ComfyUI Sequential Batcher (v1.1.0)

A highly specialized suite of custom nodes for ComfyUI designed for Recursive Self-Queuing and autonomous sequential processing. This architecture minimizes VRAM usage by processing heavy tasks (like video generation) sequentially, batch-by-batch, orchestrated entirely from within the graph.

Leer en Español: README.md

The "Formula 1" Engine Architecture

Starting with v1.0.0, this repository has pivoted exclusively to the autonomous sequential loops and global memory architecture. All legacy technical debt (deprecated batch/sequence/debug nodes) has been pruned, leaving a clean, highly maintainable codebase focused on 6 core nodes.

In v1.1.0, we have introduced progressive disk saving capabilities, audio multiplexing support, and a deep JSON hack to defeat ComfyUI's aggressive cache.

The 6 Core Nodes

The system is built around three major categories:

🔁 Loop (Autonomous Orchestration)

1. 🏁 Loop Start (Index) (SequentialLoopStart): Initiates the loop, manages the global loop index, and provides the current iteration index to downstream nodes.
2. 🚀 Loop Trigger (Auto-Queue) (SequentialLoopTrigger): Placed at the very end of your workflow. It increments the loop counter and autonomously triggers an HTTP POST request to the ComfyUI API (/prompt) to queue the next batch cycle.
   • Seed Mutator: Scans the canvas, locates nodes with a seed (seed or noise_seed), and injects a new 32-bit random seed, breaking forward cache in samplers.
   • 💉 Anti-Cache Injection (New in v1.1.0!): Specifically searches for the Loop Start node within the JSON payload and forcefully injects the new index. This shatters ComfyUI's infamous "reverse cache" (bottom-up) that froze initial nodes during Auto-Queue, guaranteeing uninterrupted progression.

🖼️ Image (Session Memory)

3. 📥 Session Image Receiver (SessionImageReceiver): Retrieves the initial image or the last generated frame from the previous cycle, intelligently detecting the start of a RAM session.
4. 📤 Session Image Sender (SessionImageSender): Extracts the final image of a batch and secures it in system memory for the next cycle.
   • 💾 Keyframe Dumping (New in v1.1.0!): Now receives the current index and performs a safety dump to the hard drive, progressively saving keyframe_XXX.png every cycle to prevent data loss.

🎞️ Video (Assembly and Validation)

5. 🛡️ Wan Frame Validator (WanFrameValidator): Validates and corrects the target number of frames to ensure they fit the 4k+1 formula required by specific models (e.g., Wan).
6. 🎞️ Incremental Auto-Stitcher (IncrementalVideoStitcher): Progressively archives generated tensors directly to the hard drive and safely assembles them at the end of all cycles.
   • 🧠 Zero OOM (New!): Replaces RAM accumulation with progressive temporary disk saves (.pt), clearing system memory immediately to enable infinite video processing without crashing the system. By disabling INPUT_IS_LIST, it handles raw tensors efficiently.
   • 🎵 Audio Passthrough (New!): Feeds the original pure audio straight to the assembled output during the final loop iteration (returning None during intermediate loops to save resources).
7. 🎥 Load Video + Source Audio (LoadVideoWithSourceAudio): (New!) Functions exactly like the standard VHS video loader (including UI preview widget and upload button), but extracts and safely exposes the complete, uncropped original audio track to ensure it travels unaltered throughout the sequential process.

Setup & Usage

Prerequisites

• VideoHelperSuite (VHS): Dynamically required for the Load Video + Source Audio node to function and replicate its UI seamlessly.
• FFmpeg: Must be installed and available in your system's PATH to manage underlying video operations.
• Torchaudio: (Usually included in ComfyUI environments) is required to extract the original pure audio track from the source.

Installation

1. Navigate to your ComfyUI custom_nodes folder.
2. Clone this repository: git clone https://github.com/your-repo/ComfyUI-Sequential-Batcher.git
3. Restart ComfyUI.

How to use the Autonomous Machine

1. The Start: Add the 🏁 Loop Start (Index) node.
   • Connect its current_loop_index to the index inputs of your SessionImageReceiver, SessionImageSender, and Incremental Auto-Stitcher. Don't forget the Sender for keyframe saving!
   • Ensure reset_loop is set to False.
2. Connecting Audio (Optional): If your workflow has sound, pull a cable from your initial node's audio output (e.g., VHS_LoadVideo) and connect it to the blue audio port on your Incremental Auto-Stitcher.
3. The End: Add the 🚀 Loop Trigger (Auto-Queue) node. Crucially, connect the text output (final_video_path) from your Incremental Auto-Stitcher to the trigger_dependency input. This forces the trigger to wait until the video is physically saved. Set your desired target_loops.
4. Execution: You no longer need to check "Auto Queue". Just press "Queue Prompt" once. Batch 0 starts, and upon finishing, the trigger invisibly signals the server. Thanks to Anti-Cache Injection, cache is destroyed on every iteration, and progress flows until your video is complete.

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Created to push the boundaries of ComfyUI automation.