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# `langchain_community.embeddings.voyageai`.VoyageEmbeddings

class langchain_community.embeddings.voyageai.VoyageEmbeddings

  Bases: `BaseModel`, `Embeddings`

  [Deprecated] Voyage embedding models.

  To use, you should have the environment variable `VOYAGE_API_KEY` set with your API key or pass it as a named parameter to the constructor.

  Example

      from langchain_community.embeddings import VoyageEmbeddings

      voyage = VoyageEmbeddings(voyage_api_key="your-api-key", model="voyage-2")
      text = "This is a test query."
      query_result = voyage.embed_query(text)

  Notes

  Deprecated since version 0.0.29.

  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 batch_size: int [Required]

    Maximum number of texts to embed in each API request.

  param max_retries: int = 6

    Maximum number of retries to make when generating.

  param model: str [Required]
  param request_timeout: Optional[Union[float, Tuple[float, float]]] = None

    Timeout in seconds for the API request.

  param show_progress_bar: bool = False

    Whether to show a progress bar when embedding. Must have tqdm installed if set to True.

  param truncation: bool = True

    Whether to truncate the input texts to fit within the context length.

    If True, over-length input texts will be truncated to fit within the context length, before vectorized by the embedding model. If False, an error will be raised if any given text exceeds the context length.

  param voyage_api_base: str = 'https://api.voyageai.com/v1/embeddings'
  param voyage_api_key: Optional[SecretStr] = None
    Constraints

      - type = string

      - writeOnly = True

      - format = password

  async aembed_documents(texts: List[str]) → List[List[float]]

    Asynchronous Embed search docs.

    Parameters

      texts (List[str]) –

    Return type

      List[List[float]]

  async aembed_query(text: str) → List[float]

    Asynchronous Embed query text.

    Parameters

      text (str) –

    Return type

      List[float]

  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

    Parameters

      - _fields_set (Optional[SetStr]) –

      - values (Any) –

    Return type

      Model

  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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model

      - exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include

      - update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model

      - self (Model) –

    Returns

      new model instance

    Return type

      Model

  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.

    Parameters

      - include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

      - exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

      - by_alias (bool) –

      - skip_defaults (Optional[bool]) –

      - exclude_unset (bool) –

      - exclude_defaults (bool) –

      - exclude_none (bool) –

    Return type

      DictStrAny

  embed_documents(texts: List[str]) → List[List[float]]

    Call out to Voyage Embedding endpoint for embedding search docs.

    Parameters

      texts (List[str]) – The list of texts to embed.

    Returns

      List of embeddings, one for each text.

    Return type

      List[List[float]]

  embed_general_texts(texts: List[str], *, input_type: Optional[str] = None) → List[List[float]]

    Call out to Voyage Embedding endpoint for embedding general text.

    Parameters

      - texts (List[str]) – The list of texts to embed.

      - input_type (Optional[str]) – Type of the input text. Default to None, meaning the type is unspecified. Other options: query, document.

    Returns

      Embedding for the text.

    Return type

      List[List[float]]

  embed_query(text: str) → List[float]

    Call out to Voyage Embedding endpoint for embedding query text.

    Parameters

      text (str) – The text to embed.

    Returns

      Embedding for the text.

    Return type

      List[float]

  classmethod from_orm(obj: Any) → Model
    Parameters

      obj (Any) –

    Return type

      Model

  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().

    Parameters

      - include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

      - exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

      - by_alias (bool) –

      - skip_defaults (Optional[bool]) –

      - exclude_unset (bool) –

      - exclude_defaults (bool) –

      - exclude_none (bool) –

      - encoder (Optional[Callable[[Any], Any]]) –

      - models_as_dict (bool) –

      - dumps_kwargs (Any) –

    Return type

      unicode

  classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
    Parameters

      - path (Union[str, Path]) –

      - content_type (unicode) –

      - encoding (unicode) –

      - proto (Protocol) –

      - allow_pickle (bool) –

    Return type

      Model

  classmethod parse_obj(obj: Any) → Model
    Parameters

      obj (Any) –

    Return type

      Model

  classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
    Parameters

      - b (Union[str, bytes]) –

      - content_type (unicode) –

      - encoding (unicode) –

      - proto (Protocol) –

      - allow_pickle (bool) –

    Return type

      Model

  classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny
    Parameters

      - by_alias (bool) –

      - ref_template (unicode) –

    Return type

      DictStrAny

  classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode
    Parameters

      - by_alias (bool) –

      - ref_template (unicode) –

      - dumps_kwargs (Any) –

    Return type

      unicode

  classmethod update_forward_refs(**localns: Any) → None

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

    Parameters

      localns (Any) –

    Return type

      None

  classmethod validate(value: Any) → Model
    Parameters

      value (Any) –

    Return type

      Model