Anthropic SDK - Official Claude AI Integration

progressive_disclosure: entry_point: summary: "Official Anthropic SDK for Claude AI - chat, streaming, function calling, vision" when_to_use: - "When integrating Claude AI into applications" - "When building AI-powered features with Claude models" - "When using function calling/tool use patterns" - "When processing images with vision models" - "When implementing streaming chat interfaces" quick_start: - "pip install anthropic (Python) or npm install @anthropic-ai/sdk (TypeScript)" - "Set ANTHROPIC_API_KEY environment variable" - "Create client and send messages with Messages API" - "Use streaming for real-time responses" installation: python: "pip install anthropic" typescript: "npm install @anthropic-ai/sdk" config: - "ANTHROPIC_API_KEY: Your API key from console.anthropic.com" - "Model: claude-3-5-sonnet-20241022 (recommended)" - "Max tokens: 1024-8192 for responses" token_estimate: entry: 85 full: 5000

Installation & Setup

Python

pip install anthropic

TypeScript

npm install @anthropic-ai/sdk

API Key Configuration

export ANTHROPIC_API_KEY='your-api-key-here'

Get your API key from: https://console.anthropic.com/settings/keys

Messages API - Basic Usage

Python - Simple Message

import anthropic
import os

client = anthropic.Anthropic(
    api_key=os.environ.get("ANTHROPIC_API_KEY")
)

message = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
)

print(message.content[0].text)

TypeScript - Simple Message

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
});

const message = await client.messages.create({
  model: 'claude-3-5-sonnet-20241022',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Explain quantum computing in simple terms' }
  ],
});

console.log(message.content[0].text);

System Prompts

# Python - System prompt for context
message = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    system="You are a helpful coding assistant specializing in Python and TypeScript.",
    messages=[
        {"role": "user", "content": "How do I handle errors in async functions?"}
    ]
)

// TypeScript - System prompt
const message = await client.messages.create({
  model: 'claude-3-5-sonnet-20241022',
  max_tokens: 1024,
  system: 'You are a helpful coding assistant specializing in Python and TypeScript.',
  messages: [
    { role: 'user', content: 'How do I handle errors in async functions?' }
  ],
});

Streaming Responses

Python - Streaming

# Real-time streaming responses
with client.messages.stream(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a short poem about coding"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Python - Async Streaming

import asyncio

async def stream_response():
    async with client.messages.stream(
        model="claude-3-5-sonnet-20241022",
        max_tokens=1024,
        messages=[
            {"role": "user", "content": "Explain recursion"}
        ]
    ) as stream:
        async for text in stream.text_stream:
            print(text, end="", flush=True)

asyncio.run(stream_response())

TypeScript - Streaming

// Streaming with event handlers
const stream = await client.messages.stream({
  model: 'claude-3-5-sonnet-20241022',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Write a short poem about coding' }
  ],
});

for await (const chunk of stream) {
  if (chunk.type === 'content_block_delta' &&
      chunk.delta.type === 'text_delta') {
    process.stdout.write(chunk.delta.text);
  }
}

Function Calling / Tool Use

Python - Function Calling

# Define tools (functions)
tools = [
    {
        "name": "get_weather",
        "description": "Get the current weather for a location",
        "input_schema": {
            "type": "object",
            "properties": {
                "location": {
                    "type": "string",
                    "description": "City name, e.g., San Francisco, CA"
                },
                "unit": {
                    "type": "string",
                    "enum": ["celsius", "fahrenheit"],
                    "description": "Temperature unit"
                }
            },
            "required": ["location"]
        }
    }
]

# Initial request
message = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,