A 100% vibecoded, visual dashboard for managing, versioning, and batch-processing JSON configuration files used in AI video generation workflows (I2V, VACE).

This tool consists of two parts:

Streamlit Web Interface: A Dockerized editor to manage prompts, LoRAs, and settings.
ComfyUI Custom Nodes: A set of nodes to read these JSON files directly into your workflows.

✨ Features

📝 Single File Editor

Visual Interface: Edit Prompts, Negative Prompts, Seeds, LoRAs, and advanced settings (Camera, FLF, VACE params) without touching raw JSON.
Smart History: Every save allows you to create a "Snapshot." You can view, restore, or edit historical versions of your prompts instantly.
Conflict Protection: Prevents accidental overwrites if the file is modified by another tab or process.
Snippet Library: Save reusable prompt fragments (e.g., "Cinematic Lighting", "Anime Style") and append them with one click.

🚀 Batch Processor

Sequence Management: Create unlimited sequences within a single JSON file.
Import Tools: Copy settings from any other file or history entry into your current batch sequence.
Promote to Single: Liked a specific shot in your batch? One-click convert a sequence back into a standalone Single File.
Infinite Looping: ComfyUI nodes automatically loop through sequences (modulo logic), allowing for infinite generation runs.

🛠️ Installation

1. Unraid / Docker Setup (The Manager)

This tool is designed to run as a lightweight container on Unraid.

Prepare a Folder: Create a folder on your server (e.g., /mnt/user/appdata/ai-manager/) and place the following files inside:
- app.py
- utils.py
- tab_single.py
- tab_batch.py
Add Container in Unraid:
- Repository: python:3.12-slim
- Network: Bridge
- WebUI: http://[IP]:[PORT:8501]
Path Mappings:
- App Location: Container /app ↔ Host /mnt/user/appdata/ai-manager/
- Project Data: Container /mnt/user/ ↔ Host /mnt/user/ (Your media/JSON location)

Post Arguments (Crucial): Enable "Advanced View" and paste this into Post Arguments:

/bin/sh -c "pip install streamlit opencv-python-headless && cd /app && streamlit run app.py --server.headless true --server.port 8501"

2. ComfyUI Setup (The Nodes)

Navigate to your ComfyUI installation: ComfyUI/custom_nodes/
Create a folder named ComfyUI-JSON-Loader.
Place the json_loader.py file inside.
Restart ComfyUI.

🖥️ Usage Guide

The Web Interface

Navigate to your container's IP (e.g., http://192.168.1.100:8501).

Navigator: Use the sidebar to browse folders and "Pin" favorites for quick access.
Editing: Select a JSON file. If it's a batch file, the app will auto-detect it and ask you to switch to the Batch Tab.
Saving:
- Update File: Saves changes to disk.
- Snapshot: Saves changes AND creates a history entry with a custom note.

ComfyUI Workflow

Search for "JSON" in ComfyUI to find the new nodes.

Standard Nodes (For Single Files)

Node Name	Description
JSON Loader (Standard/I2V)	Outputs prompts, FLF, Seed, and paths for Image-to-Video workflows.
JSON Loader (VACE Full)	Outputs everything above plus specific VACE integers (frames to skip, schedule, etc.).
JSON Loader (LoRAs Only)	Outputs the 6 LoRA strings. Keeps your main graph clean.

Batch Nodes (For Sequences)

These nodes accept a sequence_number integer input.

Input: Connect a Primitive node (set to increment) or a Batch Indexer to the sequence_number input.
Logic: If you request Sequence #5 but the file only has 3 sequences, it wraps around (Sequence #2). This allows infinite loops.

Node Name	Description
JSON Batch Loader (I2V)	Loads specific sequence data for I2V.
JSON Batch Loader (VACE)	Loads specific sequence data for VACE.
JSON Batch Loader (LoRAs)	Loads the specific LoRAs assigned to that sequence.

📂 File Structure

/ai-manager
├── app.py              # Main Streamlit entry point
├── utils.py            # Configuration, I/O logic, and Defaults
├── tab_single.py       # UI Logic for Single File Editor
├── tab_batch.py        # UI Logic for Batch Processor
└── json_loader.py      # ComfyUI Custom Node script