Chanakya - Advanced Voice Assistant

Chanakya is an advanced, open-source, and self-hostable voice assistant designed for privacy, power, and flexibility. It leverages local AI/ML models to ensure your data stays with you.

✨ Key Features

• 🗣️ Voice-Powered Interaction: A voice-first user experience.
• 🔒 Privacy by Design: Utilizes local LLMs (via Ollama), STT, and TTS to keep your data on your own hardware.
• 🛠️ Extensible Tool System: Integrates with a wide range of external tools using the Model Context Protocol (MCP).
• 🧠 Long-Term Memory: Remembers information from past conversations and allows you to manage its knowledge base.
• 🤖 Sophisticated ReAct Agent: Capable of handling complex, multi-step tasks by reasoning and acting.
• 🚀 Easy to Deploy: Comes with Docker support for quick and consistent setup.
• 🎨 Customizable UI: A clean web interface with dark mode support.

🚀 Quick Start

This guide will get you up and running in a few minutes. For more detailed instructions, please refer to our full documentation.

1. Clone the repository:

   git clone https://github.com/Rishabh-Bajpai/Chanakya-Local-Friend.git
   cd Chanakya-Local-Friend

2. Set up dependencies:

   • Ensure Docker and Ollama are installed and running.
   • Pull the required Ollama models (e.g., ollama pull hf.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF:UD-Q4_K_XL).
   • Run the dependent services for STT and TTS (see the Getting Started Guide for details).

3. Configure the application:

   cp .env.example .env
   cp mcp_config_file.json.example mcp_config_file.json

   • Edit .env and mcp_config_file.json with your settings. See the Configuration Guide for details.

4. Build and run with Docker: or (for Local Python Environment)

   sudo docker build -t chanakya-assistant .
   sudo docker run --restart=always -d --network="host" --env-file .env --name chanakya chanakya-assistant

5. Access Chanakya:

   • Open your browser and navigate to http://localhost:5001.
   • For microphone access, HTTPS is required. See the Deployment Guide for instructions on setting up SSL.

📚 Documentation

For detailed information about installation, configuration, features, and troubleshooting, please see our full documentation in the docs directory.

• Getting Started
• Configuration
• Deployment
• Usage
• Features
• Troubleshooting

🤝 Contributing

Contributions, issues, and feature requests are welcome! Check out the Contributing Guide.

⭐ Don’t forget to give the project a star if you like it!

Future Plans

We have many exciting features and improvements planned for Chanakya. Here's a look at our roadmap:

1. Fully Local Keyword Detection: Replace the current web-based API for keyword detection with a local Text-to-Speech (TTS) solution to enhance privacy and enable fully offline operation.
2. Improved Asynchronous Handling: Refactor and fix underlying asynchronous issues to improve stability and reduce the occurrence of 500 errors.
3. Switchable Personalities: Introduce different personalities for the assistant, allowing users to choose the interaction style that suits them best.
4. Document Digestion (RAG): Implement Retrieval-Augmented Generation (RAG) to allow Chanakya to read and understand documents, answering questions based on their content.
5. Auto correction on tool call failure: The assistant will analyze the error and fix it by itself on tool call failure.
6. Enhanced Usability: Focus on making the setup and configuration process easier for non-developers, potentially through a guided setup wizard in the UI.

📄 License

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

📈 Star History