langchain.vectorstores.redis.schema.RedisModel

class langchain.vectorstores.redis.schema.RedisModel[source]

Bases: BaseModel

Schema for Redis index.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param content_key: str = 'content'
param content_vector_key: str = 'content_vector'
param extra: Optional[List[langchain.vectorstores.redis.schema.RedisField]] = None
param numeric: Optional[List[langchain.vectorstores.redis.schema.NumericFieldSchema]] = None
param tag: Optional[List[langchain.vectorstores.redis.schema.TagFieldSchema]] = None
param text: List[langchain.vectorstores.redis.schema.TextFieldSchema] = [TextFieldSchema(name='content', weight=1, no_stem=False, phonetic_matcher=None, withsuffixtrie=False, no_index=False, sortable=False)]
param vector: Optional[List[Union[langchain.vectorstores.redis.schema.FlatVectorField, langchain.vectorstores.redis.schema.HNSWVectorField]]] = None
add_content_field() None[source]
add_vector_field(vector_field: Dict[str, Any]) None[source]
as_dict() Dict[str, List[Any]][source]
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters
  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) Model
get_fields() List[RedisField][source]
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model
classmethod parse_obj(obj: Any) Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode
classmethod update_forward_refs(**localns: Any) None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) Model
property content_vector: Union[langchain.vectorstores.redis.schema.FlatVectorField, langchain.vectorstores.redis.schema.HNSWVectorField]
property is_empty: bool
property metadata_keys: List[str]
property vector_dtype: numpy.dtype