INNER CODE UNIT · Python

get_bedrock_client

aws-samples/rag-using-langchain-amazon-bedrock-and-opensearch · load-data-to-opensearch.py:28

def get_bedrock_client(region):
    bedrock_client = boto3.client("bedrock-runtime", region_name=region)
    return bedrock_client


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())

View source record →