Skip to content

llm-providers.md

Latest commit

 

History

History
318 lines (234 loc) · 12.2 KB

llm-providers.md

File metadata and controls

318 lines (234 loc) · 12.2 KB
Raw
title Inference Providers
description IronClaw readily supports multiple LLM providers

IronClaw supports multiple LLM providers out of the box, including NEAR AI , Anthropic, OpenAI, Google Gemini, GitHub Copilot, Ollama, AWS Bedrock, and any OpenAI-compatible endpoint.

Providers can be configured via environment variables or the onboarding wizard. IronClaw's modular architecture allows seamless integration with new providers by implementing the LLMProvider trait.

Configuring a Provider

To config a new provider, simply run the onboarding wizard:

ironclaw onboard --provider-only

Provider Overview

Provider Backend value Requires API key Notes
NEAR AI nearai OAuth (browser) Multi-model
Anthropic anthropic ANTHROPIC_API_KEY Claude models
OpenAI openai OPENAI_API_KEY GPT models
Google Gemini gemini_oauth OAuth (browser) Gemini models; function calling
io.net ionet IONET_API_KEY Intelligence API
Mistral mistral MISTRAL_API_KEY Mistral models
Yandex AI Studio yandex YANDEX_API_KEY YandexGPT models
MiniMax minimax MINIMAX_API_KEY MiniMax-M2.7 models
Cloudflare Workers AI cloudflare CLOUDFLARE_API_KEY Access to Workers AI
GitHub Copilot github_copilot GITHUB_COPILOT_TOKEN Multi-models
Ollama ollama No Local inference
AWS Bedrock bedrock AWS credentials Native Converse API
OpenRouter openai_compatible LLM_API_KEY 300+ models
Together AI openai_compatible LLM_API_KEY Fast inference
Fireworks AI openai_compatible LLM_API_KEY Fast inference
vLLM / LiteLLM openai_compatible Optional Self-hosted
LM Studio openai_compatible No Local GUI

NEAR AI

NEARAI_MODEL=claude-3-5-sonnet-20241022
NEARAI_BASE_URL=https://private.near.ai

Popular models: Qwen/Qwen3.5-122B-A10B, black-forest-labs/FLUX.2-klein-4B, zai-org/GLM-5-FP8

Anthropic (Claude)

LLM_BACKEND=anthropic
ANTHROPIC_API_KEY=sk-ant-...

Popular models: claude-sonnet-4-20250514, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022

OpenAI (GPT)

LLM_BACKEND=openai
OPENAI_API_KEY=sk-...

Popular models: gpt-4o, gpt-4o-mini, o3-mini

Google Gemini (OAuth)

Uses Google OAuth with PKCE (S256) for authentication — no API key required. On first run, a browser opens for Google account login. Credentials (including refresh token) are saved to ~/.gemini/oauth_creds.json with 0600 permissions.

LLM_BACKEND=gemini_oauth
GEMINI_MODEL=gemini-2.5-flash

Supported features

Feature Status Notes
Function calling ✅ functionDeclarations / functionCall / functionResponse
generationConfig ✅ temperature, maxOutputTokens passed from request
thinkingConfig ✅ thinkingBudget/thinkingLevel for thinking-capable models (does NOT set includeThoughts)
toolConfig ✅ functionCallingConfig.mode: AUTO/ANY/NONE
SSE streaming ✅ Cloud Code API with streamGenerateContent?alt=sse
Token refresh ✅ Automatic via refresh token

Popular models

Model ID Notes
Gemini 3.1 Pro gemini-3.1-pro-preview Latest, strongest reasoning
Gemini 3.1 Pro Custom Tools gemini-3.1-pro-preview-customtools Enhanced tool use
Gemini 3 Pro gemini-3-pro-preview Preview
Gemini 3 Flash gemini-3-flash-preview Fast preview with thinking
Gemini 3.1 Flash Lite gemini-3.1-flash-lite-preview Preview, lightweight
Gemini 2.5 Pro gemini-2.5-pro Stable, strong reasoning
Gemini 2.5 Flash gemini-2.5-flash Fast, good quality
Gemini 2.5 Flash Lite gemini-2.5-flash-lite Fastest, lightweight

Cloud Code API vs standard API

Models containing -preview (with hyphen) or gemini-3 in the name, as well as any gemini- model with major version >= 2, route through the Cloud Code API (cloudcode-pa.googleapis.com) which supports SSE streaming and project-scoped access. Other models use the standard Generative Language API (generativelanguage.googleapis.com).

GitHub Copilot

GitHub Copilot exposes chat endpoint at https://api.githubcopilot.com. IronClaw uses that endpoint directly through the built-in github_copilot provider.

LLM_BACKEND=github_copilot
GITHUB_COPILOT_TOKEN=gho_...
GITHUB_COPILOT_MODEL=gpt-4o
# Optional advanced headers if your setup needs them:
# GITHUB_COPILOT_EXTRA_HEADERS=Copilot-Integration-Id:vscode-chat

ironclaw onboard can acquire this token for you using GitHub device login. If you already signed into Copilot through VS Code or a JetBrains IDE, you can also reuse the oauth_token stored in ~/.config/github-copilot/apps.json. If you prefer, LLM_BACKEND=github-copilot also works as an alias.

Popular models vary by subscription, but gpt-4o is a safe default. IronClaw keeps model entry manual for this provider because GitHub Copilot model listing may require extra integration headers on some clients. IronClaw automatically injects the standard VS Code identity headers (User-Agent, Editor-Version, Editor-Plugin-Version, Copilot-Integration-Id) and lets you override them with GITHUB_COPILOT_EXTRA_HEADERS.

Ollama (local)

Install Ollama from ollama.com, pull a model, then:

LLM_BACKEND=ollama
OLLAMA_MODEL=llama3.2
# OLLAMA_BASE_URL=http://localhost:11434   # default

Pull a model first: ollama pull llama3.2

MiniMax

MiniMax provides high-performance language models with 204,800 token context windows.

LLM_BACKEND=minimax
MINIMAX_API_KEY=...

Available models: MiniMax-M2.7 (default), MiniMax-M2.7-highspeed, MiniMax-M2.5, MiniMax-M2.5-highspeed

To use the China mainland endpoint, set:

MINIMAX_BASE_URL=https://api.minimaxi.com/v1

AWS Bedrock (requires --features bedrock)

Uses the native AWS Converse API via aws-sdk-bedrockruntime. Supports standard AWS authentication methods: IAM credentials, SSO profiles, and instance roles.

Build prerequisite: The aws-lc-sys crate (transitive dependency via AWS SDK) requires CMake to compile. Install it before building with --features bedrock:

  • macOS: brew install cmake
  • Ubuntu/Debian: sudo apt install cmake
  • Fedora: sudo dnf install cmake

With AWS credentials (IAM, SSO, instance roles)

LLM_BACKEND=bedrock
BEDROCK_MODEL=anthropic.claude-opus-4-6-v1
BEDROCK_REGION=us-east-1
BEDROCK_CROSS_REGION=us
# AWS_PROFILE=my-sso-profile   # optional, for named profiles

The AWS SDK credential chain automatically resolves credentials from environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY), shared credentials file (~/.aws/credentials), SSO profiles, and EC2/ECS instance roles.

Cross-region inference

Set BEDROCK_CROSS_REGION to route requests across AWS regions for capacity:

Prefix Routing
us US regions (us-east-1, us-east-2, us-west-2)
eu European regions
apac Asia-Pacific regions
global All commercial AWS regions
(unset) Single-region only

Popular Bedrock model IDs

Model ID
Claude Opus 4.6 anthropic.claude-opus-4-6-v1
Claude Sonnet 4.5 anthropic.claude-sonnet-4-5-20250929-v1:0
Claude Haiku 4.5 anthropic.claude-haiku-4-5-20251001-v1:0
Amazon Nova Pro amazon.nova-pro-v1:0
Llama 4 Maverick meta.llama4-maverick-17b-instruct-v1:0

OpenAI-Compatible Endpoints

All providers below use LLM_BACKEND=openai_compatible. Set LLM_BASE_URL to the provider's OpenAI-compatible endpoint and LLM_API_KEY to your API key.

OpenRouter

OpenRouter routes to 300+ models from a single API key.

LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://openrouter.ai/api/v1
LLM_API_KEY=sk-or-...
LLM_MODEL=anthropic/claude-sonnet-4

Popular OpenRouter model IDs:

Model ID
Claude Sonnet 4 anthropic/claude-sonnet-4
GPT-4o openai/gpt-4o
Llama 4 Maverick meta-llama/llama-4-maverick
Gemini 2.0 Flash google/gemini-2.0-flash-001
Mistral Small mistralai/mistral-small-3.1-24b-instruct

Browse all models at openrouter.ai/models.

Together AI

Together AI provides fast inference for open-source models.

LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://api.together.xyz/v1
LLM_API_KEY=...
LLM_MODEL=meta-llama/Llama-3.3-70B-Instruct-Turbo

Popular Together AI model IDs:

Model ID
Llama 3.3 70B meta-llama/Llama-3.3-70B-Instruct-Turbo
DeepSeek R1 deepseek-ai/DeepSeek-R1
Qwen 2.5 72B Qwen/Qwen2.5-72B-Instruct-Turbo

Fireworks AI

Fireworks AI offers fast inference with compound AI system support.

LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://api.fireworks.ai/inference/v1
LLM_API_KEY=fw_...
LLM_MODEL=accounts/fireworks/models/llama4-maverick-instruct-basic

vLLM / LiteLLM (self-hosted)

For self-hosted inference servers:

LLM_BACKEND=openai_compatible
LLM_BASE_URL=http://localhost:8000/v1
LLM_API_KEY=token-abc123        # set to any string if auth is not configured
LLM_MODEL=meta-llama/Llama-3.1-8B-Instruct

LiteLLM proxy (forwards to any backend, including Bedrock, Vertex, Azure):

LLM_BACKEND=openai_compatible
LLM_BASE_URL=http://localhost:4000/v1
LLM_API_KEY=sk-...
LLM_MODEL=gpt-4o                 # as configured in litellm config.yaml

LM Studio (local GUI)

Start LM Studio's local server, then:

LLM_BACKEND=openai_compatible
LLM_BASE_URL=http://localhost:1234/v1
LLM_MODEL=llama-3.2-3b-instruct-q4_K_M
# LLM_API_KEY is not required for LM Studio