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): Sequentially assembles the generated video chunks using FFmpeg.
   • 📦 Progressive History (New in v1.1.0!): No longer overwrites the previous video. It now saves cumulative MP4s (SCAIL_Final_0001.mp4, SCAIL_Final_0002.mp4), protecting your work from server crashes.
   • 🎵 Audio Multiplexing (New in v1.1.0!): Accepts a standard AUDIO input. Captures the sound with torchaudio and employs FFmpeg's -shortest command. This ensures the audio synchronizes perfectly and cuts exactly to the duration of the current cycle's assembly.

Setup & Usage

Prerequisites

• FFmpeg: Must be installed and available in your system's PATH for the Incremental Auto-Stitcher to function correctly.
• Torchaudio: (Usually included in ComfyUI environments) is required to extract the audio track before multiplexing.

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.