New node with a JS widget (web/audio_wave.js): upload an audio clip, play it, and click
the waveform to place segment boundaries (click add / drag move / dblclick note /
shift|right-click delete). Boundaries+notes serialize to a hidden segments_json that
drives Python segmentation (falls back to auto-split / notes syntax). Python node
(nodes/audio_wave_segments.py) loads the file (torchaudio/soundfile/librosa), builds
segments from the boundaries, and outputs waveform_image + audio_summary + AUDIO — same
contract as Audio Prompt Guide, so it feeds chat mode the same way. _attach_notes now
merges (keeps clicked notes). WEB_DIRECTORY re-enabled. JS is a first cut — needs testing
in ComfyUI (console logs on error); the Python node works standalone via segments_json/notes.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
New node for audio-guided video prompts (LTX): takes a ComfyUI AUDIO clip + free-text
motion notes and outputs (1) a rendered energy-envelope IMAGE with beat/segment markers
so the vision model can see the audio shape, and (2) an audio_summary STRING with
duration, tempo/beats (librosa optional), per-segment energy + 8n+1-snapped frame counts
+ stage hints + the notes. Wire waveform_image -> Judge.reference_image and audio_summary
-> Judge.user_prompt (chat mode, json_output) for beat-aligned LTX JSON. librosa optional
(energy envelope + segments work without it). Registered in __init__; README workflow added.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
No GGUF needed: huihui ships Qwen3.5-9B, Qwen3.6-27B, Qwen3.6-35B-A3B as multimodal
SAFETENSORS (abliterated), loadable via transformers AutoModelForMultimodalLM. Added
them to the model dropdown. _resolve_vl_classes now tries AutoModelForMultimodalLM
(3.5/3.6) and AutoModelForImageTextToText (Qwen3-VL) in name-based order, with
load fallback across candidates. model_select is now the model NAME only; precision
is the separate quant dropdown applied to it (repo_by_precision routes e.g. the local
fp8 dir). Aliases 3.5-9b/3.6-27b/3.6-35b. VRAM-by-quant table in README. Needs a
recent transformers for 3.5/3.6.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
EthanfelandClaude Opus 4.8