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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.2.1] - 2026-05-22

Added

  • scripts/install_server.sh — one-shot idempotent server-side install (ffmpeg check + torchaudio install + smoke test).
  • README.zh-CN.md — Chinese quick-start guide (shortest working path).
  • README.md rewritten with explicit shell $ prompts, ⚠️ pre-install warning block, step-by-step Install (the proven order) with per-step verification, and a Tested-with compatibility table — matching the ComfyUI-MiMoASR documentation style.
  • INSTALL_NOTES.md reorganized as a 9-step debug log with the three MiMo install pitfalls called out (transformers downgrade, flash-attn build, upstream repo clone).

Changed

  • README.md now uses 9 distinct verification steps. Each install step ends with a Verify: block.
  • Troubleshooting tables now distinguish errors that surface at ComfyUI startup vs at workflow runtime (lazy-imports).

[0.2.0] - 2026-05-21

Changed

  • BREAKING: dropped the bundled FasterWhisperTranscribe node. ASR is now handled externally by ComfyUI-MiMoASR (MiMoASRLoader + MiMoASRTranscribe).
  • BREAKING: JSON schema bumped to 2.0. segments[], per-segment confidence, avg_logprob, no_speech_prob, compression_ratio, and word-level timestamps are removed because MiMo's asr_sft does not expose them. Top-level text field now carries the full transcript.
  • Dropped faster-whisper from requirements.txt. Added torchaudio.

Added

  • VTT_AudioFromPath — bridge node: loads an arbitrary WAV/audio file (from absolute path) into ComfyUI's AUDIO dict so it can be fed into MiMoASRTranscribe. Optional target_sample_rate and force_mono.
  • VTT_BuildTranscriptJSON — pack ASR text + source metadata into the v2.0 JSON schema.
  • Example workflow now chains VTT_* nodes with MiMoASRLoader + MiMoASRTranscribe.

Removed

  • nodes/whisper_transcribe.py and all references to faster-whisper.

[0.1.0] - 2026-05-21

Added

  • Four nodes: VTT_LoadVideo, VTT_ExtractAudio, VTT_FasterWhisperTranscribe, VTT_SaveTranscript.
  • faster-whisper backend with per-segment confidence and word-level timestamps.
  • Multi-GPU device selection; _MODEL_CACHE for warm model instances.
  • ffmpeg-based audio extraction with on-disk caching.
  • CLI client (cli/video_to_text_cli.py) using PreviewAny to pull outputs over WebSocket.