* Add github copilot as LLM provider.
* Fix Copilot in Openclaw
* security: harden Copilot OAuth token handling
C1: Use secrecy::SecretString for oauth_token and cached session token
in CopilotTokenManager/CachedCopilotToken. Expose only at HTTP
header injection point via .expose_secret().
C2: Document risks of hardcoded VS Code OAuth client ID and editor
identity headers (ToS, rotation, staleness). Remove the unreliable
paste-token setup path (setup_github_copilot_manual_token).
C3: Fix TOCTOU race in get_token() — re-check token validity after
acquiring write lock so concurrent callers don't all perform
redundant token exchanges.
I1: Remove dead empty else {} block in get_token().
I2: Map 401 responses to LlmError::AuthFailed instead of RequestFailed
so retry/circuit-breaker logic handles auth failures correctly.
I3: Replace prepare_github_copilot_setup() with call to existing
set_llm_backend_preserving_model() helper to avoid logic drift.
I4: Add unit tests for CopilotTokenManager (caching, invalidation,
expiry/buffer behavior), poll response parsing (all OAuth device
flow states), and DeviceCodeResponse/CopilotTokenResponse deserialization.
Co-authored-by: Copilot <[email protected]>
* fix: address review feedback and code improvements (takeover #1202)
- Fix ContentPart::Text being silently dropped in convert_messages
- Replace custom truncate_for_error with crate::util::floor_char_boundary
- Fix CLAUDE.md: accurately describe dedicated provider (not "OpenAI-compatible path")
- Fix "Github" -> "GitHub" capitalization in READMEs
- Add manual token paste option to setup wizard (not just device login)
- Fix missing extension_manager field in EngineContext (merge fixup)
- cargo fmt applied
Co-Authored-By: fallenwood <[email protected]>
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: address PR review feedback for GitHub Copilot provider
- Plumb request_timeout_secs into GithubCopilotProvider (was hardcoded 120s)
- Forward stop_sequences to Copilot API via OpenAI `stop` field
- Skip empty text part in multimodal message conversion
- Improve paste-token wizard hint with specific file path guidance
Co-Authored-By: fallenwood <[email protected]>
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: 401 retry, retryable token exchange errors, shared retry-after parsing
- Retry once inline on 401 after token invalidation (was returning
AuthFailed immediately, guaranteeing user-visible failure)
- Map token exchange failures to RequestFailed (retryable) instead of
AuthFailed (non-retryable by RetryProvider)
- Use shared crate::llm::retry::parse_retry_after for HTTP-date support
and safe 60s default
- Improve paste-token wizard hint: mention `gh auth token` as primary source
Co-Authored-By: fallenwood <[email protected]>
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: 401 retry error mapping, retry status logging, token whitespace safety
- Map 401 retry get_token() failure to RequestFailed (retryable),
consistent with initial token acquisition path
- Log retry response status before returning AuthFailed
- Trim oauth_token in exchange_copilot_token to prevent header panics
from whitespace in env vars
Co-Authored-By: fallenwood <[email protected]>
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
---------
Co-authored-by: Fallenwood <[email protected]>
Co-authored-by: Copilot <[email protected]>
Co-authored-by: fallenwood <[email protected]>
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
7.9 KiB
LLM Provider Configuration
IronClaw defaults to NEAR AI for model access, but supports any OpenAI-compatible endpoint as well as Anthropic and Ollama directly. This guide covers the most common configurations.
Provider Overview
| Provider | Backend value | Requires API key | Notes |
|---|---|---|---|
| NEAR AI | nearai |
OAuth (browser) | Default; multi-model |
| Anthropic | anthropic |
ANTHROPIC_API_KEY |
Claude models |
| OpenAI | openai |
OPENAI_API_KEY |
GPT models |
| Google Gemini | gemini |
GEMINI_API_KEY |
Gemini models |
| 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 (default)
No additional configuration required. On first run, ironclaw onboard opens a browser
for OAuth authentication. Credentials are saved to ~/.ironclaw/session.json.
NEARAI_MODEL=claude-3-5-sonnet-20241022
NEARAI_BASE_URL=https://private.near.ai
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
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-syscrate (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
Using the Setup Wizard
Instead of editing .env manually, run the onboarding wizard:
ironclaw onboard
Select "OpenAI-compatible" for OpenRouter, Together AI, Fireworks, vLLM, LiteLLM, or LM Studio. You will be prompted for the base URL and (optionally) an API key. The model name is configured in the following step.