SeedVR2 nodes use ComfyUI's V3 API which calls get_executing_context()
internally to get the current node_id. When calling execute() directly
from our code (outside ComfyUI's execution pipeline), the context is
None, causing AttributeError.
Fix: wrap all SeedVR2 execute() calls inside a CurrentNodeContext
context manager with a dummy prompt_id and node_id. This provides the
required execution context that V3 API nodes expect.
Also fixed indentation — all three execute() calls (DiT, VAE, Upscaler)
are now properly inside the with block.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The previous approach tried 'from custom_nodes import ComfyUI_SeedVR2...'
which fails because ComfyUI doesn't expose custom nodes as importable
packages. Now scans nodes.NODE_CLASS_MAPPINGS directly for the three
SeedVR2 node classes (LoadDiTModel, LoadVAEModel, VideoUpscaler).
This works for both V2 and V3 API nodes.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Adds SeedVR2 as a new upscale mode alongside HiRes Fix, Model Upscale,
and Model+HiRes. Requires ComfyUI-SeedVR2_VideoUpscaler to be installed
as a dependency — the plugin calls its nodes programmatically.
Data Model:
- New seedvr2 options object on each upscale step with all SeedVR2
parameters: dit_model, resolution, max_resolution, seed,
color_correction, batch_size, noise scales, blocks_to_swap,
attention_mode, offload_device, cache_model, VAE tiling options
- _defaultSeedVR2Options() / createDefaultSeedVR2Options() helpers
- Migration: ensureStepFields adds seedvr2 defaults to existing configs
Builder UI (conf-builder-config-management.js):
- "SeedVR2 Upscale" added to mode dropdown
- When selected, shows full SeedVR2 settings: DiT model selection
(10 variants: 3B/7B x fp16/fp8/GGUF/sharp), resolution, seed,
color correction, noise scales, batch size, VRAM optimization
(blocks_to_swap, attention_mode, offload), VAE tiling with
conditional encode/decode tile size and overlap fields
Dashboard (logic_upscale_modal.js):
- Same SeedVR2 mode and fields in renderPipelineEditor via _renderStep
- All fields use existing _makeSelect/_makeNumber/_makeCheckbox helpers
Python Execution (image_generation.py):
- New seedvr2_upscale(pil_image, seedvr2_config) function
- Imports SeedVR2 nodes from NODE_CLASS_MAPPINGS at runtime
- Calls SeedVR2LoadDiTModel → SeedVR2LoadVAEModel → SeedVR2VideoUpscaler
- Converts PIL→tensor→SeedVR2→tensor→PIL
- Clear error if SeedVR2 not installed
Pipeline Integration (generation_orchestrator.py):
- Inline upscale path: mode=="seedvr2" branch decodes current latent
to PIL, calls seedvr2_upscale, saves result, updates manifest
- Supports chained steps: non-final SeedVR2 steps re-encode to latent
for the next step in the pipeline
Preset compatible: seedvr2 config serializes naturally as JSON, saved
and loaded with upscale presets without any special handling.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add "flux2" to clip_types and dual_clip_types lists so CLIPType.FLUX2
is correctly passed to ComfyUI's text encoder loader
- Add "flux2" model_sampling_override option in Builder UI dropdown
- Implement ModelSamplingFlux2 handler using fixed shift (default 2.02,
matching ComfyUI's Flux2 supported_models.py)
- Handle "flux2" in config_builder_node.py config generation with
default shift value
Users with Flux2 models (Klein, etc.) should set:
- CLIP Type: flux2
- Model Sampling Override: Flux2
- For best results: enable Advanced Sampling with Flux2 Scheduler
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
ETA calculation now uses the last 10 job durations instead of the
overall average. This adapts faster when upscale patterns change
(e.g., some configs have upscale, some don't) and prevents early
slow jobs from permanently skewing the estimate.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replace flat upscale configs with pipeline/steps/repeat architecture:
- Pipelines run independently from base image
- Steps chain sequentially within a pipeline
- Steps support repeat count for iterative refinement
Add "Save Pre-Upscaled Output" option to also keep the base image.
Add "Adjust Prompt During HiRes Fix" with prepend/append/replace
behaviors. HiRes-adjusted prompts are batch pre-encoded for efficiency.
Results written to manifest metadata and exposed as label overlays.
Fix fmtVal scoping error in buildLabelOverlay (was referenced outside
the upscale block where it was defined).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Seed: expanded per-gen behavior + new full run seed behavior (random/increment/decrement before/after entire run)
- Canvas: fix flicker during simultaneous pan+zoom via requestAnimationFrame batching
- Upscaling: 3 session-level modes (HiRes fix, model upscale, model+HiRes) with tiled VAE support
- Cooldown: configurable GPU breaks between generations with optional VRAM clearing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Worker now clones latent and frees UNet tensors + CUDA cache before
VAE decode, giving Dynamic VRAM clean memory for VAE loading.
decode_latent_with_vae now detects NaN in input/output, logs diagnostic
info, retries with float32, and handles bfloat16->numpy conversion.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
