Claude-3 api snippets

[irthomasthomas]

• Claude-3 api snippets

Claude-3 API Snippets

Sure! Here are some real code snippets that use the Anthropic Claude 3 API:

The first, from a blog post by Abid Ali Awan on KDnuggets, shows how to use the API to generate a response in Urdu:

import os
import anthropic
from IPython.display import Markdown, display

client = anthropic.Anthropic(
    api_key=os.environ["ANTHROPIC_API_KEY"],
)

Prompt = "Write a blog about neural networks."
message = client.messages.create(
    model="claude-3-opus-20240229",
    max_tokens=1024,
    system="Respond only in Urdu.",
    messages=[
        {'role': "user", "content": Prompt}
    ]
)

Markdown(message.content[0].text)

The next two code snippets are from the Amazon Bedrock User Guide:

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0

"""
Shows how to generate a message with Anthropic Claude (on demand).
"""
import boto3
import json
import logging
from botocore.exceptions import ClientError

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

def generate_message(bedrock_runtime, model_id, system_prompt, messages, max_tokens):
    body = json.dumps(
        {"anthropic_version": "bedrock-2023-05-31",
         "max_tokens": max_tokens,
         "system": system_prompt,
         "messages": messages
        }
    )
    response = bedrock_runtime.invoke_model(body=body, modelId=model_id)
    response_body = json.loads(response.get('body').read())
    return response_body

def main():
    """
    Entrypoint for Anthropic Claude message example.
    """
    try:
        bedrock_runtime = boto3.client(service_name='bedrock-runtime')
        model_id = 'anthropic.claude-3-sonnet-20240229-v1:0'
        system_prompt = "Please respond only with emoji."
        max_tokens = 1000

        # Prompt with user turn only.
        user_message = {"role": "user", "content": "Hello World"}
        messages = [user_message]
        response = generate_message(bedrock_runtime, model_id, system_prompt, messages, max_tokens)
        print("User turn only.")
        print(json.dumps(response, indent=4))

        # Prompt with both user turn and prefilled assistant response.
        # Anthropic Claude continues by using the prefilled assistant text.
        assistant_message = {"role": "assistant", "content": "<emoji>"}
        messages = [user_message, assistant_message]
        response = generate_message(bedrock_runtime, model_id, system_prompt, messages, max_tokens)
        print("User turn and prefilled assistant response.")
        print(json.dumps(response, indent=4))

    except ClientError as err:
        message = err.response["Error"]["Message"]
        logger.error("A client error occurred: %s", message)
        print("A client error occurred: " + format(message))

if __name__ == "__main__":
    main()

And:

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0

"""
Shows how to run a multimodal prompt with Anthropic Claude (on demand) and InvokeModel.
"""
import json
import logging
import base64
import boto3
from botocore.exceptions import ClientError

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

def run_multi_modal_prompt(bedrock_runtime, model_id, messages, max_tokens):
    """
    Invokes a model with a multimodal prompt.
    Args:
    bedrock_runtime: The Amazon Bedrock boto3 client.
    model_id (str): The model ID to use.
    messages (JSON): The messages to send to the model.
    max_tokens (int): The maximum number of tokens to generate.
    Returns:
    None.
    """
    body = json.dumps(
        {
            "anthropic_version": "bedrock-2023-05-31",
            "max_tokens": max_tokens,
            "messages": messages
        }
    )
    response = bedrock_runtime.invoke_model(body=body, modelId=model_id)
    response_body = json.loads(response.get('body').read())
    return response_body

def main():
    """
    Entrypoint for Anthropic Claude multimodal prompt example.
    """
    try:
        bedrock_runtime = boto3.client(service_name='bedrock-runtime')
        model_id = 'anthropic.claude-3-sonnet-20240229-v1:0'
        max_tokens = 1000
    URL: [Claude-3 API Snippets](https://www.anthropic.com/blog/claude-3-api-snippets)

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