Update app.py

app.py

@@ -1,32 +1,21 @@
 import gradio as gr
-from datasets import load_dataset
+
 from transformers import pipeline
-from presentation import main_title, examples
 
-model_name= 'hackathon-pln-es/electricidad-base-generator-fake-news'
+pipe = pipeline("text-classification", model="hackathon-pln-es/electricidad-base-generator-fake-news")
+
+def predict(text):
+  return pipe(text)[0]["text-classification_text"]
+  
+title = "Detección de FakeNews en Español"
+
+iface = gr.Interface(
+  fn=predict, 
+  inputs=[gr.inputs.Textbox(label="text", lines=3)],
+  outputs='text',
+  title=title,
+  examples=[["España desaparece"]]
+)
 
-def clasificar_comentarios(comentario):
-    cls= pipeline("text-classification", model=model_name)
-    return cls(comentario)[0]['label']
+iface.launch(debug=True)
 
-if __name__ == "__main__":
-    gr.Interface(
-        fn=clasificar_comentarios,
-        inputs=[
-            gr.inputs.Textbox(
-                lines=10,
-                label="Comentario a analizar:",
-                placeholder="Ingrese el comentario por favor...",
-                optional=False,
-            ),
-        ],
-        outputs=[
-            gr.outputs.HTML(
-                label="Resultado:"
-            )
-        ],
-        description=main_title,
-        examples=examples,
-        theme="seafoam",
-        thumbnail="None",
-    ).launch()