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ComfyUI-IndexTTS2/README.md
snicolast 7e346dc8d1 readme
2025-09-25 09:51:00 +12:00

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ComfyUI-IndexTTS2

Lightweight ComfyUI wrapper for IndexTTS 2 (voice cloning + emotion control). The nodes call the original IndexTTS2 inference and keep behavior faithful to the repo.

Original repo: https://github.com/index-tts/index-tts

Updates

  • 2025-09-22: Added IndexTTS2 Advanced node exposing sampling, speed, seed, and other generation controls.

Install

  • Clone this repository to: ComfyUI/custom_nodes/
  • In your ComfyUI Python environment:
    pip install wetext
    pip install -r requirements.txt
    

Models (checkpoints)

  • Create a folder named 'checkpoints' in the root directory
  • Download ALL files and subfolders from Hugging Face and put them under the new 'checkpoints' folder, preserving the original structure: https://huggingface.co/IndexTeam/IndexTTS-2/tree/main ` Optional, if auto-cached online if missing:
OPTIONAL: detailed checkpoint download list for total offline use
  • Additional required files for local loading (download these separately):

  • Complete checkpoints folder structure:

    ComfyUI/custom_nodes/ComfyUI-IndexTTS2/checkpoints/
    |-- config.yaml
    |-- gpt.pth
    |-- s2mel.pth
    |-- bpe.model
    |-- feat1.pt
    |-- feat2.pt
    |-- wav2vec2bert_stats.pt
    |-- campplus_cn_common.bin
    |-- bigvgan/
    |   |-- config.json
    |   |-- bigvgan_generator.pt
    |-- semantic_codec/
    |   |-- model.safetensors
    |-- qwen0.6bemo4-merge/          (required only for Text -> Emotion node)
    |   |-- [all Qwen model files]
    |-- w2v-bert-2.0/
        |-- [all bert files]
    

Nodes

  • IndexTTS2 Simple

    • Inputs: audio (speaker), text, emotion_control_weight (0.0-1.0), emotion_audio (optional), emotion_vector (optional)

    • Outputs: AUDIO (for Preview/Save), STRING (emotion source message)

    • Notes: device auto-detected, FP16 on CUDA, 200 ms pause between segments (fixed), emotion precedence = vector > second audio > original audio

  • IndexTTS2 Advanced

    • Inputs: same as Simple plus optional overrides for sampling (temperature, top-p, top-k, beams), max tokens, speech speed, interval silence, typical sampling, and seed.
    • Notes: defaults mirror the Simple node; change values only when you need reproducible or exploratory behavior.
  • IndexTTS2 Emotion Vector

    • 8 sliders (0.0-1.4) for: happy, angry, sad, afraid, disgusted, melancholic, surprised, calm
    • Constraint: sum of sliders must be <= 1.5 (no auto-scaling)
    • Output: EMOTION_VECTOR
  • IndexTTS2 Emotion From Text (optional)

    • Input: short descriptive text
    • Requires: modelscope and local QwenEmotion at checkpoints/qwen0.6bemo4-merge/
    • Outputs: EMOTION_VECTOR, STRING summary

Examples

  • Basic: Load Audio -> IndexTTS2 Simple -> Preview/Save Audio
  • Second audio emotion: Load Audio (speaker) + Load Audio (emotion) -> IndexTTS2 Simple -> Save
  • Vector emotion: IndexTTS2 Emotion Vector -> IndexTTS2 Simple -> Save
  • Text emotion: IndexTTS2 Emotion From Text -> IndexTTS2 Simple -> Save

ComfyUI-IndexTTS2 nodes

Troubleshooting

  • Tested only in Windows. DeepSpeed disabled.
  • Emotion vector sum exceeds maximum 1.5: lower one or more sliders or adjust the text-derived vector.
  • BigVGAN kernel message: custom CUDA kernel is disabled by default; falls back to PyTorch ops.
  • Missing 'wetext' module: Run pip install wetext to fix this Windows-specific dependency.
  • 404 Repository Not Found errors: Ensure all additional model files are downloaded to your checkpoints folder as described above.
  • Model loading issues: Verify your checkpoints folder contains all required files with the correct directory structure.

Expected Output: When working correctly, you should see messages like:

  • Loading config.json from local directory
  • Loading weights from local directory
  • All model paths pointing to your local checkpoints folder

Performance: The system processes audio through 4 stages (Text → GPT → S2Mel → BigVGAN). Multiple progress bars and tensor size outputs are normal during inference.