Add app.py

app.py

@@ -0,0 +1,75 @@
+import spaces
+import gradio as gr
+import torch
+from diffusers import DiffusionPipeline
+from huggingface_hub import hf_hub_download
+
+# Cargamos el modelo base - usaremos SDXL como base
+# Podés cambiar esto por cualquier modelo de HuggingFace
+MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0"
+pipe = None
+
+def load_pipeline():
+    global pipe
+    if pipe is None:
+        pipe = DiffusionPipeline.from_pretrained(
+            MODEL_ID,
+            torch_dtype=torch.float16,
+            use_safetensors=True,
+            variant="fp16"
+        )
+    return pipe
+
+@spaces.GPU(duration=120)
+def generate(prompt, negative_prompt, steps, cfg_scale, width, height, seed):
+    global pipe
+    pipe = load_pipeline()
+    pipe = pipe.to("cuda")
+    
+    generator = torch.Generator("cuda").manual_seed(int(seed))
+    
+    images = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        num_inference_steps=int(steps),
+        guidance_scale=cfg_scale,
+        width=int(width),
+        height=int(height),
+        generator=generator
+    ).images
+    
+    pipe = pipe.to("cpu")  # Liberar VRAM despues de generar
+    torch.cuda.empty_cache()
+    
+    return images[0]
+
+with gr.Blocks(title="Studio Privado", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🎨 Studio Privado - Generador de Imágenes")
+    gr.Markdown("*Tus creaciones son privadas. Nadie más puede verlas.*")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(label="Prompt", placeholder="Describe lo que querés generar...", lines=3)
+            negative_prompt = gr.Textbox(label="Negative Prompt", value="blurry, low quality, bad anatomy", lines=2)
+            
+            with gr.Row():
+                steps = gr.Slider(10, 50, value=30, step=1, label="Pasos")
+                cfg = gr.Slider(1, 20, value=7.5, step=0.5, label="CFG Scale")
+            
+            with gr.Row():
+                width = gr.Slider(512, 1024, value=1024, step=64, label="Ancho")
+                height = gr.Slider(512, 1024, value=1024, step=64, label="Alto")
+            
+            seed = gr.Number(value=42, label="Seed (-1 para random)")
+            btn = gr.Button("🚀 Generar", variant="primary", size="lg")
+        
+        with gr.Column(scale=1):
+            output = gr.Image(label="Resultado", type="pil")
+    
+    btn.click(
+        fn=generate,
+        inputs=[prompt, negative_prompt, steps, cfg, width, height, seed],
+        outputs=output
+    )
+
+demo.launch()