class langchain_community.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint[source]

Bases: BaseModel, Embeddings

Baidu Qianfan Embeddings embedding models.

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 chunk_size: int = 16

Chunk size when multiple texts are input

param client: Any = None

Qianfan client

param endpoint: str = ''

Endpoint of the Qianfan Embedding, required if custom model used.

param init_kwargs: Dict[str, Any] [Optional]

init kwargs for qianfan client init, such as query_per_second which is associated with qianfan resource object to limit QPS

param model: str = 'Embedding-V1'

Model name you could get from

for now, we support Embedding-V1 and - Embedding-V1 (默认模型) - bge-large-en - bge-large-zh

preset models are mapping to an endpoint. model will be ignored if endpoint is set

param model_kwargs: Dict[str, Any] [Optional]

extra params for model invoke using with do.

param qianfan_ak: Optional[str] = None

Qianfan application apikey

param qianfan_sk: Optional[str] = None

Qianfan application secretkey

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

Asynchronous Embed search docs.


texts (List[str]) –

Return type


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

Asynchronous Embed query text.


text (str) –

Return type


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

Embeds a list of text documents using the AutoVOT algorithm.


texts (List[str]) – A list of text documents to embed.


A list of embeddings for each document in the input list.

Each embedding is represented as a list of float values.

Return type


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

Embed query text.


text (str) –

Return type


Examples using QianfanEmbeddingsEndpoint