Move negative_prompt to required inputs, right after prompt, so it appears
above duration/steps/cfg/seed in the ComfyUI node layout.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
find_pruneable_heads_and_indices and prune_linear_layer were removed from
both pytorch_utils and modeling_utils in some transformers builds. Provide
minimal inline implementations as final fallback — prune_heads() is never
called at inference time so correctness is only needed for completeness.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Users can now wire the prompt output directly to SelvaSampler's prompt input,
making the data flow explicit instead of relying on the implicit features fallback.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
ComfyUI renders required inputs above optional ones. Moving negative_prompt
to optional puts prompt first (natural order) and negative_prompt at the
bottom where it belongs as a power-user input. Also guards against
negative_prompt=None when not connected.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Uses selva_core/utils/download_utils.py (already has URLs + MD5s for all
weights). Models download to models/selva/ on first load. Synchformer reuses
models/prismaudio/synchformer_state_dict.pth if already present (no duplicate
download for PrismAudio users), otherwise downloads to models/selva/.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
SelvaFeatureExtractor now stores the prompt in SELVA_FEATURES (both in the
returned dict and the .npz cache). SelvaSampler's prompt is now optional —
when left empty it falls back to the prompt stored in features. A non-empty
override can still be passed when CLIP text should differ from the sync text.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Some transformers builds removed these from pytorch_utils. Fall back to
modeling_utils which exposes them in all known versions.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- selva_feature_extractor: cache hash now includes resolved duration;
same video + different duration override no longer returns stale features
- selva_sampler: MPS-safe noise generation (torch.Generator on CPU then
move to device, same pattern as PrismAudioSampler)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Calls update_seq_lengths with actual feature dimensions (not seq_cfg) to
avoid rounding assertion mismatches. Progress bar tracks each Euler step.
Supports negative prompts for steering, normalizes output to [-1,1].
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
CLIP frames at 8fps→384px (normalize inside FeaturesUtils).
Sync frames at 25fps→224px, normalized to [-1,1] externally.
T5 text encoded via FeaturesUtils, sup tokens prepended, then text-conditioned
sync features extracted via TextSynch.encode_video_with_sync(). Results cached
as .npz keyed by hash(frames[:1MB] + prompt + fps + variant).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Pure PyTorch SelVA source for SelvaModelLoader/FeatureExtractor/Sampler nodes.
Imports rewritten from selva.* to selva_core.*. mel_converter.py: replaced
librosa.filters.mel with pure-numpy implementation to avoid librosa→numba→NumPy
version incompatibility in some ComfyUI environments.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The fps output was only returned on cache hits. Fresh extractions
returned only features, leaving fps null.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Point links to huggingface.co/FunAudioLLM/PrismAudio and use public
GitHub URL for install instructions.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Setting duration to 0 in PrismAudioSampler now reads the duration
stored in the PRISMAUDIO_FEATURES dict (set by the feature extractor).
Default changed from 10.0 to 0.0 so V2A workflows are wired up
automatically.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Remove synchformer_ckpt input — always resolved from models/prismaudio/
(errors early with clear message if missing)
- Replace python_env string input with dropdown: managed_env (isolated
auto-created venv, default) or comfyui_env (current Python, with warning)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When the VHS LoadVideo video_info output is connected, loaded_fps is
used automatically instead of the manual fps input.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Saves frames as uint8 .npy instead of H.264 MP4, eliminating the
lossy codec roundtrip. extract_features.py loads .npy directly and
skips decord when given a numpy file. Passes --source_fps for
correct temporal sampling.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Remove debug_zero_video/debug_zero_sync inputs from PrismAudioSampler,
DIT velocity diagnostics, conditioner stats logging, and feature stats
prints from both sampler.py and text_only.py.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The wrong model (videoprism_public_v1_large, vision-only) was used,
causing V2A audio distortion. Switch to the LvT variant which has a
text tower, pass CoT captions for joint encoding, and extract per-frame
features from outputs['frame_embeddings'] (L2-normalized, [T, 1024])
instead of manually averaging spatial patches.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add per-key conditioning output stats (after Cond_MLP/Sync_MLP, after
_substitute_empty_features) to both sampler and text_only nodes. Also
add raw T5 text feature stats in T2A before conditioning.
This lets us directly compare:
- T2A vs V2A conditioning outputs to find which path differs
- T2A vs npz text feature ranges
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Match the diagnostic output already in text_only.py to compare
V2A vs T2A latent distributions and diagnose conditioning issues.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Zero features through bias-free Cond_MLP produce near-zero activations,
not the learned null signal the model was trained with. Use empty_clip_feat
(the learned null video embedding) just like empty_sync_feat for sync.
Also improve text_prompt tooltip to encourage detailed CoT descriptions.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
AutoencoderPretransform.load_state_dict() doesn't return IncompatibleKeys.
Load into pretransform.model (AudioAutoencoder) to get the return value
and see actual missing/unexpected key counts.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Print key counts, missing/unexpected keys, and sample key names to
diagnose whether weights are actually loading correctly (strict=False
silently hides mismatches that would cause garbage audio output).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Allows isolating which feature set causes quality issues:
- debug_zero_video: zero video_features → text+sync only
- debug_zero_sync: zero sync_features → text+video only
Also logs mean/std/shape for all three feature tensors on every run.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Sync_MLP interpolates sync features based on video duration, but audio
latent length depends on the user-set audio duration. When video != audio
duration, the sequences diverge. Resample sync_cond to x's length before
the gated addition so any video/audio duration combo works.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Stream raw RGB bytes from tensor directly to ffmpeg stdin.
Eliminates all intermediate PNG file I/O — much faster for large frame counts.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Shows how long PIL+ffmpeg video export takes so we can see
if that's contributing to the gap before [extract] output appears.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Each step now prints elapsed seconds on completion.
Total time printed at the end to identify bottlenecks.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
prismaudio.json conditioner config requires:
- video_features: dim=1024 → switch videoprism_public_v1_base → large (ViT-L)
- sync_features: dim=768, length divisible by 8 → expand [num_seg,768] to
[num_seg*8,768] (per-frame) so Sync_MLP can reshape by groups of 8
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
T5-Gemma outputs BFloat16 which numpy does not support.
Cast all feature tensors with .float() before .numpy().
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When synchformer_ckpt input is empty, look for synchformer_state_dict.pth
in the ComfyUI prismaudio models directory automatically.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
videoprism/__init__.py is empty — API lives in videoprism.models.
Fix: from videoprism import models as vp (not import videoprism as vp).
Also add flax to managed venv packages (required by videoprism Flax model).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
RTX 6000 Pro (Blackwell SM 10.0) fully supports CUDA 13. Switch from
jax[cpu]+jaxlib to jax[cuda13] which bundles jaxlib and uses
pip-managed CUDA libraries. Delete _extract_env to force a rebuild.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
google/t5gemma-l-l-ul2-it is a gated HuggingFace model requiring auth.
Add optional hf_token input on the node; forward it (plus the legacy
HUGGING_FACE_HUB_TOKEN alias) to the subprocess env. Falls back to
HF_TOKEN from the host environment. Warn clearly when neither is set.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Empty string from clearing the node field caused subprocess to execute ''
which raises PermissionError. Now any blank or 'python' value uses the
auto-installed venv.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Creates data_utils/v2a_utils/feature_utils_288.py with FeaturesUtils:
- T5-Gemma text encoding via transformers
- VideoPrism video encoding via JAX videoprism package
- Synchformer visual encoder loading from checkpoint
Also fixes extract_features.py to add plugin root to sys.path so
data_utils is importable in the subprocess venv.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Exposes the video frame rate as an optional input (default 30).
Correct FPS ensures accurate temporal frame sampling in VideoPrism
and Synchformer feature extraction.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Ethanfel