Anthropic SDK

The Anthropic SDK gets a governed AsyncAnthropic client pointed at the Omni Gateway LLM proxy, with the SDK’s shared transport and proxy headers passed straight into the client constructor.

What you get

• A native anthropic.AsyncAnthropic client.
• Full header and transport injection.
• Supported at connection_kwargs().

Install

pip install "donkey-kit[anthropic]"

Quickstart

from donkey_kit.integrations.anthropic import client
 
llm = client()

reply = await llm.messages.create(
    model="claude-...",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Say hi in three words."}],
)

import Anthropic from "@anthropic-ai/sdk";
 
const client = new Anthropic({
  baseURL: process.env.DONKEY_LLM_PROXY_URL,   // a Format=Anthropic proxy
  apiKey: "unused",                              // required slot; proxy uses the headers below
  defaultHeaders: {
    client_id: process.env.DONKEY_LLM_PROXY_CLIENT_ID!,
    client_secret: process.env.DONKEY_LLM_PROXY_CLIENT_SECRET!,
  },
});
 
const reply = await client.messages.create({
  model: "claude-...",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Say hi in three words." }],
});
console.log(reply.content);

Three ways to construct

1. Off a shared Donkey instance:

from donkey_kit import Donkey
 
async with Donkey.from_env() as donkey:
    llm = donkey.anthropic.client()

2. Module-level factory (shortest):

from donkey_kit.integrations.anthropic import client
 
llm = client()

3. Governed kwargs, native constructor:

from donkey_kit import Donkey
from anthropic import AsyncAnthropic
 
async with Donkey.from_env() as donkey:
    llm = AsyncAnthropic(**donkey.anthropic.connection_kwargs())

Manual equivalent

from anthropic import AsyncAnthropic
 
llm = AsyncAnthropic(
    base_url=...,          # from DONKEY_LLM_PROXY_URL, no /v1 suffix
    api_key=...,
    default_headers=...,   # client_id / client_secret header pair
    http_client=...,       # the SDK's shared httpx client
    max_retries=0,         # the SDK retries in its own transport layer
)

connection_kwargs() returns exactly these keys, so you can drop the factory and construct AsyncAnthropic by hand at any time.

Notes

• client(), not model(...). The other adapters return a framework object already bound to a model ID, because their native constructors accept model. AsyncAnthropic is a bare client and the model ID is an argument to .messages.create(), so donkey.anthropic.client() takes no model argument.
• Proxy Format. MuleSoft Model Proxy offers three ingress Formats (OpenAI / Gemini / Anthropic), fixed when the proxy is created (MuleSoft docs ). A Format=Anthropic proxy returns a native Anthropic body from /v1/messages and 404s an OpenAI-shaped /chat/completions request. Auth is the same client_id / client_secret header pair as every other proxy. To use the native surface, set DONKEY_LLM_PROXY_URL (or llm_proxy_url) to a Format=Anthropic proxy.

See the error taxonomy for how proxy rejections surface as typed exceptions, and the verification ledger  for the current status of every constructor signature this adapter depends on.