INNER CODE UNIT · Python

create_vector_embedding_with_bedrock

aws-samples/rag-using-langchain-amazon-bedrock-and-opensearch · load-data-to-opensearch.py:33

def create_vector_embedding_with_bedrock(text, name, bedrock_client):
    payload = {"inputText": f"{text}"}
    body = json.dumps(payload)
    modelId = "amazon.titan-embed-text-v1"
    accept = "application/json"
    contentType = "application/json"
    args, _ = parse_args()
    multi_tenant = args.multi_tenant

    response = bedrock_client.invoke_model(
        body=body, modelId=modelId, accept=accept, contentType=contentType
    )
    response_body = json.loads(response.get("body").read())

    embedding = response_body.get("embedding")

    document = {
        "_index": name,

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