langchain.embeddings.awa.AwaEmbeddings

class langchain.embeddings.awa.AwaEmbeddings(*, client: Any = None, model: str = 'all-mpnet-base-v2')

Bases: BaseModel, Embeddings

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'

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

Embed a list of documents using AwaEmbedding.

Parameters

texts – The list of texts need to be embedded

Returns

List of embeddings, one for each text.

embed_query(text: str) → List[float]

Compute query embeddings using AwaEmbedding.

Parameters

text – The text to embed.

Returns

Embeddings for the text.

set_model(model_name: str) → None

Set the model used for embedding. The default model used is all-mpnet-base-v2

Parameters

model_name – A string which represents the name of model.

validator validate_environment  »  all fields

Validate that awadb library is installed.

Examples using AwaEmbeddings

• AwaEmbedding