Fix: Switch to Native Gradio SDK for ZeroGPU stability

app.py

@@ -3,14 +3,20 @@ import os
 import gc
 import torch
 
-# --- PARCHES ---
+# --- PARCHE CRÍTICO (FIX RECURSION ERROR) ---
 try:
     import gradio_client.utils as client_utils
+    if not hasattr(client_utils, "_old_json_schema_to_python_type"):
+        client_utils._old_json_schema_to_python_type = client_utils._json_schema_to_python_type
+    
     def patched_json_schema_to_python_type(schema, defs=None):
         if isinstance(schema, bool): return "Any"
-        return client_utils._json_schema_to_python_type(schema, defs)
+        return client_utils._old_json_schema_to_python_type(schema, defs)
+    
     client_utils._json_schema_to_python_type = patched_json_schema_to_python_type
-except: pass
+    print("Gradio Patch v2.5 Applied (Recursion Safe)")
+except Exception as e:
+    print(f"Patch Error: {e}")
 
 import spaces
 import gradio as gr
@@ -63,21 +69,18 @@ def generate_t2i(prompt, neg, model_name, lora_id_custom, lora_scale, steps, cfg
 
 @spaces.GPU(duration=250)
 def generate_video(prompt, model_name, lora_name, lora_custom, lora_scale, steps, cfg):
-    flush() # Limpiar todo antes de empezar
+    flush()
     from diffusers import LTXPipeline
     from diffusers.utils import export_to_video
     
     model_id = LTX_MODELS.get(model_name)
     lora_id = lora_custom if lora_custom else LTX_LORAS.get(lora_name)
     
-    # CARGA OPTIMIZADA
     pipe = LTXPipeline.from_pretrained(
         model_id, torch_dtype=torch.bfloat16, 
         low_cpu_mem_usage=True
     )
     pipe.to("cuda")
-    
-    # IMPORTANTE: Ahorro de memoria para video
     pipe.enable_vae_slicing()
     
     if lora_id:
@@ -85,7 +88,6 @@ def generate_video(prompt, model_name, lora_name, lora_custom, lora_scale, steps
             pipe.load_lora_weights(lora_id)
         except: pass
     
-    # Generar video (Reducido a 33 frames para evitar timeout/OOM)
     output = pipe(
         prompt=prompt, 
         negative_prompt="low quality, blurry, static, distorted",
@@ -106,7 +108,7 @@ def generate_video(prompt, model_name, lora_name, lora_custom, lora_scale, steps
 
 # --- INTERFAZ ---
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple")) as demo:
-    gr.HTML("<h1 style='text-align:center;'>🚀 Studio Privado v2.4 (Ultra-Stable)</h1>")
+    gr.HTML("<h1 style='text-align:center;'>🚀 Studio Privado v2.5 PRO</h1>")
     
     with gr.Tabs():
         with gr.Tab("🖼 Imagen"):