"""
  Query configuration constants.
  
  Since all tenants share the same ES mapping, we can hardcode field lists here.
  """
  
  import os
  from typing import Dict, List
  
  # Default index name
  DEFAULT_INDEX_NAME = "search_products"
  
  # Text embedding field
  TEXT_EMBEDDING_FIELD = "title_embedding"
  
  # Image embedding field
  IMAGE_EMBEDDING_FIELD = "image_embedding"
  
  # Default match fields for text search (with boost)
  DEFAULT_MATCH_FIELDS = [
      "title_zh^3.0",
      "brief_zh^1.5",
      "description_zh^1.0",
      "vendor_zh^1.5",
      "tags^1.0",
      "category_path_zh^1.5",
      "category_name_zh^1.5"
  ]
  
  # Domain-specific match fields
  DOMAIN_FIELDS: Dict[str, List[str]] = {
      "default": DEFAULT_MATCH_FIELDS,
      "title": ["title_zh^2.0"],
      "vendor": ["vendor_zh^1.5"],
      "category": ["category_path_zh^1.5", "category_name_zh^1.5"],
      "tags": ["tags^1.0"]
  }
  
  # Source fields to return in search results

  # 注意：为了在后端做多语言选择，_zh / _en 字段仍然需要从 ES 取出，
  # 但不会原样透出给前端，而是统一映射到 title / description / vendor 等字段。

  SOURCE_FIELDS = [

      # 基本标识

      "tenant_id",
      "spu_id",

      "create_time",
      "update_time",
  
      # 多语言文本字段（仅用于后端选择，不直接返回给前端）

      "title_zh",

      "title_en",

      "brief_zh",

      "brief_en",

      "description_zh",

      "description_en",

      "vendor_zh",

      "vendor_en",

      "category_path_zh",

      "category_path_en",

      "category_name_zh",

      "category_name_en",
  
      # 语言无关字段（直接返回给前端）
      "tags",
      "image_url",

      "category_id",
      "category_name",
      "category_level",
      "category1_name",
      "category2_name",
      "category3_name",
      "option1_name",
      "option2_name",
      "option3_name",
      "min_price",
      "max_price",
      "compare_at_price",

      "sku_prices",
      "sku_weights",
      "sku_weight_units",

      "total_inventory",

      "skus",

      "specifications",

  ]
  
  # Query processing settings
  ENABLE_TRANSLATION = os.environ.get("ENABLE_TRANSLATION", "true").lower() == "true"
  ENABLE_TEXT_EMBEDDING = os.environ.get("ENABLE_TEXT_EMBEDDING", "true").lower() == "true"
  TRANSLATION_API_KEY = os.environ.get("DEEPL_API_KEY")
  TRANSLATION_SERVICE = "deepl"
  
  # Ranking expression (currently disabled)
  RANKING_EXPRESSION = "bm25() + 0.2*text_embedding_relevance()"
  
  # Function score config
  FUNCTION_SCORE_CONFIG = {
      "score_mode": "sum",
      "boost_mode": "multiply",
      "functions": []
  }
  
  # Load rewrite dictionary from file if exists
  def load_rewrite_dictionary() -> Dict[str, str]:
      """Load query rewrite dictionary from file."""
      rewrite_file = os.path.join(
          os.path.dirname(os.path.dirname(__file__)),
          "config",
          "query_rewrite.dict"
      )
      
      if not os.path.exists(rewrite_file):
          return {}
      
      rewrite_dict = {}
      try:
          with open(rewrite_file, 'r', encoding='utf-8') as f:
              for line in f:
                  line = line.strip()
                  if not line or line.startswith('#'):
                      continue
                  parts = line.split('\t')
                  if len(parts) == 2:
                      rewrite_dict[parts[0].strip()] = parts[1].strip()
      except Exception as e:
          print(f"Warning: Failed to load rewrite dictionary: {e}")
      
      return rewrite_dict
  
  REWRITE_DICTIONARY = load_rewrite_dictionary()
  

  # Default facets for faceted search
  # 分类分面：使用category1_name, category2_name, category3_name
  # specifications分面：使用嵌套聚合，按name分组，然后按value聚合
  DEFAULT_FACETS = [
      "category1_name",  # 一级分类
      "category2_name",  # 二级分类
      "category3_name",  # 三级分类
      "specifications"  # 规格分面（特殊处理：嵌套聚合）
  ]