# 可根据loguru的文档配置不同 handlers
logger_conf:
  # 默认输出到控制台的日志级别, 大于等于此级别都会输出
  level: DEBUG
  # 默认输出格式
  format: '[{time:YYYY-MM-DD HH:mm:ss.SSSSSS}] [{level.name} process-{process.id}-{thread.id} {name}:{line}] - trace={extra[trace_id]} {message}'
  # 参考loguru.add()中的参数可以配置多个handler
  handlers:
      # 文件路径，支持插入一些系统环境变量，若环境变量不存在则置空。例如 HOSTNAME: 主机名。后端会处理环境变量的替换
    - sink: "/app/logs/bisheng_uns.log"
      # 日志级别
      level: INFO
      # 和原生不一样，后端会将配置使用eval()执行转为函数用来过滤特定日志级别。推荐lambda
      # filter: "lambda record: record['level'].name == 'INFO'"
      # 日志格式化函数，extra内支持trace_id
      format: "[{time:YYYY-MM-DD HH:mm:ss.SSSSSS}]|{level}|BISHENG|{extra[trace_id]}|{process.id}|{thread.id}|{message}"
      # 每天的几点进行切割
      rotation: "00:00"
      retention: "3 Days"
    - sink: "/app/logs/err-v0-BISHENG-UNS-{HOSTNAME}.log"
      level: ERROR
      filter: "lambda record: record['level'].name == 'ERROR'"
      format: "[{time:YYYY-MM-DD HH:mm:ss.SSSSSS}]|{level}|BISHENG|{extra[trace_id]}||{process.id}|{thread.id}|||#EX_ERR:POS={name},line {line},ERR=500,EMSG={message}"
      rotation: "00:00"
      retention: "3 Days"

# pdf解析需要用到的模型配置, 配置了rt_server环境变量的话会替换为对应的地址
pdf_model_params:
  layout_ep: "http://192.168.106.12:9001/v2.1/models/elem_layout_v1/infer"
  cell_model_ep: "http://192.168.106.12:9001/v2.1/models/elem_table_cell_detect_v1/infer"
  rowcol_model_ep: "http://192.168.106.12:9001/v2.1/models/elem_table_rowcol_detect_v1/infer"
  table_model_ep: "http://192.168.106.12:9001/v2.1/models/elem_table_detect_v1/infer"
  ocr_model_ep: "http://192.168.106.12:9001/v2.1/models/elem_ocr_collection_v3/infer"

# 是否全部走ocr识别, false的话则由代码逻辑判断是否需要走ocr识别
is_all_ocr: false
# ocr识别需要的配置项
ocr_conf:
  params:
    sort_filter_boxes: true,
    enable_huarong_box_adjust: true,
    rotateupright: false,
    support_long_image_segment: true,
    split_long_sentence_blank: true
  scene_mapping:
    print:
      det: general_text_det_mrcnn_v2.0
      recog: transformer-blank-v0.2-faster
    hand:
      det: general_text_det_mrcnn_v2.0
      recog: transformer-hand-v1.16-faster
    print_recog:
      recog: transformer-blank-v0.2-faster
    hand_recog:
      recog: transformer-hand-v1.16-faster
    det:
      det: general_text_det_mrcnn_v2.0