> ## Documentation Index
> Fetch the complete documentation index at: https://docs.llmrouter.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Factory Droid

> Route Factory Droid through LLM Router to automatically compress massive terminal logs, redact local .env secrets, and optimize token costs.

***

> ## Documentation Index
>
> Fetch the complete documentation index at: [https://docs.llmrouter.app/llms.txt](https://docs.llmrouter.app/llms.txt)
> Use this file to discover all available pages before exploring further.

# Factory Droid & LLM Router

[Factory Droid](https://factory.ai) is an enterprise-grade AI coding agent that lives in your terminal and handles end-to-end development workflows.

Because terminal agents frequently read massive error logs and local `.env` files, routing Factory Droid through **LLM Router** is highly recommended. It automatically prunes bloated terminal history to save costs and redacts your local API keys before they are sent to third-party AI providers.

## Step 1: Installing Factory Droid

If you haven't already installed Factory Droid, run the following command for your OS:

**macOS / Linux:**

```bash theme={null} theme={null}
curl -fsSL https://app.factory.ai/cli | sh
```

**Windows:**

```powershell theme={null} theme={null}
irm https://app.factory.ai/cli/windows | iex
```

## Step 2: Configuring LLM Router

Factory Droid supports BYOK (Bring Your Own Key), which allows us to override the default API endpoints and point all traffic directly to LLM Router.

### 1. Get Your LLM Router API Key

1. Visit the [LLM Router Dashboard](https://llmrouter.app/dashboard)
2. Generate a new API Key (e.g., `sk-router-...`)

### 2. Configure Custom Models in Droid

You need to edit Factory Droid's local settings file.

**Configuration file location:**

* macOS/Linux: `~/.factory/settings.json`
* Windows: `%USERPROFILE%\.factory\settings.json`

<Tip>
  You can configure LLM Router using either the OpenAI format or the Anthropic
  format. Remember to replace `your_llm_router_key` with your actual API Key.
</Tip>

**Method A: OpenRouter / OpenAI Protocol (Recommended)**
Use this to let LLM Router automatically handle routing, or to specifically request OpenAI/Llama models.

```json theme={null} theme={null}
{
  "customModels": [
    {
      "displayName": "LLM Router (Auto Fallback)",
      "model": "openai/gpt-4o", // Or use a tag-based routed model
      "baseUrl": "https://api.llmrouter.app/v1",
      "apiKey": "your_llm_router_key",
      "provider": "generic-chat-completion-api",
      "maxOutputTokens": 8192
    }
  ]
}
```

**Method B: Anthropic Protocol**
Use this if you specifically want to route to Claude models using Anthropic's native formatting.

```json theme={null} theme={null}
{
  "customModels": [
    {
      "displayName": "LLM Router (Claude 3.5 Sonnet)",
      "model": "anthropic/claude-3-5-sonnet",
      "baseUrl": "https://api.llmrouter.app/v1",
      "apiKey": "your_llm_router_key",
      "provider": "anthropic",
      "maxOutputTokens": 8192
    }
  ]
}
```

## Step 3: Start Using Factory Droid

### 1. Launch Droid

Navigate to your project directory and start the droid CLI:

```bash theme={null} theme={null}
cd /path/to/your/project
droid
```

### 2. Select Your LLM Router Model

Once Droid is running, type the `/model` command to change your active AI model:

```text theme={null} theme={null}
/model
```

Your custom LLM Router configurations will appear in a separate "Custom models" section in the terminal UI. Select the one you just configured.

### 3. Start Coding

You can now use Droid to analyze code, implement features, and fix bugs. All traffic is now securely flowing through LLM Router.

***

## Why route Factory Droid through LLM Router?

Terminal-based agents are powerful, but they are incredibly token-hungry and pose unique security risks.

* **PII Redaction:** Droid often reads your local directory to understand context. If it accidentally reads your `.env` file, LLM Router will automatically redact your database passwords and AWS keys before sending the prompt to OpenAI or Anthropic.
* **Context Pruning:** If Droid runs a build command (`npm run build`) and it spits out 10,000 lines of terminal logs, LLM Router's Middle-Out Compression will truncate the bloated middle sections, saving you massive amounts of input token costs.
* **Resilience:** If OpenAI goes down while Droid is refactoring a file, LLM Router will automatically fall back to another provider without breaking your terminal session.