Fix: Absolute pinning of huggingface-hub and dual-layer HfFolder injection

app.py

@@ -1,12 +1,43 @@
 import sys
-# --- LÍNEA 1: PARCHE DE AUDIO PARA PYTHON 3.13 ---
+import os
+
+# --- LÍNEA 1: PARCHE DE EMERGENCIA TOTAL (HfFolder + audioop) ---
+try:
+    import huggingface_hub
+    # Si la pieza falta en la librería del servidor, la inyectamos manualmente
+    if not hasattr(huggingface_hub, "HfFolder"):
+        class MockHfFolder:
+            @staticmethod
+            def get_token(): return os.getenv("HF_TOKEN")
+            @staticmethod
+            def save_token(token): pass
+            @staticmethod
+            def delete_token(): pass
+        huggingface_hub.HfFolder = MockHfFolder
+        sys.modules["huggingface_hub.HfFolder"] = MockHfFolder
+        print("HfFolder Patch Applied")
+except: pass
+
 try:
     import audioop_lts
     sys.modules["audioop"] = audioop_lts
-except ImportError:
+    print("Audioop Patch Applied")
+except:
     from unittest.mock import MagicMock
     sys.modules["audioop"] = MagicMock()
-# ------------------------------------------------
+# --------------------------------------------------------------
+
+# --- PARCHE PARA EL BUG DE 'BOOL' EN GRADIO_CLIENT ---
+try:
+    import gradio_client.utils as client_utils
+    if hasattr(client_utils, "get_type"):
+        old_get_type = client_utils.get_type
+        def new_get_type(schema):
+            if isinstance(schema, bool): return "Any"
+            return old_get_type(schema)
+        client_utils.get_type = new_get_type
+except: pass
+# -----------------------------------------------------
 
 import spaces
 import gradio as gr
@@ -56,7 +87,6 @@ def generate_video(prompt, init_image, lora_scale):
     kwargs = {"prompt": prompt, "negative_prompt": NEG_DEFAULT, "num_frames": 49, 
               "num_inference_steps": 30, "generator": torch.Generator("cuda").manual_seed(42)}
     if init_image is not None:
-        # Conversión segura de imagen para Gradio 5
         if isinstance(init_image, dict):
             init_image = init_image["composite"] if "composite" in init_image else init_image["background"]
         kwargs["image"] = Image.fromarray(init_image).convert("RGB").resize((768, 512))
@@ -67,7 +97,6 @@ def generate_video(prompt, init_image, lora_scale):
     export_to_video(output.frames[0], tmp.name, fps=24)
     return tmp.name
 
-# INTERFAZ
 with gr.Blocks(title="Image Utility v2.1") as demo:
     gr.HTML("<h1 style='text-align:center;'>🛠 Image Processing Utility v2.1.4</h1>")
     with gr.Tabs():
@@ -89,12 +118,10 @@ with gr.Blocks(title="Image Utility v2.1") as demo:
             with gr.Row():
                 with gr.Column():
                     v_p = gr.Textbox(label="Motion Vector String", lines=3)
-                    # Mejora en el componente de imagen para permitir carga directa
                     v_img = gr.Image(label="Source Buffer", type="numpy", sources=["upload", "clipboard"])
                     v_ls = gr.Slider(0, 1.5, 0.8, label="Motion Weight")
                     v_btn = gr.Button("Process Sequence", variant="primary")
                 v_out = gr.Video(label="Sequence Output")
             v_btn.click(generate_video, [v_p, v_img, v_ls], v_out)
 
-# Habilitar cola para ZeroGPU y activar API para sincronización de frontend
-demo.queue(api_open=True).launch(show_api=True)
+demo.queue().launch(show_api=True)