Claude Sonnet 3.5 API Tutorial: Getting Started With Anthropic's API

Anthropic's Claude 3.5 Sonnet: A Powerful LLM and its API

Claude 3.5 Sonnet, Anthropic's latest large language model (LLM), surpasses competitors like GPT-4o and Gemini Pro 1.5 in various benchmarks, particularly in visual reasoning. This article guides you through using Claude 3.5 Sonnet via its API. For a comprehensive overview of Claude 3.5 Sonnet itself, please see this article on What Is Claude 3.5 Sonnet.

Understanding Claude 3.5 Sonnet

Claude 3.5 Sonnet is part of Anthropic's Claude 3.5 family, with Claude 3.5 Opus and Claude 3.5 Haiku slated for release later this year. Its superior image processing and generation capabilities, along with strong performance in coding and reasoning tasks, set it apart. A key feature is "Artifacts," enhancing conversation management (learn more in this introductory article on Claude Sonnet 3.5).

Connecting to the Anthropic API

To access the Claude 3.5 Sonnet API:

1. Account Creation: Register for an Anthropic API account at the Anthropic Console, providing necessary details and email verification.
2. API Key Generation: Obtain your API key from the "Get API keys" section within your account.

Environment Setup

Install the anthropic library:

pip install anthropic

Initialize the Anthropic client using your API key:

import anthropic
client = anthropic.Anthropic(api_key='your_api_key_here')

Messages API vs. Text Completions API

Claude 3.5 Sonnet's API features a powerful Messages API for dynamic interactions. The older Text Completions API is now legacy; users are encouraged to transition to the Messages API for enhanced functionality and future support. Note that Artifacts are currently only accessible through the Claude.ai web interface.

Using the Messages API

The Messages API accepts structured input messages (text or images) to generate conversational responses. It supports single queries and multi-turn conversations.

Required Parameters:

• model: Specifies the model ("claude-3-5-sonnet-20240620").
• messages: A list of input messages, each with a "role" ("user" or "assistant") and "content."

Available Models (as of this writing):

Optional Parameters:

• max_tokens
• temperature
• stop_sequences
• stream
• system
• tools
• top_k
• top_p

Practical Use Cases

Single Message:

pip install anthropic

Multi-Turn Conversation:

import anthropic
client = anthropic.Anthropic(api_key='your_api_key_here')

Image Content:

response = client.messages.create(
    model="claude-3-5-sonnet-20240620",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello, world"}]
)

System Prompts and Stop Sequences:

response = client.messages.create(
    model="claude-3-5-sonnet-20240620",
    max_tokens=512,
    messages=[
        {"role": "user", "content": "Hello there."},
        {"role": "assistant", "content": "Hi, I'm Claude. How can I help you?"},
        {"role": "user", "content": "Can you explain LLMs in plain English?"}
    ]
)

Tool Definitions:

response = client.messages.create(
    model="claude-3-5-sonnet-20240620",
    max_tokens=512,
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "base64",
                        "media_type": "image/jpeg",
                        "data": "media_file"
                    }
                },
                {"type": "text", "text": "What is in this image?"}
            ]
        }
    ]
)

Conclusion

This guide provides a practical introduction to using Anthropic's Claude 3.5 Sonnet API. Its capabilities make it a versatile tool for various AI applications. For comparisons with ChatGPT, see What Is Claude 3.5 Sonnet and Claude vs ChatGPT for Data Science.

FAQs

(Answers to FAQs remain the same as in the original text, with minor stylistic adjustments if needed.)

The above is the detailed content of Claude Sonnet 3.5 API Tutorial: Getting Started With Anthropic's API. For more information, please follow other related articles on the PHP Chinese website!