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@robot-resources/router
@robot-resources/router/lib/python-bridge.js

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Readme

@robot-resources/router

Intelligent LLM cost optimization via local proxy.

Automatically route each LLM request to the cheapest model that can handle it. 60-90% cost savings with no quality loss.

Quick Start

# Run directly (no install needed) — runs the setup wizard on first invocation
npx @robot-resources/router

# Or install globally
npm install -g @robot-resources/router
rr-router

On first run, the wizard:

Installs the Python router engine (venv + pip) in ~/.robot-resources/.venv/
Registers the router as a background service (launchd on macOS, systemd on Linux)
Auto-configures detected AI tools (Claude Code, Cursor) as MCP clients
If no tools are detected, prints copy-pasteable SDK base_url instructions

After that, calls like rr-router start, rr-router status, or rr-router report skip the wizard. Use --setup to re-run it.

Requirements

Node.js >= 18.0.0
Python >= 3.10 (auto-detected; used for the routing engine)

Enterprise / Docker

Inside Docker, the wizard skips service registration and prints three ways to run the router: Dockerfile CMD, Compose sidecar, or background process. Set RR_API_KEY in advance to bypass the auto-signup step entirely.

How It Works

Your Agent (Claude Code, Cursor, etc.)
    |
    | POST /v1/chat/completions  (OpenAI-compatible)
    | model: "auto"
    v
┌─────────────────────────────┐
│  Robot Resources Router     │
│  localhost:3838              │
│                             │
│  1. Detect task type        │
│  2. Find cheapest model     │
│  3. Forward to provider     │
│  4. Track cost savings      │
└─────────────────────────────┘
    |
    v
  Anthropic / OpenAI / Google

Each message is classified (coding, reasoning, simple_qa, etc.) and routed to the cheapest model with sufficient capability for that task.

Example Savings

Turn 1: "hello"                    → gemini-2.0-flash-lite        $0.0000
Turn 2: "what's 2+2?"              → gemini-2.0-flash-lite        $0.0000
Turn 3: "refactor this React code" → gpt-4o-mini                  $0.0002
Turn 4: "thanks, looks good"       → gemini-2.0-flash-lite        $0.0000
─────────────────────────────────────────────────────────────────────────
Total with RR:       $0.0002
Without RR (gpt-4o): $0.0075
Savings:             97%

Configuration

Set provider API keys as environment variables:

export ANTHROPIC_API_KEY="sk-ant-..."
export OPENAI_API_KEY="sk-..."
export GOOGLE_API_KEY="..."

CLI Commands

rr-router start              # Start proxy on localhost:3838
rr-router start --port 4000  # Custom port
rr-router status             # Show status
rr-router report weekly      # Cost savings report (7 days)
rr-router report monthly     # Cost savings report (30 days)

Agent Integration

Point any OpenAI-compatible agent to the proxy:

{
  "baseUrl": "http://localhost:3838",
  "model": "auto"
}

The proxy handles routing transparently. Your agent doesn't need to know about model selection.

License

MIT