Elimina FastAPI y deja solo Gradio para compatibilidad con Spaces y @gradio/client

app.py

@@ -582,80 +582,6 @@ with gr.Blocks(title="Modelos Libres de IA", theme=gr.themes.Soft()) as demo:
             )
 
 # Configuración para Hugging Face Spaces
+# Elimina FastAPI y usa solo Gradio
 if __name__ == "__main__":
-    # Crear la aplicación FastAPI
-    app = FastAPI(title="NTIA Space API")
-    
-    # Configurar CORS
-    app.add_middleware(
-        CORSMiddleware,
-        allow_origins=["*"],
-        allow_credentials=True,
-        allow_methods=["*"],
-        allow_headers=["*"],
-    )
-    
-    # Endpoints API
-    @app.get("/models")
-    async def api_models():
-        try:
-            return {
-                "text": [{"id": k, "label": v} for k, v in MODELS["text"].items()],
-                "image": [{"id": k, "label": v} for k, v in MODELS["image"].items()],
-                "video": [{"id": k, "label": v} for k, v in MODELS["video"].items()],
-                "chat": [{"id": k, "label": v} for k, v in MODELS["chat"].items()]
-            }
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=str(e))
-
-    @app.post("/generate_text")
-    async def api_generate_text(request: TextRequest):
-        try:
-            result = generate_text(request.prompt, request.model_name, request.max_length)
-            return {"response": result}
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=str(e))
-
-    @app.post("/generate_image")
-    async def api_generate_image(request: ImageRequest):
-        try:
-            result = generate_image(request.prompt, request.model_name, request.num_inference_steps)
-            
-            if isinstance(result, str) and result.startswith("Error"):
-                raise HTTPException(status_code=500, detail=result)
-            
-            # Convertir PIL Image a base64
-            buffer = BytesIO()
-            result.save(buffer, format="PNG")
-            img_str = base64.b64encode(buffer.getvalue()).decode()
-            
-            return {"image": f"data:image/png;base64,{img_str}"}
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=str(e))
-
-    @app.post("/generate_video")
-    async def api_generate_video(request: VideoRequest):
-        try:
-            result = generate_video(request.prompt, request.model_name, request.num_frames, request.num_inference_steps)
-            
-            if isinstance(result, str) and result.startswith("Error"):
-                raise HTTPException(status_code=500, detail=result)
-            
-            return {"video": "video_data_placeholder", "frames": len(result) if isinstance(result, list) else 0}
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=str(e))
-
-    @app.post("/chat")
-    async def api_chat(request: ChatRequest):
-        try:
-            result = chat_with_model(request.message, request.history, request.model_name)
-            return {"response": result[-1]["content"] if result else "No response"}
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=str(e))
-    
-    # Montar Gradio en FastAPI
-    app = gr.mount_gradio_app(app, demo, path="/")
-    
-    # Lanzar con uvicorn
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860) 
+    demo.launch()