mvllm 0.1.0

A FastAPI-based load balancer for vLLM servers with OpenAI-compatible API

vLLM Router

Intelligent load balancer for distributed vLLM server clusters

What problem does it solve?

When you have multiple GPU servers running vLLM, you face:

• Fragmented Resources: Multiple independent GPUs cannot be managed unifiedly
• Unbalanced Load: Some servers are overloaded while others are idle
• Poor Availability: Single server failure affects overall service

vLLM Router provides a unified entry point that intelligently distributes requests to the best servers.

Key Advantages

🎯 Intelligent Load Balancing

• Real-time Monitoring: Direct metrics from vLLM /metrics endpoints
• Smart Algorithm: (running + waiting * 0.5) / capacity
• Priority Selection: Prefers servers with load < 50%
• Zero Queue: Direct forwarding without intermediate queues

🔄 High Availability

• Automatic Failover: Detects and removes unhealthy servers
• Smart Retry: Automatically retries failed requests on other servers
• Hot Reload: Configuration changes without service restart

Quick Start

Installation

git clone https://github.com/xerrors/mvllm.git
pip install -e .

mvllm run

Configuration

Create server configuration file:

cp servers.example.toml servers.toml

Edit servers.toml:

[servers]
servers = [
    { url = "http://gpu-server-1:8081", max_concurrent_requests = 3 },
    { url = "http://gpu-server-2:8088", max_concurrent_requests = 5 },
    { url = "http://gpu-server-3:8089", max_concurrent_requests = 4 },
]

[config]
health_check_interval = 10
request_timeout = 120
max_retries = 3

Running

# Production mode (fullscreen monitoring)
mvllm run

# Development mode (console logging)
mvllm run --console

# Custom port
mvllm run --port 8888

Usage Examples

Chat Completions

curl -X POST http://localhost:8888/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama3.1:8b",
    "messages": [
      {"role": "user", "content": "Hello, please introduce yourself"}
    ]
  }'

Check Load Status

curl http://localhost:8888/health
curl http://localhost:8888/load-stats

API Endpoints

• POST /v1/chat/completions - Chat completions
• POST /v1/completions - Text completions
• GET /v1/models - Model listing
• GET /health - Health status
• GET /load-stats - Load statistics

Deployment

Docker

docker build -t mvllm .
docker run -d -p 8888:8888 -v $(pwd)/servers.toml:/app/servers.toml mvllm

Docker Compose

version: '3.8'
services:
  mvllm:
    build: .
    ports:
      - "8888:8888"
    volumes:
      - ./servers.toml:/app/servers.toml

Configuration

Server Configuration

• url: vLLM server address
• max_concurrent_requests: Maximum concurrent requests

Global Configuration

• health_check_interval: Health check interval (seconds)
• request_timeout: Request timeout (seconds)
• max_retries: Maximum retry attempts

Monitoring

• Real-time Load Monitoring: Shows running and waiting requests per server
• Health Status: Real-time server availability monitoring
• Resource Utilization: GPU cache usage and other metrics

Chinese Version

For Chinese documentation, see README.zh.md

License

MIT License