- Add rife_chunked.py with RifeStreamVFI ComfyUI node that downloads a
video from a presigned URL and runs RIFE N× interpolation in temporal
chunks (default chunk_size=64, 1-frame overlap at boundaries)
- Peak RAM scales with chunk_size instead of total frame count:
OLED 3840×2160: ~18 GB/chunk vs ~137 GB full-video
LED_Wall 6144×1952: ~24 GB/chunk vs ~200+ GB full-video
- Uses ComfyUI NODE_CLASS_MAPPINGS['RIFE VFI'] via lazy import so load
order with ComfyUI-Frame-Interpolation is not constrained
- Register node in __init__.py
Made-with: Cursor
- add NILOR_SQS_ENABLED to config.json5 with default false
- extend NilorNodesConfig with sqs_enabled; apply env override when allowed
- update __init__.py to gate worker startup via cfg.sqs_enabled instead of raw env
This commit aligns the nilor-nodes with the project's new unified, name-based I/O system, as specified in the workflow override fix plan. This change establishes a stable, human-readable API contract for all workflows, replacing the previous fragile node-ID-based system.
Key Changes:
- **`MediaStreamInput` & `NilorUserInput`**: Added a static, non-overridable `input_name` string widget. Workflow authors now assign a logical name to each input, which is used by the Brain API to inject data.
- **`MediaStreamOutput`**: Added a static `output_name` widget. This provides a stable key for the Brain API to identify and retrieve specific outputs.
- **`MediaStreamOutput` (Logic)**: Corrected the completion logic to properly parse the full dictionary of named outputs it receives from the Brain API, ensuring it sends the correct, complete payload upon job completion.
These changes are a critical part of the larger refactor to improve the security, scalability, and maintainability of the ComfyUI integration.
Sylvester Meighan