langchain_community.embeddings.awa
.AwaEmbeddingsΒΆ
- class langchain_community.embeddings.awa.AwaEmbeddings[source]ΒΆ
Bases:
BaseModel
,Embeddings
Embedding documents and queries with Awa DB.
- clientΒΆ
The AwaEmbedding client.
- modelΒΆ
The name of the model used for embedding. Default is βall-mpnet-base-v2β.
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 model: str = 'all-mpnet-base-v2'ΒΆ
- async aembed_documents(texts: List[str]) List[List[float]] ΒΆ
Asynchronous Embed search docs.
- async aembed_query(text: str) List[float] ΒΆ
Asynchronous Embed query text.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model ΒΆ
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 = βallowβ 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 ΒΆ
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include β fields to include in new model
exclude β fields to exclude from new model, as with values this takes precedence over include
update β 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 β 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 ΒΆ
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- embed_documents(texts: List[str]) List[List[float]] [source]ΒΆ
Embed a list of documents using AwaEmbedding.
- Parameters
texts β The list of texts need to be embedded
- Returns
List of embeddings, one for each text.
- embed_query(text: str) List[float] [source]ΒΆ
Compute query embeddings using AwaEmbedding.
- Parameters
text β The text to embed.
- Returns
Embeddings for the text.
- classmethod from_orm(obj: Any) Model ΒΆ
- 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 ΒΆ
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 ΒΆ
- classmethod parse_obj(obj: Any) Model ΒΆ
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ΒΆ
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny ΒΆ
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode ΒΆ
- set_model(model_name: str) None [source]ΒΆ
Set the model used for embedding. The default model used is all-mpnet-base-v2
- Parameters
model_name β A string which represents the name of model.
- classmethod update_forward_refs(**localns: Any) None ΒΆ
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- classmethod validate(value: Any) Model ΒΆ