Update app.py

app.py

@@ -16,30 +16,26 @@ model_path = hf_hub_download(
 # Cargar el modelo usando la ruta absoluta
 model = joblib.load(model_path)
 
-# --- Funciones ---
+# Single prediction
 def predict_single(text):
     return model.predict([text])[0]
 
+single_interface = gr.Interface(
+    fn=predict_single,
+    inputs=gr.Textbox(label="Input text"),
+    outputs=gr.Textbox(label="Predicted category")
+)
+
+# Batch prediction
 def predict_batch(texts):
     return [model.predict([t])[0] for t in texts]
 
-# --- Blocks ---
-with gr.Blocks() as demo:
-    # Endpoint single prediction
-    single_input = gr.Textbox(label="Input text")
-    single_output = gr.Textbox(label="Predicted category")
-    single_btn = gr.Button("Predict")
-    single_btn.click(predict_single, inputs=single_input, outputs=single_output)
-
-    # Endpoint batch prediction
-    batch_input = gr.Textbox(label="Batch texts (comma separated)")
-    batch_output = gr.Textbox(label="Predictions (comma separated)")
-    batch_btn = gr.Button("Predict Batch")
-    batch_btn.click(
-        lambda x: predict_batch(x.split(",")),
-        inputs=batch_input,
-        outputs=batch_output
-    )
-
-# --- Lanzar en API mode ---
-demo.launch(server_name="0.0.0.0", server_port=7860, api_mode=True)
+batch_interface = gr.Interface(
+    fn=predict_batch,
+    inputs=gr.Textbox(label="Batch texts (comma separated)"),
+    outputs=gr.Textbox(label="Predictions (comma separated)")
+)
+
+# Lanzar ambos
+single_interface.launch(server_name="0.0.0.0", server_port=7860, share=True)
+batch_interface.launch(server_name="0.0.0.0", server_port=7861, share=True)