Update app.py

app.py

@@ -1,11 +1,10 @@
-# app.py — FLUX.1 via Hugging Face InferenceClient (CPU-compatible)
+# app.py — MODELO NUEVO: SDXL via HF Inference (gratuito para HF Pro)
 import gradio as gr
 import os
 import time
 import logging
 from typing import Optional, Tuple
 from PIL import Image
-import io
 from agent import ImprovedSemanticAgent
 from huggingface_hub import InferenceClient
 
@@ -14,71 +13,51 @@ logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 # ================================================================
-# NUEVO GENERADOR USANDO Hugging Face InferenceClient
+# GENERADOR CON SDXL EN HF INFERENCE (GRATUITO PARA HF PRO)
 # ================================================================
 
-class HuggingFaceFluxGenerator:
+class SDXLHFGenerator:
     def __init__(self):
-        # HF_TOKEN se toma automáticamente si está en los secrets como HF_TOKEN
-        # Pero tú usas "PS", así que lo leemos explícitamente
-        hf_token = os.getenv("PS")
+        hf_token = os.getenv("PS")  # Tu secret se llama "PS"
         if not hf_token:
-            raise ValueError("❌ Secret 'PS' (HF_TOKEN) no encontrado en el entorno.")
+            raise ValueError("❌ Secret 'PS' (tu HF_TOKEN) no encontrado en el entorno.")
         self.client = InferenceClient(
-            provider="together",  # FLUX.1-dev disponible en Together
+            provider="hf-inference",
             api_key=hf_token
         )
 
-    def generate_image(
-        self,
-        prompt: str,
-        width: int = 1024,
-        height: int = 1024,
-        image_input: Optional[str] = None,
-        progress_callback=None
-    ) -> Tuple[Optional[str], str]:
+    def generate_image(self, prompt: str, width: int = 1024, height: int = 1024, progress_callback=None) -> Tuple[Optional[str], str]:
         try:
             if progress_callback:
-                progress_callback(0.5, desc="🚀 Generando con FLUX.1 vía HF Inference...")
-
-            if image_input is None:
-                # Text-to-image
-                image = self.client.text_to_image(
-                    prompt=prompt,
-                    model="black-forest-labs/FLUX.1-dev",
-                    width=width,
-                    height=height
-                )
-            else:
-                # Image-to-image (primero abrimos la imagen local)
-                init_image = Image.open(image_input).convert("RGB")
-                image = self.client.image_to_image(
-                    prompt=prompt,
-                    image=init_image,
-                    model="black-forest-labs/FLUX.1-dev",
-                    strength=0.75
-                )
-
-            output_path = f"/tmp/flux_hf_{int(time.time())}.png"
+                progress_callback(0.5, desc="🎨 Generando con SDXL (vía HF Inference)...")
+            
+            image = self.client.text_to_image(
+                prompt=prompt,
+                model="stabilityai/stable-diffusion-xl-base-1.0",
+                width=width,
+                height=height
+            )
+            
+            output_path = f"/tmp/sdxl_hf_{int(time.time())}.png"
             image.save(output_path)
-
+            
             if progress_callback:
                 progress_callback(1.0, desc="✅ ¡Imagen generada!")
-
-            return output_path, "✅ Imagen generada con FLUX.1-dev vía Hugging Face Inference"
-
+            
+            return output_path, "✅ Imagen generada con SDXL vía Hugging Face Inference (gratuito para HF Pro)"
+        
         except Exception as e:
-            return None, f"❌ Error en HF Inference: {str(e)}"
+            return None, f"❌ Error en generación: {str(e)}"
 
 
 # ================================================================
-# INTERFAZ GRADIO (mismo flujo semántico)
+# INTERFAZ GRADIO
 # ================================================================
 
 def create_interface():
-    # Inicializar generador y agente
+    # Inicializar
     try:
-        generator = HuggingFaceFluxGenerator()
+        generator = SDXLHFGenerator()
     except Exception as e:
         generator = None
         logger.error(f"Error al iniciar generador: {e}")
@@ -88,7 +67,6 @@ def create_interface():
     def generate_wrapper(
         prompt: str,
         aspect_ratio: str,
-        input_image,
         enable_semantic_enhancement: bool,
         enhancement_category: str,
         progress=gr.Progress()
@@ -111,7 +89,7 @@ def create_interface():
             except Exception as e:
                 enhancement_info = f"⚠️ Error en enhancement: {str(e)}"
 
-        # Resolución por aspect ratio
+        # Resolución
         aspect_ratios = {
             "1:1": (1024, 1024),
             "16:9": (1344, 768),
@@ -128,7 +106,6 @@ def create_interface():
             prompt=final_prompt,
             width=width,
             height=height,
-            image_input=input_image,
             progress_callback=progress
         )
 
@@ -139,8 +116,8 @@ def create_interface():
         try:
             if not prompt.strip():
                 return "⚠️ Prompt vacío"
-            # Extraer el prompt mejorado del status si es posible, o usar el original
-            enhanced = prompt  # en este flujo, el mejorado ya se usó
+            # Usa el prompt original o el mejorado (en este flujo, ya está mejorado)
+            enhanced = prompt
             success = agent.db.store_cache_result(prompt, enhanced, category, 0.95, "user_curated")
             return "✅ Prompt guardado como ejemplo de alta calidad." if success else "❌ Error al guardar."
         except Exception as e:
@@ -160,14 +137,14 @@ def create_interface():
     h1, h2, h3 { color: #ffffff !important; font-weight: 300 !important; }
     """
 
-    with gr.Blocks(css=custom_css, title="FLUX.1 + SEMANTIC AI", theme=gr.themes.Base()) as interface:
+    with gr.Blocks(css=custom_css, title="SDXL + SEMANTIC AI (HF Inference)", theme=gr.themes.Base()) as interface:
         gr.HTML("""
         <div style="text-align: center; padding: 20px; background: #000000;">
             <h1 style="color: #ffffff; font-size: 2.5em; font-weight: 300; margin: 0; letter-spacing: 2px;">
-                FLUX.1 + SEMANTIC AI
+                SDXL + SEMANTIC AI (HF Inference)
             </h1>
             <p style="color: #cccccc; font-size: 1.1em; margin: 10px 0 0 0;">
-                Generación con FLUX.1 vía Hugging Face Inference + búsqueda semántica en 100k prompts
+                Testing de prompts con generación gratuita (HF Pro)
             </p>
         </div>
         """)
@@ -190,8 +167,7 @@ def create_interface():
                         choices=["1:1", "16:9", "9:16", "4:3", "3:4", "21:9", "9:21"],
                         value="1:1"
                     )
-                    input_image = gr.Image(label="🖼️ Imagen (img2img)", type="filepath")
-                    generate_btn = gr.Button("🧠 GENERAR CON FLUX.1", variant="primary")
+                    generate_btn = gr.Button("🧠 GENERAR CON SDXL", variant="primary")
 
                 with gr.Column():
                     output_image = gr.Image(label="Imagen generada", type="filepath", height=500)
@@ -203,7 +179,7 @@ def create_interface():
         example_btn.click(get_semantic_example_wrapper, [enhancement_category, prompt_input], example_output)
         generate_btn.click(
             generate_wrapper,
-            [prompt_input, aspect_ratio, input_image, enable_semantic_enhancement, enhancement_category],
+            [prompt_input, aspect_ratio, enable_semantic_enhancement, enhancement_category],
             [output_image, status_output]
         )
         save_btn.click(save_high_quality_prompt, [prompt_input, enhancement_category, status_output], [save_status])