ComponentsText embedding modelsAwaDBOn this pageAwaDBAwaDB 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 awadbimport the library​from langchain.embeddings import AwaEmbeddingsEmbedding = AwaEmbeddings()Set embedding modelUsers 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"Embedding.set_model("all-mpnet-base-v2")res_query = Embedding.embed_query("The test information")res_document = Embedding.embed_documents(["test1", "another test"])PreviousAleph AlphaNextAzureOpenAIimport the library