AwaEmbeddings

class langchain_community.embeddings.awa.AwaEmbeddings

Bases: BaseModel, Embeddings

Embedding documents and queries with Awa DB.

client

The AwaEmbedding client.

model

The name of the model used for embedding. Default is “all-mpnet-base-v2”.

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'

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

Asynchronous Embed search docs.

Parameters:

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

Returns:

List of embeddings.

Return type:

List[List[float]]

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

Asynchronous Embed query text.

Parameters:

text (str) – Text to embed.

Returns:

Embedding.

Return type:

List[float]

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

Embed a list of documents using AwaEmbedding.

Parameters:

texts (List[str]) – The list of texts need to be embedded

Returns:

List of embeddings, one for each text.

Return type:

List[List[float]]

embed_query(text: str) → List[float]

Compute query embeddings using AwaEmbedding.

Parameters:

text (str) – The text to embed.

Returns:

Embeddings for the text.

Return type:

List[float]

set_model(model_name: str) → None

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

Parameters:

model_name (str) – A string which represents the name of model.

Return type:

None

Examples using AwaEmbeddings

• AwaDB