Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,28 +1,33 @@
 #streamlit_app.py
+# streamlit_app.py
 import streamlit as st
 import pandas as pd
 import os
-import io
-import logging
-from contextlib import redirect_stdout
+import json
+import plotly.express as px
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+from datetime import datetime, timedelta
+import numpy as np
+import time
+import re
+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")
+
 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).")
 
-# Capture stdout and logs
-log_stream = io.StringIO()
-logging.basicConfig(stream=log_stream, level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
-
 from evaluation import evaluate_model
 
-# Redirect print statements to log_stream
-with redirect_stdout(log_stream):
-    evaluate_model("drug_analysis_data_3months")
+# Run evaluation on the scraped CSV folder (no logs shown)
+evaluate_model("drug_analysis_data_3months")
 
 st.set_page_config(
     page_title="Twitter Drug Crime Monitoring",
@@ -30,9 +35,6 @@ st.set_page_config(
     initial_sidebar_state="expanded"
 )
 
-st.subheader("📊 Scraper Evaluation Logs")
-st.text(log_stream.getvalue())
-
 
 # Import NLTK with error handling
 import nltk