MetadataFilter#

pydantic model llama_index.core.vector_stores.MetadataFilter#

Comprehensive metadata filter for vector stores to support more operators.

Value uses Strict* types, as int, float and str are compatible types and were all converted to string before.

See: https://docs.pydantic.dev/latest/usage/types/#strict-types

Show JSON schema

{
   "title": "MetadataFilter",
   "description": "Comprehensive metadata filter for vector stores to support more operators.\n\nValue uses Strict* types, as int, float and str are compatible types and were all\nconverted to string before.\n\nSee: https://docs.pydantic.dev/latest/usage/types/#strict-types",
   "type": "object",
   "properties": {
      "key": {
         "title": "Key",
         "type": "string"
      },
      "value": {
         "title": "Value",
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "number"
            },
            {
               "type": "string"
            }
         ]
      },
      "operator": {
         "default": "==",
         "allOf": [
            {
               "$ref": "#/definitions/FilterOperator"
            }
         ]
      }
   },
   "required": [
      "key",
      "value"
   ],
   "definitions": {
      "FilterOperator": {
         "title": "FilterOperator",
         "description": "Vector store filter operator.",
         "enum": [
            "==",
            ">",
            "<",
            "!=",
            ">=",
            "<=",
            "in",
            "nin",
            "text_match"
         ],
         "type": "string"
      }
   }
}

Fields

field key: str [Required]#

field operator: FilterOperator = FilterOperator.EQ#

field value: Union[StrictInt, StrictFloat, StrictStr] [Required]#

classmethod from_dict(filter_dict: Dict) → MetadataFilter#

Create MetadataFilter from dictionary.

Parameters: filter_dict – Dict with key, value and operator.