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

This notebook explains how to useAwaEmbeddings in LangChain.

# pip install awadb

import the library​

from langchain_community.embeddingsimport AwaEmbeddings

Embedding= AwaEmbeddings()

Set embedding model

Users can useEmbedding.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 obtainedhere \ \

Thedefault model isall-mpnet-base-v2, it can be used without setting.

text="our embedding test"

Embedding.set_model("all-mpnet-base-v2")

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

Related​

• Embedding modelconceptual guide
• Embedding modelhow-to guides