Dariusz L 391b05949a Add analysis progress reporting & UI polling
Add real-time analysis progress reporting and client-side polling during workflow analysis. __init__.py: import asyncio, track per-analysis progress in self.analysis_progress, pass an update callback to analyze endpoint (using asyncio.to_thread), set progress states on success/error, and expose a new GET /model_linker/analyze-progress/{analysis_id} endpoint. core/linker.py: add optional progress_callback parameter to analyze_and_find_matches and emit staged progress updates (extracting, scanning, analyzing, identifying, matching, per-model progress and completed). web/linker.js: introduce analysis progress UI rendering, polling loop (pollAnalysisProgress) keyed by an analysis token, send analysis_id with analyze request, show progress bar/message, and replace search-source buttons with a compact select picker. These changes improve UX by providing live feedback during potentially long analysis runs.
2026-04-25 02:38:37 +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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Python 45.7%
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