Update app.py

app.py

@@ -2,7 +2,6 @@ import gradio as gr
 from gradio_client import Client
 import trimesh
 import os
-import numpy as np
 
 # --- Constants ---
 # We use the InstantMesh space as the backend engine because it is currently
@@ -40,10 +39,10 @@ def generate_3d_geometry(input_image, do_remove_background):
         raise gr.Error("Please upload an image first!")
 
     print("Initializing Client connection to backend...")
+    # Initialize the client inside the function to ensure a fresh connection
     client = Client(BACKEND_SPACE)
     
     # 1. Preprocess: Remove background (crucial for accurate geometry)
-    # The backend space expects this step first.
     print("Step 1: Removing background...")
     try:
         processed_image_path = client.predict(
@@ -57,14 +56,18 @@ def generate_3d_geometry(input_image, do_remove_background):
     # 2. Generate: Create the 3D mesh from the processed image
     print("Step 2: Generating 3D mesh (this may take 30-60 seconds)...")
     try:
-        # We ask for the .obj output for easier STL conversion
+        # The AI generates the mesh.
         result_paths = client.predict(
             processed_image_path,
             api_name="/generate_mesh"
         )
-        # The API returns a tuple path usually: (glb_path, obj_path)
-        # We prefer the OBJ path if available as it's cleaner for geometry
-        obj_output_path = result_paths[1] 
+        
+        # InstantMesh API returns a tuple: (glb_path, obj_path)
+        # We extract the OBJ path (index 1) for reliable STL conversion.
+        if isinstance(result_paths, (list, tuple)) and len(result_paths) > 1:
+            obj_output_path = result_paths[1]
+        else:
+            obj_output_path = result_paths
 
     except Exception as e:
          raise gr.Error(f"3D Generation failed: {e}")
@@ -74,7 +77,7 @@ def generate_3d_geometry(input_image, do_remove_background):
     stl_output_path = convert_obj_to_stl(obj_output_path)
     
     if stl_output_path is None:
-        raise gr.Error("Failed to convert model to STL.")
+        raise gr.Error("Failed to convert model to STL. The AI may have generated a corrupted mesh.")
 
     # Return the interactive 3D model path and the downloadable STL path
     return obj_output_path, stl_output_path
@@ -82,27 +85,26 @@ def generate_3d_geometry(input_image, do_remove_background):
 
 # --- Gradio Interface UI Setup ---
 css = """
-#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
+#col-container {max-width: 800px; margin-left: auto; margin-right: auto;}
 h1 {text-align: center;}
 """
 
 with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown("""
-            # AI Geometry to STL Converter
-            **Expert Note:** While you may have many photos, current top-tier generative AI works best by taking your *best, clearest single view* and intelligently constructing the rest of the geometry. 
-            Upload your best, evenly lit photo of the geometric shape below.
+            # 🧊 AI Image to 3D STL Generator
+            Upload your **best, clearest, and most evenly lit single photo** of the geometric shape below. The AI will extrapolate the geometry and generate a downloadable STL file for 3D printing or CAD use.
             """)
             
         with gr.Row():
             with gr.Column():
                 input_img = gr.Image(label="Upload Best Image", type="filepath", height=300)
-                rm_bg_checkbox = gr.Checkbox(label="Remove Background (Recommended)", value=True, info="Helps isolate the shape accurately.")
+                rm_bg_checkbox = gr.Checkbox(label="Remove Background (Recommended)", value=True, info="Helps the AI isolate the exact shape of your object.")
                 gen_btn = gr.Button("Generate 3D Model & STL", variant="primary")
             
             with gr.Column():
                 # The interactive 3D viewer
-                model_output = gr.Model3D(label="Interactive 3D Preview", clear_color=[1.0, 1.0, 1.0, 0.0], interactive=True, height=300)
+                model_output = gr.Model3D(label="Interactive 3D Preview", clear_color=[1.0, 1.0, 1.0, 0.0], height=300)
                 # The download button for the STL
                 stl_download = gr.File(label="Download STL File", file_count="single")
 
@@ -114,6 +116,6 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
         api_name="run_generation"
     )
 
-# Launch the app
+# Launch the app with a queue to prevent timeouts
 if __name__ == "__main__":
     demo.queue(max_size=10).launch()