Create app.py

app.py

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+import pickle
+import gradio as gr
+
+from sklearn.feature_extraction.text import TfidfVectorizer
+
+tfidf = TfidfVectorizer(stop_words='english')
+
+filename = 'movie_reviews_sentiment_analysis.pkl'
+#Load and test saved model
+loaded_model = pickle.load(open(filename, 'rb'))
+
+def movie_review(review):
+    new_review = tfidf.transform(review)
+    
+    result = loaded_model.predict(new_review)
+    
+    return result
+
+#create input and output objects
+#input object1
+input = gr.inputs.Textbox(label="Enter Review")
+
+#output object
+output = gr.outputs.Textbox(label= "Review Prediction") 
+
+#create interface
+gui = gr.Interface(fn=movie_review,
+                   inputs=[input],
+                   outputs=output).launch()