Update frontend.py

frontend.py

@@ -72,6 +72,7 @@ def speak(text, lang='en'):
 
 tab1, tab2 = st.tabs(["🧠 Analyze Review", "📚 Bulk Reviews"])
 
+# === SINGLE REVIEW ANALYSIS ===
 # === SINGLE REVIEW ANALYSIS ===
 with tab1:
     st.title("📊 ChurnSight AI — Product Feedback Assistant")
@@ -80,8 +81,9 @@ with tab1:
     review = st.text_area("📝 Enter Customer Feedback", value=st.session_state.review, height=180)
     st.session_state.review = review
 
-    analyze = False  # ✅ define outside
+    analyze = False  # ✅ Flag to track if analyze was clicked
     col1, col2, col3 = st.columns(3)
+
     with col1:
         analyze = st.button("🔍 Analyze")
     with col2:
@@ -101,10 +103,7 @@ with tab1:
     if st.session_state.review and (analyze or st.session_state.trigger_example_analysis):
         with st.spinner("Analyzing feedback..."):
             try:
-                model_used = (
-                    None if sentiment_model == "Auto-detect"
-                    else sentiment_model
-                )
+                model_used = None if sentiment_model == "Auto-detect" else sentiment_model
                 payload = {
                     "text": st.session_state.review,
                     "model": model_used or "distilbert-base-uncased-finetuned-sst-2-english",
@@ -164,23 +163,33 @@ with tab1:
             suggestions = ["What made the user upset?", "Is this user likely to churn?"]
         else:
             suggestions = ["What are the key takeaways?", "Is there any concern raised?"]
+
         selected_q = st.selectbox("💡 Suggested Questions", ["Type your own..."] + suggestions)
         q_input = st.text_input("🔍 Your Question") if selected_q == "Type your own..." else selected_q
+
         if q_input:
-            follow_payload = {"text": st.session_state.review, "question": q_input, "verbosity": verbosity}
-            res = requests.post(f"{backend_url}/followup/", json=follow_payload, headers=headers)
-            if res.ok:
-                st.success(res.json().get("answer"))
-            else:
-                st.error("Failed to answer.")
+            try:
+                follow_payload = {
+                    "text": st.session_state.review,
+                    "question": q_input,
+                    "verbosity": verbosity
+                }
+                headers = {"x-api-key": st.session_state.get("api_token", "my-secret-key")}
+                res = requests.post(f"{backend_url}/followup/", json=follow_payload, headers=headers)
+                if res.ok:
+                    st.success(res.json().get("answer"))
+                else:
+                    st.error("Failed to get follow-up answer.")
+            except Exception as e:
+                st.error(f"⚠️ Follow-up error: {e}")
 
         if st.checkbox("📊 Show Churn Risk Trends"):
             try:
                 df = pd.DataFrame(st.session_state.churn_log)
                 df["date"] = pd.to_datetime(df["timestamp"]).dt.date
                 trend = df.groupby(["date", "churn_risk"]).size().unstack(fill_value=0).reset_index()
+                y_columns = [col for col in trend.columns if col != "date"]
                 st.markdown("#### 📅 Daily Churn Trend")
-                y_columns = [col for col in trend.columns if col not in ["date"]]
                 fig = px.bar(trend, x="date", y=y_columns, barmode="group")
                 st.plotly_chart(fig, use_container_width=True)
                 st.download_button("⬇️ Export Trend CSV", trend.to_csv(index=False), "churn_trend.csv")