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api/models.py 14.4 KB
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  """
  Request and response models for the API.
  """
  
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  from pydantic import BaseModel, Field, field_validator
  from typing import List, Dict, Any, Optional, Union, Literal
  
  
  class RangeFilter(BaseModel):
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      """范围过滤器(支持数值和日期时间字符串)"""
      gte: Optional[Union[float, str]] = Field(None, description="大于等于 (>=)。数值或ISO日期时间字符串")
      gt: Optional[Union[float, str]] = Field(None, description="大于 (>)。数值或ISO日期时间字符串")
      lte: Optional[Union[float, str]] = Field(None, description="小于等于 (<=)。数值或ISO日期时间字符串")
      lt: Optional[Union[float, str]] = Field(None, description="小于 (<)。数值或ISO日期时间字符串")
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      def model_post_init(self, __context):
          """确保至少指定一个边界值"""
          if not any([self.gte, self.gt, self.lte, self.lt]):
              raise ValueError('至少需要指定一个范围边界(gte, gt, lte, lt)')
      
      class Config:
          json_schema_extra = {
              "examples": [
                  {"gte": 50, "lte": 200},
                  {"gt": 100},
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                  {"lt": 50},
                  {"gte": "2023-01-01T00:00:00Z"}
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              ]
          }
  
  
  class FacetConfig(BaseModel):
      """分面配置(简化版)"""
      field: str = Field(..., description="分面字段名")
      size: int = Field(10, ge=1, le=100, description="返回的分面值数量")
      type: Literal["terms", "range"] = Field("terms", description="分面类型")
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      multi_select: bool = Field(
          True,
          description="是否支持多选(disjunctive faceting)。启用后,选中该分面的过滤器时,仍会显示其他可选项"
      )
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      ranges: Optional[List[Dict[str, Any]]] = Field(
          None,
          description="范围分面的范围定义(仅当 type='range' 时需要)"
      )
      
      class Config:
          json_schema_extra = {
              "examples": [
                  {
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                      "field": "category.keyword",
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                      "size": 15,
                      "type": "terms"
                  },
                  {
                      "field": "price",
                      "size": 4,
                      "type": "range",
                      "ranges": [
                          {"key": "0-50", "to": 50},
                          {"key": "50-100", "from": 50, "to": 100},
                          {"key": "100-200", "from": 100, "to": 200},
                          {"key": "200+", "from": 200}
                      ]
                  }
              ]
          }
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  class SearchRequest(BaseModel):
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      """搜索请求模型(重构版)"""
      
      # 基础搜索参数
      query: str = Field(..., description="搜索查询字符串,支持布尔表达式(AND, OR, RANK, ANDNOT)")
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      size: int = Field(10, ge=1, le=1000, description="返回结果数量")
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      from_: int = Field(0, ge=0, alias="from", description="分页偏移量")
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      language: Literal["zh", "en"] = Field(
          "zh",
          description="响应语言:'zh'(中文)或 'en'(英文),用于选择 title/description/vendor 等多语言字段"
      )
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      # 过滤器 - 精确匹配和多值匹配
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      filters: Optional[Dict[str, Union[str, int, bool, List[Union[str, int]], Dict[str, Any], List[Dict[str, Any]]]]] = Field(
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          None,
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          description="精确匹配过滤器。单值表示精确匹配,数组表示 OR 匹配(匹配任意一个值)。支持 specifications 嵌套过滤:{\"specifications\": {\"name\": \"color\", \"value\": \"green\"}} 或 [{\"name\": \"color\", \"value\": \"green\"}, ...]",
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          json_schema_extra={
              "examples": [
                  {
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                      "category_name": ["手机", "电子产品"],
                      "vendor_zh.keyword": "奇乐",
                      "specifications": {"name": "颜色", "value": "白色"}
                  },
                  {
                      "specifications": [
                          {"name": "颜色", "value": "白色"},
                          {"name": "尺寸", "value": "256GB"}
                      ]
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                  }
              ]
          }
      )
      
      # 范围过滤器 - 数值范围
      range_filters: Optional[Dict[str, RangeFilter]] = Field(
          None,
          description="数值范围过滤器。支持 gte, gt, lte, lt 操作符",
          json_schema_extra={
              "examples": [
                  {
                      "price": {"gte": 50, "lte": 200},
                      "days_since_last_update": {"lte": 30}
                  }
              ]
          }
      )
      
      # 排序
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      sort_by: Optional[str] = Field(None, description="排序字段名。支持:'price'(价格,自动根据sort_order选择min_price或max_price)、'sales'(销量)、'create_time'(创建时间)、'update_time'(更新时间)")
      sort_order: Optional[str] = Field("desc", description="排序方向: 'asc'(升序)或 'desc'(降序)。注意:price+asc=价格从低到高,price+desc=价格从高到低")
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      # 分面搜索
      facets: Optional[List[FacetConfig]] = Field(
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          None,
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          description="分面配置对象列表。支持 specifications 分面:field=\"specifications\"(所有规格名称)或 field=\"specifications.color\"(指定规格名称)",
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          json_schema_extra={
              "examples": [
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                  [
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                      {"field": "category1_name", "size": 15, "type": "terms"},
                      {"field": "category2_name", "size": 10, "type": "terms"},
                      {"field": "specifications.color", "size": 20, "type": "terms"},
                      {"field": "specifications.size", "size": 15, "type": "terms"}
                  ],
                  [
                      {"field": "category1_name", "size": 15, "type": "terms"},
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                      {
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                          "field": "min_price",
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                          "type": "range",
                          "ranges": [
                              {"key": "0-50", "to": 50},
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                              {"key": "50-100", "from": 50, "to": 100},
                              {"key": "100-200", "from": 100, "to": 200},
                              {"key": "200+", "from": 200}
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                          ]
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                      },
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                      {"field": "specifications", "size": 10, "type": "terms"}
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                  ]
              ]
          }
      )
      
      # 高级选项
      min_score: Optional[float] = Field(None, ge=0, description="最小相关性分数阈值")
      highlight: bool = Field(False, description="是否高亮搜索关键词(暂不实现)")
      debug: bool = Field(False, description="是否返回调试信息")
      
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      # SKU筛选参数
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      sku_filter_dimension: Optional[List[str]] = Field(
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          None,
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          description=(
              "子SKU筛选维度(店铺配置),为字符串列表。"
              "指定后,每个SPU下的SKU将按这些维度的组合进行分组,每个维度组合只保留一个SKU返回。"
              "例如:['color'] 表示按颜色分组,每种颜色选一款;['color', 'size'] 表示按颜色+尺码组合分组。"
              "支持的值:'option1'、'option2'、'option3' 或选项名称(如 'color'、'size',将通过 option1_name/2_name/3_name 匹配)。"
          )
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      )
      
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      # 个性化参数(预留)
      user_id: Optional[str] = Field(None, description="用户ID,用于个性化搜索和推荐")
      session_id: Optional[str] = Field(None, description="会话ID,用于搜索分析")
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  class ImageSearchRequest(BaseModel):
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      """图片搜索请求模型"""
      image_url: str = Field(..., description="查询图片的 URL")
      size: int = Field(10, ge=1, le=100, description="返回结果数量")
      filters: Optional[Dict[str, Union[str, int, bool, List[Union[str, int]]]]] = None
      range_filters: Optional[Dict[str, RangeFilter]] = None
  
  
  class SearchSuggestRequest(BaseModel):
      """搜索建议请求模型(框架,暂不实现)"""
      query: str = Field(..., min_length=1, description="搜索查询字符串")
      size: int = Field(5, ge=1, le=20, description="返回建议数量")
      types: List[Literal["query", "product", "category", "brand"]] = Field(
          ["query"],
          description="建议类型:query(查询建议), product(商品建议), category(类目建议), brand(品牌建议)"
      )
  
  
  class FacetValue(BaseModel):
      """分面值"""
      value: Union[str, int, float] = Field(..., description="分面值")
      label: Optional[str] = Field(None, description="显示标签(如果与 value 不同)")
      count: int = Field(..., description="匹配的文档数量")
      selected: bool = Field(False, description="是否已选中(当前过滤器中)")
  
  
  class FacetResult(BaseModel):
      """分面结果(标准化格式)"""
      field: str = Field(..., description="字段名")
      label: str = Field(..., description="分面显示名称")
      type: Literal["terms", "range"] = Field(..., description="分面类型")
      values: List[FacetValue] = Field(..., description="分面值列表")
      total_count: Optional[int] = Field(None, description="该字段的总文档数")
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  class SkuResult(BaseModel):
      """SKU 结果"""
      sku_id: str = Field(..., description="SKU ID")
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      # 与 ES nested skus 结构对齐
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      price: Optional[float] = Field(None, description="价格")
      compare_at_price: Optional[float] = Field(None, description="原价")
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      sku_code: Optional[str] = Field(None, description="SKU编码")
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      stock: int = Field(0, description="库存数量")
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      weight: Optional[float] = Field(None, description="重量")
      weight_unit: Optional[str] = Field(None, description="重量单位")
      option1_value: Optional[str] = Field(None, description="选项1取值(如颜色)")
      option2_value: Optional[str] = Field(None, description="选项2取值(如尺码)")
      option3_value: Optional[str] = Field(None, description="选项3取值")
      image_src: Optional[str] = Field(None, description="SKU图片地址")
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  class SpuResult(BaseModel):
      """SPU 搜索结果"""
      spu_id: str = Field(..., description="SPU ID")
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      title: Optional[str] = Field(None, description="商品标题")
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      brief: Optional[str] = Field(None, description="商品短描述")
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      handle: Optional[str] = Field(None, description="商品handle")
      description: Optional[str] = Field(None, description="商品描述")
      vendor: Optional[str] = Field(None, description="供应商/品牌")
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      category: Optional[str] = Field(None, description="类目(兼容字段,等同于category_name)")
      category_path: Optional[str] = Field(None, description="类目路径(多级,用于面包屑)")
      category_name: Optional[str] = Field(None, description="类目名称(展示用)")
      category_id: Optional[str] = Field(None, description="类目ID")
      category_level: Optional[int] = Field(None, description="类目层级")
      category1_name: Optional[str] = Field(None, description="一级类目名称")
      category2_name: Optional[str] = Field(None, description="二级类目名称")
      category3_name: Optional[str] = Field(None, description="三级类目名称")
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      tags: Optional[List[str]] = Field(None, description="标签列表")
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      price: Optional[float] = Field(None, description="价格(min_price)")
      compare_at_price: Optional[float] = Field(None, description="原价")
      currency: str = Field("USD", description="货币单位")
      image_url: Optional[str] = Field(None, description="主图URL")
      in_stock: bool = Field(True, description="是否有库存")
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      # SKU 扁平化信息
      sku_prices: Optional[List[float]] = Field(None, description="所有SKU价格列表")
      sku_weights: Optional[List[int]] = Field(None, description="所有SKU重量列表")
      sku_weight_units: Optional[List[str]] = Field(None, description="所有SKU重量单位列表")
      total_inventory: Optional[int] = Field(None, description="总库存")
      option1_name: Optional[str] = Field(None, description="选项1名称(如颜色)")
      option2_name: Optional[str] = Field(None, description="选项2名称(如尺码)")
      option3_name: Optional[str] = Field(None, description="选项3名称")
      specifications: Optional[List[Dict[str, Any]]] = Field(
          None,
          description="规格列表(与 ES specifications 字段对应)"
      )
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      skus: List[SkuResult] = Field(default_factory=list, description="SKU列表")
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      relevance_score: float = Field(..., ge=0.0, description="相关性分数(ES原始分数)")
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  class SearchResponse(BaseModel):
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      """搜索响应模型(外部友好格式)"""
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      # 核心结果
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      results: List[SpuResult] = Field(..., description="搜索结果列表")
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      total: int = Field(..., description="匹配的总文档数")
      max_score: float = Field(..., description="最高相关性分数")
      
      # 分面搜索结果(标准化格式)
      facets: Optional[List[FacetResult]] = Field(
          None,
          description="分面统计结果(标准化格式)"
      )
      
      # 查询信息
      query_info: Dict[str, Any] = Field(
          default_factory=dict,
          description="查询处理信息(原始查询、改写、语言检测、翻译等)"
      )
      
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      # 推荐与建议
      suggestions: List[str] = Field(default_factory=list, description="搜索建议")
      related_searches: List[str] = Field(default_factory=list, description="相关搜索")
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      # 性能指标
      took_ms: int = Field(..., description="搜索总耗时(毫秒)")
      performance_info: Optional[Dict[str, Any]] = Field(None, description="详细性能信息")
      
      # 调试信息
      debug_info: Optional[Dict[str, Any]] = Field(None, description="调试信息(仅当 debug=True)")
  
  
  class SearchSuggestResponse(BaseModel):
      """搜索建议响应模型(框架,暂不实现)"""
      query: str = Field(..., description="原始查询")
      suggestions: List[Dict[str, Any]] = Field(..., description="建议列表")
      took_ms: int = Field(..., description="耗时(毫秒)")
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  class DocumentResponse(BaseModel):
      """Single document response model."""
      id: str = Field(..., description="Document ID")
      source: Dict[str, Any] = Field(..., description="Document source")
  
  
  class HealthResponse(BaseModel):
      """Health check response model."""
      status: str = Field(..., description="Service status")
      elasticsearch: str = Field(..., description="Elasticsearch status")
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  class ErrorResponse(BaseModel):
      """Error response model."""
      error: str = Field(..., description="Error message")
      detail: Optional[str] = Field(None, description="Detailed error information")