hidden gradio element

app.py

@@ -127,8 +127,8 @@ def extract_glb(
 
 @spaces.GPU(duration=180)
 def generate_model_from_images_and_upload(
-    image_inputs_arg, # Temporarily change name to see raw input
-    input_type_arg,   # Temporarily change name
+    image_inputs: List[str],
+    input_type: str,
     seed_val: int,
     ss_guidance_strength_val: float,
     ss_sampling_steps_val: int,
@@ -143,22 +143,16 @@ def generate_model_from_images_and_upload(
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     os.makedirs(user_dir, exist_ok=True)
 
-    # --- START DEBUG LOGS ---
-    print(f"DEBUG: Raw image_inputs_arg: {image_inputs_arg}")
-    print(f"DEBUG: Type of image_inputs_arg: {type(image_inputs_arg)}")
-    if isinstance(image_inputs_arg, list):
-        print(f"DEBUG: Length of image_inputs_arg list: {len(image_inputs_arg)}")
-        if len(image_inputs_arg) > 0:
-            print(f"DEBUG: First element of image_inputs_arg: {image_inputs_arg[0]}")
-            print(f"DEBUG: Type of first element: {type(image_inputs_arg[0])}")
+    # --- KEEP DEBUG LOGS for this test run ---
+    print(f"DEBUG: Raw image_inputs (as received by function): {image_inputs}")
+    print(f"DEBUG: Type of image_inputs: {type(image_inputs)}")
+    if isinstance(image_inputs, list):
+        print(f"DEBUG: Length of image_inputs list: {len(image_inputs)}")
+        if len(image_inputs) > 0:
+            print(f"DEBUG: First element of image_inputs: {image_inputs[0]}")
+            print(f"DEBUG: Type of first element: {type(image_inputs[0])}")
     # --- END DEBUG LOGS ---
-
-    # Assign to original names for the rest of the script to function if data is as expected
-    # If image_inputs_arg is not what we expect (a list), this might error or behave unexpectedly
-    image_inputs: List[str] = image_inputs_arg if isinstance(image_inputs_arg, list) else []
-    input_type: str = input_type_arg if isinstance(input_type_arg, str) else ""
-
-
+    
     print(f"Processed image_inputs: {image_inputs}, input_type: {input_type}") # Original log line
 
     pil_images = []
@@ -377,9 +371,17 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
     )
 
     # --- Add this section to explicitly register the API function for image to 3D ---
-    # These State components are placeholders for API-only inputs
-    api_image_inputs_state = gr.State(value=[]) # For List[str] of image_inputs
-    api_input_type_state = gr.State(value="url") # For input_type: "url", "filepath", or "base64"
+    # Use gr.File for image_inputs for better API handling of URL lists
+    # This component will be hidden and only used for the API definition.
+    api_image_files_placeholder = gr.File(
+        label="API Image Input Placeholder",
+        file_count="multiple", # Allows a list of files/URLs
+        visible=False,
+        interactive=False # Not for UI interaction
+    )
+    
+    # input_type still needed to differentiate between URL, base64, filepath
+    api_input_type_state = gr.State(value="url")
     api_model_description_state = gr.State(value="ImagenModel") # For model_description
 
     with gr.Row(visible=False): # Hide this row in the UI
@@ -391,7 +393,7 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
     api_image_gen_trigger_btn.click(
          generate_model_from_images_and_upload,
          inputs=[ # Order must match the Python function's parameters
-             api_image_inputs_state,
+             api_image_files_placeholder, # <--- CHANGED: Use the gr.File component here
              api_input_type_state,
              seed, # UI component
              ss_guidance_strength, # UI component