- Consolidate character voice info into block generation messages
- Fix tokenizer path structure to match actual storage location (vibevoice/ instead of VibeVoice/tokenizer/)
- Use consistent path for tokenizer downloads so they're found on subsequent runs
- Comment out non-error device_map debug messages
- Remove duplicate SINGLE SEGMENT text printing
- Fix logged_characters to only log once per character (not per priority check)
VibeVoice:
- Added .to() method for device management
- Added device checking before generation that properly detects parameter device
- Fixed target_device to always use cuda if available (not self.device which gets updated)
RVC:
- Created RVCModelWrapper class to wrap model dicts with .to() method
- Added .to() method to RVCEngine for device management
- Added device checking to convert_voice() method
- Updated rvc_factory to properly load and wrap RVC models
- Added model caching to minimal_reference_wrapper to prevent reloading
- Added clear_model_cache() method for VRAM management
- Disabled CUDNN benchmark in vc_infer_pipeline.py to prevent VRAM spikes on Python 3.12+
All engines now support Clear VRAM button across multiple cycles.
Fix ChatterBox Official 23-Lang device placement bug
Technical implementation:
- Add .to() method to ChatterBoxOfficial23LangTTS class for device migration
- Add .to() method to ChatterboxVC class for voice conversion device handling
- Improve wrapper's _move_all_components_to_device() with better recursion depth
- Fix unified_model_interface device resolution for 'auto' mode
- Add ComfyUI model management re-registration after wrapper.model_load()
- Fix model_finalizer setup when re-registering with ComfyUI
- Add device check in processor to call wrapper.model_load() instead of direct .to()
Fixes device mismatch errors:
- Fix 'Expected all tensors to be on the same device' error on second run
- Fix 'Inference tensors do not track version counter' after CPU detachment
- Fix 'Clear VRAM' button not working after model reload
Fixed critical issues preventing v2 model auto-download:
1. Removed silent v1 fallback in from_local - now raises FileNotFoundError to trigger download
2. Updated unified_model_interface factory to pass model_version parameter
3. Factory now properly tries from_local first, then from_pretrained for auto-download
4. Added model_version parameter to generate_speech and load_tts_model signatures
5. Pass model_version from engine config through unified TTS node to processor
6. Updated README to clarify v1/v2 files coexist in same directory
Now when v2 is selected but files missing:
- from_local raises error instead of falling back to v1
- from_pretrained downloads missing v2 files automatically
- Model loads correctly with v2 tokenization enabled
- Add detection for external IndexTTS installations that conflict with bundled version
- Display clear error message with uninstall instructions when conflicts are found
- Remove unnecessary adapter initialization log message
- Resolves import errors reported in issues #115, #116, and #101
- Corrected invalid torchaudio+cu128 syntax to proper pip install torchaudio --index-url format
- Updated both torchaudio and torchvision warning commands to use cu129 index
- Fixes installation errors where users got 'Expected end or semicolon' pip errors
Fix IndexTTS-2 auto-download system with complete model verification
Technical implementation:
- Move auto-download logic from unified interface to IndexTTS engine initialization
- Add comprehensive model verification using IndexTTSDownloader._verify_model()
- Handle mixed missing files scenarios (partial downloads, corrupted files)
- Improve error messages showing specific missing files and download status
- Fix auto-download trigger timing to occur before model loading attempt
Fix IndexTTS-2 bundled import conflicts with system packages
Technical fix:
- Add sys.modules override to force bundled indextts during import
- Prevent conflicts with system-installed indextts packages
- Ensure bundled IndexTTS-2 code resolves internal imports correctly
- Restore original module state after import to avoid side effects
- Detects mixed CUDA/CPU PyTorch installations on first model load
- Warns about GPU PyTorch + CPU TorchAudio performance issues
- Shows exact fix commands with proper CUDA index URLs
- Prevents performance degradation debugging sessions
- Only shows warning once per session
- Initial IndexTTS-2 TTS engine implementation
- Basic unified interface integration
- Auto-download system for IndexTTS-2 models
- Character voice switching support via QwenEmotion
- Token-based chunking system
- ComfyUI model management integration
- Fixed debug output and basic inference working
- Multi-language text preprocessing foundation
- Basic error handling framework
Note: Initial implementation - requires further testing and refinement
MAJOR: IndexTTS-2 TTS engine integration
- Core IndexTTS engine with unified model interface integration
- Auto-downloader for HuggingFace models + GitHub source code
- Engine adapter with emotion support [Alice:angry_bob] syntax
- Cache integration for IndexTTS-2 parameters
- Factory registration for proper model management
MAJOR: Character parser modularization (930 → 300 lines each)
- Split into base_parser.py, language_resolver.py, segment_processor.py, validation.py
- Added emotion support with backward compatibility
- New split_by_character_with_emotions() method for advanced engines
- Flexible tag parsing: [de:Alice:angry_bob] support
- Language disambiguation to avoid Alice vs language code conflicts
- Full backward compatibility maintained
FEATURES:
- IndexTTS-2 emotion disentanglement (speaker vs emotion separation)
- Duration control and precise voice cloning
- Multi-modal emotion control (audio refs, text, vectors)
- Character switching with emotion references
- All official IndexTTS-2 parameters exposed
DOCS: Implementation plan and architectural TODO items added
Fix VibeVoice model reloading and transformers compatibility
Technical changes:
- Fix unified model interface cache key missing additional_params
- Add transformers>=4.51.3 requirement for VibeVoice compatibility
- Remove excessive debug prints from VibeVoice engine
- Fix RVC numba JIT disable logic for correct Python version detection
- Fix attention_mode and quantize_llm_4bit not triggering model reloads
Add ChatterBox Official 23-Lang to ComfyUI VRAM management
Technical improvements:
- Register ChatterBox 23-Lang in unified model interface
- Update processors to use unified interface for model loading
- Fix Python 3.13 compatibility by replacing librosa.effects.trim with safe_trim fallback
- Add proper factory method using ChatterboxOfficial23LangTTS.from_local()
Fix VibeVoice model reloading and add VRAM management
Technical improvements:
- Add class-level model caching to prevent reloading on each run
- Register VibeVoice in unified model interface
- Update adapter to use unified interface for ComfyUI integration
- Fix OOM errors on subsequent runs
- Add VC component detection system to check s3gen availability for all languages
- Implement universal ChatterBox model loading with component mixing fallback
- Fix VC download system to handle subdirectories (German havok2 model)
- Add graceful handling of optional files (conds.pt) vs required files (s3gen)
- Propagate 401 authentication errors properly through download system
- Add intelligent fallback: German variants → German base → English
- Return silent audio for unsupported VC languages instead of crashing
- Remove misleading claims about unverified VC language support
- Fix file format detection (.pt vs .safetensors) in VC downloads
Resolves VC crashes with Japanese/incomplete models and improves German model support
✅ Major Achievement: Higgs Audio can now be safely unloaded from VRAM without crashes!
Key Implementation:
- Created StatelessHiggsAudioWrapper that isolates tensor state to prevent CUDA Graph corruption
- Unified model interface integration with CPU-first loading to prevent VRAM overflow
- Enhanced ComfyUI model wrapper to handle stateless TTS models generically
- Fixed device consistency for all model components (main_model, audio_tokenizer, semantic_model, tokenizer_encoder, tokenizer_quantizer)
Results:
- Successfully freed 11007MB VRAM without crashes
- Model unloading/reloading cycle works correctly
- CUDA Graph corruption issue resolved through tensor isolation
Note: Device mismatch issue during voice cloning still needs resolution, but core memory management functionality is working.
- Remove repeated 'TTS Model loaded_size query' messages
- Only show CUDA graph checking for Higgs Audio models (not ChatterBox)
- Comment out cache key generation debug (not needed for end users)
- Reduces console spam while preserving relevant debugging for Higgs models
Remove restrictive logic that blocked language switching when no explicit [lang:character] tags present. Character alias system (Alice→German, Bob→French) now correctly loads language-specific models:
- F5-DE for German segments
- F5-FR for French segments
- F5TTS_v1_Base for English segments
Language switching works with both explicit tags and character alias mappings.
- Add global cache invalidation system to prevent reuse of corrupted model state
- Implement deferred CUDA graph initialization in Higgs Audio engine (prevents corruption during model loading)
- Add shadow storage system for Higgs Audio models to avoid PyTorch memory conflicts
- Implement timestamped engine caching across all unified nodes (TTS Text, TTS SRT, Voice Changer)
- Add comprehensive ComfyUI model management integration with proper device handling
- Fix model unloading/reloading cycle to prevent "Assertion input[0] != 0 failed" CUDA crashes
- Add model resurrection system that reuses existing models instead of creating new instances
- Implement intelligent cache validation with global invalidation flags
- Add extensive debugging and state tracking for model lifecycle management
- Fix device compatibility between string and torch.device objects in ComfyUI integration
This resolves the critical memory corruption issue that occurred when using ComfyUI's
"Unload models" or "Clear VRAM" buttons with Higgs Audio models containing CUDA graphs.
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