aPersona - AI-Powered Personal Assistant
A fully local, offline AI-powered personal assistant that learns from your personal files, preferences, and behavior to act as your intelligent secretary.
🔹 Key Features
- 100% Local & Offline: No cloud dependencies, complete data privacy
- User Authentication: Secure local user management
- File Analysis: Automatic categorization of documents, images, PDFs
- Semantic Search: Vector-based search through your personal data
- Local LLM Integration: Powered by Ollama with RAG capabilities
- Auto-Learning: Adaptive behavior based on user interactions
- Smart Reminders: Context-aware suggestions and notifications
- Personal Context: Deep understanding of your preferences and habits
🛠 Technology Stack
Backend
- FastAPI: Modern Python web framework
- SQLAlchemy: Database ORM
- ChromaDB: Vector database for embeddings
- SentenceTransformers: Text embeddings
- Ollama: Local LLM runtime
Frontend
- React: Modern UI framework
- TailwindCSS: Utility-first CSS framework
- Vite: Fast build tool
AI/ML
- Hugging Face Transformers: Pre-trained models
- PyTorch: ML framework
- Pillow: Image processing
- PyPDF2: PDF text extraction
📁 Project Structure
apersona/
├── backend/ # FastAPI backend
│ ├── app/
│ │ ├── api/ # API routes
│ │ ├── core/ # Core configuration
│ │ ├── db/ # Database models
│ │ ├── services/ # Business logic
│ │ └── main.py # FastAPI app
│ ├── ai_core/ # AI/ML components
│ │ ├── embeddings/ # Text embeddings
│ │ ├── llm/ # LLM integration
│ │ ├── rag/ # RAG system
│ │ └── auto_learning/ # Adaptive learning
│ └── requirements.txt
├── frontend/ # React frontend
│ ├── src/
│ │ ├── components/ # React components
│ │ ├── pages/ # Page components
│ │ ├── services/ # API services
│ │ └── utils/ # Utility functions
│ └── package.json
├── data/ # Local data storage
│ ├── uploads/ # User uploaded files
│ ├── processed/ # Processed files
│ └── vectors/ # Vector embeddings
└── docs/ # Documentation
🚀 Quick Start
Prerequisites
- Python 3.11+
- Node.js 18+
- Ollama installed locally
Backend Setup
cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload
Frontend Setup
cd frontend
npm install
npm run dev
AI Setup
# Install Ollama models
ollama pull mistral
ollama pull nomic-embed-text
🧠 Auto-Learning System
The auto-learning module continuously adapts to user behavior through:
- Interaction Patterns: Learning from user queries and responses
- Preference Tracking: Monitoring file usage and search patterns
- Context Building: Understanding user's work and personal contexts
- Response Optimization: Improving answer relevance over time
- Proactive Suggestions: Anticipating user needs based on patterns
🔒 Privacy & Security
- All data stored locally
- No external API calls
- Encrypted user authentication
- Secure file handling
- Optional data anonymization
📚 Documentation
🤝 Contributing
This is a personal project focused on privacy and local execution. Feel free to fork and adapt for your needs.
📄 License
MIT License - See LICENSE file for details