Agregado SD 3.5 Large (Premium) al Space - Modelo de alta calidad con soporte completo

app.py

@@ -107,6 +107,9 @@ MODELS = {
         "black-forest-labs/FLUX.1-dev": "FLUX.1 Dev (Requiere acceso)",
         "black-forest-labs/FLUX.1-schnell": "FLUX.1 Schnell (Requiere acceso)",
         
+        # 🌟 Modelos Premium de Alta Calidad
+        "stabilityai/stable-diffusion-3.5-large": "🌟 SD 3.5 Large (Alta Calidad)",
+        
         # 📦 Modelos adicionales
         "CompVis/ldm-text2im-large-256": "Latent Diffusion Model 256"
     },
@@ -234,6 +237,41 @@ def load_image_model(model_name):
                         safety_checker=None
                     )
             
+            # Configuración especial para SD 3.5 Large (Premium)
+            elif "stable-diffusion-3.5-large" in model_name:
+                try:
+                    from diffusers import StableDiffusion3Pipeline
+                    print("🌟 Cargando SD 3.5 Large (Premium)...")
+                    print(f"🔧 Modelo: {model_name}")
+                    
+                    # SD 3.5 Large requiere bfloat16 para mejor rendimiento
+                    pipe = StableDiffusion3Pipeline.from_pretrained(
+                        model_name,
+                        torch_dtype=torch.bfloat16 if torch.cuda.is_available() else torch.float32,
+                        use_auth_token=HF_TOKEN if HF_TOKEN else None
+                    )
+                    
+                    print("✅ SD 3.5 Large cargado exitosamente")
+                    
+                except Exception as e:
+                    print(f"❌ Error cargando SD 3.5 Large: {e}")
+                    print(f"🔍 Tipo de error: {type(e).__name__}")
+                    
+                    # Si es un error de autenticación, dar instrucciones específicas
+                    if "401" in str(e) or "unauthorized" in str(e).lower():
+                        print("🔐 Error de autenticación. Asegúrate de:")
+                        print("   1. Tener acceso al modelo SD 3.5 Large en Hugging Face")
+                        print("   2. Configurar HF_TOKEN en las variables de entorno del Space")
+                        print("   3. Que el token tenga permisos para acceder a modelos gated")
+                    
+                    # Fallback a SDXL
+                    print("🔄 Fallback a SDXL...")
+                    pipe = StableDiffusionPipeline.from_pretrained(
+                        "stabilityai/stable-diffusion-xl-base-1.0",
+                        torch_dtype=torch_dtype,
+                        safety_checker=None
+                    )
+            
             # Configuración especial para SD 2.1 (problemático)
             elif "stable-diffusion-2-1" in model_name:
                 try:
@@ -656,6 +694,11 @@ def generate_image(prompt, model_name, negative_prompt="", seed=0, width=1024, h
             guidance_scale = max(3.5, min(guidance_scale, 7.5))
             num_inference_steps = max(15, num_inference_steps)
             print(f"🔐 Modelo FLUX - Ajustando parámetros: guidance={guidance_scale}, steps={num_inference_steps}")
+        elif "stable-diffusion-3.5-large" in model_name:
+            # SD 3.5 Large funciona mejor con guidance_scale entre 3.5-4.5 y 28 steps
+            guidance_scale = max(3.5, min(guidance_scale, 4.5))
+            num_inference_steps = max(28, num_inference_steps)
+            print(f"🌟 SD 3.5 Large - Ajustando parámetros: guidance={guidance_scale}, steps={num_inference_steps}")
         
         generator = torch.Generator(device=device).manual_seed(seed)