# 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-M2.5 models |
| Cloudflare Workers AI | `cloudflare` | `CLOUDFLARE_API_KEY` | Access to Workers AI |
| 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`.

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

---

## Anthropic (Claude)

```env
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)

```env
LLM_BACKEND=openai
OPENAI_API_KEY=sk-...
```

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

---

## Ollama (local)

Install Ollama from [ollama.com](https://ollama.com), pull a model, then:

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

Pull a model first: `ollama pull llama3.2`

---

## MiniMax

[MiniMax](https://platform.minimax.io) provides high-performance language models with 204,800 token context windows.

```env
LLM_BACKEND=minimax
MINIMAX_API_KEY=...
```

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

To use the China mainland endpoint, set:

```env
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)

```env
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](https://openrouter.ai) routes to 300+ models from a single API key.

```env
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](https://openrouter.ai/models).

### Together AI

[Together AI](https://www.together.ai) provides fast inference for open-source models.

```env
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](https://fireworks.ai) offers fast inference with compound AI system support.

```env
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:

```env
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):

```env
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:

```env
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:

```bash
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.
