xszyou/Fay

What it solves

Fay provides a comprehensive framework for deploying digital humans (virtual avatars) across various terminals, such as mobile apps, websites, large screens, and single-chip microcomputers. It bridges the gap between high-level AI models and end-user interfaces by integrating speech recognition, language processing, and avatar animation into a single pipeline.

How it works

The framework acts as an orchestration layer that connects several modular components:

• Input/Output: Integrates ASR (Automatic Speech Recognition) for listening and TTS (Text-to-Speech) for speaking.
• Intelligence: Connects to LLMs (via OpenAI-compatible interfaces), including support for "thinking" models like DeepSeek, to handle dialogue and decision-making.
• Avatar Control: Interfaces with digital human models to drive visual animations and expressions.
• Agent Capabilities: Uses an agent-based system for autonomous tool calling and MCP (Model Context Protocol) tool management.
• Memory & Knowledge: Supports custom knowledge bases, Q&A pairs, and bionic memory to improve self-awareness and consistency.

Who it’s for

Developers and businesses looking to implement virtual teachers, virtual anchors, news broadcasters, or interactive AI assistants into their own hardware or software products.

Highlights

• Full-Stack Integration: Supports the entire pipeline from voice input to digital human animation.
• Flexible Deployment: Works in both server and standalone modes and supports fully offline usage.
• Multi-Terminal Support: Designed for easy integration into apps, websites, and embedded systems.
• Advanced Agent Features: Includes support for autonomous tool calling, bionic memory, and wake-word/interrupt handling.
• Concurrent Handling: Supports multiple users and multiple concurrent streams.