Update app.py

app.py

@@ -3,9 +3,7 @@ from fastapi import FastAPI
 from pydantic import BaseModel
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 import torch
-from threading import Thread
 import uvicorn
-import requests
 
 # Configurar FastAPI
 app = FastAPI()
@@ -40,18 +38,16 @@ async def predict(input: TextInput):
     
     return {"entities": entities}
 
-# Iniciar el servidor de FastAPI en un hilo separado
-def start_api():
-    uvicorn.run(app, host="0.0.0.0", port=8000)
-
-api_thread = Thread(target=start_api, daemon=True)
-api_thread.start()
-
 # Configurar Gradio
 def predict_gradio(text):
-    response = requests.post("https://asmalljob-docker01.hf.space/predict", json={"text": text})  # Asegúrate de que esta URL es correcta
+    response = requests.post("http://localhost:8000/predict", json={"text": text})
     entities = response.json().get("entities", [])
     return entities
 
 demo = gr.Interface(fn=predict_gradio, inputs="text", outputs="json")
 demo.launch(share=True)
+
+# Iniciar el servidor de FastAPI
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)
+