LLMule Client

A peer-to-peer client for sharing Large Language Models (LLMs) across the LLMule network. Run your local LLMs and share them with the community.

🌐 Official Website: https://llmule.xyz 💬 Join our Community: Discord Channel

Features

• Automatic detection of local LLM models (Ollama & LM Studio)
• Real-time connection to the LLMule network
• Model tier categorization (Tiny, Small, Medium)
• Health monitoring and automatic reconnection
• Secure API key authentication

Prerequisites

• Node.js v20 or higher
• One of the following LLM backends:
  • Ollama (recommended)
  • LM Studio

Installation

1. Clone the repository:

git clone https://github.com/cm64-studio/LLMule-client.git
cd LLMule-client

2. Install dependencies:

npm install

3. Create a configuration file:

cp .env.example .env

Configuration

Edit .env file with your settings. Don't worry about the API key - you'll get it automatically during the first run registration process at llmule.xyz.

# Server Configuration
API_URL=https://api.llmule.xyz
SERVER_URL=wss://api.llmule.xyz/llm-network

# LLM Provider URLs (defaults)
OLLAMA_URL=http://localhost:11434
LMSTUDIO_URL=http://localhost:1234/v1

# Advanced
LOG_LEVEL=info
MAX_RETRIES=5

Supported Models

Tier 1 - Small (3B)

• TinyLlama
• Minimum Requirements: 4GB RAM

Tier 2 - Medium (7B)

• Mistral 7B
• Minimum Requirements: 8GB RAM

Tier 3 - Large (14B)

• Microsoft Phi-4
• Minimum Requirements: 16GB RAM

Supported LLM Providers

LLMule supports the following LLM providers:

• Ollama: Run models like Llama, Mistral, and more locally
• LM Studio: Run various open-source models with a nice UI
• EXO: Run distributed models across multiple devices

Configuration

Set up your providers in your .env file:

OLLAMA_URL=http://localhost:11434
LMSTUDIO_URL=http://localhost:1234/v1
EXO_URL=http://localhost:52415

Usage

1. Start your LLM backend (Ollama or LM Studio)

2. Run the client:

npm start

3. First-time setup:
   • On first run, you'll be guided through the registration process at llmule.xyz
   • Your API key will be automatically configured after registration
   • Select the models you want to share
   • The client will automatically connect to the LLMule network

Running as a Service

Systemd Service (Linux)

1. Create service file:

sudo nano /etc/systemd/system/llmule-client.service

2. Add configuration:

[Unit]
Description=LLMule Client
After=network.target ollama.service

[Service]
Type=simple
User=ubuntu
WorkingDirectory=/path/to/llmule-client
ExecStart=/usr/bin/npm start
Restart=always
Environment=NODE_ENV=production

[Install]
WantedBy=multi-user.target

3. Enable and start:

sudo systemctl enable llmule-client
sudo systemctl start llmule-client

Monitoring

Check client status:

npm run status

View logs:

# Live logs
npm run logs

# Error logs
npm run logs:error

Troubleshooting

Common issues and solutions:

1. Connection Issues

# Check network connectivity
curl -v $SERVER_URL

# Verify Ollama is running
curl http://localhost:11434/api/tags

2. Model Detection Issues

# List Ollama models
ollama list

# Check LM Studio API
curl http://localhost:1234/v1/models

Contributing

1. Fork the repository
2. Create feature branch
3. Commit changes
4. Push to branch
5. Create Pull Request

Security

• API keys are stored securely
• All network traffic is encrypted
• Models are sandboxed
• Resource limits enforced

Support

• GitHub Issues: Report Bug
• Email: andres@cm64.studio

License

MIT License - see LICENSE for details