operating-room-monitor-server/.env.example

# Copy to `.env` and adjust. Loaded by pydantic-settings (field names → UPPER_SNAKE_CASE env vars).
# Used by local `start.sh` and Docker Compose. See also docs/video-backends.md.

# --- PostgreSQL ---
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=operation_room
POSTGRES_HOST=localhost
POSTGRES_PORT=35432

# Optional: full async SQLAlchemy URL (overrides POSTGRES_* when set and matches defaults logic — see Settings).
# DATABASE_URL=postgresql+asyncpg://postgres:postgres@localhost:35432/operation_room

# --- YOLO 视觉推理（内部调用，无独立 HTTP）---
# 耗材分类权重默认 app/resources/consumable_classifier.pt；手部检测为空时退化为全帧分类。
# CONSUMABLE_CLASSIFIER_WEIGHTS=/absolute/path/to/consumable_classifier.pt
CONSUMABLE_CLASSIFIER_IMGSZ=224
CONSUMABLE_CLASSIFIER_DEVICE=
# 视觉待确认 options 最多为模型 top3 与 candidate_consumables 的交集（非本变量）。
CONSUMABLE_CLASSIFIER_TOPK=5
# CONSUMABLE_MIN_CLS_CONFIDENCE=0.5
# 时间窗（秒）：窗内多次推理取众数后再走自动记账 / 待确认。
# CONSUMABLE_VISION_WINDOW_SEC=15
# 可选：Excel「商品名称」「产品编码」表；空则物品 id 用名称。
# CONSUMABLE_CATALOG_XLSX_PATH=/path/to/视频中的商品信息表.xlsx
# HAND_DETECTION_WEIGHTS=/absolute/path/to/hand_detect.pt
# HAND_DETECTION_IMGSZ=640
# HAND_DETECTION_CONF=0.25
# HAND_DETECTION_PAD_RATIO=0.30
# HAND_DETECTION_MIN_CROP_PX=64
# HAND_DETECTION_DEVICE=
# Device: empty → auto (macOS MPS if available; Linux CUDA if available). Docker image uses CPU torch unless you change it.

# --- Surgery recording API retries ---
# SURGERY_RECORDING_MAX_ATTEMPTS=3
# SURGERY_RECORDING_RETRY_DELAY_SECONDS=1.0

# --- Video: RTSP + optional Hikvision HCNetSDK (Linux x86_64 + glibc recommended) ---
# Client `camera_ids` must match keys in your RTSP map (sample IDs: or-cam-01, or-cam-02).
#
# VIDEO_DEFAULT_BACKEND=rtsp
# Values: rtsp | hikvision_sdk | auto  (auto: SDK .so loaded and HIKVISION_SDK_ENABLED=true → prefer SDK)
#
# Per-camera backend override (JSON object):
# VIDEO_CAMERA_BACKEND_OVERRIDES_JSON={"or-cam-01":"rtsp","or-cam-02":"hikvision_sdk"}
#
# RTSP URL resolution (first match wins per camera_id):
# 1) VIDEO_RTSP_URLS_JSON_FILE — JSON file: {"or-cam-01":"rtsp://...","or-cam-02":"rtsp://..."}
# 2) merged with VIDEO_RTSP_URLS_JSON (inline JSON string; overrides same keys from file)
# 3) else VIDEO_RTSP_URL_TEMPLATE with {camera_id}
# Example file (committed): app/resources/camera_rtsp_urls.sample.json
# VIDEO_RTSP_URLS_JSON_FILE=app/resources/camera_rtsp_urls.sample.json
# In Docker (WORKDIR /app): VIDEO_RTSP_URLS_JSON_FILE=/app/app/resources/camera_rtsp_urls.sample.json
# WARNING: if VIDEO_RTSP_URLS_JSON_FILE is set but the path is missing, the app will fail to start.
#
# VIDEO_RTSP_URL_TEMPLATE=rtsp://user:pass@192.168.1.64:554/Streaming/Channels/101
# VIDEO_RTSP_URLS_JSON={"or-cam-01":"rtsp://user:pass@192.168.1.101:554/Streaming/Channels/101","or-cam-02":"rtsp://user:pass@192.168.1.102:554/Streaming/Channels/101"}
#
# VIDEO_OPEN_TIMEOUT_SEC=15
# 连续读帧失败次数达到阈值后释放 RTSP 并重连。
# VIDEO_READ_FAILURE_RECONNECT_THRESHOLD=15
# VIDEO_RECONNECT_BACKOFF_SECONDS=1.0
# VIDEO_INFERENCE_INTERVAL_SEC=2
# VIDEO_INFERENCE_CONFIDENCE_THRESHOLD=0.35
# 置信度 >= 此值且命中候选清单时自动 vision 记账。提高到 0.9 可减少自动记账、更多走待确认。
# VIDEO_AUTO_CONFIRM_CONFIDENCE=0.55
# 置信度处于 [VIDEO_VOICE_CONFIRM_MIN_CONFIDENCE, VIDEO_AUTO_CONFIRM_CONFIDENCE) 时入队待确认（客户端拉取 pending-confirmation）。
# VIDEO_VOICE_CONFIRM_MIN_CONFIDENCE=0.35
# 待确认话术由服务端生成（prompt_text），TTS 一般在客户端播放；医生 WAV 上传后服务端 ASR 解析。
# 解析顺序：① pending 里展示的 topk（序号/名称）；② 仍不匹配时，对「开始手术」请求体中的 candidate_consumables 全文做名称子串匹配——医生报清单内其它耗材也以医生为准入账。
# 是否启用低置信度人工确认（客户端播报 + resolve 回传；服务端无麦克风/扬声器要求）。
# VOICE_CONFIRMATION_ENABLED=true
# VIDEO_VOICE_CONFIRM_DOCTOR_ID=voice
# （已弃用）服务端本机录音 / ffmpeg 音频输入；当前闭环不依赖。
# VOICE_RECORD_SECONDS=5
# VOICE_FFMPEG_INPUT=
# 停录后写库失败时，后台重试落库间隔（秒）。
# ARCHIVE_PERSIST_RETRY_INTERVAL_SECONDS=30
# VIDEO_DETAIL_COOLDOWN_SEC=15
# VIDEO_JPEG_QUALITY=85
# VIDEO_RESULT_DOCTOR_ID=vision

# --- Hikvision: mount vendor Linux x86_64 .so at runtime (do not commit proprietary binaries) ---
# HIKVISION_LIB_DIR=/opt/hikvision/lib
# Optional: single library path (overrides directory search in code)
# HIKVISION_LIB_PATH=
# HIKVISION_SDK_ENABLED=false
# HIKVISION_DEVICE_IP=
# HIKVISION_DEVICE_PORT=8000
# HIKVISION_USER=
# HIKVISION_PASSWORD=
# HIKVISION_CHANNEL=1
# After SDK login, OpenCV still pulls frames via RTSP; template placeholders: {ip} {user} {password} {channel} {camera_id}
# HIKVISION_PREVIEW_RTSP_TEMPLATE=rtsp://{user}:{password}@{ip}:554/Streaming/Channels/101
# Per-camera RTSP when using SDK path (same shape as VIDEO_RTSP_URLS_JSON):
# HIKVISION_CAMERA_RTSP_URLS_JSON={"or-cam-01":"rtsp://...","or-cam-02":"rtsp://..."}
# HIKVISION_SDK_FALLBACK_TO_RTSP=true

# --- Baidu Speech（可选，遗留；当前手术闭环由客户端完成 TTS/ASR，服务端可不配置）---
# BAIDU_SPEECH_APP_ID=
# BAIDU_SPEECH_API_KEY=
# BAIDU_SPEECH_SECRET_KEY=
# BAIDU_SPEECH_CONNECTION_TIMEOUT_MS=
# BAIDU_SPEECH_SOCKET_TIMEOUT_MS=