🔁 ComfyUI Sequential Batcher & Video Loop Master (Beta v0.9.2)

Important

This version is currently in BETA. We have renamed the project from "Job Iterator" to Sequential Batcher to better reflect its purpose: processing batches one-by-one to save VRAM.

The ultimate tool for creating complex iterative workflows and frame-by-frame video processing in ComfyUI. Designed to handle huge tasks (like high-res video generation with Wan2.2 or LTX Video) without crashing your GPU by using intelligent sequential looping instead of VRAM-heavy batching.

🚀 Why use this?

Standard ComfyUI batching processes everything at once (4D tensors). For video or large batches, this leads to Out of Memory (OOM) errors. Sequential Batcher allows you to "split" these tasks and process them one-by-one (sequentially) within a single "Queue Prompt" run, then "gather" the results back into a single batch or video file.

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🛠️ Installation

1. Clone this repo into custom_nodes/comfyui-sequential-batcher.
2. Restart ComfyUI.
3. Dependencies (torch, numpy) will be handled automatically if using ComfyUI Manager.

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📖 Key Concepts

• SEQUENCE: A simple list of values (numbers, strings, etc.).
• BATCH (formerly JOB): A structured collection of "steps". Each step has named Attributes.
• Iteration: The magic happens in nodes like Batch To List, Image Batch To List, or Latent Batch To List. When ComfyUI sees a "List" output from these nodes, it executes all downstream nodes once for each item in that list.

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🎞️ Video Workflow (Wan2.2 / LTX-Video / Future Models)

Video models produce many frames that can easily exceed 24GB VRAM.

1. Split: Use Latent Batch To List to turn your video latent into a list of single frames.
2. Process: Connect to your KSampler/VAE Decoder. ComfyUI will process Frame 1, then Frame 2, then Frame 3...
3. Gather: Use Latent List To Batch (or Image List To Batch if you decoded first) to reconstruct the full video batch for saving.

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🔢 Detailed Node Reference

🔄 Loop Category (🔁 Sequential Batcher/Loop)

• 🔁 Sequential Loop Index: The simplest way to start a loop.
  • Input: count (How many times to run).
  • Output: index (0, 1, 2...). Useful for seeding or selecting specific items.
• 🔁 Repeat: Takes any input and repeats it N times.
  • Input: input (Any), count (INT).
  • Output: output (List of the same input).

🛠️ Batch Category (🔁 Sequential Batcher/Job)

• 🛠️ Make Batch: Turns a sequence into a "Batch" object.
  • Input: sequence (The data), name (The attribute name, e.g., "cfg_scale").
• 🖇️ Combine Batches: Merges multiple batches.
  • Modes: zip (paired) or product (every combination).
• 🔄 Batch To List: CRITICAL. Converts a Batch into a stream of attributes that triggers the sequential loop.
• 📥 Get Attribute: Extracts a specific value from the current batch step by its name.

🖼️ Image & Latent Category (🔁 Sequential Batcher/Image & /Latent)

• 🖼️ Image Batch To List: Splits a [N,H,W,C] tensor into N separate images.
• 🖼️ Image List To Batch: Reconstructs a batch from iterated images.
• 🎞️ Latent Batch To List: Splits video latents frame-by-frame for VRAM-safe processing.
• 🎞️ Latent List To Batch: Merges individual frames back into a video latent batch.
• ⏳ Progress Bar: Generates a visual progress indicator.

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💡 Pro Tips

• Use 🖇️ Combine Batches in product mode to create XY Plots (e.g., test every Prompt against every CFG scale).
• Use 🔍 Model Finder to automatically iterate through a folder of LoRAs or Checkpoints.
• Combine with ⌨️ Interact to pause your workflow at a specific frame and inspect variables in the terminal.