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AwaDB is an AI Native database for the search and storage of embedding vectors used by LLM Applications.

This notebook explains how to use AwaEmbeddings in LangChain.

# pip install awadb

import the libraryโ€‹

from langchain_community.embeddings import AwaEmbeddings

API Reference:

Embedding = AwaEmbeddings()

Set embedding model

Users can use Embedding.set_model() to specify the embedding model. \ The input of this function is a string which represents the model's name. \ The list of currently supported models can be obtained here \ \

The default model is all-mpnet-base-v2, it can be used without setting.

text = "our embedding test"

res_query = Embedding.embed_query("The test information")
res_document = Embedding.embed_documents(["test1", "another test"])

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