Dariusz L 2242412b87 Improve model info UI and sanitize descriptions
Enhance the LinkerManager dialog UI and add safe HTML handling for model descriptions. This adds tooltip '?' helpers with explanatory titles for multiple info rows, wraps descriptions with a collapsible "Show more" widget, and implements sanitizeDescriptionHtml to allow a safe subset of tags/styles/links (and enforce target/rel for external links). Styling updates polish tabs, footer buttons and the description area, remove inline button sizing, and introduce a tab content animation. Also adjust click handling for description toggle and trained-words copy behavior and standardize footer button classes.
2026-04-25 00:18:54 +02:00
2025-11-04 03:08:32 +01:00
2025-11-04 21:19:19 +01:00

ComfyUI Model Linker Extension

A ComfyUI extension that helps users relink missing models in workflows using fuzzy matching.

https://github.com/user-attachments/assets/fedf3645-aa66-49f7-b01d-8c3b5127faf4

Model Linker Interface

Features

  • Scans all nodes in workflows to find missing models
  • Uses fuzzy matching to suggest similar model files
  • Updates workflow JSON in UI/memory (user saves themselves)
  • Supports all node types
  • Optional auto-resolve for 100% confidence matches

Installation

  1. Clone or download this repository
  2. Place it in your ComfyUI custom_nodes/ directory
  3. Restart ComfyUI

Usage

  1. Open a workflow with missing models
  2. Click the "🔗 — Model Linker" button in ComfyUI's top menu bar
  3. Review missing models and their suggested matches
  4. Click "Resolve" for individual models or "Auto-Resolve 100% Matches" for perfect matches
  5. Save your workflow when ready

Features

  • Subgraph Support: Automatically detects and handles missing models inside subgraphs
  • Smart Matching: Shows 100% confidence matches when available, otherwise shows best matches (≥70% confidence)
  • Fuzzy Matching: Uses intelligent similarity scoring to find model files even with different naming
  • Auto-Resolve: One-click resolution for all perfect matches
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Description
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Readme MIT
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