Getting Started Guide

pip install anthropic

pip install anthropic[bedrock]  # AWS Bedrock
pip install anthropic[vertex]   # Google Vertex AI
pip install anthropic[aiohttp]  # Alternative async HTTP

export ANTHROPIC_API_KEY='your-api-key'

from anthropic import Anthropic

client = Anthropic(api_key="your-api-key")

from anthropic import Anthropic

client = Anthropic()

message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ]
)

print(message.content[0].text)

message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    system="You are a helpful AI assistant specializing in Python programming.",
    messages=[
        {"role": "user", "content": "How do I read a file?"}
    ]
)

messages = [
    {"role": "user", "content": "My name is Alice."},
    {"role": "assistant", "content": "Hello Alice! Nice to meet you."},
    {"role": "user", "content": "What's my name?"}
]

message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=messages
)

print(message.content[0].text)  # "Your name is Alice."

with client.messages.stream(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a short story"}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
print()

import base64

with open("image.jpg", "rb") as f:
    image_data = base64.standard_b64encode(f.read()).decode()

message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "image",
                "source": {
                    "type": "base64",
                    "media_type": "image/jpeg",
                    "data": image_data
                }
            },
            {"type": "text", "text": "What's in this image?"}
        ]
    }]
)

from anthropic import APIError, RateLimitError

try:
    message = client.messages.create(
        model="claude-sonnet-4-5-20250929",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello"}]
    )
except RateLimitError as e:
    print(f"Rate limited. Retry after {e.response.headers.get('retry-after')}s")
except APIError as e:
    print(f"API error: {e.message}")

import asyncio
from anthropic import AsyncAnthropic

async def main():
    client = AsyncAnthropic()

    message = await client.messages.create(
        model="claude-sonnet-4-5-20250929",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello"}]
    )

    print(message.content[0].text)

asyncio.run(main())

with Anthropic() as client:
    message = client.messages.create(...)
# Client automatically closed

try:
    message = client.messages.create(...)
except APIError as e:
    # Handle error
    ...

import httpx

client = Anthropic(
    timeout=httpx.Timeout(60.0)
)

message = client.messages.create(...)
print(f"Input tokens: {message.usage.input_tokens}")
print(f"Output tokens: {message.usage.output_tokens}")