Update app.py

app.py

@@ -1,47 +1,42 @@
 import numpy as np
 import pandas as pd
 import streamlit as st
-
-import gradio as gr
-import joblib
-
-# Load artifacts using joblib
-vectorizer = joblib.load("tfidf_vectorizer(1).pkl")
-model = joblib.load("model(1).pkl")
-mlb = joblib.load("mlb.pkl")
-
-# Define prediction function
-
-def predict_tags(title, description):
-    try:
-        print(f"[DEBUG] Title: {repr(title)}")
-        print(f"[DEBUG] Description: {repr(description)}")
-        
-        if not title.strip() or not description.strip():
-            return "⚠️ Please enter both title and description."
-
-        input_text = title + " " + description
-        input_vector = vectorizer.transform([input_text])
-        prediction = model.predict(input_vector)
-        predicted_tags = mlb.inverse_transform(prediction)
-
-        if predicted_tags and predicted_tags[0]:
-            return "✅ Predicted Tags: " + ", ".join(predicted_tags[0])
-        else:
-            return "ℹ️ No tags predicted. Try refining your question."
-
-    except Exception as e:
-        return f"❌ Error: {str(e)}"
-
-# Gradio app
-iface = gr.Interface(
-    fn=predict_tags,
-    inputs=[
-        gr.Textbox(label="Enter Question Title", type="text"),
-        gr.Textbox(label="Enter Question Description", lines=4, type="text")
-    ],
-    outputs="text",
-    title="🔖 Stack Overflow Tags Predictor",
-    description="Enter a question's title and description to get tag suggestions."
-)
-iface.launch()
+import pickle
+
+# Load models using pickle
+with open("tfidf_vectorizer(1).pkl", "rb") as f:
+    vectorizer = pickle.load(f)
+
+with open("model(1).pkl", "rb") as f:
+    model = pickle.load(f)
+
+with open("mlb.pkl", "rb") as f:
+    mlb = pickle.load(f)
+
+# Streamlit App UI
+st.set_page_config(page_title="🔖 Stack Overflow Tags Predictor", layout="centered")
+
+st.title("🔖 Stack Overflow Tags Predictor")
+st.write("Enter the question's title and description to get suggested tags.")
+
+# Input fields
+title = st.text_input("Enter Question Title:")
+description = st.text_area("Enter Question Description:")
+
+# Prediction logic
+if st.button("Predict Tags"):
+    if not title.strip() or not description.strip():
+        st.warning("⚠️ Please enter both title and description.")
+    else:
+        try:
+            input_text = title + " " + description
+            input_vector = vectorizer.transform([input_text])
+            prediction = model.predict(input_vector)
+            predicted_tags = mlb.inverse_transform(prediction)
+
+            if predicted_tags and predicted_tags[0]:
+                st.success("✅ Predicted Tags: " + ", ".join(predicted_tags[0]))
+            else:
+                st.info("ℹ️ No tags predicted. Try refining your question.")
+        except Exception as e:
+            st.error(f"❌ Error: {str(e)}")