This project provides an exceptionally fast AI voice assistant, targeting users who need near real-time voice interaction. It leverages a combination of specialized AI models and efficient transport mechanisms to achieve response times under 500ms.

How It Works

The assistant utilizes a modular architecture for its core components: Deepgram for Speech-to-Text (STT), a Cerebras LLM for natural language understanding and response generation, and Cartesia for Text-to-Speech (TTS). Communication is handled via LiveKit transport, enabling low-latency, real-time audio streaming. This stack is optimized for speed and efficiency.

Quick Start & Requirements

• Install: pip install -r requirements.txt
• Prerequisites: Python 3.x, Deepgram API key, LiveKit Cloud project credentials.
• Setup: Requires creating a .env file from .env.example and populating it with API keys.
• Demo: https://cerebras.vercel.app

Highlighted Details

• Achieves response times under 500ms.
• Built with approximately 50 lines of code for the core logic.
• Integrates Deepgram STT, Cerebras LLM, and Cartesia TTS.
• Uses LiveKit for real-time transport.

Maintenance & Community

No specific community channels or maintenance details are provided in the README.

Licensing & Compatibility

The README does not specify a license.

Limitations & Caveats

The project relies on third-party API keys (Deepgram, LiveKit) which may incur costs. The absence of a specified license raises questions about commercial use and redistribution.