Update app.py

app.py

@@ -0,0 +1,47 @@
+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()