mailos 0.1.2

An AI-powered email monitoring and response system

📯 Mailos

Mailos is a Python framework that transforms email inboxes into an intelligent multi-agent system powered by Large Language Models (LLMs). It creates a network of AI agents that monitor email accounts and orchestrate automated interactions, leveraging various AI providers including OpenAI, Anthropic, and AWS Bedrock.

🤖 Multi-Agent System

Mailos transforms emails into a sophisticated multi-agent ecosystem:

• Each email account becomes an autonomous agent capable of understanding and responding to messages
• Agents can collaborate and coordinate responses across multiple email accounts
• Built-in tool system allows agents to perform complex tasks (weather lookup, PDF manipulation, code execution)
• Configurable system prompts guide agent behavior and decision-making
• Smart filtering prevents unnecessary auto-replies and feedback loops

✨ Features

• 🤖 Multiple LLM Provider Support (OpenAI, Anthropic Claude, AWS Bedrock)
• 📧 IMAP Email Monitoring
• ⚡ Real-time Email Processing
• 🔄 Automatic Response Generation
• 🎯 Smart Reply Filtering
• 🌐 Web-based Configuration Interface
• ⏱️ Scheduled Email Checking
• 🛠️ Extensible Tool System
• 🔒 Optional Authentication System

🚀 Installation

pip install mailos

🏃 Quick Start

1. Launch the web interface:

mailos

2. Open your browser and navigate to http://localhost:8080

3. Click "Add New Checker" and configure your email account:

   • Email credentials (IMAP server, port, etc.)
   • LLM provider settings
   • Auto-reply preferences
   • Tool configurations
   • System prompts

⚙️ Configuration

Authentication Settings

By default, the web interface is accessible without authentication. To enable authentication:

# Enable authentication
export MAILOS_AUTH_ENABLED=true

# Optional: Configure custom credentials (defaults to admin/admin)
export MAILOS_AUTH_USERNAME=your_username
export MAILOS_AUTH_PASSWORD=your_password

# Start Mailos
mailos

Email Settings

• IMAP server and port
• Email address and password
• Monitoring frequency
• Auto-reply settings
• Tool permissions

LLM Provider Options

OpenAI

{
    "llm_provider": "openai",
    "model": "gpt-4",
    "api_key": "your-api-key"
}

Anthropic Claude

{
    "llm_provider": "anthropic",
    "model": "claude-3-sonnet",
    "api_key": "your-api-key"
}

AWS Bedrock (Claude)

{
    "llm_provider": "bedrock-anthropic",
    "model": "anthropic.claude-3-sonnet",
    "aws_access_key": "your-access-key",
    "aws_secret_key": "your-secret-key",
    "aws_region": "us-east-1"
}

🛠️ Tool System

Mailos includes a powerful tool system that extends agent capabilities:

Built-in Tools

• Weather Tool: Fetch weather information
• PDF Tool: Create and manipulate PDF documents
• Python Interpreter: Execute Python code
• Bash Command: Run system commands

Tool Configuration

{
    "enabled_tools": ["weather", "python_interpreter"],
    "tool_config": {
        "weather": {
            "default_units": "metric",
            "api_key": "your-api-key"
        },
        "python_interpreter": {
            "timeout": 30,
            "max_memory": 128
        }
    }
}

🔧 Development

1. Clone the repository:

git clone https://github.com/tomatyss/mailos.git
cd mailos

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install development dependencies:

pip install -e ".[dev]"

4. Run tests:

pytest

🏗️ Architecture

The package consists of several key components:

1. Email Monitor: Continuously checks for new emails using IMAP

startLine: 29
endLine: 78

2. LLM Integration: Supports multiple AI providers through a unified interface

startLine: 8
endLine: 65

3. Reply Handler: Manages email response generation and filtering

startLine: 169
endLine: 192

System Requirements

• Python 3.8 or higher
• pip package manager
• IMAP-enabled email account
• API keys for chosen LLM provider
• Internet connection for email and API access

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

Development Setup

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests and linting
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

Ivan Iufriakov ([e-mail])

🙏 Acknowledgments

• PyWebIO for the web interface
• APScheduler for task scheduling
• OpenAI, Anthropic, and AWS for their LLM services