This project provides a fast, streaming Text-to-Speech (TTS) engine using C++ bindings for the Orpheus TTS model, integrated with WebRTC via FastRTC. It targets developers and researchers seeking low-latency, high-quality speech synthesis for real-time applications, offering a significant performance improvement over Python-only implementations.

How It Works

The core of Orpheus-CPP leverages C++ for performance-critical TTS inference, wrapping the Orpheus model. It utilizes WebRTC for efficient, low-latency audio streaming, enabling real-time communication and playback. The integration with FastRTC further optimizes the WebRTC stack for speed and resource efficiency.

Quick Start & Requirements

• Install via pip: pip install orpheus-cpp
• Additional dependency: pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu (for CPU) or --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/metal (for Apple Silicon).
• Demo: Run python -m orpheus_cpp and visit http://localhost:7860.
• Official Docs: https://github.com/freddyaboulton/orpheus-cpp

Highlighted Details

• Supports synchronous and asynchronous TTS generation.
• Offers streaming capabilities with configurable pre-buffer sizes for latency tuning.
• Integrates with FastRTC for WebRTC-based streaming.

Maintenance & Community

• Project maintained by freddyaboulton.
• No explicit community links (Discord/Slack) or roadmap mentioned in the README.

Licensing & Compatibility

• MIT License.
• Permissive license suitable for commercial use and integration into closed-source projects.

Limitations & Caveats

The README notes that reducing pre_buffer_size too much may impact audio smoothness. Installation of llama-cpp-python requires specific wheel URLs, indicating potential build complexities or dependency management needs.