commai 0.0.2

Gobal toolbox that allows you to connect, and verify your tools

Commune: Modular Consensus System

Commune AI provides a powerful framework for building distributed AI applications with modular consensus mechanisms. The system enables seamless integration of AI models, distributed computing, and blockchain technology.

Features

These components can be applied to:

• 🔗 Networks - Create and manage distributed networks with custom consensus mechanisms
• 🤖 AI Models - Deploy and serve AI models in a distributed environment
• 💫 Modules - Build modular components that can be composed into larger systems
• 🔑 Keys - Manage cryptographic keys and identities securely
• 🖥️ Servers - Deploy and monitor distributed services
• ✨ Validation - Implement custom validation rules and scoring mechanisms

Quick Tour

To immediately start using Commune, you can create and serve a module with just a few lines of code:

import commune as c

# Create a simple module
class MyModule(c.Module):
    def __init__(self, param1=1):
        self.set_config(locals())
        
    def forward(self, x):
        return x * self.param1

# Serve the module
module = c.serve('MyModule')

Basic CLI usage:

# Create a new module
>>>c new_module my_module

# Serve a module
>>>c serve my_module

# Call a module function
>>>c call my_module/forward 10

Installation

With pip

pip install commai

From source

git clone https://github.com/commune-ai/commune.git
cd commune
pip install -e .

Development setup

chmod +x ./run/***
sudo ./run/install.sh  # Install development environment

Core Components

1. Module System

Modules are the building blocks of Commune applications:

import commune as c

class CustomModule(c.Module):
    def __init__(self, config=None):
        self.set_config(config)
    
    def process(self, data):
        return self.model(data)

2. Network Management

Create and manage distributed networks:

# Start a local network
c.serve('mymodule', network='local')

# Join a subnet
c.serve('mymodule', network='subspace', netuid=0)

3. Validation System

Implement custom validation rules:

class Validator(c.Module):
    def validate(self, module):
        score = self.evaluate_performance(module)
        return score

CLI Reference

Commune provides an intuitive CLI interface:

# Module operations
c new_module <name>        # Create new module
c serve <module>           # Serve module
c call <module>/<function> # Call module function
c modules                  # List modules

# Key management
c add_key <name>          # Generate new key
c keys                    # List keys
c sign <message>          # Sign message

# Server management
c servers                 # List servers
c connect <module>        # Connect to server
c logs <module>           # View logs

Why Commune?

1. Modular Design:

   • Build complex systems from simple components
   • Easy-to-use module system
   • Flexible composition of services

2. Distributed Computing:

   • Scale across multiple nodes
   • Built-in consensus mechanisms
   • Robust networking layer

3. AI Integration:

   • Deploy AI models as services
   • Distributed training support
   • Model validation and scoring

4. Security:

   • Built-in key management
   • Secure communication
   • Validation mechanisms

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

MIT License