🎛️ AI Settings Manager for ComfyUI

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:

1. Streamlit Web Interface: A Dockerized editor to manage prompts, LoRAs, settings, and branching history.
2. ComfyUI Custom Nodes: A set of nodes to read these JSON files (including custom keys) 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.
• 🔧 Custom Parameters: Add arbitrary key-value pairs (e.g., controlnet_strength, my_custom_value) that persist and can be read by ComfyUI.
• 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.
• Smart Import: Copy settings from any other file or history entry into your current batch sequence.
• Custom Keys per Shot: Define unique parameters for specific shots in a batch (e.g., Shot 1 has fog: 0.5, Shot 2 has fog: 0.0).
• Promote to Single: One-click convert a specific batch sequence back into a standalone Single File.

🕒 Visual Timeline (New!)

• Git-Style Branching: A dedicated tab visualizes your edit history as a horizontal node graph.
• Non-Destructive: If you jump back to an old version and make changes, the system automatically forks a new branch so you never lose history.
• Visual Diff: Inspect any past version and see a "Delta View" highlighting exactly what changed (e.g., Seed: 100 -> 555) compared to your current state.
• Interactive Mode (WIP): A zoomed-out, interactive canvas to explore complex history trees.

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🛠️ Installation

1. Unraid / Docker Setup (The Manager)

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

1. 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
   • history_tree.py (New logic engine)
   • tab_single.py
   • tab_batch.py
   • tab_timeline.py
   • tab_timeline_wip.py
2. Add Container in Unraid:
   • Repository: python:3.12-slim
   • Network: Bridge
   • WebUI: http://[IP]:[PORT:8501]
3. Path Mappings:
   • App Location: Container /app ↔ Host /mnt/user/appdata/ai-manager/
   • Project Data: Container /mnt/user/ ↔ Host /mnt/user/ (Your media/JSON location)
4. Post Arguments (Crucial): Enable "Advanced View" and paste this command to install the required graph engines:

   /bin/sh -c "apt-get update && apt-get install -y graphviz && pip install streamlit opencv-python-headless graphviz streamlit-agraph && cd /app && streamlit run app.py --server.headless true --server.port 8501"
   

2. ComfyUI Setup (The Nodes)

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

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🖥️ Usage Guide

The Web Interface

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

• Custom Parameters: Scroll to the bottom of the editor (Single or Batch) to find the "🔧 Custom Parameters" section. Type a Key (e.g., strength) and Value (e.g., 0.8) and click "Add".
• Timeline: Switch to the Timeline Tab to see your version history.
  • Restore: Select a node from the list or click on the graph (WIP tab) to view details. Click "Restore" to revert settings to that point.
  • Branching: If you restore an old node and click "Save/Snap", a new branch is created automatically.

ComfyUI Workflow

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

Standard Nodes

Node Name	Description
JSON Loader (Standard/I2V)	Outputs prompts, FLF, Seed, and paths for I2V.
JSON Loader (VACE Full)	Outputs everything above plus VACE integers (frames to skip, schedule, etc.).
JSON Loader (LoRAs Only)	Outputs the 6 LoRA strings.

Universal Custom Nodes (New!)

These nodes read any key you added in the "Custom Parameters" section. They work for both Single files (ignores sequence input) and Batch files (reads specific sequence).

Node Name	Description
JSON Loader (Custom 1)	Reads 1 custom key. Input the key name (e.g., "strength"), outputs the value string.
JSON Loader (Custom 3)	Reads 3 custom keys.
JSON Loader (Custom 6)	Reads 6 custom keys.

Batch Nodes

These nodes require an integer input (Primitive or Batch Indexer) for sequence_number.

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 specific LoRAs for that sequence.

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📂 File Structure

/ai-manager
├── app.py                  # Main entry point & Tab controller
├── utils.py                # I/O logic, Config, and Defaults
├── history_tree.py         # Graph logic, Branching engine, Graphviz generator
├── tab_single.py           # Single Editor UI
├── tab_batch.py            # Batch Processor UI
├── tab_timeline.py         # Stable Timeline UI (Compact Graphviz + Diff Inspector)
├── tab_timeline_wip.py     # Interactive Timeline UI (Streamlit Agraph)
└── json_loader.py          # ComfyUI Custom Node script