AVA - Afsah's Virtual Assistant (Local Agentic AI) 🚀

The future of personalized, powerful, and private AI assistance, running locally on your hardware.

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Overview

AVA (Afsah's Virtual Assistant) is an ambitious project to build a compact, yet highly capable, agentic AI model designed to run locally on modest consumer hardware, specifically targeting an NVIDIA RTX A2000 GPU with 4GB VRAM.

The goal is to create a true "daily driver" AI assistant that can perform complex tasks, understand context, utilize tools, and provide a seamless user experience through both command-line and graphical interfaces, including remote access capabilities.

This repository contains all the code, documentation, and resources for Project AVA.

Key Features & Goals

• Local First: Runs entirely on your machine, ensuring privacy and data control.
• Optimized Performance: Aggressively optimized for 4GB VRAM using 4-bit quantization, QLoRA, and knowledge distillation.
• Advanced Agentic Capabilities: Function calling, tool use, structured output, and reasoning mechanisms.
• Direct Data Access: Planned integration with Model Context Protocol (MCP) for real-time data interaction.
• User-Friendly Interfaces: Both CLI and GUI (Open WebUI based) options.
• Remote Accessibility: Securely access AVA's local inference server from other devices.

Getting Started

1. Detailed Documentation: For a full understanding of the project's architecture, roadmap, setup, and usage, please refer to the docs/README.md.
2. Installation: Check docs/INSTALLATION.md for setup instructions.
3. Roadmap: See docs/ROADMAP.md to understand the development phases.

Navigating the Repository

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├── .github/              # GitHub-specific files (workflows, issue templates)
├── config/               # Configuration files for AVA, tools, APIs
├── data/                 # Data files used by AVA (synthetic datasets, etc.)
├── docs/                 # Detailed project documentation <--- START HERE
├── models/               # LLM models (quantized, adapters)
├── notebooks/            # Jupyter notebooks for experimentation
├── scripts/              # Utility scripts
├── src/                  # Source code for AVA
├── tests/                # Automated tests
├── .env.example          # Example environment variables file
├── .gitignore            # Specifies intentionally untracked files
├── CONTRIBUTING.md       # Guidelines for contributing
├── LICENSE               # Project license (e.g., MIT)
├── README.md             # This file - main project README
└── requirements.txt      # Python package dependencies

Contributing

Contributions are highly welcome! Please see CONTRIBUTING.md and the docs/DEVELOPMENT.md guidelines.

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Join us in building AVA, your next-generation local AI daily driver!