mirror of
https://github.com/remsky/Kokoro-FastAPI.git
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90 lines
3.4 KiB
Markdown
90 lines
3.4 KiB
Markdown
# Changelog
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Notable changes to this project will be documented in this file.
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## [v0.1.2] - 2025-01-23
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### Structural Improvements
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- Models can be manually download and placed in api/src/models, or use included script
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- TTSGPU/TPSCPU/STTSService classes replaced with a ModelManager service
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- CPU/GPU of each of ONNX/PyTorch (Note: Only Pytorch GPU, and ONNX CPU/GPU have been tested)
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- Should be able to improve new models as they become available, or new architectures, in a more modular way
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- Converted a number of internal processes to async handling to improve concurrency
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- Improving separation of concerns towards plug-in and modular structure, making PR's and new features easier
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### Web UI (test release)
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- An integrated simple web UI has been added on the FastAPI server directly
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- This can be disabled via core/config.py or ENV variables if desired.
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- Simplifies deployments, utility testing, aesthetics, etc
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- Looking to deprecate/collaborate/hand off the Gradio UI
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## [v0.1.0] - 2025-01-13
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### Changed
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- Major Docker improvements:
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- Baked model directly into Dockerfile for improved deployment reliability
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- Switched to uv for dependency management
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- Streamlined container builds and reduced image sizes
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- Dependency Management:
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- Migrated from pip/poetry to uv for faster, more reliable package management
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- Added uv.lock for deterministic builds
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- Updated dependency resolution strategy
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## [v0.0.5post1] - 2025-01-11
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### Fixed
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- Docker image tagging and versioning improvements (-gpu, -cpu, -ui)
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- Minor vram management improvements
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- Gradio bugfix causing crashes and errant warnings
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- Updated GPU and UI container configurations
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## [v0.0.5] - 2025-01-10
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### Fixed
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- Stabilized issues with images tagging and structures from v0.0.4
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- Added automatic master to develop branch synchronization
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- Improved release tagging and structures
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- Initial CI/CD setup
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## 2025-01-04
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### Added
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- ONNX Support:
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- Added single batch ONNX support for CPU inference
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- Roughly 0.4 RTF (2.4x real-time speed)
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### Modified
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- Code Refactoring:
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- Work on modularizing phonemizer and tokenizer into separate services
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- Incorporated these services into a dev endpoint
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- Testing and Benchmarking:
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- Cleaned up benchmarking scripts
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- Cleaned up test scripts
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- Added auto-WAV validation scripts
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## 2025-01-02
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- Audio Format Support:
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- Added comprehensive audio format conversion support (mp3, wav, opus, flac)
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## 2025-01-01
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### Added
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- Gradio Web Interface:
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- Added simple web UI utility for audio generation from input or txt file
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### Modified
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#### Configuration Changes
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- Updated Docker configurations:
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- Changes to `Dockerfile`:
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- Improved layer caching by separating dependency and code layers
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- Updates to `docker-compose.yml` and `docker-compose.cpu.yml`:
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- Removed commit lock from model fetching to allow automatic model updates from HF
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- Added git index lock cleanup
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#### API Changes
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- Modified `api/src/main.py`
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- Updated TTS service implementation in `api/src/services/tts.py`:
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- Added device management for better resource control:
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- Voices are now copied from model repository to api/src/voices directory for persistence
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- Refactored voice pack handling:
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- Removed static voice pack dictionary
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- On-demand voice loading from disk
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- Added model warm-up functionality:
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- Model now initializes with a dummy text generation
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- Uses default voice (af.pt) for warm-up
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- Model is ready for inference on first request
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