- Implemented GET /v1/models endpoint
- Returns list of all TTS models with metadata
- Includes voice lists for each model
- Provides engine-specific information (sample rate, description)
- Enables frontend voice discovery and model type mapping
Response format:
{
"object": "list",
"data": [
{
"id": "tts-1",
"engine": "piper",
"description": "Fast neural TTS with 100+ voices",
"sample_rate": 22050,
"voices": [...],
"voice_count": 40
},
...
]
}
🦝 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fixed Silero model caching to track language+speaker combination
- Updated Russian voices to use ru_v3 model (was v4_ru)
- Updated Spanish voices to use v3_es model (was v1_es)
- All model loading now properly switches between languages
Status:
✅ English (v3_en) - 119 voices working
✅ German (v3_de) - 6 voices working
✅ French (v3_fr) - 7 voices working
⚠️ Russian (ru_v3) - Model loading issue (investigating speaker format)
⚠️ Spanish (v3_es) - Model loading issue (investigating speaker format)
🦝 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
INTEGRATED: Silero TTS (tts-1-silero)
- Added silero_wrapper class to speech.py for PyTorch Hub integration
- CPU-friendly, no GPU required (48kHz sample rate)
- Supports 5 languages: English (117 speakers), Russian, German, Spanish, French
- Loads on-demand via torch.hub from snakers4/silero-models
- Added 6 OpenAI-compatible voice mappings (alloy, echo, fable, etc.)
PREPARED: Chatterbox & Kokoro TTS
- Added dependencies to requirements.txt:
* git+https://github.com/resemble-ai/chatterbox.git
* transformers>=4.35.0 (for Kokoro)
* huggingface-hub[cli] (for model downloads)
- Created Makefile targets for downloading models
- Created test targets for all three new engines
Makefile Enhancements:
- make voices-silero: Download Silero models (en, ru, de, es, fr)
- make test-silero: Test Silero TTS endpoint
- make voices-chatterbox: Download Chatterbox models via HF CLI
- make test-chatterbox: Test Chatterbox with emotion control
- make voices-kokoro: Download Kokoro models via HF CLI
- make test-kokoro: Test Kokoro fast synthesis
speech.py Changes:
- Added silero_wrapper class with tts() method
- Added tts-1-silero model handler in generate_speech()
- Registered tts-1-silero model in app
- Added PCM media type for Silero (48000 Hz)
- Global state: silero_model, silero_speakers dict
Configuration:
- Updated voice_to_speaker.default.yaml with tts-1-silero section
- Mapped all 6 OpenAI voices to Silero speakers (en_0 through en_5)
Documentation:
- Updated docs/MODELS.md: Silero marked as ✅ INTEGRATED
- Updated roadmap: Phase 1 task 3 completed
- Updated status footer: 3 models rescued
- Added integration examples and Makefile commands
Next Steps:
- Test Silero integration in Docker
- Implement Chatterbox emotion control engine
- Implement Kokoro fast decoder engine
Makefile improvements:
- Add voices-xtts target to download speaker samples
- Add test-xtts target for testing HD model
- Split voices into voices-piper and voices-xtts
- Update help text with all new targets
speech.py:
- Fix threading import scope issue for XTTS
- Remove redundant 'import threading' inside Piper block
docs/CLAUDE.md:
- Complete guide for Claude Code contributors
- Makefile-first development philosophy
- Never create dirs manually, always use Makefile
- Documentation requirements and testing philosophy
- Common mistakes to avoid
- Raccoon mission values and principles
This ensures consistent, repeatable deployments and makes it easy
to add new TTS engines following the same pattern.
🦝 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Renamed all references from openedai-speech to uncloseai-speech across
the entire codebase, including:
- Project name in README and documentation
- Docker image names in compose files
- Makefile deployment paths and container names
- Configuration examples in vars.sh.example
This establishes our raccoon mission fork as UncloseAI Speech, a unified
TTS system supporting multiple engines (Piper, XTTS, etc.) with OpenAI
API compatibility.
🦝 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
This commit resolves the "download entire voices" issue by properly handling
absolute paths in Piper model configuration and improves the deployment system.
Key changes:
- speech.py: Detect absolute paths and omit --data-dir/--download-dir flags
when using absolute model paths, allowing Piper to load models directly
- speech.py: Add debug logging and stderr capture for Piper subprocess
- voice_to_speaker.default.yaml: Use absolute paths for all Piper models
- Makefile: Load deployment config from vars.sh for better security
- Makefile: Change restart to rebuild container ensuring code updates apply
- Add vars.sh.example template for deployment configuration
- .gitignore: Add vars.sh to prevent committing deployment secrets
Tested successfully with en_US-libritts_r-medium model using absolute path:
/app/voices/en/en_US/libritts_r/medium/en_US-libritts_r-medium.onnx
🦝 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
