Create pages/3_Deployment.py

pages/3_Deployment.py

@@ -0,0 +1,31 @@
+import streamlit as st
+import pickle
+
+st.set_page_config(page_title="🎯 YouTube Comment Sentiment Predictor")
+
+st.title("🎯 Live Sentiment Classifier")
+
+# Load the complete pipeline (TF-IDF + Model)
+with open("text_classification.pkl", "rb") as f:
+    pipeline = pickle.load(f)
+
+# User input
+user_input = st.text_area("*Enter a YouTube comment to analyze:*")
+
+if st.button("Predict Sentiment"):
+    if user_input.strip():
+        prediction = pipeline.predict([user_input])[0]
+
+        st.markdown(f"## ✅ Prediction: `{prediction.capitalize()}`")
+
+        if prediction == "positive":
+            st.success("😊 Positive Sentiment")
+        elif prediction == "negative":
+            st.error("😠 Negative Sentiment")
+        else:
+            st.info("😐 Neutral Sentiment")
+    else:
+        st.warning("⚠️ Please enter a comment to analyze.")
+
+if st.button("Go to Model Page"):
+    st.switch_page("pages/2_Model_Training.py")