INNER CODE UNIT · Python

create_langchain_vector_embedding_using_bedrock

aws-samples/rag-using-langchain-amazon-bedrock-and-opensearch · ask-bedrock-with-rag.py:37

def create_langchain_vector_embedding_using_bedrock(bedrock_client, bedrock_embedding_model_id):
    bedrock_embeddings_client = BedrockEmbeddings(
        client=bedrock_client,
        model_id=bedrock_embedding_model_id)
    return bedrock_embeddings_client
    

def create_opensearch_vector_search_client(index_name, opensearch_password, bedrock_embeddings_client, opensearch_endpoint, _is_aoss=False):
    docsearch = OpenSearchVectorSearch(
        index_name=index_name,
        embedding_function=bedrock_embeddings_client,
        opensearch_url=f"https://{opensearch_endpoint}",
        http_auth=(index_name, opensearch_password),
        is_aoss=_is_aoss
    )
    return docsearch

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