OpenClaw

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.

alexrudloff0 来源安装数☆ 0 仓库 Stars

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install alexrudloff/llmrouter

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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 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

Python 3.10+ with pip
Ollama (optional - only if using local classification)
Anthropic API key or Claude Code OAuth token (or other provider key)

Setup

# 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

# 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

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

# 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"...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/alexrudloff/llmrouter
Version: —
Commit: 0a701e964ae063d83caf311357be1cc5323e8d9e
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# 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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