/aida

AI Digital Assistant

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Aida AI Assistant

Aida is a sophisticated AI assistant that combines voice interaction, text processing, and memory capabilities to provide a natural and context-aware conversational experience.

⚠️ Development Status Warning

IMPORTANT: This project is in early development and is NOT production-ready!

  • 🚧 Active Development: This project is under heavy development and changes frequently
  • 🐛 Bugs Expected: You will encounter bugs, crashes, and incomplete features
  • ⚗️ Experimental: Many features are experimental and may not work as expected
  • 🔧 Breaking Changes: Updates may include breaking changes without notice
  • ⚡ Unstable: Core functionality may be unstable or entirely non-functional

Known Limitations

  • Voice recognition may be unreliable
  • Memory system is experimental and slow
  • Limited error handling
  • Incomplete documentation

Use at your own risk! This is currently a proof-of-concept and learning project.

Features

  • Voice and text interaction modes
  • Wake word detection ("Jarvis")
  • Real-time speech-to-text processing
  • Natural text-to-speech responses
  • Long-term memory and context awareness
  • Web search capabilities
  • Conversation history management
  • Multi-user support

Prerequisites

  • Python 3.10+
  • Docker (for Qdrant vector database)
  • Required API keys:
    • ElevenLabs (TTS)
    • Deepgram (STT)
    • Picovoice (Wake word)
    • Anthropic Claude (LLM)
    • Perplexity (Web search)
    • OpenAI (Embeddings)

Installation

  1. Clone the repository:
git clone https://github.com/BurtTheCoder/aida.git
cd aida
  1. Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate  # Unix/macOS
# or
.\venv\Scripts\activate  # Windows
  1. Install required packages:
pip install -r requirements.txt
  1. Set up environment variables:
cp .env.example .env
# Edit .env with your API keys
  1. Start Qdrant database:
cd storage
docker-compose up -d
  1. Initialize memory system:
python setup_memory.py

Usage

Running the Assistant

Basic usage:

python main.py

Available command-line arguments:

  • --mode: Choose between 'voice' or 'text' mode (default: voice)
  • --debug: Enable debug logging
  • --no-tts: Disable text-to-speech in text mode
  • --user-id: Specify user ID for memory persistence

Examples:

# Run in text mode
python main.py --mode text

# Run with debug logging
python main.py --debug

# Run for specific user
python main.py --user-id user123

Project Structure

aida/
├── config/            # Configuration files
├── core/              # Core functionality
├── modes/             # Interaction modes
├── services/          # Service implementations
├── storage/           # Database and persistence
├── tools/             # Agent Tools
├── utils/             # Helper utilities
└── main.py            # Entry point

Core Components

Assistant (core/assistant.py)

  • Main assistant logic
  • Tool management
  • Input processing

Memory System (services/memory_service.py)

  • Long-term memory storage
  • Context retrieval
  • Memory management

Voice Processing

  • Wake word detection (services/wake_word.py)
  • Speech-to-text (services/stt_service.py)
  • Text-to-speech (services/tts_service.py)

Tools

  • Web search (tools/web_search.py)
  • Memory operations (tools/memory_tools.py)

Development

Adding New Features

  1. Create new service in services/
  2. Add configuration in config/
  3. Implement tool in tools/ if needed
  4. Update assistant to use new feature

Testing

Run tests:

python -m pytest tests/

Logging

Logs are handled by the custom logging system in utils/logging.py. Enable debug logging with the --debug flag.

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit changes
  4. Submit pull request

Acknowledgments

  • ElevenLabs for TTS
  • Deepgram for STT
  • Anthropic for Claude AI
  • Picovoice for wake word detection
  • Qdrant for vector storage