Create app.py

app.py

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+import streamlit as st
+import pickle
+import re
+import numpy as np
+
+# Streamlit page configuration
+st.set_page_config(page_title="Stack Overflow Tags Predictor", layout="centered")
+
+# ✅ Text preprocessing
+def clean_text(text):
+    text = re.sub(r"<.*?>", " ", text)  # Remove HTML tags
+    text = re.sub(r"\W", " ", text)     # Remove special characters
+    text = re.sub(r"\s+", " ", text.lower()).strip()  # Normalize whitespace and lowercase
+    return text
+
+# ✅ Load pickled model, vectorizer, and label binarizer
+@st.cache_resource
+def load_artifacts():
+    with open("model (1).pkl", "rb") as f:
+        model = pickle.load(f)
+    with open("tfidf (1).pkl", "rb") as f:
+        vectorizer = pickle.load(f)
+    with open("mlb (1).pkl", "rb") as f:
+        mlb = pickle.load(f)
+    return model, vectorizer, mlb
+
+# Load artifacts
+model, vectorizer, mlb = load_artifacts()
+
+# UI
+st.title("🔖 Stack Overflow Tags Predictor")
+st.markdown("Enter a question's *title* and *description*, and this app will suggest relevant tags.")
+
+# User Inputs
+title = st.text_input("📝 Question Title")
+body = st.text_area("📄 Question Description", height=200)
+
+# Prediction Button
+if st.button("🔍 Predict Tags"):
+    if not title.strip() or not body.strip():
+        st.warning("⚠ Please enter both a title and a description.")
+    else:
+        input_text = clean_text(title + " " + body)
+        X_input = vectorizer.transform([input_text])
+
+        try:
+            y_pred = model.predict(X_input)
+        except Exception as e:
+            st.error(f"❌ Prediction failed: {e}")
+            y_pred = None
+
+        if y_pred is not None:
+            predicted_tags = mlb.inverse_transform(y_pred)
+
+            if predicted_tags and predicted_tags[0]:
+                st.success("✅ Predicted Tags:")
+                st.write(", ".join(predicted_tags[0]))
+            else:
+                st.info("🤔 No tags predicted. Try refining your question.")