3ab6a9cc5578446604bb1dd9af88c8ce44da4cbf
Refactor and harden the Model Linker extension: normalize string quoting/formatting and improve logging and error responses across API routes. Make route registration more robust to missing PromptServer and dependencies. Add/expand download-related features: safer request parsing (including is_urn handling), CivitAI URN support & direct download URL resolution, popular/model-list/HuggingFace/CivitAI search fallbacks, improved header handling for HF/CivitAI, and better category/directory mapping. Improve downloader reliability and UX: folder_paths fallback, pre-initialize download progress entries, smoother speed calculation and CLI logging, cancellation cleanup on Windows, stronger exception handling, and consistent JSON responses from endpoints.
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
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
- Clone or download this repository
- Place it in your ComfyUI custom_nodes/ directory
- Restart ComfyUI
Usage
- Open a workflow with missing models
- Click the "🔗 — Model Linker" button in ComfyUI's top menu bar
- Review missing models and their suggested matches
- Click "Resolve" for individual models or "Auto-Resolve 100% Matches" for perfect matches
- 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
Languages
JavaScript
47.5%
Python
45.7%
CSS
6.8%
