Create app.py

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+from joblib import dump, load
+
+model_names = ['Logistic_Regression', 'LDA', 'QDA', 'Naive_Bayes', 'SVC']
+models = {}
+
+vectorizer = load('vectorizer.joblib')
+
+for name in model_names:
+  models[name] = load(name + '.joblib')
+
+
+def predict(text, method):
+
+  prediction = models[method].predict_proba(vectorizer.transform([text]).toarray())[0]
+
+
+  return {'Negative Comment':prediction[0], 'Positive Comment':prediction[1]}
+
+
+input_module1 = gr.Textbox(label='Review Comment')
+input_module2 = gr.Dropdown(choices=model_names, label = "method")
+
+output_module = gr.Label(num_top_classes=2,label = "Predicted Probabilities")
+
+gr.Interface(fn=predict, inputs=[input_module1,input_module2], outputs=output_module).launch(debug=True)