Create app.py

app.py

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+import gradio as gr
+from sklearn.feature_extraction.text import CountVectorizer
+import joblib
+
+vectorizer = CountVectorizer()
+nb_classifier = joblib.load('./nb_classifier.pkl')
+def classify(text):
+  corpus=[text]
+  features = vectorizer.transform(corpus)
+  features = features.toarray()
+  prediction = nb_classifier.predict(features)
+  if(prediction == 1):
+     return "Fake News"
+  else:
+     return "Not Fake News"
+
+GUI = gr.Interface(inputs = ['text'], outputs = ['text'], fn = classify, title = "Fake News Detection System")
+GUI.launch()