Update app.py

app.py

@@ -1,17 +1,15 @@
 import sys
 import importlib
+import os
+import urllib.request
 
 # =================================================================
 # CRITICAL PYTHON 3.13 / GRADIO SDK CONFLICT MONKEY-PATCHES
-# Executed by intercepting and adjusting real modules dynamically.
 # =================================================================
 
 # 1. Safely inject HfFolder directly into the real huggingface_hub without blocking other imports
 try:
-    # Force load the actual installed huggingface_hub package first
     real_hf_hub = importlib.import_module('huggingface_hub')
-    
-    # If the real package is missing HfFolder (Python 3.13 / hub 0.26+ issue), inject a compliant stub
     if not hasattr(real_hf_hub, 'HfFolder'):
         class MockHfFolder:
             @classmethod
@@ -22,9 +20,7 @@ try:
             def delete_token(cls): pass
 
         real_hf_hub.HfFolder = MockHfFolder
-        # Ensure it's globally visible across all sub-module reference caches
         sys.modules['huggingface_hub'].HfFolder = MockHfFolder
-        print("Successfully injected missing HfFolder component into huggingface_hub.")
 except Exception as patch_err_1:
     print(f"Pre-import HfFolder patch skipped or failed: {patch_err_1}")
 
@@ -44,22 +40,20 @@ except Exception as patch_err_2:
     print(f"Schema serialization engine patch deferred: {patch_err_2}")
 # =================================================================
 
-import os
 import cv2
 import gradio as gr
 import numpy as np
 import onnxruntime as ort
-from huggingface_hub import hf_hub_download
 
-# Map open model checkpoints using verified community organization targets
+# Explicit public direct mirror links bypassing authenticated API wrappers
 MODELS = {
     "RealESRGAN_x2plus (Faster 2x)": {
-        "repo_id": "onnx-community/RealESRGAN_x2plus_onnx",
-        "filename": "model.onnx",
+        "url": "https://huggingface.co/onnx-community/RealESRGAN_x2plus_onnx/resolve/main/model.onnx",
+        "local_name": "RealESRGAN_x2plus.onnx"
     },
     "RealESRGAN_x4plus (General 4x)": {
-        "repo_id": "onnx-community/RealESRGAN_x4plus_onnx",
-        "filename": "model.onnx",
+        "url": "https://huggingface.co/onnx-community/RealESRGAN_x4plus_onnx/resolve/main/model.onnx",
+        "local_name": "RealESRGAN_x4plus.onnx"
     }
 }
 
@@ -69,9 +63,8 @@ ort_session = None
 
 def load_model(model_choice):
     """
-    Switches the active ONNX runtime model configuration.
-    Uses the native hf_hub_download wrapper which works seamlessly
-    when hitting official community/organization repos.
+    Downloads model weights directly via open browser mirrors into the transient container space
+    to completely circumvent the 401 unauthenticated API token requirements.
     """
     global current_model_name, ort_session
     
@@ -79,9 +72,22 @@ def load_model(model_choice):
         return ort_session
 
     cfg = MODELS[model_choice]
-    
-    print(f"Loading weights for {model_choice}...")
-    model_path = hf_hub_download(repo_id=cfg["repo_id"], filename=cfg["filename"])
+    cache_dir = "/tmp/models"
+    os.makedirs(cache_dir, exist_ok=True)
+    model_path = os.path.join(cache_dir, cfg["local_name"])
+
+    # Download only if the model file is not already cached locally
+    if not os.path.exists(model_path):
+        print(f"Downloading weights for {model_choice} directly via public mirror stream...")
+        try:
+            # Custom User-Agent prevents generic scraper blockades on CDN edges
+            opener = urllib.request.build_opener()
+            opener.addheaders = [('User-Agent', 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)')]
+            urllib.request.install_opener(opener)
+            urllib.request.urlretrieve(cfg["url"], model_path)
+            print(f"Successfully cached model file locally at: {model_path}")
+        except Exception as dl_err:
+            raise RuntimeError(f"Direct weight initialization stream failed: {dl_err}")
 
     # Configure ONNX runtime parameters optimized for CPU processing execution
     session_options = ort.SessionOptions()
@@ -140,7 +146,7 @@ def upscale_image(input_img, model_choice):
 # Define the user interface layout
 with gr.Blocks(title="AI Lightweight Image Upscaler (ONNX)") as demo:
     gr.Markdown("# 🖼️ AI Image Resizer & Upscaler (ONNX Engine)")
-    gr.Markdown("Running locally on Hugging Face Free CPU hardware using official `onnx-community` model tracks.")
+    gr.Markdown("Running locally on Hugging Face Free CPU hardware using direct public weight streams.")
     
     with gr.Row():
         with gr.Column():