Fay is an agent framework that connects digital humans or large language models to business systems.
The framework addresses the challenge of deploying digital human applications across diverse platforms and model architectures. It works by sitting between digital human models (supporting 2.5D, 3D, mobile, PC, and web formats) and language models (OpenAI-compatible APIs and Deepseek), while allowing flexible swapping of supporting components like text-to-speech and automatic speech recognition. The tool provides multiple interaction interfaces including text, voice, digital human control, management, and automated broadcast modes, with support for concurrent multi-user sessions and both server and single-machine deployment modes.
Developers should choose this framework if they need to build digital human applications that must work across multiple platforms and integrate with various AI model providers. It suits projects ranging from virtual teachers and news anchors to custom chatbot applications with knowledge bases and personality customization. The framework supports offline-only operation, voice command configuration through CSV files, agent-based tool calling, and MCP tool management, making it adaptable to different business requirements.
Development activity shows consistent feature expansion with recent additions including support for thinking-based language models, biometric memory systems, and configuration management centers. The project maintains comprehensive documentation and changelog tracking, indicating ongoing refinement of the codebase. Multiple interface types and deployment modes continue to be actively developed and integrated into a unified codebase following a consolidation of previous separate versions.
