perf(backend): optimize STL preview generation with decimation and smaller figure size

backend/preview_utils.py

@@ -8,38 +8,46 @@ from mpl_toolkits import mplot3d
 def generate_stl_preview(stl_path: str, output_path: str):
     """
     Generates a PNG preview image for an STL file.
+    Optimized for large files using decimation and smaller figure size.
     """
     try:
         # Load the STL file
         your_mesh = mesh.Mesh.from_file(stl_path)
 
-        # Create a new plot
-        figure = plt.figure(figsize=(8, 8))
-        # Use transparent background for a premium look
+        # Decimate if too many triangles to avoid OOM and slow rendering
+        # 20,000 triangles is plenty for a small thumbnail
+        vectors = your_mesh.vectors
+        if len(vectors) > 20000:
+            step = len(vectors) // 20000
+            vectors = vectors[::step]
+
+        # Create a new plot with smaller size for faster rendering
+        figure = plt.figure(figsize=(4, 4))
+        # Use transparent background
         figure.patch.set_alpha(0.0)
         
         axes = figure.add_subplot(111, projection='3d')
-        axes.set_facecolor((0,0,0,0)) # Transparent background inside plot
+        axes.set_facecolor((0,0,0,0)) 
 
         # Add the mesh to the plot
-        poly = mplot3d.art3d.Poly3DCollection(your_mesh.vectors)
+        poly = mplot3d.art3d.Poly3DCollection(vectors)
         # Professional-looking blue/gray color
         poly.set_facecolor([0.2, 0.5, 0.8, 0.9])
-        poly.set_edgecolor([0.1, 0.1, 0.1, 0.2])
+        poly.set_edgecolor([0.1, 0.1, 0.1, 0.1]) # Reduced edge opacity
         axes.add_collection3d(poly)
 
-        # Auto-scale the plot
+        # Auto-scale the plot using original mesh bounds for accuracy
         scale = your_mesh.points.flatten()
         axes.auto_scale_xyz(scale, scale, scale)
         
-        # Hide axes for a clean look
+        # Hide axes
         axes.set_axis_off()
         
-        # Adjust view for better perspective
+        # Adjust view
         axes.view_init(elev=30, azim=45)
 
-        # Save the result
-        plt.savefig(output_path, dpi=100, bbox_inches='tight', transparent=True)
+        # Save with lower DPI for speed
+        plt.savefig(output_path, dpi=80, bbox_inches='tight', transparent=True)
         plt.close(figure)
         return True
     except Exception as e: