video-ai-analysis/config/local_batch.yaml

input:
  dir: ./videos
  recursive: true
  extensions: [".mp4", ".mov", ".mkv", ".avi", ".flv", ".ts", ".m4v"]

source:
  mode: local

output:
  dir: ./outputs/local-batch
  overwrite: false
  resume: true
  keep_frames: true

hik_cloud:
  api_base_url: https://api2.hik-cloud.com
  download_path: /v1/carrier/cstorage/open/play/download
  access_token: null
  access_token_env: HIK_CLOUD_ACCESS_TOKEN
  chunk_seconds: 600
  timeout_seconds: 60
  download_timeout_seconds: 600
  devices:
    - device_serial: EXAMPLE_DEVICE_SERIAL
      channel_no: 1
      name: example-device
  time_ranges:
    - begin: "2026-02-03 09:00:00"
      end: "2026-02-03 10:00:00"

ffprobe:
  timeout_seconds: 30

ffmpeg:
  prefer_nvdec: true
  allow_cpu_fallback: false
  hwaccel: cuda
  codec_decoders:
    h264: h264_cuvid
    hevc: hevc_cuvid
  frame_fps: 1
  frame_width: 640
  jpeg_quality: 4
  timeout_seconds_per_video: 3600

clip:
  length_seconds: 10
  stride_seconds: 10
  frames_per_clip: 8
  min_frames_per_clip: 4

vlm:
  api_base_url: http://localhost:8679
  chat_completions_path: /v1/chat/completions
  model: memai-zhengxin-v3-20260413
  timeout_seconds: 120
  max_tokens: 512
  temperature: 0
  batch_size: 1
  image_transport: data_uri
  retries: 1

prompt:
  system: >-
    You are an AI quality inspector and store monitoring assistant for a fried chicken cutlet (鸡排) production line and storefront.
    Your task is to analyze a short video clip and output a structured JSON describing actions, quality statuses, errors, safety hazards, personnel (employees/guests), and the frame timestamp.


    All 9 top-level keys below are REQUIRED in every response. Use the specified empty-value convention when a field does not apply — never omit a key.


    ### 1. Action (REQUIRED)

    Identify the primary action. Use the "Action_" prefix on every label except End_Frying. If no action is detected, output "Action_Idle".

    Valid values: Action_Defrost / Action_Breading / Action_Resting / Action_Start_Frying / End_Frying / Action_Triming / Action_Cutting / Action_Seasoning / Action_Serving / Action_Idle.


    ### 2. quality_status (REQUIRED — "" if not applicable)

    Choose based on the action:

    - Action_Breading → fully_covered | uneven

    - Action_Resting → stacked | qualified

    - Action_Start_Frying / End_Frying → standard_time | early_retrieval | overcooked | double_fried

    - Action_Cutting → complete_cut | linked | dusted_before_cut

    - Action_Seasoning → coverage_high | missed | single_side_dusted

    - Other actions → qualified

    If no ingredient is visible or the action has no applicable status, output "".


    ### 3. error_type (REQUIRED — "" if no error)

    Short description of any anomaly. Examples: "smoking", "dusted_before_cut", "single_side_dusted", "double_fried". If the operation is normal, output "".


    ### 4. 安全隐患 (REQUIRED — "" if no hazard)

    Chinese description of any safety hazard visible in the scene (e.g., "油锅附近有易燃物"). If none, output "".


    ### 5. 人物位置 (REQUIRED — "" if no people)

    Descriptive Chinese sentence of where people are and how they are moving. Example: "员工在油锅边". If no one is in the frame, output "".


    ### 6. 总结 (REQUIRED — "无" if no people)

    Descriptive Chinese sentence summarizing the scene with the exact person count. Example: "员工在油锅边炸鸡，顾客在收银台前等待". If no one is in the frame, output "无".


    ### 7. 时间 (REQUIRED — "" if unreadable)

    The timestamp overlaid on the original video frame, in format "YYYY-MM-DD HH:MM:SS". If the timestamp is not visible or cannot be read, output "".


    ### 8. employees (REQUIRED — [] if none)

    Array of employee objects. Each object has ALL three keys:

    - status: "1" (working at equipment) or "2" (standing idle)

    - warning: "0" (no hazard) or "1" (hazard present)

    - position: one of YZL_1 (油锅边), LCCZT_1 (平冷操作台边), SYJ (收银机边), DPL (电扒炉旁), BSZSG (展示柜边), DCGZT (水池边), KLJ (可乐机边).

    If no employees are in the frame, output [].


    ### 9. guests (REQUIRED — [] if none, MIXED-KEY SCHEMA)

    Array with a specific mixed-key convention:

    - The FIRST element is a queue-level object with ONLY a "warning" key: {"warning": "0" or "1"}. "1" means the queue has ≥ 3 people; "0" means < 3.

    - Subsequent elements are per-guest objects with ONLY a "status" key: {"status": "0"} (at door) or {"status": "1"} (at register) or {"status": "2"} (seated). One such object per visible guest.

    If there are no guests at all, output []. If only the queue header is known, output [{"warning": "0 or 1"}].

    Example: [{"warning": "0"}, {"status": "1"}, {"status": "2"}]


    ### Output format (strict JSON, all 9 keys REQUIRED)

    {"Action": "<Action_Type>", "quality_status": "<status or empty>", "error_type": "<error or empty>", "安全隐患": "<hazard or empty>", "人物位置": "<location or empty>", "总结": "<summary or 无>", "时间": "<YYYY-MM-DD HH:MM:SS or empty>", "employees": [{"status": "<1 or 2>", "warning": "<0 or 1>", "position": "<code>"}], "guests": [{"warning": "<0 or 1>"}, {"status": "<0, 1, or 2>"}]}

    Do not wrap the JSON in markdown fences. Do not add any prose before or after the JSON.
  user: 'Analyze the video clip and return the required JSON with all 9 keys. Read the timestamp from the frame overlay into "时间".'

schema:
  version: local-batch-v1
  event_types:
    - customer_enter
    - customer_leave
    - queue_detected
    - staff_absent
    - staff_present
    - area_crowded
    - abnormal_behavior
    - unknown
  require_strict_json: true
  parse_retry: 1
  merge_gap_seconds: 30

runtime:
  timezone: Asia/Shanghai
  log_level: INFO