fix: try valid caption for generation_all to avoid NameError

api_info.txt

@@ -0,0 +1,118 @@
+Loaded as API: https://tencent-hunyuan3d-2.hf.space
+Client.predict() Usage Info
+---------------------------
+Named API endpoints: 12
+
+ - predict(api_name="/lambda") -> 
+    Parameters:
+     - None
+    Returns:
+     - None
+
+ - predict(api_name="/lambda_1") -> 
+    Parameters:
+     - None
+    Returns:
+     - None
+
+ - predict(caption, image, mv_image_front, mv_image_back, mv_image_left, mv_image_right, steps, guidance_scale, seed, octree_resolution, check_box_rembg, num_chunks, randomize_seed, api_name="/shape_generation") -> (file, output, mesh_stats, seed)
+    Parameters:
+     - [Textbox] caption: str | None (not required, defaults to:   None)  
+     - [Image] image: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_front: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_back: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_left: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_right: filepath | None (not required, defaults to:   None)  
+     - [Slider] steps: float (not required, defaults to:   30)  (numeric value between 1 and 100) 
+     - [Number] guidance_scale: float (not required, defaults to:   5.0)  
+     - [Slider] seed: float (not required, defaults to:   1234)  (numeric value between 0 and 10000000.0) 
+     - [Slider] octree_resolution: float (not required, defaults to:   256)  (numeric value between 16 and 512) 
+     - [Checkbox] check_box_rembg: bool (not required, defaults to:   True)  
+     - [Slider] num_chunks: float (not required, defaults to:   8000)  (numeric value between 1000 and 5000000) 
+     - [Checkbox] randomize_seed: bool (not required, defaults to:   True)  
+    Returns:
+     - [File] file: filepath 
+     - [Html] output: str 
+     - [Json] mesh_stats: Dict[Any, Any] (any valid json) 
+     - [Slider] seed: float (numeric value between 0 and 10000000.0) 
+
+ - predict(api_name="/lambda_2") -> (include_texture, simplify_mesh, download)
+    Parameters:
+     - None
+    Returns:
+     - [Checkbox] include_texture: bool 
+     - [Checkbox] simplify_mesh: bool 
+     - [Downloadbutton] download: filepath 
+
+ - predict(api_name="/lambda_3") -> 
+    Parameters:
+     - None
+    Returns:
+     - None
+
+ - predict(caption, image, mv_image_front, mv_image_back, mv_image_left, mv_image_right, steps, guidance_scale, seed, octree_resolution, check_box_rembg, num_chunks, randomize_seed, api_name="/generation_all") -> (file, file, output, mesh_stats, seed)
+    Parameters:
+     - [Textbox] caption: str | None (not required, defaults to:   None)  
+     - [Image] image: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_front: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_back: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_left: filepath | None (not required, defaults to:   None)  
+     - [Image] mv_image_right: filepath | None (not required, defaults to:   None)  
+     - [Slider] steps: float (not required, defaults to:   30)  (numeric value between 1 and 100) 
+     - [Number] guidance_scale: float (not required, defaults to:   5.0)  
+     - [Slider] seed: float (not required, defaults to:   1234)  (numeric value between 0 and 10000000.0) 
+     - [Slider] octree_resolution: float (not required, defaults to:   256)  (numeric value between 16 and 512) 
+     - [Checkbox] check_box_rembg: bool (not required, defaults to:   True)  
+     - [Slider] num_chunks: float (not required, defaults to:   8000)  (numeric value between 1000 and 5000000) 
+     - [Checkbox] randomize_seed: bool (not required, defaults to:   True)  
+    Returns:
+     - [File] file: filepath 
+     - [File] file: filepath 
+     - [Html] output: str 
+     - [Json] mesh_stats: Dict[Any, Any] (any valid json) 
+     - [Slider] seed: float (numeric value between 0 and 10000000.0) 
+
+ - predict(api_name="/lambda_4") -> (include_texture, simplify_mesh, download)
+    Parameters:
+     - None
+    Returns:
+     - [Checkbox] include_texture: bool 
+     - [Checkbox] simplify_mesh: bool 
+     - [Downloadbutton] download: filepath 
+
+ - predict(api_name="/lambda_5") -> 
+    Parameters:
+     - None
+    Returns:
+     - None
+
+ - predict(value, api_name="/on_gen_mode_change") -> inference_steps
+    Parameters:
+     - [Radio] value: Literal['Turbo', 'Fast', 'Standard'] (not required, defaults to:   Turbo)  
+    Returns:
+     - [Slider] inference_steps: float (numeric value between 1 and 100) 
+
+ - predict(value, api_name="/on_decode_mode_change") -> octree_resolution
+    Parameters:
+     - [Radio] value: Literal['Low', 'Standard', 'High'] (not required, defaults to:   Standard)  
+    Returns:
+     - [Slider] octree_resolution: float (numeric value between 16 and 512) 
+
+ - predict(api_name="/lambda_6") -> 
+    Parameters:
+     - None
+    Returns:
+     - None
+
+ - predict(file_out, file_out2, file_type, reduce_face, export_texture, target_face_num, api_name="/on_export_click") -> (output, download)
+    Parameters:
+     - [File] file_out: filepath (required)  
+     - [File] file_out2: filepath (required)  
+     - [Dropdown] file_type: Literal['glb', 'obj', 'ply', 'stl'] (not required, defaults to:   glb)  
+     - [Checkbox] reduce_face: bool (not required, defaults to:   False)  
+     - [Checkbox] export_texture: bool (not required, defaults to:   False)  
+     - [Slider] target_face_num: float (not required, defaults to:   10000)  (numeric value between 100 and 1000000) 
+    Returns:
+     - [Html] output: str 
+     - [Downloadbutton] download: filepath 
+

app.py

@@ -92,10 +92,10 @@ def generate_3d_model(image: Image.Image, with_texture: bool = True) -> tuple[st
         
         if with_texture:
             try:
-                debug_logs.append("Attempting /generation_all endpoint...")
-                # Intentar /generation_all con parámetros exactos
+                debug_logs.append("Attempting /generation_all with 'A 3D model of a vehicle' caption...")
+                # Intentar /generation_all con caption explícito
                 result = client.predict(
-                    caption="",
+                    caption="A 3D model of a vehicle", # Intentando evitar NameError por None/Empty
                     image=handle_file(temp_path),
                     mv_image_front=None,
                     mv_image_back=None,
@@ -113,21 +113,20 @@ def generate_3d_model(image: Image.Image, with_texture: bool = True) -> tuple[st
                 
                 os.unlink(temp_path)
                 
+                debug_logs.append("API call successful!")
                 debug_logs.append(f"Result type: {type(result)}")
+                
                 if isinstance(result, tuple):
-                    debug_logs.append(f"Result length: {len(result)}")
-                    for i, item in enumerate(result):
-                        debug_logs.append(f"Item {i}: {item}")
-                    
-                    # El segundo archivo suele ser el modelo con texturas (OBJ/GLB)
+                    debug_logs.append(f"Result items: {len(result)}")
+                    # El return es (file, file, output, mesh_stats, seed)
+                    # result[1] debería ser el textured file
                     if len(result) >= 2 and result[1]:
-                        debug_logs.append("Detailed model (texture) found in index 1.")
-                        final_model_path = result[1]
+                         debug_logs.append(f"Textured model found: {result[1]}")
+                         final_model_path = result[1]
                     else:
-                        debug_logs.append("Detailed model NOT found, using index 0.")
-                        final_model_path = result[0]
+                         debug_logs.append(f"No textured model in pos 1. Pos 0: {result[0]}")
+                         final_model_path = result[0]
                 else:
-                     debug_logs.append(f"Single result: {result}")
                      final_model_path = result
                 
                 return final_model_path, final_model_path, "\n".join(debug_logs)
@@ -142,7 +141,7 @@ def generate_3d_model(image: Image.Image, with_texture: bool = True) -> tuple[st
         # Fallback a /shape_generation (solo geometría)
         debug_logs.append("Falling back to /shape_generation...")
         result = client.predict(
-            caption=None,
+            caption="A 3D model of a vehicle",
             image=handle_file(temp_path),
             mv_image_front=None,
             mv_image_back=None,
@@ -160,13 +159,12 @@ def generate_3d_model(image: Image.Image, with_texture: bool = True) -> tuple[st
         
         os.unlink(temp_path)
         
-        debug_logs.append(f"Fallback result type: {type(result)}")
         if isinstance(result, tuple):
-             debug_logs.append(f"Fallback result length: {len(result)}")
              final_model_path = result[0]
         else:
              final_model_path = result
              
+        debug_logs.append(f"Fallback success: {final_model_path}")
         return final_model_path, final_model_path, "\n".join(debug_logs)
         
     except Exception as e:

inspect_api.py

@@ -0,0 +1,11 @@
+from gradio_client import Client
+import sys
+
+# Redirect stdout to file
+with open('api_info.txt', 'w', encoding='utf-8') as f:
+    sys.stdout = f
+    client = Client("tencent/Hunyuan3D-2")
+    client.view_api()
+    sys.stdout = sys.__stdout__
+
+print("API info written to api_info.txt")