HunyuanEmbeddings

class langchain_community.embeddings.hunyuan.HunyuanEmbeddings

Bases: Embeddings, BaseModel

Tencent Hunyuan embedding models API by Tencent.

For more information, see https://cloud.tencent.com/document/product/1729

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

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

param client: Any = None

The tencentcloud client.

param embedding_ctx_length: int = 1024

The max embedding context length of hunyuan embedding (defaults to 1024).

param hunyuan_secret_id: SecretStr | None = None (alias 'secret_id')

Hunyuan Secret ID

param hunyuan_secret_key: SecretStr | None = None (alias 'secret_key')

Hunyuan Secret Key

param region: Literal['ap-guangzhou', 'ap-beijing'] = 'ap-guangzhou'

The region of hunyuan service.

param request_cls: Type | None = None

The request class of tencentcloud sdk.

param show_progress_bar: bool = False

Show progress bar when embedding. Default is False.

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]

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

Embed search docs.

Parameters:

texts (List[str])

Return type:

List[List[float]]

embed_query(text: str) → List[float]

Embed query text.

Parameters:

text (str)

Return type:

List[float]