Cohere Command model

Anda membuat permintaan inferensi ke Cohere Command model dengan InvokeModelatau InvokeModelWithResponseStream(streaming). Anda memerlukan ID model untuk model yang ingin Anda gunakan. Untuk mendapatkan ID model, lihatModel pondasi yang didukung di Amazon Bedrock.

Permintaan dan Tanggapan

Contoh kode

Contoh ini menunjukkan cara memanggil Cohere Commandmodel.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""
Shows how to generate text using a Cohere model.
"""
import json
import logging
import boto3


from botocore.exceptions import ClientError

logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)


def generate_text(model_id, body):
    """
    Generate text using a Cohere model.
    Args:
        model_id (str): The model ID to use.
        body (str) : The reqest body to use.
    Returns:
        dict: The response from the model.
    """

    logger.info("Generating text with Cohere model %s", model_id)

    accept = 'application/json'
    content_type = 'application/json'

    bedrock = boto3.client(service_name='bedrock-runtime')

    response = bedrock.invoke_model(
        body=body,
        modelId=model_id,
        accept=accept,
        contentType=content_type
    )

    logger.info("Successfully generated text with Cohere model %s", model_id)

    return response


def main():
    """
    Entrypoint for Cohere example.
    """

    logging.basicConfig(level=logging.INFO,
                        format="%(levelname)s: %(message)s")

    model_id = 'cohere.command-text-v14'
    prompt = """Summarize this dialogue: 
"Customer: Please connect me with a support agent.
AI: Hi there, how can I assist you today?
Customer: I forgot my password and lost access to the email affiliated to my account. Can you please help me?
AI: Yes of course. First I'll need to confirm your identity and then I can connect you with one of our support agents.
"""
    try:
        body = json.dumps({
            "prompt": prompt,
            "max_tokens": 200,
            "temperature": 0.6,
            "p": 1,
            "k": 0,
            "num_generations": 2,
            "return_likelihoods": "GENERATION"
        })
        response = generate_text(model_id=model_id,
                                 body=body)

        response_body = json.loads(response.get('body').read())
        generations = response_body.get('generations')

        for index, generation in enumerate(generations):

            print(f"Generation {index + 1}\n------------")
            print(f"Text:\n {generation['text']}\n")
            if 'likelihood' in generation:
                print(f"Likelihood:\n {generation['likelihood']}\n")
            
            print(f"Reason: {generation['finish_reason']}\n\n")

    except ClientError as err:
        message = err.response["Error"]["Message"]
        logger.error("A client error occurred: %s", message)
        print("A client error occured: " +
              format(message))
    else:
        print(f"Finished generating text with Cohere model {model_id}.")


if __name__ == "__main__":
    main()