agentfather 1.0.0

AI agent framework with email, file, and voice processing

AgentFather

A comprehensive AI agent framework with email, file, and voice processing capabilities built on top of LangChain.

Features

• 🤖 AI Agent Framework: Built on LangChain for intelligent automation
• 📧 Email Processing: Advanced email handling and automation
• 📁 File Management: Comprehensive file operations and processing
• 🎤 Voice Processing: Speech recognition and text-to-speech capabilities
• 🔧 Modular Design: Easy to extend and customize
• 🚀 Production Ready: Includes testing, documentation, and deployment tools

Installation

From PyPI (Recommended)

pip install agentfather

From Source

git clone https://github.com/yourusername/agentfather.git
cd agentfather
pip install -e .

Development Installation

git clone https://github.com/yourusername/agentfather.git
cd agentfather
pip install -e ".[dev,test,docs]"

Quick Start

Basic Usage

from agentfather import AgentFather

# Initialize the agent
agent = AgentFather()

# Process an email
result = agent.process_email("[e-mail]", "Hello, I need help with my order")

# Process a file
result = agent.process_file("document.pdf")

# Process voice input
result = agent.process_voice("audio.wav")

Command Line Interface

# Run the agent interactively
agentfather

# Process specific tasks
agentfather email --input "[e-mail]"
agentfather file --input "document.pdf"
agentfather voice --input "audio.wav"

Project Structure

agentfather/
├── agentfather/              # Main package
│   ├── __init__.py
│   ├── core/                 # Core functionality
│   │   ├── __init__.py
│   │   ├── agent.py
│   │   └── config.py
│   ├── email/                # Email processing
│   │   ├── __init__.py
│   │   ├── email_functions.py
│   │   └── Email.py
│   ├── files/                # File processing
│   │   ├── __init__.py
│   │   ├── path_functions.py
│   │   └── path.py
│   ├── voice/                # Voice processing
│   │   ├── __init__.py
│   │   ├── voice_functions.py
│   │   ├── Vosk.py
│   │   └── eleven_labs.py
│   ├── utils/                # Utilities
│   │   ├── __init__.py
│   │   ├── langchain_imports.py
│   │   ├── rag_functions.py
│   │   └── file_functions.py
│   └── cli.py                # Command line interface
├── DummyData/                # Sample data
├── tests/                    # Test suite
├── docs/                     # Documentation
├── setup.py                  # Package setup
├── pyproject.toml           # Modern package configuration
├── README.md                # This file
├── LICENSE                  # License file
├── CHANGELOG.md             # Version history
├── .gitignore               # Git ignore rules
├── requirements.txt         # Dependencies
├── requirements-dev.txt     # Development dependencies
└── MANIFEST.in              # Package manifest

Configuration

Create a .env file in your project root:

# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here

# Email Configuration
EMAIL_HOST=smtp.gmail.com
EMAIL_PORT=587
EMAIL_USER=[e-mail]
EMAIL_PASSWORD=your_app_password

# Voice Configuration
ELEVENLABS_API_KEY=your_elevenlabs_api_key
VOSK_MODEL_PATH=/path/to/vosk/model

# Database Configuration
DATABASE_URL=postgresql://user:password@localhost/dbname

# Redis Configuration
REDIS_URL=redis://localhost:6379

Usage Examples

Email Processing

from agentfather.email import EmailProcessor

processor = EmailProcessor()

# Process incoming emails
emails = processor.fetch_emails()
for email in emails:
    response = processor.process_email(email)
    processor.send_response(email.sender, response)

File Processing

from agentfather.files import FileProcessor

processor = FileProcessor()

# Process different file types
processor.process_pdf("document.pdf")
processor.process_docx("document.docx")
processor.process_image("image.png")

Voice Processing

from agentfather.voice import VoiceProcessor

processor = VoiceProcessor()

# Speech to text
text = processor.speech_to_text("audio.wav")

# Text to speech
processor.text_to_speech("Hello, world!", "output.wav")

RAG (Retrieval-Augmented Generation)

from agentfather.utils import RAGProcessor

rag = RAGProcessor()

# Add documents to knowledge base
rag.add_documents(["doc1.pdf", "doc2.txt"])

# Query the knowledge base
response = rag.query("What is the main topic?")

Development

Setting up Development Environment

# Clone the repository
git clone https://github.com/yourusername/agentfather.git
cd agentfather

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

# Install development dependencies
pip install -e ".[dev,test,docs]"

# Install pre-commit hooks
pre-commit install

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=agentfather

# Run specific test categories
pytest -m unit
pytest -m integration
pytest -m "not slow"

Code Quality

# Format code
black agentfather/
isort agentfather/

# Lint code
flake8 agentfather/
mypy agentfather/

# Security check
bandit -r agentfather/
safety check

Building Documentation

# Build docs
cd docs
make html

# Serve docs locally
python -m http.server 8000

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Follow PEP 8 style guidelines
• Write comprehensive tests for new features
• Update documentation for any API changes
• Use type hints for all function parameters and return values
• Write clear commit messages

License

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

Support

• 📧 Email: [e-mail]
• 💬 Discord: Join our community
• 📖 Documentation: Read the docs
• 🐛 Issues: Report a bug

Changelog

See CHANGELOG.md for a list of changes and version history.

Acknowledgments

• LangChain for the AI framework
• OpenAI for language models
• ElevenLabs for voice synthesis
• Vosk for speech recognition

Roadmap

• Web UI interface
• Mobile app support
• Multi-language support
• Advanced analytics dashboard
• Plugin system
• Cloud deployment templates
• Enterprise features