langchain_cohere.embeddings.CohereEmbeddings

class langchain_cohere.embeddings.CohereEmbeddings[source]

Bases: BaseModel, Embeddings

Implements the Embeddings interface with Cohere’s text representation language models.

Find out more about us at https://cohere.com and https://huggingface.co/CohereForAI

This implementation uses the Embed API - see https://docs.cohere.com/reference/embed

To use this you’ll need to a Cohere API key - either pass it to cohere_api_key parameter or set the COHERE_API_KEY environment variable.

API keys are available on https://cohere.com - it’s free to sign up and trial API keys work with this implementation.

Basic Example:
cohere_embeddings = CohereEmbeddings(model="embed-english-light-v3.0")
text = "This is a test document."

query_result = cohere_embeddings.embed_query(text)
print(query_result)

doc_result = cohere_embeddings.embed_documents([text])
print(doc_result)

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 async_client: Any = None

Cohere async client.

param base_url: Optional[str] = None

Override the default Cohere API URL.

param client: Any = None

Cohere client.

param cohere_api_key: Optional[str] = None
param max_retries: int = 3

Maximum number of retries to make when generating.

param model: str = 'embed-english-v2.0'

Model name to use.

param request_timeout: Optional[float] = None

Timeout in seconds for the Cohere API request.

param truncate: Optional[str] = None

Truncate embeddings that are too long from start or end (“NONE”|”START”|”END”)

param user_agent: str = 'langchain:partner'

Identifier for the application making the request.

async aembed(texts: List[str], *, input_type: Optional[Union[Literal['search_document', 'search_query', 'classification', 'clustering'], Any]] = None) → List[List[float]][source]
Parameters

  • texts (List[str]) –

  • input_type (Optional[Union[Literal['search_document', 'search_query', 'classification', 'clustering'], ~typing.Any]]) –

Return type

List[List[float]]

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

Async call out to Cohere’s embedding endpoint.

Parameters

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

Returns

List of embeddings, one for each text.

Return type

List[List[float]]

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

Async call out to Cohere’s embedding endpoint.

Parameters

text (str) – The text to embed.

Returns

Embeddings for the text.

Return type

List[float]

aembed_with_retry(**kwargs: Any) → Any[source]

Use tenacity to retry the embed call.

Parameters

kwargs (Any) –

Return type

Any

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(texts: List[str], *, input_type: Optional[Union[Literal['search_document', 'search_query', 'classification', 'clustering'], Any]] = None) → List[List[float]][source]
Parameters

  • texts (List[str]) –

  • input_type (Optional[Union[Literal['search_document', 'search_query', 'classification', 'clustering'], ~typing.Any]]) –

Return type

List[List[float]]

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

Embed a list of document texts.

Parameters

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

Returns

List of embeddings, one for each text.

Return type

List[List[float]]

embed_query(text: str) → List[float][source]

Call out to Cohere’s embedding endpoint.

Parameters

text (str) – The text to embed.

Returns

Embeddings for the text.

Return type

List[float]

embed_with_retry(**kwargs: Any) → Any[source]

Use tenacity to retry the embed call.

Parameters

kwargs (Any) –

Return type

Any

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

Examples using CohereEmbeddings