Create app.py

app.py

@@ -0,0 +1,27 @@
+import joblib
+import gradio as gr
+
+# Load the model and vectorizer
+model = joblib.load('scripts/modeli/logistic_regression_model.pkl')
+vectorizer = joblib.load('scripts/modeli/tfidf_vectorizer.pkl')
+
+def predict_review_rating(review_text):
+    # Transform the review text using the loaded vectorizer
+    review_tfidf = vectorizer.transform([review_text])
+    
+    # Make prediction
+    prediction = model.predict(review_tfidf)
+    
+    return prediction[0]
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=predict_review_rating,
+    inputs=gr.Textbox(label="Enter Review Text"),
+    outputs=gr.Textbox(label="Predicted Rating"),
+    title="TripAdvisor Review Rating Predictor",
+    description="Enter a TripAdvisor review and get the predicted rating (1-5)."
+)
+
+# Launch the interface
+interface.launch()