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Anthropic SDK

This guide shows you how to point the official Anthropic SDK at the to11 gateway. Set the base_url to your gateway’s /v1 endpoint and use the Anthropic messages API as usual.

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Python

pip install anthropic

import anthropic

client = anthropic.Anthropic(
    base_url="http://localhost:4000/v1",
    api_key="sk-ant-...",  # your Anthropic API key
)

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello from to11!"}],
)
print(message.content[0].text)

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TypeScript / Node.js

npm install @anthropic-ai/sdk

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

const client = new Anthropic({
  baseURL: "http://localhost:4000/v1",
  apiKey: "sk-ant-...", // your Anthropic API key
});

const message = await client.messages.create({
  model: "claude-sonnet-4-6",
  max_tokens: 256,
  messages: [{ role: "user", content: "Hello from to11!" }],
});
console.log(message.content[0].text);

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Streaming

with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=256,
    messages=[{"role": "user", "content": "Count to 10"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
When the upstream provider is Anthropic, the gateway uses the normalised streaming path to parse SSE into canonical events and re-serialise them. Telemetry (TTFT, token counts) is captured identically on both streaming paths.

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System messages

Pass a top-level system parameter as you normally would: 
message = client.messages.create(
    model="claude-sonnet-4-6",
    system="You are a helpful assistant that speaks only in haiku.",
    max_tokens=256,
    messages=[{"role": "user", "content": "Tell me about the ocean"}],
)

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Tool use

Tool definitions follow the Anthropic input_schema format: 
message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=256,
    messages=[{"role": "user", "content": "What's the weather in Paris?"}],
    tools=[{
        "name": "get_weather",
        "description": "Get current weather for a location",
        "input_schema": {
            "type": "object",
            "properties": {
                "location": {"type": "string"}
            },
            "required": ["location"],
        },
    }],
)

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Extended thinking

Extended thinking blocks are preserved in Anthropic-format responses when enabled on the model. The thinking content type passes through the gateway as-is.

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Cross-format routing

If you route an Anthropic-format request to an OpenAI model, the gateway translates automatically: 
# Anthropic SDK format, but targeting an OpenAI model
message = client.messages.create(
    model="gpt-4o",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello!"}],
)
The system parameter is converted to a {"role": "system"} message, and tool definitions are translated to OpenAI’s parameters format.