0.4.2
modelcontextprotocol/registry0.4.2May 19, 2025by edwko
AI Summary
Introduces high-throughput batched decoding interfaces and improved audio handling to eliminate clipping artifacts.
Key Highlights
- Fade-in/out audio decoding to prevent clipping artifacts
- New batched inference backends (EXL2 Async, VLLM, llama.cpp)
- Single-stream decoding support via llama.cpp
- Support for OuteTTS-1.0-0.6B model
New Features
- Fade-in/out audio decoding
- EXL2 Async backend
- VLLM backend
- llama.cpp Async Server Endpoint
- Single-stream decode endpoint
- OuteTTS 1.0 0.6B model support
- Batched interface parameters
- Enhanced pre-prompt normalization
Full Release Notes
# OuteTTS v0.4.2 * **Fade-in / Fade-out Audio Decoding** Introduced quick fade-in and fade-out on decoded audio chunks to eliminate clipping artifacts at segment boundaries. * **Batched Decoding Interfaces** Added support for high-throughput, batched inference via three new backends: * **EXL2 Async**: Asynchronous batch processing using the EXL2. * **VLLM**: Asynchronous batch decoding with VLLM. (Experiment support) * **llama.cpp Async Server Endpoint**: Connects to a continuously-batched llama.cpp server for async inference. * **Single-Stream Decoding** * **llama.cpp Server Endpoint**: single-stream decode endpoint for llama.cpp server. * **OuteTTS 1.0 0.6B Model Support** Compatibility with the new [OuteTTS-1.0-0.6B](https://huggingface.co/OuteAI/OuteTTS-1.0-0.6B), including config defaults. * **Batched Interface Parameters** New configuration options to control batched interface. * Enhanced pre-prompt normalization pipeline. * Documentation Updates, expanded the batched interface usage.