Overview
- Skill Key
- alexrudloff/llmrouter
- Author
- alexrudloff
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/alexrudloff/llmrouter
- Latest Commit SHA
- 0a701e964ae063d83caf311357be1cc5323e8d9e
Official OpenClaw
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llmrouter
Intelligent LLM proxy that routes requests to appropriate models based on complexity. Save money by using cheaper models for simple tasks. Tested with Anthropic, OpenAI, Gemini, Kimi/Moonshot, and Ollama.
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
安装方式
直接复制以下提示词，发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店，若未安装，请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店，然后安装 llmrouter 技能。 若已安装，则直接安装 llmrouter 技能。
Extracted Content
SKILL.md excerpt
# LLM Router
An intelligent proxy that classifies incoming requests by complexity and routes them to appropriate LLM models. Use cheaper/faster models for simple tasks and reserve expensive models for complex ones.
**Works with [OpenClaw](https://github.com/openclaw/openclaw)** to reduce token usage and API costs by routing simple requests to smaller models.
**Status:** Tested with Anthropic, OpenAI, Google Gemini, Kimi/Moonshot, and Ollama.
## Quick Start
### Prerequisites
1. **Python 3.10+** with pip
2. **Ollama** (optional - only if using local classification)
3. **Anthropic API key** or Claude Code OAuth token (or other provider key)
### Setup
```bash
# Clone if not already present
git clone https://github.com/alexrudloff/llmrouter.git
cd llmrouter
# Create virtual environment (required on modern Python)
python3 -m venv venv
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
# Pull classifier model (if using local classification)
ollama pull qwen2.5:3b
# Copy and customize config
cp config.yaml.example config.yaml
# Edit config.yaml with your API key and model preferences
```
### Verify Installation
```bash
# Start the server
source venv/bin/activate
python server.py
# In another terminal, test health endpoint
curl http://localhost:4001/health
# Should return: {"status": "ok", ...}
```
### Start the Server
```bash
python server.py
```
Options:
- `--port PORT` - Port to listen on (default: 4001)
- `--host HOST` - Host to bind (default: 127.0.0.1)
- `--config PATH` - Config file path (default: config.yaml)
- `--log` - Enable verbose logging
- `--openclaw` - Enable OpenClaw compatibility (rewrites model name in system prompt)
## Configuration
Edit `config.yaml` to customize:
### Model Routing
```yaml
# Anthropic routing
models:
super_easy: "anthropic:claude-haiku-4-5-20251001"
easy: "anthropic:claude-haiku-4-5-20251001"
medium: "anthropic:claude-sonnet-4-20250514"
hard: "anthropic:claude-opus-4-20250514"...
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