Adapters

Providers translate between AFK’s normalized contracts (LLMRequest/LLMResponse) and provider-specific APIs. AFK ships with three built-in providers and supports custom providers for internal deployments.

Built-in providers

OpenAI

Direct integration via the OpenAI Python SDK. Supports all GPT-4.1 and o-series models.

Anthropic

Direct integration via the Anthropic SDK. Supports Claude Opus 4.5 and Opus.

LiteLLM

Proxy adapter for 100+ providers (Azure, Bedrock, Gemini, Mistral, local models, etc.).

Capability comparison

Feature	OpenAI	Anthropic	LiteLLM
Text generation
Tool calling			(provider-dependent)
Structured output			Provider-dependent
Streaming
Vision (image input)			Provider-dependent
Custom endpoints

Usage

from afk.llms import LLMBuilder

# OpenAI
openai_client = LLMBuilder().provider("openai").model("gpt-5.5").build()

# Anthropic
anthropic_client = LLMBuilder().provider("anthropic").model("opus-4.8").build()

# LiteLLM (any provider)
gemini_client = LLMBuilder().provider("litellm").model("gemini/gemini-2.5-pro").build()

Custom provider

Implement provider and transport contracts

from afk.llms import LLMProvider, LLMRequest, LLMResponse, LLMTransport

class MyTransport(LLMTransport):
    provider_id = "my-provider"

    async def chat(self, request: LLMRequest, *, response_model=None) -> LLMResponse:
        # Translate LLMRequest → your provider's format
        payload = self._build_payload(request)
        resp = await self._post(payload)
        return self._parse_response(resp.json())

class MyProvider(LLMProvider):
    provider_id = "my-provider"

    def create_transport(self, *, settings, middlewares=None, observers=None, provider_settings=None):
        return MyTransport()

from afk.llms import register_llm_provider

register_llm_provider(MyProvider())

Use it

client = LLMBuilder().provider("my-provider").model("my-model").build()

agent = Agent(name="demo", model=client, instructions="...")

Custom transport

Use provider-specific settings for custom endpoints, proxy URLs, or credentials:

client = (
    LLMBuilder()
    .provider("openai")
    .model("gpt-5.5")
    .with_provider_settings("openai", {"base_url": "https://proxy.example.com/v1"})
    .build()
)

Next steps

Control & Session

Retry, caching, rate limiting, and circuit breaking.

Agent Integration

How agents resolve and use LLM clients.

Contracts Control & Session

Start Here

Core Building Blocks

LLM Runtime

Production

Integrations

Built-in providers

OpenAI

Anthropic

LiteLLM

Capability comparison

Usage

Custom provider

Custom transport

Next steps

Control & Session

Agent Integration

​Built-in providers

OpenAI

Anthropic

LiteLLM

​Capability comparison

​Usage

​Custom provider

​Custom transport

​Next steps

Control & Session

Agent Integration

Built-in providers

Capability comparison

Usage

Custom provider

Custom transport

Next steps