generation fix pyversion

app.py

@@ -144,49 +144,50 @@ async def generate_model(request: GenerateRequest):
         # OR we just pass them and let PyPRT handle if it's geographic.
         # Standard CityEngine works best with metric local coordinates.
         
-        # Vertices list for PyPRT
-        vertices = []
-        for x, y in coords: # web mercator or lat/long
-            vertices.extend([x, 0, y]) # Simple mapping to X, Y=0, Z
-            
-        indices = list(range(len(coords)))
-        face_counts = [len(coords)]
-        
-        initial_shape = pyprt.InitialShape(vertices, indices, face_counts)
-        
+        # Flatten coordinates: [(x, y), ...] -> [x, 0, y, x, 0, y, ...]
+        # PyPRT expects a flattened list of coords.
+        flattened_coords = []
+        for x, y in coords:
+            flattened_coords.extend([x, 0, y])
+
+        initial_shape = pyprt.InitialShape(flattened_coords, indices, face_counts)
+
         # Setup Model Generator
         model_generator = pyprt.ModelGenerator([initial_shape])
         
-        # Generate
+        # Determine output path - Create a unique temp directory
+        output_path = tempfile.mkdtemp()
+        output_filename = "model"
+
         # Generate
         # PyPRT generate_model signature: 
         # (self: ModelGenerator, shapeAttributes: list[dict], rulePackagePath: str, geometryEncoderName: str, geometryEncoderOptions: dict)
         
-        with tempfile.NamedTemporaryFile(suffix=".glb", delete=False) as tmp:
-            output_path = os.path.dirname(tmp.name)
-            output_filename = os.path.basename(tmp.name)
-            
-            models = model_generator.generate_model(
-                [request.attributes], 
-                rpk_path, 
-                "com.esri.prt.codecs.GLBEncoder",
-                {
-                    'outputPath': output_path,
-                    'outputFilename': output_filename,
-                    'emitReport': False
-                }
-            )
-            
-            # The file should now exist at tmp.name (or slightly different name depending on encoder)
-            # GLB encoder often appends .glb if missing or uses exact name
-            expected_file = os.path.join(output_path, output_filename + ".glb")
-            if not os.path.exists(expected_file):
-                 expected_file = os.path.join(output_path, output_filename)
-            
-            if os.path.exists(expected_file):
-                return FileResponse(expected_file, media_type="model/gltf-binary", filename="output.glb")
-            else:
-                 raise HTTPException(status_code=500, detail="GLB file generation failed")
+        models = model_generator.generate_model(
+            [request.attributes], 
+            rpk_path, 
+            "com.esri.prt.codecs.GLBEncoder",
+            {
+                'outputPath': output_path,
+                'outputFilename': output_filename,
+                'emitReport': False
+            }
+        )
+        
+        # Check for output
+        # GLB encoder usually creates {outputFilename}.glb or {outputFilename}_0.glb depending on rule
+        # We need to find *any* .glb file in that directory
+        
+        generated_files = [f for f in os.listdir(output_path) if f.endswith(".glb")]
+        
+        if generated_files:
+            file_path = os.path.join(output_path, generated_files[0])
+            # Note: We are returning the file but not cleaning up the temp dir immediately. 
+            # In production, consider a background task or context manager to cleanup.
+            return FileResponse(file_path, media_type="model/gltf-binary", filename="output.glb")
+        else:
+             logger.error(f"No GLB file found in {output_path}")
+             raise HTTPException(status_code=500, detail="GLB generation failed: No file created")
 
     except Exception as e:
         logger.error(f"Generation error: {e}")