Update src/streamlit_app.py

src/streamlit_app.py

@@ -14,6 +14,15 @@ import seaborn as sns
 import matplotlib.pyplot as plt
 
 from alerts import compute_dynamic_risk,assign_dynamic_risk_level,trigger_alerts
+# Detect if running in Hugging Face Space
+IS_HF = os.getenv("SPACE_ID") or os.getenv("HF_SPACE_ID")
+
+# Optional: you can also check simulation flag if you imported from alerts.py
+if IS_HF:
+    st.warning("🚨 Email alerts are simulated in this Hugging Face Space (no real emails sent).")
+else:
+    st.info("📩 Real email alerts enabled (local environment).")
+    
 from evaluation import evaluate_model
 
 # Run evaluation on the scraped CSV folder
@@ -502,6 +511,8 @@ st.sidebar.info(f"Showing {len(df)} tweets")
 
 # ---------------- EMAIL ALERTS SECTION ---------------
 
+from alerts import IS_HF  # import the HF detection flag
+
 st.sidebar.header("📩 Email Alerts")
 num_tweets = st.sidebar.number_input(
     "Number of high-risk tweets to send", 
@@ -513,9 +524,12 @@ num_tweets = st.sidebar.number_input(
 send_button = st.sidebar.button("Send Alerts")
 
 if send_button:
-    st.info(f"Sending top {num_tweets} high-risk tweets via email...")
-    trigger_alerts(max_tweets=num_tweets)
-    st.success(f"✅ Alerts sent for top {num_tweets} tweets!")
+    if IS_HF:
+        st.warning(f"🚨 HF Space detected: Alerts are simulated. Would send top {num_tweets} tweets.")
+    else:
+        st.info(f"Sending top {num_tweets} high-risk tweets via email...")
+        trigger_alerts(max_tweets=num_tweets)
+        st.success(f"✅ Alerts sent for top {num_tweets} tweets!")
 
 # ------------------------
 # EXECUTIVE SUMMARY