Dariusz L e8b49dd184 Add AzLogs logging system and integrate
Introduce a new logging subsystem under core/log_system (logger.py, config.py, log_funcs.py) implementing AzLogs (LogLevel enum, colored console output, optional file rotation) and a lightweight wrapper (log_debug/info/warn/error/exception) with safe fallback when AzLogs is unavailable. Integrate these log functions across many core modules (downloader, linker, matcher, scanner, workflow_analyzer, workflow_updater, sources and related files) and export logger and helper log functions from core.__init__. Replace several direct logging calls in linker with the new log_* helpers and update core.__init__ exports. Also include small code style and robustness tweaks (path/filename normalization, JSON/file handling, minor refactors and formatting fixes) to improve matching and model-list/popular lookups.
2026-04-21 23:51:46 +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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