Create app.py

app.py

@@ -0,0 +1,15 @@
+import gradio as gr
+def prediction(text):
+  text_processed=(preprocess_nltk(text))
+  ans=pipe2.predict([text_processed])
+  classes = ['Irrelevant', 'Natural', 'Negative', 'Positive']
+  predicted_label = ans[0]
+  return(f"The above text is:{classes[predicted_label]}" )
+
+pre = gr.Interface(
+    fn=prediction,
+    inputs=["text"],
+    outputs=[gr.Textbox(label="Prediction", lines=3)],
+)
+
+pre.launch()