runtime/config.example.yml

# =============================================================================
# MBFS Sentinel - Configuration Template
# =============================================================================
#
# Usage:
#   1. Copy this file to config.yml:    cp config.example.yml config.yml
#   2. Update values to match your environment
#   3. Restart mbfs-sentinel to apply changes
#
# Notes:
#   - All paths can be relative (to the executable) or absolute
#   - Durations use seconds unless noted otherwise
#   - Set 'enabled: true' on any plugin you want to activate
#
# =============================================================================


# =============================================================================
# General Settings
# =============================================================================
general:
  project_name: MBFS Sentinel       # Display name shown in UI and logs
  port: 8003                        # HTTP API port (Axum server)
  dev_mode: false                   # Enable development mode (extra logging, relaxed checks)
  device_id: c9869e48ab4a2341fe4e08587b20d6c402da59ce2e26d934b9d3d6d503e0bd5a  # Unique device identifier (from mbfs-mv-core)

# =============================================================================
# Database (PostgreSQL + pgvector)
# =============================================================================
database:
  # PostgreSQL connection URL
  # Format: postgresql://user:password@host:port/database?sslmode=disable
  url: "postgresql://root:123123@localhost:5434/dev?sslmode=disable"

  # Secret key for signing JWT tokens (MUST change in production!)
  secret_key: "secret"

# =============================================================================
# MinIO Storage (S3-compatible object storage)
# =============================================================================
# Used for storing face crops, event snapshots, evidence images/videos.
# Any S3-compatible service can be used (AWS S3, MinIO, etc.)
# =============================================================================
minio:
  endpoint: "localhost:9000"        # MinIO server host:port
  access_key: "minioadmin"          # Access key (username)
  secret_key: "minioadmin"          # Secret key (password)
  bucket: "mbfs-sentinel"           # Bucket name for all stored objects
  secure: false                     # Use TLS/SSL connection (true for HTTPS)
  url: http://localhost:9000        # Public-facing URL for generating download links

# =============================================================================
# AI Models
# =============================================================================
# Directory and filenames for core ONNX models (face detection & recognition).
# Plugin-specific models are configured in their respective sections below.
# =============================================================================
models:
  dir: './models'                              # Path to model files directory
  detection_name: ""    # Face detection model (RetinaFace)
  recognition_name: ""  # Face recognition/embedding model (ArcFace)

# =============================================================================
# Batch Processing
# =============================================================================
# Controls how frames are batched before inference to maximize GPU throughput.
# Larger batches = higher throughput but more latency and VRAM usage.
# =============================================================================
batch:
  detection_size: 24              # Face detection batch size (frames per batch)
  recognition_size: 96            # Face recognition batch size (face crops per batch)
  collection_timeout_ms: 100      # Max wait time to fill a batch before processing (ms)

# =============================================================================
# Worker Threads
# =============================================================================
workers:
  num_ai: 3                       # Number of AI inference worker threads
  upload: 24                      # Number of upload worker threads (MinIO/S3)

# =============================================================================
# Face Tracking
# =============================================================================
# Settings for tracking detected faces across consecutive frames.
# Used by face recognition to maintain identity continuity.
# =============================================================================
tracking:
  high_confidence_threshold: 0.65 # Min confidence for a high-quality face match
  timeout: 2.0                    # Seconds before a tracked face expires (no re-detection)
  similarity: 0.55                # Cosine similarity threshold for re-identification
  log_cooldown: 3.0               # Min seconds between logging the same face identity
  min_detections: 2               # Min detection count before a face is logged as event

# =============================================================================
# Image Upload
# =============================================================================
upload:
  queue_max_size: 100             # Max pending uploads in queue (overflow is dropped)
  jpeg_quality: 70                # JPEG compression quality for uploaded images (0-100)

# =============================================================================
# Camera Manager
# =============================================================================
# Connection to the external camera management service.
# Sentinel periodically sends a survival signal to indicate it is alive.
# =============================================================================
camera_manager:
  url: http://localhost:8000                # Camera manager API base URL
  survival_signal_interval: 10              # Interval in seconds for survival heartbeat

# =============================================================================
# Core AI Node (Cluster mode)
# =============================================================================
# URL of the central AI node when running in distributed/cluster mode.
# =============================================================================
core_ai:
  url: http://10.8.0.3:8003

# =============================================================================
# TensorRT Configuration
# =============================================================================
# TensorRT engine caching speeds up model loading after first run.
# Engine files are GPU-specific and will be rebuilt if hardware changes.
# =============================================================================
tensorrt:
  enabled: true                   # false = skip TensorRT, use CUDA (faster startup, slower inference)
  cache_dir: trt_cache            # Directory for cached TensorRT engine files
  lib_dir: null                   # Custom TensorRT library path (null = system default)

# =============================================================================
# License
# =============================================================================
license:
  key: ''                         # License key (obtained from license server)
  active_key: ''                  # Active license key (set after successful activation)

license_server:
  url: https://ai-mv-core.mbfs.com.vn      # License server URL
  check_interval_secs: 86400                # License recheck interval (86400 = 24 hours)

# =============================================================================
# Processing Loop
# =============================================================================
# Low-level tuning for the frame processing pipeline.
# Default values work well for most setups. Only adjust if needed.
# =============================================================================
processing:
  max_batch_size: 24              # Max frames per processing batch
  loop_sleep_ms: 10               # Sleep between processing loops (ms)
  channel_buffer_size: 256        # Channel buffer for frame pipeline
  face_log_queue_size: 256        # Face event logging queue size
  face_log_workers: 2             # Face event logging worker threads
  dispatch_max_fps: 15            # Default max dispatch rate per pipeline runner (fps).
                                  # Coordinator drops batches dispatched faster than this
                                  # to avoid wasting Arc clones + mutex contention on frames
                                  # the runner can't keep up with. Camera decode rate is
                                  # capped separately at 15fps in mbfs-camera.
                                  # Plugins can override per-plugin via manifest.toml:
                                  #   [runtime]
                                  #   max_fps = 8


# =============================================================================
# Plugins - AI Pipeline Configurations
# =============================================================================
#
# Each plugin can be independently enabled/disabled. Common sub-sections:
#
#   enabled        - Whether the plugin is active (true/false)
#   confidence     - Min detection confidence threshold (0.0 - 1.0)
#   nms_threshold  - Non-Maximum Suppression IoU threshold (0.0 - 1.0)
#
#   tracking:      - ByteTrack multi-object tracker settings
#     enabled                - Enable/disable object tracking
#     high_conf_threshold    - High confidence detection threshold
#     low_conf_threshold     - Low confidence detection threshold
#     confirm_frames         - Frames needed to confirm a new track
#     max_lost_frames        - Max frames before a lost track is removed
#
#   alert:         - Alert system settings (consecutive detection triggers)
#     consecutive_threshold  - Consecutive detections needed to trigger alert
#     max_miss               - Max missed frames before resetting alert counter
#     cooldown_secs          - Cooldown between alerts for the same object
#
#   data_lake:     - Event storage configuration
#     enabled          - Enable event logging
#     bucket_prefix    - MinIO bucket prefix for this plugin's events
#     min_count        - Min detection count before saving event
#     jpeg_quality     - JPEG quality for event snapshots (0-100)
#     queue_size       - Event processing queue size
#     workers          - Number of event processing workers
#     batch_size       - Events per batch write
#     parquet_enabled  - Enable Parquet file export
#     parquet_batch_size - Rows per Parquet batch
#     save_json        - Save raw JSON alongside Parquet
#     db_enabled       - Write events to PostgreSQL
#     db_batch_size    - DB insert batch size
#     db_batch_timeout_ms - Max wait before flushing DB batch (ms)
#     db_channel_size  - DB write channel buffer size
#     save_crops       - Save cropped detection images to MinIO
#     crop_jpeg_quality - JPEG quality for crop images (0-100)
#
#   dedup:         - Deduplication settings (prevent duplicate events)
#     cooldown_seconds             - Min seconds between events for same object
#     grid_size                    - Spatial grid cell size for position-based dedup
#     high_confidence_threshold    - Confidence above which dedup is stricter
#     significant_count_threshold  - Detection count to consider object significant
#     max_tracked_per_camera       - Max tracked objects per camera for dedup
#
# =============================================================================
plugins:

  # ---------------------------------------------------------------------------
  # Shared Models
  # ---------------------------------------------------------------------------
  # Model files referenced by multiple plugins. Avoids duplicating filenames.
  # These are loaded once and shared across plugins that need them.
  # ---------------------------------------------------------------------------
  shared_models:
    detection_model: det_10g_fp16_dynamic.onnx.enc      # Face detection (RetinaFace)
    recognition_model: mbfs_rec_vit_b_v3.onnx.enc       # Face recognition (ViT)
    human_detection_model: mbfs_human_det_v4.onnx       # Human/person detection (YOLO)
    helmet_model: helmet_dt_v10.onnx                    # Helmet detection
    lpr_detection_model: lp_detection_v4.onnx           # License plate detection
    lpr_ocr_model: mbfs_ocr_license_plate_b16_v5.onnx  # License plate OCR
    vehicle_model: yolov8_coco.onnx                     # Vehicle detection (COCO classes)

  # ---------------------------------------------------------------------------
  # Face Recognition (builtin)
  # ---------------------------------------------------------------------------
  # Detects faces, extracts embeddings, and matches against enrolled identities.
  # Requires: detection_model + recognition_model from shared_models.
  # ---------------------------------------------------------------------------
  face_recognition:
    enabled: false
    min_detection_score: 0.7              # Min face detection confidence
    min_size: 32                          # Min face size in pixels (width or height)
    min_ratio: 0.0001                     # Min face area ratio relative to frame
    unknown_min_score: 0.50               # Min score to classify as "unknown" (below = discard)
    enrollment_min_detection_score: 0.7   # Stricter detection threshold for face enrollment
    enrollment_min_size: 100              # Min face size for enrollment (px)
    enrollment_max_angle: 15.0            # Max yaw/pitch angle for enrollment (degrees)
    data_lake:
      enabled: true
      bucket_prefix: face-recognition-events
      min_count: 1
      jpeg_quality: 85
      queue_size: 512
      workers: 1
      batch_size: 16
      parquet_enabled: true
      parquet_batch_size: 1000
      save_json: false
      db_enabled: true
      db_batch_size: 32
      db_batch_timeout_ms: 100
      db_channel_size: 512
      save_crops: true
      crop_jpeg_quality: 90
    dedup:
      cooldown_seconds: 5.0
      grid_size: 100.0
      high_confidence_threshold: 0.65
      significant_count_threshold: 3
      max_tracked_per_camera: 50

  # ===========================================================================
  # Dynamic Plugins
  # ===========================================================================
  # Plugins loaded at runtime from DLLs in the plugins/ directory.
  # Each plugin has a manifest.toml defining its models and capabilities.
  # Config values here override manifest defaults.
  # ===========================================================================
  dynamic_plugins:

    # -------------------------------------------------------------------------
    # Human Detection
    # -------------------------------------------------------------------------
    # Detects humans/persons in the frame. Foundation for many other plugins.
    # Model: human_detection_model from shared_models.
    # -------------------------------------------------------------------------
    human_detection:
      enabled: false
      confidence: 0.75
      nms_threshold: 0.45
      alert:
        consecutive_threshold: 5
        max_miss: 2
        cooldown_secs: 10.0
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: human-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Facial Expression Recognition
    # -------------------------------------------------------------------------
    # Classifies facial expressions (happy, sad, angry, surprised, etc.).
    # Two-stage: face detection -> expression classification.
    # -------------------------------------------------------------------------
    facial_expression:
      enabled: false
      confidence: 0.5
      nms_threshold: 0.45
      alert:
        consecutive_threshold: 5
        max_miss: 2
        cooldown_secs: 10.0
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: facial-expression-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Object Detection (General)
    # -------------------------------------------------------------------------
    # General-purpose object detection using COCO or custom classes.
    # Useful for counting/tracking arbitrary object types.
    # -------------------------------------------------------------------------
    object_detection:
      enabled: false
      confidence: 0.75
      nms_threshold: 0.45
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: object-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Smoke & Fire Detection
    # -------------------------------------------------------------------------
    # Detects smoke and fire in the frame. Triggers alerts when detected
    # consecutively to reduce false positives.
    # -------------------------------------------------------------------------
    smoke_fire_detection:
      enabled: false
      confidence: 0.75
      alert:
        consecutive_threshold: 5          # Consecutive detections to trigger alert
        max_miss: 2                       # Max missed frames before reset
        cooldown_secs: 10.0               # Alert cooldown (seconds)
      data_lake:
        enabled: true
        bucket_prefix: smoke-fire-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Behavior Detection
    # -------------------------------------------------------------------------
    # Detects abnormal behaviors (loitering, falling, running, etc.).
    # Uses human detection + tracking to analyze movement patterns.
    # -------------------------------------------------------------------------
    behavior_detection:
      enabled: false
      confidence: 0.75
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 5                 # Higher confirm frames for behavior analysis
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: behavior-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Helmet Detection
    # -------------------------------------------------------------------------
    # Detects whether people are wearing safety helmets (construction sites, etc.).
    # Triggers alerts for "no helmet" detections.
    # -------------------------------------------------------------------------
    helmet_detection:
      enabled: false
      confidence: 0.75
      alert:
        consecutive_threshold: 5
        max_miss: 2
        cooldown_secs: 10.0
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: helmet-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Weapon Detection
    # -------------------------------------------------------------------------
    # Detects weapons (guns, knives, etc.) in the frame.
    # Lower confidence threshold and shorter cooldown for safety-critical alerts.
    # -------------------------------------------------------------------------
    weapon_detection:
      enabled: false
      confidence: 0.5                     # Lower threshold for safety-critical detection
      nms_threshold: 0.45
      alert:
        consecutive_threshold: 5
        max_miss: 2
        cooldown_secs: 5.0                # Shorter cooldown for urgent alerts
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: weapon-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 5.0             # Longer dedup for weapon events
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Phone Usage Detection
    # -------------------------------------------------------------------------
    # Two-stage: detect humans -> crop -> classify phone usage.
    # Higher confidence threshold to reduce false positives on small objects.
    # -------------------------------------------------------------------------
    phone_usage_detection:
      enabled: false
      confidence: 0.8                     # Higher threshold (small object, prone to FP)
      nms_threshold: 0.45
      crop_padding: 0.1                   # Extra padding around human crop for context
      alert:
        consecutive_threshold: 5
        max_miss: 2
        cooldown_secs: 5.0
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: phone-usage-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 30.0            # Longer cooldown to avoid spam
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Fight Detection
    # -------------------------------------------------------------------------
    # Detects physical fights/altercations between people.
    # Uses pose or interaction analysis on tracked humans.
    # -------------------------------------------------------------------------
    fight_detection:
      enabled: false
      confidence: 0.5
      nms_threshold: 0.45
      alert:
        consecutive_threshold: 5
        max_miss: 2
        cooldown_secs: 5.0
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: fight-detection-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # People Counting (migrated from builtin to dynamic plugin)
    # -------------------------------------------------------------------------
    people_counting:
      enabled: false
      confidence: 0.25
      nms_threshold: 0.45
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: people-counting-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # License Plate Recognition (migrated from builtin to dynamic plugin)
    # -------------------------------------------------------------------------
    license_plate_recognition:
      enabled: false
      confidence: 0.5
      nms_threshold: 0.45
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 2
        max_lost_frames: 15
      data_lake:
        enabled: true
        bucket_prefix: license-plate-recognition-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 10.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

    # -------------------------------------------------------------------------
    # Traffic Violation Detection (migrated from builtin to dynamic plugin)
    # -------------------------------------------------------------------------
    traffic_violation_detection:
      enabled: false
      confidence: 0.5
      nms_threshold: 0.45
      tracking:
        enabled: true
        high_conf_threshold: 0.5
        low_conf_threshold: 0.1
        confirm_frames: 3
        max_lost_frames: 30
      data_lake:
        enabled: true
        bucket_prefix: traffic-violation-events
        min_count: 1
        jpeg_quality: 85
        queue_size: 512
        workers: 2
        batch_size: 16
        parquet_enabled: true
        parquet_batch_size: 1000
        save_json: false
        db_enabled: true
        db_batch_size: 16
        db_batch_timeout_ms: 100
        db_channel_size: 256
        save_crops: true
        crop_jpeg_quality: 90
      dedup:
        cooldown_seconds: 3.0
        grid_size: 100.0
        high_confidence_threshold: 0.75
        significant_count_threshold: 5
        max_tracked_per_camera: 50

# =============================================================================
# Logging
# =============================================================================
logging:
  enabled: true
  dir: logs                       # Log files directory (relative to executable)
  max_days: 7                     # Auto-cleanup logs older than N days