Update app.py

app.py

@@ -3,31 +3,38 @@ import joblib
 import re
 from bs4 import BeautifulSoup
 
-# Load saved models
+# Load models
 model = joblib.load("tag_predictor_model.pkl")
 vectorizer = joblib.load("tfidf_vectorizer.pkl")
 mlb = joblib.load("label_binarizer.pkl")
 
-# Clean user input
+# Text cleaning function
 def clean_text(text):
     soup = BeautifulSoup(text, "html.parser").get_text()
     text = re.sub(r'[^a-zA-Z\s]', '', text.lower())
     return " ".join([word for word in text.split() if len(word) > 2])
 
-# Streamlit UI
+# App layout
 st.title("🤖 Stack Overflow Tag Predictor")
-st.write("Enter a Stack Overflow question to predict relevant tags.")
+st.write("Enter a Stack Overflow question (title + body) to predict relevant tags.")
 
-# Input form
-title = st.text_input("Enter Question Title")
-body = st.text_area("Enter Question Body")
+# Input fields
+title = st.text_input("📌 Question Title")
+body = st.text_area("📝 Question Body")
 
+# Predict
 if st.button("Predict Tags"):
-    input_text = title + " " + body
-    cleaned = clean_text(input_text)
-    vectorized = vectorizer.transform([cleaned])
-    prediction = model.predict(vectorized)
-    predicted_tags = mlb.inverse_transform(prediction)
+    if not title and not body:
+        st.warning("Please enter either a title or body.")
+    else:
+        with st.spinner("Predicting..."):
+            input_text = title + " " + body
+            cleaned = clean_text(input_text)
+            vectorized = vectorizer.transform([cleaned])
+            probas = model.predict_proba(vectorized)
+            prediction = (probas >= 0.3).astype(int)
+            predicted_tags = mlb.inverse_transform(prediction)
+
+        st.subheader("📍 Predicted Tags:")
+        st.write(", ".join(predicted_tags[0]) if predicted_tags[0] else "No tags predicted.")
 
-    st.subheader("📌 Predicted Tags:")
-    st.write(", ".join(predicted_tags[0]) if predicted_tags else "No tags predicted.")