview.mjpg?t=${Date.now()}`;
+}
+
+function setResolutionInputs(width, height, fps) {
+  const widthInput = document.getElementById("width_input");
+  const heightInput = document.getElementById("height_input");
+  const fpsInput = document.getElementById("fps_input");
+  const presetSelect = document.getElementById("resolution_select");
+  if (widthInput) widthInput.value = String(width || "");
+  if (heightInput) heightInput.value = String(height || "");
+  if (fpsInput) fpsInput.value = String(fps || "");
+  if (presetSelect) {
+    const preset = `${width}x${height}@${fps}`;
+    const hasPreset = Array.from(presetSelect.options).some((opt) => opt.value === preset);
+    presetSelect.value = hasPreset ? preset : "";
+  }
+}
+
+function renderResolutionOptions() {
+  return [
+    '<option value="">Preset</option>',
+    ...RESOLUTION_PRESETS.map(([w, h, fps]) => `<option value="${w}x${h}@${fps}">${w}x${h} @ ${fps}</option>`),
+  ].join("");
+}
+
+function renderSourceOptions(cameraSources) {
+  const options = (cameraSources && cameraSources.options) || [];
+  if (!options.length) {
+    return '<option value="realsense">Preferred RealSense (default)</option>';
+  }
+  return options
+    .map((item) => `<option value="${escapeHtml(item.value)}">${escapeHtml(item.label || item.value)}</option>`)
+    .join("");
+}
+
+function renderCameraInventory(cameraSources, camera) {
+  const lines = [];
+  const preferred = String((cameraSources && cameraSources.preferred_realsense_serial) || (camera && camera.preferred_realsense_serial) || "").trim();
+  const active = String((camera && camera.realsense_serial) || "").trim();
+  const activeSource = String((camera && camera.source) || "").trim();
+
+  if (preferred) {
+    lines.push(`Preferred RealSense: ${preferred}`);
+  }
+  if (active) {
+    lines.push(`Active RealSense: ${active}`);
+  }
+
+  const rsDevices = (cameraSources && cameraSources.realsense_devices) || [];
+  if (rsDevices.length) {
+    lines.push("RealSense devices:");
+    for (const item of rsDevices) {
+      const serial = String(item.serial || "").trim() || "-";
+      const name = String(item.name || "Intel RealSense").trim();
+      const tags = [];
+      if (item.is_preferred) tags.push("default");
+      if (item.is_active) tags.push("live");
+      lines.push(`- ${name} [${serial}]${tags.length ? ` (${tags.join(", ")})` : ""}`);
+    }
+  }
+
+  const videoDevices = (cameraSources && cameraSources.video_devices) || [];
+  if (videoDevices.length) {
+    lines.push("Video nodes:");
+    for (const item of videoDevices) {
+      const name = String(item.name || "").trim();
+      const label = String(item.value || item.label || "").trim();
+      const suffix = label === activeSource ? " (live)" : "";
+      lines.push(`- ${label}${name ? ` :: ${name}` : ""}${suffix}`);
+    }
+  }
+
+  return lines.join("\n") || "No camera inventory available.";
+}
+
+function personImageUrl(personId, kind) {
+  return `/api/person_image?id=${encodeURIComponent(personId)}&kind=${encodeURIComponent(kind)}&t=${Date.now()}`;
+}
+
+function renderPeopleCards(items) {
+  if (!items.length) {
+    return '<div class="status-box"><i>No people enrolled yet.</i></div>';
+  }
+  return items.map((person) => {
+    const personId = String(person.person_id || "");
+    const title = escapeHtml(person.display_name || person.short_id || personId || "guest");
+    const meta = [
+      `ID: ${escapeHtml(person.short_id || personId || "-")}`,
+      `Created: ${escapeHtml(person.created_date || "-")}`,
+      `Seen: ${person.times_seen ?? 0}`,
+      `Samples: ${person.sample_count ?? 0}`,
+      `Last Seen: ${escapeHtml(formatTime(person.last_seen_at || 0))}`,
+    ].join("\n");
+    return `
+      <article class="person-card">
+        <div class="person-card-head">
+          <img src="${personImageUrl(personId, "face")}" alt="${title} face">
+          <img src="${personImageUrl(personId, "scene")}" alt="${title} scene">
+        </div>
+        <div class="person-card-body">
+          <div class="person-title">${title}</div>
+          <div class="person-meta">${meta}</div>
+          <div class="person-actions">
+            <a class="btn ghost" href="/api/download_person?id=${encodeURIComponent(personId)}">Download</a>
+            <button class="btn ghost person-add-photo" data-id="${escapeHtml(personId)}">Add Photo</button>
+            <button class="btn ghost danger person-delete" data-id="${escapeHtml(personId)}">Delete</button>
+          </div>
+        </div>
+      </article>
+    `;
+  }).join("");
+}
+
+function selectedCameraSerial(source, cameraSources, camera) {
+  const src = String(source || "").trim();
+  if (src.startsWith("realsense:")) {
+    return src.split(":", 2)[1] || "";
+  }
+  if (src === "realsense") {
+    return String((camera && camera.realsense_serial) || (cameraSources && cameraSources.preferred_realsense_serial) || "").trim();
+  }
+  const devices = (cameraSources && cameraSources.realsense_devices) || [];
+  const exact = devices.find((item) => item.value === src);
+  return String((exact && exact.serial) || "").trim();
+}
+
+function formatPromptKeyLabel(key) {
+  return String(key || "")
+    .split("_")
+    .filter(Boolean)
+    .map((part) => part.charAt(0).toUpperCase() + part.slice(1))
+    .join(" ");
+}
+
+function promptFilenameForKey(key) {
+  const item = (window.__audioPromptLibrary || []).find((entry) => entry.key === key);
+  return item ? String(item.filename || `${key}.wav`) : `${key}.wav`;
+}
+
+function promptTextForKey(key) {
+  const item = (window.__audioPromptLibrary || []).find((entry) => entry.key === key);
+  return item ? String(item.text || "") : "";
+}
+
+function populateAudioPromptRecorder(prompts) {
+  window.__audioPromptLibrary = Array.isArray(prompts) ? prompts.slice() : [];
+  const keySelect = document.getElementById("audio_prompt_record_key");
+  const filenameInput = document.getElementById("audio_prompt_record_filename");
+  const textArea = document.getElementById("audio_prompt_record_text");
+  if (!keySelect || !filenameInput || !textArea) return;
+
+  const previousKey = keySelect.value;
+  keySelect.innerHTML = (window.__audioPromptLibrary || [])
+    .map((item) => `<option value="${escapeHtml(item.key)}">${escapeHtml(formatPromptKeyLabel(item.key))}</option>`)
+    .join("");
+  if (previousKey && (window.__audioPromptLibrary || []).some((item) => item.key === previousKey)) {
+    keySelect.value = previousKey;
+  }
+  const activeKey = keySelect.value || ((window.__audioPromptLibrary[0] && window.__audioPromptLibrary[0].key) || "");
+  if (activeKey) {
+    keySelect.value = activeKey;
+    if (!filenameInput.value || filenameInput.dataset.autofill !== "0") {
+      filenameInput.value = promptFilenameForKey(activeKey);
+      filenameInput.dataset.autofill = "1";
+    }
+    if (!textArea.value || textArea.dataset.autofill !== "0") {
+      textArea.value = promptTextForKey(activeKey);
+      textArea.dataset.autofill = "1";
+    }
+  }
+}
+
+async function refreshAudioPromptRecordStatus() {
+  const status = document.getElementById("audio_prompt_record_status_box");
+  if (!status) return;
+  try {
+    const res = await apiGet("/api/audio_prompt_record_status");
+    const s = res.status || {};
+    if (s.running) {
+      status.textContent = [
+        `Recording prompt: ${s.key || "-"}`,
+        `Filename: ${s.filename || "-"}`,
+        `Started: ${formatTime(s.started_at || 0)}`,
+        "Status: generating Gemini audio and recording speaker output...",
+      ].join("\n");
+      return;
+    }
+    if (s.finished_at) {
+      if (s.ok) {
+        const result = s.result || {};
+        status.textContent = [
+          `Recorded prompt: ${result.key || s.key || "-"}`,
+          `Saved speaker file: ${result.filename || s.filename || "-"}`,
+          `Saved raw file: ${result.raw_filename || "-"}`,
+          `Finished: ${formatTime(s.finished_at || 0)}`,
+        ].join("\n");
+      } else {
+        status.textContent = [
+          `Prompt recording failed for ${s.key || "-"}`,
+          `Finished: ${formatTime(s.finished_at || 0)}`,
+          `${s.error || "Unknown error"}`,
+        ].join("\n");
+      }
+      return;
+    }
+    status.textContent = "Prompt recorder idle.";
+  } catch (e) {
+    status.textContent = `Prompt recorder unavailable\n${e.message}`;
+  }
+}
+
+function renderAudioPromptCards(items) {
+  if (!items.length) {
+    return '<div class="status-box"><i>No audio prompt keys available.</i></div>';
+  }
+  return items.map((item) => {
+    const exists = !!item.exists;
+    const key = String(item.key || "");
+    const filename = String(item.filename || "");
+    return `
+      <article class="audio-prompt-card ${exists ? "ready" : "missing"}">
+        <div class="audio-prompt-head">
+          <div>
+            <div class="audio-prompt-title">${escapeHtml(formatPromptKeyLabel(key))}</div>
+            <div class="audio-prompt-key">${escapeHtml(key)}</div>
+          </div>
+          <div class="replay-tags">
+            <span class="replay-tag ${exists ? "active" : "warn"}">${exists ? "uploaded" : "missing"}</span>
+          </div>
+        </div>
+        <div class="audio-prompt-text">${escapeHtml(item.text || "")}</div>
+        <div class="audio-prompt-meta">
+          File: ${escapeHtml(filename || "-")}<br>
+          Size: ${formatSize(item.size || 0)}<br>
+          Raw: ${item.raw_exists ? escapeHtml(item.raw_filename || "-") : "missing"}<br>
+          Updated: ${formatTime(item.mtime || 0)}
+        </div>
+        <div class="audio-prompt-actions">
+          <button class="btn ghost audio-prompt-upload" data-key="${escapeHtml(key)}" data-filename="${escapeHtml(filename)}">${exists ? "Replace" : "Upload"}</button>
+          <button class="btn ghost audio-prompt-record" data-key="${escapeHtml(key)}">Record</button>
+          ${exists ? `<a class="btn ghost" href="/api/download_audio_prompt?key=${encodeURIComponent(key)}">Download</a>` : ""}
+          <button class="btn ghost danger audio-prompt-delete" data-key="${escapeHtml(key)}" ${exists ? "" : "disabled"}>Delete</button>
+        </div>
+      </article>
+    `;
+  }).join("");
+}
+
+async function refreshAudioPromptPanel() {
+  const list = document.getElementById("audio_prompt_list");
+  const status = document.getElementById("audio_prompt_status_box");
+  const modeToggle = document.getElementById("audio_prompt_mode_toggle");
+  const toggle = document.getElementById("audio_prompt_fallback_toggle");
+  const fileInput = document.getElementById("audio_prompt_upload_file");
+  if (!list || !status || !toggle || !fileInput || !modeToggle) return;
+  try {
+    const res = await apiGet("/api/audio_prompts");
+    const prompts = res.prompts || [];
+    const promptMode = String(res.mode || "audio").trim().toLowerCase() === "gemini" ? "gemini" : "audio";
+    const fallbackToGemini = !!res.fallback_to_gemini;
+    const available = prompts.filter((item) => item.exists).length;
+    modeToggle.dataset.mode = promptMode;
+    modeToggle.textContent = promptMode === "gemini" ? "Situation Speech: GEMINI" : "Situation Speech: AUDIO";
+    toggle.dataset.enabled = fallbackToGemini ? "1" : "0";
+    toggle.textContent = fallbackToGemini ? "Gemini Fallback: ON" : "Gemini Fallback: OFF";
+    populateAudioPromptRecorder(prompts);
+    status.textContent = [
+      `Prompt folder: ${res.dir || "AI_Photographer/Data/Audio"}`,
+      `Available clips: ${available} / ${prompts.length}`,
+      `Fixed AI situation speech: ${promptMode.toUpperCase()}`,
+      `Missing-clip Gemini fallback: ${fallbackToGemini ? "ON" : "OFF"}`,
+      promptMode === "audio"
+        ? "Recorded audio is the default for AI situations such as greeting on detection, photo request, countdown, refusal, retake, and thank-you. After those fixed prompts finish, normal Gemini conversation continues."
+        : "Gemini is currently speaking the fixed AI situation prompts directly. General Gemini conversation remains available before and after the photo flow."
+    ].join("\n");
+    list.innerHTML = renderAudioPromptCards(prompts);
+
+    list.querySelectorAll(".audio-prompt-upload").forEach((btn) => {
+      btn.addEventListener("click", () => {
+        fileInput.dataset.key = btn.dataset.key || "";
+        fileInput.dataset.filename = btn.dataset.filename || "";
+        fileInput.click();
+      });
+    });
+    list.querySelectorAll(".audio-prompt-record").forEach((btn) => {
+      btn.addEventListener("click", () => {
+        const key = btn.dataset.key || "";
+        const keySelect = document.getElementById("audio_prompt_record_key");
+        const filenameInput = document.getElementById("audio_prompt_record_filename");
+        const textArea = document.getElementById("audio_prompt_record_text");
+        if (keySelect) keySelect.value = key;
+        if (filenameInput) {
+          filenameInput.value = promptFilenameForKey(key);
+          filenameInput.dataset.autofill = "1";
+        }
+        if (textArea) {
+          textArea.value = promptTextForKey(key);
+          textArea.dataset.autofill = "1";
+          textArea.focus();
+        }
+      });
+    });
+    list.querySelectorAll(".audio-prompt-delete").forEach((btn) => {
+      btn.addEventListener("click", async () => {
+        const key = btn.dataset.key || "";
+        if (!key) return;
+        if (!confirm(`Delete audio prompt clip for ${key}?`)) return;
+        await apiGet(`/api/delete_audio_prompt?key=${encodeURIComponent(key)}`);
+        await refreshAudioPromptPanel();
+        await refreshAudioPromptRecordStatus();
+      });
+    });
+  } catch (e) {
+    status.textContent = `Audio prompt library unavailable\n${e.message}`;
+    list.innerHTML = "";
+    toggle.textContent = "Gemini Fallback";
+    delete toggle.dataset.enabled;
+  }
+}
+
+function bindTopActions() {
+  const topStatus = document.getElementById("top_status");
+  const topCapture = document.getElementById("top_capture");
+  const topTest = document.getElementById("top_test");
+  const topFix = document.getElementById("top_fix");
+
+  if (topStatus) {
+    topStatus.onclick = () => window.open("/api/status", "_blank", "noopener");
+  }
+  if (topCapture) {
+    topCapture.onclick = async () => {
+      try {
+        const res = await apiGet("/api/capture");
+        alert(`Captured:\n${res.result || res.path || "OK"}`);
+        await renderPhotos();
+      } catch (e) {
+        alert(`Capture failed: ${e.message}`);
+      }
+    };
+  }
+  if (topTest) {
+    topTest.onclick = async () => {
+      try {
+        const res = await apiGet("/api/test");
+        alert(JSON.stringify(res, null, 2));
+      } catch (e) {
+        alert(`Camera test failed: ${e.message}`);
+      }
+    };
+  }
+  if (topFix) {
+    topFix.onclick = async () => {
+      if (!confirm("Run the camera fix flow?")) return;
+      try {
+        const res = await apiGet("/api/fix");
+        alert(JSON.stringify(res, null, 2));
+      } catch (e) {
+        alert(`Fix failed: ${e.message}`);
+      }
+    };
+  }
+}
+
+async function refreshAutonomousPanel() {
+  const panel = document.getElementById("auto_state_panel");
+  if (!panel) return;
+  try {
+    const r = await apiGet("/api/autonomous_state");
+    if (!r.ok) {
+      panel.innerHTML = "<i>Autonomous state unavailable</i>";
+      return;
+    }
+    const s = r.state || {};
+    panel.innerHTML = `
+      <div class="info-grid">
+        <div class="stat-line"><span>State</span><b>${escapeHtml(s.state || "IDLE")}</b></div>
+        <div class="stat-line"><span>Session</span><b>${s.session_id ?? 0}</b></div>
+        <div class="stat-line"><span>Detector</span><b>${escapeHtml((s.detector_backend || "normal").toUpperCase())}</b></div>
+        <div class="stat-line"><span>YOLO Runtime</span><b>${escapeHtml((s.yolo_runtime || "-").toUpperCase())}</b></div>
+        <div class="stat-line"><span>AI Blocked</span><b>${s.ai_blocked ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Block Reason</span><b>${escapeHtml(s.ai_block_reason || "-")}</b></div>
+        <div class="stat-line"><span>People</span><b>${s.person_count ?? 0}</b></div>
+        <div class="stat-line"><span>Faces</span><b>${s.face_count ?? 0}</b></div>
+        <div class="stat-line"><span>Group</span><b>${s.group_detected ? `Yes (${s.group_size ?? 0})` : "No"}</b></div>
+        <div class="stat-line"><span>Intent</span><b>${s.intent_detected ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Depth</span><b>${s.depth_m == null ? "-" : fmtNum(s.depth_m, 2)}</b></div>
+        <div class="stat-line"><span>Approach</span><b>${fmtNum(s.approach_speed_mps || 0, 2)} m/s</b></div>
+        <div class="stat-line"><span>Guest</span><b>${escapeHtml(s.recognized_person_label || "-")}</b></div>
+        <div class="stat-line"><span>Known Guest</span><b>${s.recognized_person_known ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Match</span><b>${s.recognized_person_match_score ? fmtNum(s.recognized_person_match_score, 2) : "-"}</b></div>
+      </div>
+    `;
+  } catch (_e) {
+    panel.innerHTML = "<i>Autonomous state unavailable</i>";
+  }
+}
+
+async function refreshAiReadinessPanel() {
+  const panel = document.getElementById("ai_readiness_panel");
+  if (!panel) return;
+  try {
+    const data = await apiGet("/api/ai_readiness");
+    panel.innerHTML = `
+      <div class="info-grid">
+        <div class="stat-line"><span>Ready</span><b>${data.ok ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Backend</span><b>${escapeHtml((data.backend || "normal").toUpperCase())}</b></div>
+        <div class="stat-line"><span>Runtime</span><b>${escapeHtml((data.yolo_runtime || "-").toUpperCase())}</b></div>
+        <div class="stat-line"><span>YOLO Loaded</span><b>${data.yolo_loaded ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Person Model</span><b>${data.person_model_ok ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Face Model</span><b>${data.face_model_ok ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Strict Required</span><b>${data.strict_required ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Block Reason</span><b>${escapeHtml(data.block_reason || "-")}</b></div>
+      </div>
+    `;
+  } catch (_e) {
+    panel.innerHTML = "<i>AI readiness unavailable</i>";
+  }
+}
+
+async function refreshRuntimeHealthPanel() {
+  const panel = document.getElementById("runtime_health_panel");
+  if (!panel) return;
+  try {
+    const r = await apiGet("/api/runtime_health");
+    if (!r.ok) {
+      panel.innerHTML = "<i>Runtime health unavailable</i>";
+      return;
+    }
+    const h = r.health || {};
+    panel.innerHTML = `
+      <div class="info-grid">
+        <div class="stat-line"><span>WS</span><b>${h.ws_connected ? "Connected" : "Down"}</b></div>
+        <div class="stat-line"><span>WS State</span><b>${escapeHtml(h.ws_state || "-")}</b></div>
+        <div class="stat-line"><span>Mic Enabled</span><b>${h.mic_enabled ? "Yes" : "No"}</b></div>
+        <div class="stat-line"><span>Mic</span><b>${escapeHtml(h.mic_state || "-")}</b></div>
+        <div class="stat-line"><span>Speaker</span><b>${escapeHtml(h.speaker_state || "-")}</b></div>
+        <div class="stat-line"><span>Gate</span><b>${h.audio_gate_open ? "Open" : "Closed"}</b></div>
+        <div class="stat-line"><span>Mic Restarts</span><b>${h.mic_restarts ?? 0}</b></div>
+        <div class="stat-line"><span>Speaker Restarts</span><b>${h.speaker_restarts ?? 0}</b></div>
+        <div class="stat-line"><span>WS Restarts</span><b>${h.ws_restarts ?? 0}</b></div>
+        <div class="stat-line"><span>Last WS Error</span><b>${escapeHtml(h.ws_last_error || "-")}</b></div>
+      </div>
+    `;
+  } catch (_e) {
+    panel.innerHTML = "<i>Runtime health unavailable</i>";
+  }
+}
+
+async function renderPeople() {
+  const list = document.getElementById("people_list");
+  const status = document.getElementById("people_status_box");
+  if (!list || !status) return;
+  try {
+    const res = await apiGet("/api/people");
+    const people = res.people || [];
+    status.textContent = people.length
+      ? `Registered guests: ${people.length}\nReturning guests are recognized from saved face samples in photos/people/.`
+      : "No people enrolled yet. AI mode will create a guest profile the first time a single face is confirmed.";
+    list.innerHTML = renderPeopleCards(people);
+    list.querySelectorAll(".person-delete").forEach((btn) => {
+      btn.addEventListener("click", async () => {
+        const personId = btn.dataset.id || "";
+        if (!personId) return;
+        if (!confirm(`Delete person ${personId}?`)) return;
+        await apiGet(`/api/delete_person?id=${encodeURIComponent(personId)}`);
+        await renderPeople();
+      });
+    });
+    list.querySelectorAll(".person-add-photo").forEach((btn) => {
+      btn.addEventListener("click", () => {
+        const personId = btn.dataset.id || "";
+        const input = document.getElementById("people_upload_file");
+        if (!input) return;
+        input.dataset.personId = personId;
+        input.click();
+      });
+    });
+  } catch (e) {
+    status.textContent = `People registry unavailable\n${e.message}`;
+    list.innerHTML = "";
+  }
+}
+
+async function refreshCameraPanel() {
+  const statusBox = document.getElementById("camera_status_box");
+  const infoPanel = document.getElementById("camera_info_panel");
+  const chipRow = document.getElementById("camera_chip_row");
+  const selector = document.getElementById("camera_source_select");
+  const sourceMeta = document.getElementById("camera_source_meta");
+  const inventoryBox = document.getElementById("camera_inventory_box");
+  if (!statusBox || !infoPanel || !chipRow) return;
+
+  try {
+    const [health, cameraSources] = await Promise.all([
+      apiGet("/api/camera_health"),
+      selector && !window.__cameraSourcesCache ? apiGet("/api/camera_sources") : Promise.resolve(window.__cameraSourcesCache || null),
+    ]);
+
+    if (cameraSources && cameraSources.ok) {
+      window.__cameraSourcesCache = cameraSources;
+      if (selector) {
+        const currentValue = selector.dataset.initialized === "1"
+          ? (selector.value || cameraSources.selected_source || "realsense")
+          : (cameraSources.selected_source || "realsense");
+        selector.innerHTML = renderSourceOptions(cameraSources);
+        selector.value = currentValue;
+        if (!selector.value) selector.value = cameraSources.selected_source || "realsense";
+        selector.dataset.initialized = "1";
+      }
+      if (sourceMeta) {
+        const rsCount = (cameraSources.realsense_devices || []).length;
+        const vidCount = (cameraSources.video_devices || []).length;
+        const activeLabel = (cameraSources.active_device && cameraSources.active_device.label) || cameraSources.active_source || "-";
+        sourceMeta.textContent = `Preferred RS: ${cameraSources.preferred_realsense_serial || "-"} | Active: ${activeLabel} | RealSense devices: ${rsCount} | Video nodes: ${vidCount}`;
+      }
+    }
+
+    const camera = (health && health.camera) || {};
+    statusBox.textContent = camera.ok ? cameraStatusLines(camera) : `Camera not ready\nSource: ${camera.source || "-"}\nRequested: ${camera.requested_profile || "-"}\nError: ${camera.last_error || "-"}`;
+    chipRow.innerHTML = `
+      <div class="chip"><span>Requested</span><strong>${escapeHtml(camera.requested_source || camera.source || "-")}</strong></div>
+      <div class="chip"><span>Backend</span><strong>${escapeHtml(camera.backend || "-")}</strong></div>
+      <div class="chip"><span>Active Profile</span><strong>${escapeHtml(camera.profile || "-")}</strong></div>
+      <div class="chip"><span>Frame Time</span><strong>${escapeHtml(formatTime(camera.frame_time))}</strong></div>
+    `;
+    infoPanel.textContent = JSON.stringify(health, null, 2);
+    if (inventoryBox) {
+      inventoryBox.textContent = renderCameraInventory(cameraSources, camera);
+    }
+
+    const widthInput = document.getElementById("width_input");
+    if (widthInput && widthInput.dataset.initialized !== "1") {
+      setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps);
+      widthInput.dataset.initialized = "1";
+    }
+  } catch (e) {
+    statusBox.textContent = `Camera service unavailable\n${e.message}`;
+    infoPanel.textContent = JSON.stringify({ ok: false, error: e.message }, null, 2);
+    chipRow.innerHTML = "";
+    if (inventoryBox) inventoryBox.textContent = "Camera inventory unavailable.";
+  }
+}
+
+function renderReplayList(items, opts = {}) {
+  const manualMode = !!opts.manualMode;
+  const testRunning = !!opts.testRunning;
+  if (!items.length) {
+    return '<div class="status-box"><i>No replay files found.</i></div>';
+  }
+  return items.map((item) => {
+    const tags = [];
+    if (item.active) tags.push('<span class="replay-tag active">active</span>');
+    if (item.greeting) tags.push('<span class="replay-tag">greeting</span>');
+    if (!item.trigger_ok) tags.push('<span class="replay-tag warn">triggerless</span>');
+    return `
+      <article class="replay-row ${item.active ? "active" : ""}">
+        <div class="replay-main">
+          <div class="replay-title">${escapeHtml(item.name)}</div>
+          <div class="replay-meta">${formatSize(item.size || 0)} · ${formatTime(item.mtime || 0)}</div>
+        </div>
+        <div class="replay-tags">${tags.join("")}</div>
+        <div class="replay-row-actions">
+          <button class="btn ghost replay-test" data-name="${escapeHtml(item.name)}" ${manualMode && !testRunning ? "" : "disabled"}>Test</button>
+          <button class="btn ghost replay-use" data-name="${escapeHtml(item.name)}">Use</button>
+          <button class="btn ghost replay-rename" data-name="${escapeHtml(item.name)}">Rename</button>
+          <a class="btn ghost" href="/api/download_replay?name=${encodeURIComponent(item.name)}">Download</a>
+          <button class="btn ghost danger replay-delete" data-name="${escapeHtml(item.name)}" ${(item.active || item.greeting) ? "disabled" : ""}>Delete</button>
+        </div>
+      </article>
+    `;
+  }).join("");
+}
+
+function renderReplayRecordStatus(status) {
+  if (!status || !status.started_at) {
+    return "Recorder idle.";
+  }
+  if (status.running) {
+    return `Recording ${status.name || "-"} for ${status.seconds || 0}s...\nOutput: ${status.output || "-"}`;
+  }
+  if (status.ok) {
+    return `Recording saved\n${status.output || "-"}\nFinished: ${formatTime(status.finished_at || 0)}`;
+  }
+  return `Recorder error\n${status.error || "-"}${(status.output ? `\nOutput: ${status.output}` : "")}`;
+}
+
+function renderReplayTestStatus(status) {
+  if (!status || !status.started_at) {
+    return "Replay test idle.";
+  }
+  if (status.running) {
+    return `Testing replay\n${status.name || "-"}`;
+  }
+  if (status.ok) {
+    return `Replay test complete\n${status.result || status.name || "-"}`;
+  }
+  return `Replay test error\n${status.error || "-"}`;
+}
+
+async function refreshReplayPanel() {
+  const selector = document.getElementById("replay_select");
+  const activeNote = document.getElementById("replay_active_note");
+  const list = document.getElementById("replay_manager_list");
+  const status = document.getElementById("replay_record_status");
+  const testStatus = document.getElementById("replay_test_status");
+  const greetingSelect = document.getElementById("opt_greeting_replay_file");
+  try {
+    const [replayResp, activeResp, recordResp, testResp] = await Promise.all([
+      apiGet("/api/replays"),
+      apiGet("/api/get_replay"),
+      apiGet("/api/replay_record_status").catch(() => ({ ok: false, status: {} })),
+      apiGet("/api/replay_test_status").catch(() => ({ ok: false, status: {} })),
+    ]);
+    const items = replayResp.items || [];
+    const activeReplay = activeResp.replay || "";
+    const replayTest = testResp.status || {};
+    const manualMode = window.__runtimeMode === "manual";
+
+    if (selector) {
+      selector.innerHTML = items.map((item) => `<option value="${escapeHtml(item.name)}">${escapeHtml(item.name)}</option>`).join("");
+      selector.value = activeReplay || (items[0] && items[0].name) || "";
+    }
+    if (activeNote) {
+      activeNote.textContent = activeReplay
+        ? `Active replay: ${activeReplay}. Manual R2+X and AI photo capture use this replay when AI capture replay is enabled. Replay recording and replay test are manual-mode only.`
+        : "No active replay selected.";
+    }
+    if (list) {
+      list.innerHTML = renderReplayList(items, { manualMode, testRunning: !!replayTest.running });
+      list.querySelectorAll(".replay-test").forEach((btn) => {
+        btn.addEventListener("click", async () => {
+          const name = btn.dataset.name || "";
+          await apiGet(`/api/test_replay?name=${encodeURIComponent(name)}`);
+          await refreshReplayPanel();
+        });
+      });
+      list.querySelectorAll(".replay-use").forEach((btn) => {
+        btn.addEventListener("click", async () => {
+          await apiGet(`/api/set_replay?name=${encodeURIComponent(btn.dataset.name || "")}`);
+          await refreshReplayPanel();
+        });
+      });
+      list.querySelectorAll(".replay-rename").forEach((btn) => {
+        btn.addEventListener("click", async () => {
+          const oldName = btn.dataset.name || "";
+          const currentLeaf = oldName.split("/").pop() || oldName;
+          const nextName = window.prompt("Rename replay", currentLeaf);
+          if (!nextName || !nextName.trim()) return;
+          await apiGet(
+            `/api/rename_replay?old=${encodeURIComponent(oldName)}&new=${encodeURIComponent(nextName.trim())}`
+          );
+          await refreshReplayPanel();
+        });
+      });
+      list.querySelectorAll(".replay-delete").forEach((btn) => {
+        btn.addEventListener("click", async () => {
+          const name = btn.dataset.name || "";
+          if (!confirm(`Delete replay ${name}?`)) return;
+          await apiGet(`/api/delete_replay?name=${encodeURIComponent(name)}`);
+          await refreshReplayPanel();
+        });
+      });
+    }
+    if (status) {
+      status.textContent = renderReplayRecordStatus(recordResp.status || {});
+    }
+    if (testStatus) {
+      testStatus.textContent = renderReplayTestStatus(replayTest);
+    }
+    if (greetingSelect) {
+      const current = greetingSelect.dataset.current || greetingSelect.value;
+      greetingSelect.innerHTML = items.map((item) => `<option value="${escapeHtml(item.name)}">${escapeHtml(item.name)}</option>`).join("");
+      if (current) greetingSelect.value = current;
+      if (!greetingSelect.value && items.length) greetingSelect.value = items[0].name;
+      delete greetingSelect.dataset.current;
+    }
+  } catch (e) {
+    if (activeNote) activeNote.textContent = `Replay inventory unavailable: ${e.message}`;
+    if (list) list.innerHTML = "";
+    if (status) status.textContent = `Recorder unavailable\n${e.message}`;
+    if (testStatus) testStatus.textContent = `Replay test unavailable\n${e.message}`;
+  }
+}
+
+async function renderControls() {
+  const ctrl = document.getElementById("controls");
+  const [modeResp, micResp, cameraSources] = await Promise.all([
+    apiGet("/api/mode"),
+    apiGet("/api/mic"),
+    apiGet("/api/camera_sources").catch(() => ({ ok: false, options: [] })),
+  ]);
+
+  window.__cameraSourcesCache = cameraSources && cameraSources.ok ? cameraSources : null;
+
+  const mode = modeResp.mode || "manual";
+  window.__runtimeMode = mode;
+  const modePolicy = modeResp.policy || {};
+  const micEnabled = !!(micResp.options && micResp.options.mic_enabled);
+
+  let backend = "normal";
+  let strictLocked = false;
+  let aiOptions = {
+    hard_target_lock_enabled: true,
+    retake_prompt_enabled: true,
+    autonomous_greeting_replay_enabled: true,
+    autonomous_greeting_replay_file: "right_hand_up.jsonl",
+    autonomous_capture_replay_enabled: true,
+    face_recognition_enabled: true,
+    face_recognition_threshold: 0.88,
+    active_replay: "photo_G3.jsonl",
+  };
+  let aiReadinessMarkup = "";
+  let aiOptionsMarkup = "";
+  if (mode === "ai") {
+    try {
+      const bj = await apiGet("/api/detector_backend");
+      backend = bj.backend || "normal";
+      strictLocked = !!bj.locked;
+    } catch (_e) {}
+
+    try {
+      const oj = await apiGet("/api/ai_options");
+      if (oj && oj.ok && oj.options) aiOptions = oj.options;
+    } catch (_e) {}
+
+    aiReadinessMarkup = `
+      <section class="panel strong">
+        <div class="panel-header">
+          <div>
+            <div class="panel-eyebrow">AI Vision</div>
+            <h3>Detection Backend</h3>
+          </div>
+        </div>
+        <div class="selector-row">
+          <select id="det_backend_select">
+            <option value="normal">Normal</option>
+            <option value="yolo">YOLO</option>
+          </select>
+          <button id="det_backend_set" class="btn ghost">Apply Backend</button>
+        </div>
+        ${strictLocked ? '<div class="meta" style="margin-top:10px;color:#8b3120;"><b>Strict AI profile active:</b> backend is locked to YOLO in AI mode.</div>' : ""}
+        <div id="ai_readiness_panel" class="info-box"><i>Loading AI readiness...</i></div>
+      </section>
+    `;
+
+    aiOptionsMarkup = `
+      <section class="panel">
+        <div class="panel-header">
+          <div>
+            <div class="panel-eyebrow">AI Session</div>
+            <h3>Session Options</h3>
+          </div>
+        </div>
+        <div class="inline-actions">
+          <label><input type="checkbox" id="opt_hard_lock" ${aiOptions.hard_target_lock_enabled ? "checked" : ""}> Hard Target Lock</label>
+          <label><input type="checkbox" id="opt_retake_prompt" ${aiOptions.retake_prompt_enabled ? "checked" : ""}> Retake Prompt</label>
+          <label><input type="checkbox" id="opt_capture_replay" ${aiOptions.autonomous_capture_replay_enabled ? "checked" : ""}> Use Active Replay During AI Photo</label>
+          <label><input type="checkbox" id="opt_greeting_replay" ${aiOptions.autonomous_greeting_replay_enabled ? "checked" : ""}> Greeting Replay</label>
+          <label><input type="checkbox" id="opt_face_recognition" ${aiOptions.face_recognition_enabled ? "checked" : ""}> Returning Guest Recognition</label>
+        </div>
+        <div class="selector-row" style="margin-top:12px;">
+          <select id="opt_greeting_replay_file"></select>
+          <input id="opt_face_threshold" type="number" min="0.50" max="0.995" step="0.01" value="${Number(aiOptions.face_recognition_threshold || 0.88).toFixed(2)}" placeholder="face threshold">
+          <button id="opt_ai_save" class="btn ghost">Save AI Options</button>
+        </div>
+        <div class="status-box">AI welcomes approaching guests, asks if they want a photo, guides them into frame, and captures using the active replay when enabled. Returning-guest recognition stores samples in <code>photos/people/</code>. Active replay: ${escapeHtml(aiOptions.active_replay || "-")}.</div>
+      </section>
+    `;
+  }
+
+  const recorderMarkup = mode === "manual"
+    ? `
+        <section class="panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Recorder</div>
+              <h3>Record New Replay</h3>
+            </div>
+          </div>
+          <div class="selector-row">
+            <input id="replay_record_name" type="text" placeholder="photo_wave">
+            <input id="replay_record_seconds" type="number" min="1" step="1" value="15" placeholder="seconds">
+            <button id="replay_record_start" class="btn primary">Start Recording</button>
+          </div>
+          <div class="meta" style="margin-top:10px;">Recorded files are saved directly in <code>Data/G1</code> and become available in the active replay selector.</div>
+          <div id="replay_record_status" class="status-box">Recorder idle.</div>
+        </section>
+      `
+    : `
+        <section class="panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Recorder</div>
+              <h3>Manual Mode Only</h3>
+            </div>
+          </div>
+          <div class="status-box">Replay recording and replay test are disabled outside manual mode. Replay selection, rename, upload, download, and delete remain available.</div>
+          <div id="replay_record_status" class="status-box">Recorder idle.</div>
+        </section>
+      `;
+
+  ctrl.innerHTML = `
+    <div class="dashboard-stack">
+      <div class="control-grid">
+        <section class="panel strong">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Runtime Mode</div>
+              <h3>${escapeHtml(mode.toUpperCase())}</h3>
+            </div>
+          </div>
+          <div class="selector-row">
+            <select id="mode_select">
+              <option value="manual">Manual</option>
+              <option value="ai">AI</option>
+            </select>
+            <button id="mode_set" class="btn primary">Set Mode</button>
+          </div>
+          <div class="status-box">${escapeHtml(modePolicy.description || "")}</div>
+        </section>
+
+        <section class="panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Gemini Mic</div>
+              <h3>${micEnabled ? "Microphone ON" : "Microphone OFF"}</h3>
+            </div>
+          </div>
+          <div class="action-row">
+            <button id="mic_toggle" class="btn ${micEnabled ? "ghost danger" : "primary"}">${micEnabled ? "Turn Mic Off" : "Turn Mic On"}</button>
+          </div>
+          <div class="status-box">Microphone audio can stay on in both modes. Manual mode still disables mapped photo commands and AI detection.</div>
+        </section>
+      </div>
+
+      <section class="panel strong">
+        <div class="panel-header">
+          <div>
+            <div class="panel-eyebrow">Camera Console</div>
+            <h2>Live Camera</h2>
+          </div>
+        </div>
+        <div class="camera-grid">
+          <div>
+            <div class="preview-shell">
+              <div id="preview_placeholder" class="preview-placeholder">Live preview is off.<br>Use the toggle below when you need a live camera feed.</div>
+              <img id="live_preview" class="camera-preview" alt="live preview">
+            </div>
+            <div class="preview-toolbar" style="margin-top:12px;">
+              <button id="toggle_preview" class="btn ghost">Show Live Camera</button>
+              <button id="capture_now_btn" class="btn primary">Capture Now</button>
+              <button id="camera_refresh_btn" class="btn ghost">Refresh Camera</button>
+            </div>
+            <div id="preview_hint" class="meta" style="margin-top:10px;">Live preview is off. Turn it on only when needed.</div>
+            <div id="camera_chip_row" class="chip-row"></div>
+            <div id="camera_status_box" class="status-box">Loading camera status...</div>
+          </div>
+          <div>
+            <div class="selector-row">
+              <select id="camera_source_select">${renderSourceOptions(cameraSources)}</select>
+              <button id="camera_apply_btn" class="btn ghost">Switch Camera</button>
+              <button id="camera_save_default_btn" class="btn ghost">Save As Default</button>
+            </div>
+            <div id="camera_source_meta" class="meta" style="margin-top:10px;">Loading available camera sources...</div>
+            <pre id="camera_inventory_box" class="status-box" style="margin-top:10px;">Loading camera inventory...</pre>
+            <div class="resolution-row" style="margin-top:14px;">
+              <select id="resolution_select">${renderResolutionOptions()}</select>
+              <input id="width_input" type="number" min="1" step="1" placeholder="width">
+              <input id="height_input" type="number" min="1" step="1" placeholder="height">
+              <input id="fps_input" type="number" min="1" step="1" placeholder="fps">
+              <button id="apply_resolution_btn" class="btn ghost">Apply Resolution</button>
+            </div>
+            <div class="meta" style="margin-top:10px;">Use a preset or enter width, height, and fps manually. The direct camera service will reopen with the requested settings.</div>
+            <pre id="camera_info_panel" class="raw-box">Checking camera...</pre>
+          </div>
+        </div>
+      </section>
+
+      <div class="control-grid">
+        <section class="panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Replay</div>
+              <h3>Capture Motion</h3>
+            </div>
+          </div>
+          <div class="selector-row">
+            <select id="replay_select"></select>
+            <button id="replay_set" class="btn ghost">Set Active Replay</button>
+          </div>
+          <div id="replay_active_note" class="status-box">Loading replay status...</div>
+        </section>
+
+        ${recorderMarkup}
+      </div>
+
+      <section class="panel">
+        <div class="panel-header">
+          <div>
+            <div class="panel-eyebrow">Replay Files</div>
+            <h3>Replay Inventory</h3>
+          </div>
+        </div>
+        <div class="action-row">
+          <button id="replay_upload_btn" class="btn ghost">Upload Replay</button>
+          <input id="replay_upload_file" type="file" accept=".jsonl" style="display:none;">
+        </div>
+        <div id="replay_test_status" class="status-box">Replay test idle.</div>
+        <div id="replay_manager_list" class="replay-list"></div>
+      </section>
+
+      <section class="panel">
+        <div class="panel-header">
+          <div>
+            <div class="panel-eyebrow">AI Voice Assets</div>
+            <h3>Audio Prompt Library</h3>
+          </div>
+          <div class="action-row">
+            <button id="audio_prompt_mode_toggle" class="btn ghost">Situation Speech</button>
+            <button id="audio_prompt_fallback_toggle" class="btn ghost">Gemini Fallback</button>
+          </div>
+        </div>
+        <div class="status-box">Upload prerecorded WAV clips for fixed AI situation prompts. In audio mode, AI detection, confirmation, countdown, retake, and thank-you situations use these clips first. Gemini can be switched back on for those same situations from the dashboard.</div>
+        <div id="audio_prompt_status_box" class="status-box">Loading audio prompt library...</div>
+        <div class="audio-prompt-recorder">
+          <div class="selector-row">
+            <select id="audio_prompt_record_key"></select>
+            <input id="audio_prompt_record_filename" type="text" placeholder="filename.wav">
+            <button id="audio_prompt_record_start" class="btn primary">Record From Text</button>
+          </div>
+          <textarea id="audio_prompt_record_text" class="prompt-editor" rows="4" placeholder="Prompt text to speak exactly..."></textarea>
+          <div id="audio_prompt_record_status_box" class="status-box">Prompt recorder idle.</div>
+        </div>
+        <input id="audio_prompt_upload_file" type="file" accept=".wav" style="display:none;">
+        <div id="audio_prompt_list" class="audio-prompt-grid"></div>
+      </section>
+
+      <section class="panel">
+        <div class="panel-header">
+          <div>
+            <div class="panel-eyebrow">Actions</div>
+            <h3>Operator Actions</h3>
+          </div>
+        </div>
+        <div class="action-row">
+          <button id="req_photo" class="btn ghost">Request Photo</button>
+          <button id="clear_photos" class="btn ghost danger">Clear Photos</button>
+          <button id="download_zip" class="btn ghost">Download All</button>
+          <button id="upload_now" class="btn ghost">Upload Now</button>
+          <button id="scripts_fix_check" class="btn ghost">Check RealSense</button>
+          <button id="scripts_fix_run" class="btn ghost danger">Fix RealSense</button>
+        </div>
+      </section>
+
+      ${aiReadinessMarkup}
+      ${aiOptionsMarkup}
+
+      <div class="status-grid">
+        <section class="panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">AI State</div>
+              <h3>Autonomous State</h3>
+            </div>
+          </div>
+          <div id="auto_state_panel" class="info-box"><i>Loading...</i></div>
+        </section>
+
+        <section class="panel">
+          <div class="panel-header">
+            <div>
+              <div class="panel-eyebrow">Runtime</div>
+              <h3>Runtime Health</h3>
+            </div>
+          </div>
+          <div id="runtime_health_panel" class="info-box"><i>Loading...</i></div>
+        </section>
+      </div>
+    </div>
+  `;
+
+  if (mode === "ai") {
+    setTimeout(() => {
+      const bSel = document.getElementById("det_backend_select");
+      const bBtn = document.getElementById("det_backend_set");
+      if (bSel) {
+        bSel.value = backend;
+        if (strictLocked) {
+          bSel.disabled = true;
+          bSel.value = "yolo";
+        }
+      }
+      if (bBtn && strictLocked) {
+        bBtn.disabled = true;
+      }
+      const greetingSel = document.getElementById("opt_greeting_replay_file");
+      if (greetingSel) {
+        greetingSel.dataset.current = aiOptions.autonomous_greeting_replay_file || "";
+      }
+    }, 0);
+  }
+
+  document.getElementById("mode_select").value = mode;
+
+  document.getElementById("mode_set").addEventListener("click", async () => {
+    const sel = document.getElementById("mode_select").value;
+    await apiGet(`/api/set_mode?mode=${encodeURIComponent(sel)}`);
+    await renderControls();
+    await renderPhotos();
+  });
+
+  document.getElementById("mic_toggle").addEventListener("click", async () => {
+    const nextEnabled = micEnabled ? 0 : 1;
+    await apiGet(`/api/set_mic?enabled=${nextEnabled}`);
+    await renderControls();
+  });
+
+  const replaySet = document.getElementById("replay_set");
+  if (replaySet) {
+    replaySet.addEventListener("click", async () => {
+      const name = encodeURIComponent(document.getElementById("replay_select").value);
+      await apiGet(`/api/set_replay?name=${name}`);
+      await refreshReplayPanel();
+    });
+  }
+
+  const replayRecordStart = document.getElementById("replay_record_start");
+  if (replayRecordStart) {
+    replayRecordStart.addEventListener("click", async () => {
+      const name = (document.getElementById("replay_record_name").value || "").trim();
+      const seconds = Number(document.getElementById("replay_record_seconds").value || "15");
+      if (!name) {
+        alert("Enter a replay file name first.");
+        return;
+      }
+      await apiGet(`/api/replay_record_start?name=${encodeURIComponent(name)}&seconds=${encodeURIComponent(seconds)}`);
+      await refreshReplayPanel();
+    });
+  }
+
+  const replayUploadBtn = document.getElementById("replay_upload_btn");
+  const replayUploadFile = document.getElementById("replay_upload_file");
+  if (replayUploadBtn && replayUploadFile) {
+    replayUploadBtn.addEventListener("click", () => replayUploadFile.click());
+    replayUploadFile.addEventListener("change", async () => {
+      const file = replayUploadFile.files && replayUploadFile.files[0];
+      if (!file) return;
+      const requestedName = window.prompt("Replay name", file.name) || file.name;
+      const form = new FormData();
+      form.append("file", file, file.name);
+      form.append("name", requestedName);
+      try {
+        await apiPostFormData("/api/upload_replay", form);
+        await refreshReplayPanel();
+      } catch (e) {
+        alert(`Replay upload failed: ${e.message}`);
+      } finally {
+        replayUploadFile.value = "";
+      }
+    });
+  }
+
+  const audioPromptUploadFile = document.getElementById("audio_prompt_upload_file");
+  const audioPromptModeToggle = document.getElementById("audio_prompt_mode_toggle");
+  const audioPromptFallbackToggle = document.getElementById("audio_prompt_fallback_toggle");
+  const audioPromptRecordKey = document.getElementById("audio_prompt_record_key");
+  const audioPromptRecordFilename = document.getElementById("audio_prompt_record_filename");
+  const audioPromptRecordText = document.getElementById("audio_prompt_record_text");
+  const audioPromptRecordStart = document.getElementById("audio_prompt_record_start");
+  if (audioPromptUploadFile) {
+    audioPromptUploadFile.addEventListener("change", async () => {
+      const file = audioPromptUploadFile.files && audioPromptUploadFile.files[0];
+      const key = audioPromptUploadFile.dataset.key || "";
+      if (!file || !key) return;
+      const defaultName = audioPromptUploadFile.dataset.filename || `${key}.wav`;
+      const requestedName = window.prompt("Audio filename", defaultName) || defaultName;
+      const form = new FormData();
+      form.append("key", key);
+      form.append("file", file, file.name);
+      form.append("filename", requestedName);
+      try {
+        await apiPostFormData("/api/upload_audio_prompt", form);
+        await refreshAudioPromptPanel();
+      } catch (e) {
+        alert(`Audio prompt upload failed: ${e.message}`);
+      } finally {
+        audioPromptUploadFile.value = "";
+        delete audioPromptUploadFile.dataset.key;
+        delete audioPromptUploadFile.dataset.filename;
+      }
+    });
+  }
+  if (audioPromptModeToggle) {
+    audioPromptModeToggle.addEventListener("click", async () => {
+      const current = String(audioPromptModeToggle.dataset.mode || "audio").trim().toLowerCase();
+      const next = current === "gemini" ? "audio" : "gemini";
+      await apiGet(`/api/set_audio_prompt_mode?mode=${encodeURIComponent(next)}`);
+      await refreshAudioPromptPanel();
+    });
+  }
+  if (audioPromptFallbackToggle) {
+    audioPromptFallbackToggle.addEventListener("click", async () => {
+      const current = audioPromptFallbackToggle.dataset.enabled === "1";
+      await apiGet(`/api/set_audio_prompt_fallback?enabled=${current ? 0 : 1}`);
+      await refreshAudioPromptPanel();
+    });
+  }
+  if (audioPromptRecordKey && audioPromptRecordFilename && audioPromptRecordText) {
+    audioPromptRecordKey.addEventListener("change", () => {
+      const key = audioPromptRecordKey.value || "";
+      audioPromptRecordFilename.value = promptFilenameForKey(key);
+      audioPromptRecordFilename.dataset.autofill = "1";
+      audioPromptRecordText.value = promptTextForKey(key);
+      audioPromptRecordText.dataset.autofill = "1";
+    });
+    audioPromptRecordFilename.addEventListener("input", () => {
+      audioPromptRecordFilename.dataset.autofill = "0";
+    });
+    audioPromptRecordText.addEventListener("input", () => {
+      audioPromptRecordText.dataset.autofill = "0";
+    });
+  }
+  if (audioPromptRecordStart && audioPromptRecordKey && audioPromptRecordFilename && audioPromptRecordText) {
+    audioPromptRecordStart.addEventListener("click", async () => {
+      const key = (audioPromptRecordKey.value || "").trim();
+      const filename = (audioPromptRecordFilename.value || "").trim();
+      const text = (audioPromptRecordText.value || "").trim();
+      if (!key) {
+        alert("Select a prompt key first.");
+        return;
+      }
+      if (!text) {
+        alert("Prompt text is required.");
+        return;
+      }
+      try {
+        await apiPostJson("/api/audio_prompt_record", { key, filename, text });
+        await refreshAudioPromptRecordStatus();
+      } catch (e) {
+        alert(`Prompt recording failed: ${e.message}`);
+      }
+    });
+  }
+
+  const peopleUploadBtn = document.getElementById("people_upload_btn");
+  const peopleUploadFile = document.getElementById("people_upload_file");
+  const peopleResetBtn = document.getElementById("people_reset_btn");
+  if (peopleUploadBtn && peopleUploadFile) {
+    peopleUploadBtn.addEventListener("click", () => {
+      peopleUploadFile.dataset.personId = "";
+      peopleUploadFile.click();
+    });
+    peopleUploadFile.addEventListener("change", async () => {
+      const file = peopleUploadFile.files && peopleUploadFile.files[0];
+      if (!file) return;
+      const form = new FormData();
+      form.append("file", file, file.name);
+      if (peopleUploadFile.dataset.personId) {
+        form.append("person_id", peopleUploadFile.dataset.personId);
+      }
+      try {
+        await apiPostFormData("/api/upload_person", form);
+        await renderPeople();
+      } catch (e) {
+        alert(`People upload failed: ${e.message}`);
+      } finally {
+        peopleUploadFile.value = "";
+        delete peopleUploadFile.dataset.personId;
+      }
+    });
+  }
+  if (peopleResetBtn) {
+    peopleResetBtn.addEventListener("click", async () => {
+      if (!confirm("Delete all saved people profiles?")) return;
+      await apiGet("/api/reset_people");
+      await renderPeople();
+    });
+  }
+
+  document.getElementById("req_photo").addEventListener("click", async () => {
+    await apiGet("/api/request_photo");
+  });
+  document.getElementById("clear_photos").addEventListener("click", async () => {
+    if (!confirm("Delete ALL photos?")) return;
+    await apiGet("/api/clear_photos");
+    await renderPhotos();
+  });
+  document.getElementById("download_zip").addEventListener("click", async () => {
+    const r = await apiGet("/api/download_zip");
+    if (r.ok) window.location = `/${r.archive}`;
+  });
+  document.getElementById("upload_now").addEventListener("click", async () => {
+    await apiGet("/api/upload_now");
+  });
+  document.getElementById("scripts_fix_check").addEventListener("click", async () => {
+    const r = await apiGet("/api/run_scripts_fix?mode=--check");
+    alert(`RealSense check:\n${(r.stdout || []).join("\n") || "true"}`);
+  });
+  document.getElementById("scripts_fix_run").addEventListener("click", async () => {
+    if (!confirm("Run RealSense fix script?")) return;
+    const r = await apiGet("/api/run_scripts_fix?mode=--fix");
+    alert(`Fix output:\n${(r.stdout || []).join("\n")}`);
+  });
+
+  document.getElementById("toggle_preview").addEventListener("click", () => {
+    setPreviewEnabled(!window.__previewEnabled);
+  });
+  document.getElementById("camera_refresh_btn").addEventListener("click", async () => {
+    window.__cameraSourcesCache = null;
+    await refreshCameraPanel();
+    restartPreview();
+  });
+  document.getElementById("capture_now_btn").addEventListener("click", async () => {
+    const statusBox = document.getElementById("camera_status_box");
+    statusBox.textContent = "Capturing...";
+    try {
+      const resp = await apiGet("/api/capture");
+      statusBox.textContent = `Saved\n${resp.result || "OK"}`;
+      await renderPhotos();
+      await refreshCameraPanel();
+    } catch (e) {
+      statusBox.textContent = `Capture failed\n${e.message}`;
+    }
+  });
+  document.getElementById("camera_apply_btn").addEventListener("click", async () => {
+    const selector = document.getElementById("camera_source_select");
+    const statusBox = document.getElementById("camera_status_box");
+    const source = selector.value;
+    statusBox.textContent = `Switching camera to ${source}...`;
+    try {
+      await apiGet(`/api/set_camera_source?source=${encodeURIComponent(source)}`);
+      restartPreview();
+      await refreshCameraPanel();
+    } catch (e) {
+      statusBox.textContent = `Camera switch failed\n${e.message}`;
+    }
+  });
+  document.getElementById("camera_save_default_btn").addEventListener("click", async () => {
+    const selector = document.getElementById("camera_source_select");
+    const statusBox = document.getElementById("camera_status_box");
+    const camera = ((await apiGet("/api/camera_health")).camera) || {};
+    const cameraSources = window.__cameraSourcesCache || await apiGet("/api/camera_sources");
+    const serial = selectedCameraSerial(selector.value, cameraSources, camera);
+    if (!serial) {
+      statusBox.textContent = "Default camera save failed\nSelect a RealSense source first.";
+      return;
+    }
+    statusBox.textContent = `Saving preferred camera ${serial}...`;
+    try {
+      await apiGet(`/api/set_preferred_camera?serial=${encodeURIComponent(serial)}`);
+      window.__cameraSourcesCache = null;
+      await refreshCameraPanel();
+      statusBox.textContent = `Preferred camera saved\n${serial}`;
+    } catch (e) {
+      statusBox.textContent = `Default camera save failed\n${e.message}`;
+    }
+  });
+  document.getElementById("resolution_select").addEventListener("change", (e) => {
+    const value = e.target.value;
+    const match = value.match(/^(\d+)x(\d+)@(\d+)$/);
+    if (!match) return;
+    setResolutionInputs(Number(match[1]), Number(match[2]), Number(match[3]));
+  });
+  document.getElementById("apply_resolution_btn").addEventListener("click", async () => {
+    const width = Number(document.getElementById("width_input").value);
+    const height = Number(document.getElementById("height_input").value);
+    const fps = Number(document.getElementById("fps_input").value);
+    const statusBox = document.getElementById("camera_status_box");
+    statusBox.textContent = `Applying resolution ${width}x${height}@${fps}...`;
+    try {
+      const resp = await apiGet(`/api/set_camera_resolution?width=${encodeURIComponent(width)}&height=${encodeURIComponent(height)}&fps=${encodeURIComponent(fps)}`);
+      const camera = resp.camera || {};
+      setResolutionInputs(camera.requested_width, camera.requested_height, camera.requested_fps);
+      restartPreview();
+      await refreshCameraPanel();
+    } catch (e) {
+      statusBox.textContent = `Resolution change failed\n${e.message}`;
+    }
+  });
+
+  if (mode === "ai") {
+    const backendButton = document.getElementById("det_backend_set");
+    if (backendButton) {
+      backendButton.addEventListener("click", async () => {
+        const v = document.getElementById("det_backend_select").value || "normal";
+        try {
+          await apiGet(`/api/set_detector_backend?backend=${encodeURIComponent(v)}`);
+          await renderControls();
+        } catch (e) {
+          alert(e.message);
+        }
+      });
+    }
+    const aiSave = document.getElementById("opt_ai_save");
+    if (aiSave) {
+      aiSave.addEventListener("click", async () => {
+        const hard = document.getElementById("opt_hard_lock").checked ? 1 : 0;
+        const retake = document.getElementById("opt_retake_prompt").checked ? 1 : 0;
+        const greetEnabled = document.getElementById("opt_greeting_replay").checked ? 1 : 0;
+        const greetFile = document.getElementById("opt_greeting_replay_file").value || "";
+        const captureReplay = document.getElementById("opt_capture_replay").checked ? 1 : 0;
+        const faceRecognition = document.getElementById("opt_face_recognition").checked ? 1 : 0;
+        const faceThreshold = document.getElementById("opt_face_threshold").value || "0.88";
+        try {
+          await apiGet(
+            `/api/set_ai_options?hard_target_lock_enabled=${hard}&retake_prompt_enabled=${retake}` +
+            `&autonomous_greeting_replay_enabled=${greetEnabled}` +
+            `&autonomous_greeting_replay_file=${encodeURIComponent(greetFile)}` +
+            `&autonomous_capture_replay_enabled=${captureReplay}` +
+            `&face_recognition_enabled=${faceRecognition}` +
+            `&face_recognition_threshold=${encodeURIComponent(faceThreshold)}`
+          );
+          await renderControls();
+        } catch (e) {
+          alert(e.message);
+        }
+      });
+    }
+  }
+
+  setPreviewEnabled(window.__previewEnabled);
+  await refreshCameraPanel();
+  await refreshReplayPanel();
+  await refreshAudioPromptPanel();
+  await refreshAudioPromptRecordStatus();
+  await refreshAutonomousPanel();
+  await refreshAiReadinessPanel();
+  await refreshRuntimeHealthPanel();
+  await renderPeople();
+
+  if (window.__dashboardPoll) clearInterval(window.__dashboardPoll);
+  window.__peoplePollCounter = 0;
+  window.__dashboardPoll = setInterval(async () => {
+    await refreshCameraPanel().catch(() => {});
+    await refreshReplayPanel().catch(() => {});
+    await refreshAutonomousPanel().catch(() => {});
+    await refreshAiReadinessPanel().catch(() => {});
+    await refreshRuntimeHealthPanel().catch(() => {});
+    window.__peoplePollCounter += 1;
+    if (window.__peoplePollCounter % 4 === 0) {
+      await renderPeople().catch(() => {});
+    }
+    if (window.__peoplePollCounter % 8 === 0) {
+      await refreshAudioPromptPanel().catch(() => {});
+    }
+    await refreshAudioPromptRecordStatus().catch(() => {});
+  }, 1500);
+}
+
+async function renderPhotos() {
+  const list = document.getElementById("list");
+  if (!list) return;
+  list.innerHTML = "";
+  const res = await apiGet("/api/photos");
+  const photos = res.photos || [];
+  if (!photos.length) {
+    list.innerHTML = '<div class="panel"><i>No photos yet.</i></div>';
+    return;
+  }
+  for (const photo of photos) {
+    const card = el("article", "card");
+    card.innerHTML = `
+      <img class="thumb" src="/${encodeURIComponent(photo.name)}?t=${Date.now()}" alt="${escapeHtml(photo.name)}">
+      <div class="card-body">
+        <div class="name">${escapeHtml(photo.name)}</div>
+        <div class="photo-meta">${formatSize(photo.size || 0)}<br>${formatTime(photo.mtime || 0)}</div>
+        <div class="actions">
+          <a href="/${encodeURIComponent(photo.name)}" target="_blank">Open</a>
+          <a href="#" data-name="${encodeURIComponent(photo.name)}" class="del">Delete</a>
+          <a href="/api/reupload?name=${encodeURIComponent(photo.name)}">Reupload</a>
+        </div>
+      </div>
+    `;
+    card.querySelector(".thumb").addEventListener("click", () => openPreview(photo.name));
+    list.appendChild(card);
+  }
+
+  document.querySelectorAll("a.del").forEach((anchor) => {
+    anchor.addEventListener("click", async (ev) => {
+      ev.preventDefault();
+      const name = anchor.getAttribute("data-name");
+      if (!confirm("Delete this photo?")) return;
+      await apiGet(`/api/delete?name=${name}`);
+      await renderPhotos();
+    });
+  });
+}
+
+function openPreview(name) {
+  const modal = document.getElementById("preview_modal");
+  const img = document.getElementById("modal_img");
+  const actions = document.getElementById("modal_actions");
+  img.src = `/${encodeURIComponent(name)}`;
+  actions.innerHTML = `
+    <a href="/${encodeURIComponent(name)}" target="_blank">Open / Download</a>
+    <a href="/api/reupload?name=${encodeURIComponent(name)}">Reupload</a>
+    <a href="#" id="modal_delete">Delete</a>
+  `;
+  document.getElementById("modal_delete").addEventListener("click", async (ev) => {
+    ev.preventDefault();
+    if (!confirm("Delete this photo?")) return;
+    await apiGet(`/api/delete?name=${encodeURIComponent(name)}`);
+    closeModal();
+    await renderPhotos();
+  });
+  modal.style.display = "flex";
+}
+
+function closeModal() {
+  const modal = document.getElementById("preview_modal");
+  if (modal) modal.style.display = "none";
+}
+
+window.addEventListener("load", () => {
+  bindTopActions();
+  const modalClose = document.getElementById("modal_close");
+  if (modalClose) modalClose.addEventListener("click", closeModal);
+  renderControls().catch((e) => {
+    const ctrl = document.getElementById("controls");
+    if (ctrl) ctrl.innerHTML = `<div class="panel"><div class="status-box">Dashboard load failed\n${escapeHtml(e.message)}</div></div>`;
+  });
+  renderPhotos().catch(() => {});
+});
+
+window.addEventListener("beforeunload", () => {
+  if (window.__dashboardPoll) clearInterval(window.__dashboardPoll);
+  if (window.__previewEnabled) setPreviewEnabled(false);
+});
+
+async function openScriptsModal() {
+  const modal = document.getElementById("scripts_modal");
+  const list = document.getElementById("scripts_list");
+  const editor = document.getElementById("script_editor");
+  const fname = document.getElementById("script_filename");
+  list.innerHTML = "Loading...";
+  try {
+    const r = await apiGet("/api/scripts");
+    if ((r.scripts || []).length === 0) {
+      list.innerHTML = "<i>No scripts</i>";
+    } else {
+      list.innerHTML = "";
+      r.scripts.forEach((s) => {
+        const row = document.createElement("div");
+        row.className = "script-row";
+        row.innerHTML = `<b>${escapeHtml(s)}</b> &nbsp; <button class="btn-secondary btn-small" data-name="${escapeHtml(s)}" data-act="set">Set</button> <button class="btn-secondary btn-small" data-name="${escapeHtml(s)}" data-act="edit">Edit</button> <button class="btn-danger btn-small" data-name="${escapeHtml(s)}" data-act="del">Delete</button>`;
+        list.appendChild(row);
+      });
+      list.querySelectorAll("button").forEach((btn) => {
+        btn.addEventListener("click", async () => {
+          const act = btn.getAttribute("data-act");
+          const name = btn.getAttribute("data-name");
+          if (act === "set") {
+            await fetch("/api/set_sanad_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ name }) });
+            alert(`Set as active: ${name}`);
+          } else if (act === "del") {
+            if (!confirm(`Delete script ${name}?`)) return;
+            await fetch("/api/delete_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ name }) });
+            await openScriptsModal();
+          } else if (act === "edit") {
+            const r = await apiGet(`/api/script_content?name=${encodeURIComponent(name)}`);
+            if (r.ok) {
+              editor.value = r.script || "";
+              fname.value = name;
+            }
+          }
+        });
+      });
+    }
+  } catch (_e) {
+    list.innerHTML = "<i>Error</i>";
+  }
+
+  try {
+    const a = await apiGet("/api/sanad_script");
+    if (a.ok) editor.value = a.script || "";
+  } catch (_e) {}
+
+  document.getElementById("scripts_modal_close").onclick = () => {
+    modal.style.display = "none";
+  };
+  document.getElementById("script_upload").onclick = async () => {
+    const name = fname.value.trim();
+    const script = editor.value || "";
+    if (!name) {
+      alert("Enter filename");
+      return;
+    }
+    await fetch("/api/upload_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ filename: name, script }) });
+    await openScriptsModal();
+  };
+  document.getElementById("script_save").onclick = async () => {
+    await fetch("/api/sanad_script", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ script: editor.value || "" }) });
+    alert("Saved active SANAD script");
+  };
+
+  modal.style.display = "flex";
+}
diff --git a/Web/style.css b/Web/style.css
new file mode 100644
index 0000000..21fb02a
--- /dev/null
+++ b/Web/style.css
@@ -0,0 +1,730 @@
+:root {
+  --bg: #efe8db;
+  --bg-accent: #d7e0d4;
+  --panel: rgba(249, 248, 244, 0.96);
+  --panel-strong: #fbfaf7;
+  --ink: #1c241f;
+  --muted: #5f675d;
+  --line: rgba(38, 58, 44, 0.14);
+  --line-strong: rgba(32, 58, 44, 0.24);
+  --accent: #255f4a;
+  --accent-2: #8f3b24;
+  --soft: #ecf3ec;
+  --warn: #8b3120;
+  --shadow: 0 22px 50px rgba(24, 34, 26, 0.10);
+}
+
+* {
+  box-sizing: border-box;
+}
+
+body {
+  margin: 0;
+  color: var(--ink);
+  background:
+    radial-gradient(circle at top left, rgba(143, 59, 36, 0.08), transparent 28%),
+    radial-gradient(circle at top right, rgba(37, 95, 74, 0.10), transparent 34%),
+    linear-gradient(180deg, #f4efe4 0%, var(--bg) 46%, #e6ede5 100%);
+  font-family: "Trebuchet MS", "Gill Sans", "Segoe UI", sans-serif;
+}
+
+button,
+input,
+select,
+textarea {
+  font: inherit;
+}
+
+code,
+pre,
+.meta-code {
+  font-family: "IBM Plex Mono", "SFMono-Regular", Consolas, monospace;
+}
+
+.page-shell {
+  max-width: 1560px;
+  margin: 0 auto;
+  padding: 22px 22px 40px;
+}
+
+.topbar {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  gap: 16px;
+  padding: 18px 20px;
+  border: 1px solid var(--line);
+  border-radius: 24px;
+  background: linear-gradient(180deg, rgba(255,255,255,0.72), rgba(249,248,244,0.95));
+  box-shadow: var(--shadow);
+}
+
+.brand-block {
+  display: flex;
+  align-items: center;
+  gap: 14px;
+}
+
+.brand-mark {
+  width: 54px;
+  height: 54px;
+  border-radius: 18px;
+  display: grid;
+  place-items: center;
+  background: linear-gradient(135deg, #214f40, #547a62);
+  color: #f8fbf8;
+  font-weight: 800;
+  letter-spacing: 0.08em;
+}
+
+.eyebrow,
+.panel-eyebrow,
+.section-eyebrow {
+  text-transform: uppercase;
+  letter-spacing: 0.16em;
+  font-size: 11px;
+  color: var(--muted);
+}
+
+.title {
+  font-family: Georgia, "Times New Roman", serif;
+  font-size: 32px;
+  font-weight: 700;
+}
+
+.top-actions {
+  display: flex;
+  flex-wrap: wrap;
+  justify-content: flex-end;
+  gap: 10px;
+}
+
+.btn,
+.btn-secondary,
+.btn-small,
+.btn-danger {
+  appearance: none;
+  border-radius: 999px;
+  border: 1px solid var(--line-strong);
+  padding: 11px 16px;
+  cursor: pointer;
+  transition: transform 0.14s ease, box-shadow 0.14s ease, background 0.14s ease;
+  text-decoration: none;
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  gap: 8px;
+}
+
+.btn:hover,
+.btn-secondary:hover,
+.btn-small:hover,
+.btn-danger:hover,
+button:hover {
+  transform: translateY(-1px);
+}
+
+.btn.primary,
+button.primary,
+.top-actions .btn.primary {
+  background: var(--accent);
+  color: #fff;
+  border-color: var(--accent);
+  box-shadow: 0 12px 24px rgba(37, 95, 74, 0.22);
+}
+
+.btn.ghost,
+.btn-secondary,
+button.ghost {
+  background: rgba(255,255,255,0.82);
+  color: var(--accent);
+}
+
+.btn.danger,
+.btn-danger,
+button.danger {
+  background: rgba(255,255,255,0.82);
+  color: var(--warn);
+  border-color: rgba(139, 49, 32, 0.3);
+}
+
+.meta-strip {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 12px;
+  margin: 16px 0 20px;
+}
+
+.meta-pill {
+  background: rgba(255,255,255,0.7);
+  border: 1px solid var(--line);
+  color: var(--muted);
+  padding: 10px 14px;
+  border-radius: 999px;
+}
+
+.dashboard-layout {
+  display: grid;
+  grid-template-columns: minmax(0, 1.5fr) minmax(320px, 0.9fr);
+  gap: 22px;
+  align-items: start;
+}
+
+.dashboard-main,
+.dashboard-side {
+  min-width: 0;
+}
+
+.dashboard-side {
+  display: grid;
+  gap: 22px;
+}
+
+.dashboard-stack,
+.status-grid,
+.control-grid,
+.camera-grid {
+  display: grid;
+  gap: 18px;
+}
+
+.control-grid {
+  grid-template-columns: repeat(2, minmax(0, 1fr));
+}
+
+.camera-grid {
+  grid-template-columns: minmax(0, 1.25fr) minmax(320px, 0.95fr);
+}
+
+.status-grid {
+  grid-template-columns: repeat(2, minmax(0, 1fr));
+}
+
+.panel {
+  background: var(--panel);
+  border: 1px solid var(--line);
+  border-radius: 24px;
+  padding: 18px;
+  box-shadow: var(--shadow);
+  min-width: 0;
+}
+
+.panel.strong {
+  background: linear-gradient(180deg, rgba(255,255,255,0.88), var(--panel-strong));
+}
+
+.panel-header {
+  display: flex;
+  justify-content: space-between;
+  align-items: flex-start;
+  gap: 12px;
+  margin-bottom: 12px;
+}
+
+.panel-header h2,
+.panel-header h3,
+.panel h4,
+.panel h3 {
+  margin: 0;
+  font-family: Georgia, "Times New Roman", serif;
+}
+
+.panel-copy,
+.meta,
+.subtle {
+  color: var(--muted);
+}
+
+.preview-shell {
+  position: relative;
+  overflow: hidden;
+  border-radius: 20px;
+  border: 1px solid var(--line);
+  background:
+    radial-gradient(circle at top left, rgba(37,95,74,0.12), transparent 28%),
+    linear-gradient(180deg, #dde8df 0%, #cfd9cc 100%);
+}
+
+.preview-shell::after {
+  content: "";
+  position: absolute;
+  inset: 0;
+  background: linear-gradient(180deg, transparent 0%, rgba(18, 28, 22, 0.10) 100%);
+  pointer-events: none;
+}
+
+.camera-preview {
+  width: 100%;
+  display: none;
+  aspect-ratio: 4 / 3;
+  object-fit: cover;
+  background: #d6ded3;
+}
+
+.preview-placeholder {
+  display: grid;
+  place-items: center;
+  aspect-ratio: 4 / 3;
+  color: var(--muted);
+  text-align: center;
+  padding: 20px;
+}
+
+.preview-toolbar,
+.inline-actions,
+.action-row,
+.resolution-row,
+.selector-row {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+  align-items: center;
+}
+
+.selector-row select,
+.resolution-row select,
+.selector-row input,
+.resolution-row input {
+  min-width: 110px;
+  max-width: 100%;
+}
+
+select,
+input,
+textarea {
+  appearance: none;
+  border: 1px solid var(--line-strong);
+  border-radius: 999px;
+  padding: 11px 14px;
+  background: rgba(255,255,255,0.9);
+  color: var(--ink);
+}
+
+textarea.script-editor {
+  width: 100%;
+  height: 260px;
+  margin-top: 6px;
+  border-radius: 18px;
+  font-family: "IBM Plex Mono", Consolas, monospace;
+}
+
+.status-box,
+.info-box,
+.raw-box {
+  margin-top: 12px;
+  padding: 14px;
+  border-radius: 18px;
+  border: 1px solid var(--line);
+  background: linear-gradient(180deg, rgba(255,255,255,0.62), rgba(236,243,236,0.92));
+}
+
+.status-box {
+  white-space: pre-wrap;
+}
+
+.raw-box {
+  white-space: pre-wrap;
+  overflow: auto;
+  max-height: 260px;
+}
+
+.info-grid {
+  display: grid;
+  grid-template-columns: repeat(2, minmax(0, 1fr));
+  gap: 10px 14px;
+}
+
+.stat-line {
+  display: flex;
+  justify-content: space-between;
+  gap: 12px;
+  color: var(--muted);
+  padding-bottom: 6px;
+  border-bottom: 1px dashed rgba(38, 58, 44, 0.12);
+}
+
+.stat-line b {
+  color: var(--ink);
+  text-align: right;
+}
+
+.chip-row {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 8px;
+  margin-top: 10px;
+}
+
+.chip {
+  display: inline-flex;
+  align-items: center;
+  gap: 8px;
+  border-radius: 999px;
+  padding: 8px 12px;
+  background: rgba(255,255,255,0.78);
+  border: 1px solid var(--line);
+  color: var(--muted);
+}
+
+.chip strong {
+  color: var(--ink);
+}
+
+.replay-list {
+  display: grid;
+  gap: 12px;
+}
+
+.audio-prompt-grid {
+  display: grid;
+  grid-template-columns: repeat(auto-fill, minmax(280px, 1fr));
+  gap: 14px;
+}
+
+.audio-prompt-recorder {
+  display: grid;
+  gap: 12px;
+  padding: 14px;
+  margin: 14px 0;
+  border-radius: 18px;
+  border: 1px solid var(--line);
+  background: rgba(255,255,255,0.58);
+}
+
+.audio-prompt-card {
+  display: grid;
+  gap: 12px;
+  padding: 16px;
+  border-radius: 20px;
+  border: 1px solid var(--line);
+  background: rgba(255,255,255,0.74);
+  box-shadow: 0 12px 24px rgba(24, 34, 26, 0.06);
+}
+
+.audio-prompt-card.ready {
+  background: linear-gradient(180deg, rgba(236,243,236,0.98), rgba(255,255,255,0.92));
+}
+
+.audio-prompt-head {
+  display: flex;
+  justify-content: space-between;
+  gap: 12px;
+  align-items: flex-start;
+}
+
+.audio-prompt-title {
+  font-weight: 800;
+  font-size: 15px;
+}
+
+.audio-prompt-key {
+  margin-top: 4px;
+  color: var(--muted);
+  font-size: 12px;
+  font-family: "IBM Plex Mono", "SFMono-Regular", Consolas, monospace;
+}
+
+.audio-prompt-text {
+  padding: 12px 14px;
+  border-radius: 16px;
+  background: rgba(255,255,255,0.84);
+  border: 1px dashed rgba(38, 58, 44, 0.14);
+  color: var(--ink);
+  line-height: 1.45;
+}
+
+.audio-prompt-meta {
+  color: var(--muted);
+  font-size: 13px;
+  line-height: 1.5;
+}
+
+.audio-prompt-actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 8px;
+}
+
+.audio-prompt-actions .btn {
+  padding: 8px 12px;
+  font-size: 13px;
+}
+
+.prompt-editor {
+  width: 100%;
+  min-height: 112px;
+  resize: vertical;
+  border-radius: 18px;
+  border: 1px solid var(--line-strong);
+  padding: 12px 14px;
+  background: rgba(255,255,255,0.88);
+  color: var(--ink);
+}
+
+.replay-row {
+  display: grid;
+  grid-template-columns: minmax(0, 1fr) auto auto;
+  gap: 12px;
+  align-items: center;
+  padding: 14px 16px;
+  border-radius: 18px;
+  border: 1px solid var(--line);
+  background: rgba(255,255,255,0.72);
+}
+
+.replay-row.active {
+  border-color: rgba(37, 95, 74, 0.32);
+  background: linear-gradient(180deg, rgba(236,243,236,0.98), rgba(255,255,255,0.92));
+}
+
+.replay-main {
+  min-width: 0;
+}
+
+.replay-title {
+  font-weight: 700;
+  overflow-wrap: anywhere;
+}
+
+.replay-meta {
+  margin-top: 4px;
+  color: var(--muted);
+  font-size: 13px;
+}
+
+.replay-tags,
+.replay-row-actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 8px;
+  align-items: center;
+  justify-content: flex-end;
+}
+
+.replay-tag {
+  display: inline-flex;
+  align-items: center;
+  border-radius: 999px;
+  padding: 6px 10px;
+  font-size: 12px;
+  line-height: 1;
+  background: rgba(255,255,255,0.9);
+  border: 1px solid var(--line);
+  color: var(--muted);
+}
+
+.replay-tag.active {
+  background: rgba(37, 95, 74, 0.12);
+  border-color: rgba(37, 95, 74, 0.28);
+  color: var(--accent);
+}
+
+.replay-tag.warn {
+  background: rgba(139, 49, 32, 0.08);
+  border-color: rgba(139, 49, 32, 0.24);
+  color: var(--warn);
+}
+
+.cards-grid {
+  display: grid;
+  grid-template-columns: repeat(auto-fill, minmax(230px, 1fr));
+  gap: 16px;
+}
+
+.people-grid {
+  display: grid;
+  gap: 14px;
+  grid-template-columns: repeat(auto-fill, minmax(250px, 1fr));
+}
+
+.person-card {
+  background: linear-gradient(180deg, rgba(255,255,255,0.78), rgba(236,243,236,0.94));
+  border: 1px solid var(--line);
+  border-radius: 22px;
+  overflow: hidden;
+  box-shadow: 0 12px 26px rgba(24, 34, 26, 0.08);
+}
+
+.person-card-head {
+  display: grid;
+  grid-template-columns: 1fr 1fr;
+  gap: 1px;
+  background: rgba(38, 58, 44, 0.08);
+}
+
+.person-card-head img {
+  width: 100%;
+  aspect-ratio: 1 / 1;
+  object-fit: cover;
+  display: block;
+  background: #d7dfd5;
+}
+
+.person-card-body {
+  padding: 14px;
+  display: grid;
+  gap: 10px;
+}
+
+.person-title {
+  font-weight: 800;
+  font-size: 15px;
+  line-height: 1.3;
+  overflow-wrap: anywhere;
+}
+
+.person-meta {
+  color: var(--muted);
+  font-size: 13px;
+  white-space: pre-wrap;
+}
+
+.person-actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 8px;
+}
+
+.person-actions .btn,
+.person-actions .btn-secondary,
+.person-actions .btn-danger {
+  padding: 8px 12px;
+  font-size: 13px;
+}
+
+.card {
+  background: rgba(255,255,255,0.72);
+  border: 1px solid var(--line);
+  border-radius: 20px;
+  overflow: hidden;
+  box-shadow: 0 12px 24px rgba(24, 34, 26, 0.07);
+}
+
+.card .thumb {
+  width: 100%;
+  aspect-ratio: 4 / 3;
+  object-fit: cover;
+  display: block;
+  cursor: pointer;
+  background: #d7dfd5;
+}
+
+.card-body {
+  padding: 14px;
+}
+
+.card .name {
+  font-weight: 700;
+  font-size: 14px;
+  overflow-wrap: anywhere;
+}
+
+.photo-meta {
+  margin-top: 8px;
+  color: var(--muted);
+  font-size: 13px;
+}
+
+.actions,
+.modal-actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+  margin-top: 12px;
+}
+
+.actions a,
+.modal-actions a {
+  color: var(--accent);
+  text-decoration: none;
+}
+
+.modal {
+  position: fixed;
+  inset: 0;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  padding: 20px;
+  background: rgba(10, 18, 13, 0.62);
+  backdrop-filter: blur(8px);
+}
+
+.modal-content {
+  position: relative;
+  width: min(960px, 100%);
+  max-height: 92vh;
+  overflow: auto;
+  background: #fbfaf7;
+  border-radius: 24px;
+  padding: 18px;
+  box-shadow: 0 30px 60px rgba(0,0,0,0.24);
+}
+
+.modal-content img {
+  width: 100%;
+  border-radius: 18px;
+}
+
+.modal-wide {
+  width: min(1000px, 100%);
+}
+
+.modal-close {
+  position: absolute;
+  top: 14px;
+  right: 14px;
+  width: 38px;
+  height: 38px;
+  border-radius: 50%;
+  border: 1px solid var(--line);
+  background: rgba(255,255,255,0.92);
+  cursor: pointer;
+}
+
+.script-row {
+  display: block;
+}
+
+@media (max-width: 1180px) {
+  .dashboard-layout,
+  .camera-grid {
+    grid-template-columns: 1fr;
+  }
+}
+
+@media (max-width: 860px) {
+  .topbar,
+  .panel-header,
+  .selector-row,
+  .resolution-row,
+  .preview-toolbar,
+  .action-row,
+  .top-actions {
+    flex-direction: column;
+    align-items: stretch;
+  }
+
+  .control-grid,
+  .status-grid,
+  .info-grid {
+    grid-template-columns: 1fr;
+  }
+
+  .page-shell {
+    padding: 14px 14px 28px;
+  }
+
+  .title {
+    font-size: 24px;
+  }
+
+  .replay-row {
+    grid-template-columns: 1fr;
+  }
+
+  .replay-tags,
+  .replay-row-actions {
+    justify-content: flex-start;
+  }
+}
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..2c360f9
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,10 @@
+requests>=2.31.0
+boto3>=1.34.0
+websockets>=12.0
+pyzmq>=25.1.0
+Pillow>=10.0.0
+numpy>=1.24.0
+opencv-python>=4.8.0
+ultralytics>=8.3.0
+PyAudio>=0.2.13
+google-generativeai>=0.8.0