Update src/streamlit_app.py

src/streamlit_app.py

@@ -6,6 +6,7 @@ from dotenv import load_dotenv
 from google_search import google_search
 from mistral_llm import summarize_texts, detect_fake_news, analyze_sentiment
 
+# Load environment variables (e.g., Hugging Face token)
 load_dotenv(dotenv_path=os.path.join(os.path.dirname(__file__), '..', '.env'))
 
 st.set_page_config(page_title="🔥 Brand Crisis Detector", layout="wide", page_icon="🔥")
@@ -13,15 +14,15 @@ st.title("🔥 Real-Time Brand Crisis Detector")
 st.markdown("Analyze web content about your brand in real-time using AI ⚡")
 st.caption(f"🕒 Last refreshed: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
 
-query = st.text_input("🔍 Enter a brand or keyword", placeholder="e.g., Nvidia, Nestle, Jio", label_visibility="visible")
+query = st.text_input("🔍 Enter a brand or keyword", placeholder="e.g., Nvidia, Nestle, Jio")
 
 if st.button("Start Analysis 🚀") or (query and st.session_state.get("last_query") != query):
     st.session_state.last_query = query
 
     with st.spinner(f"🔎 Searching Google for **{query}**..."):
-        t1 = time.time()
+        start_time = time.time()
         articles = google_search(query, num_results=10)
-        fetch_time = round(time.time() - t1, 2)
+        fetch_time = round(time.time() - start_time, 2)
 
     if not articles:
         st.warning("❌ No results found. Try a different query.")
@@ -31,16 +32,16 @@ if st.button("Start Analysis 🚀") or (query and st.session_state.get("last_que
 
     titles = [a['title'] for a in articles]
     links = [a['link'] for a in articles]
-    contents = [a['snippet'] for a in articles]
+    snippets = [a['snippet'] for a in articles]
 
     with st.spinner("🧠 Summarizing, classifying, and detecting fake news..."):
-        t2 = time.time()
-        summaries = summarize_texts(contents)
-        sentiments = analyze_sentiment(contents)
-        fakeness = detect_fake_news(contents)
-        process_time = round(time.time() - t2, 2)
+        start_ai = time.time()
+        summaries = summarize_texts(snippets)
+        sentiments = analyze_sentiment(snippets)
+        fakeness = detect_fake_news(snippets)
+        ai_time = round(time.time() - start_ai, 2)
 
-    st.info(f"⏱️ AI analysis completed in {process_time} seconds.")
+    st.info(f"⏱️ AI analysis completed in {ai_time} seconds.")
 
     for i in range(len(articles)):
         with st.container():
@@ -50,3 +51,5 @@ if st.button("Start Analysis 🚀") or (query and st.session_state.get("last_que
             st.markdown(f"**🕵️ Fake News Score:** `{fakeness[i]}`")
             st.markdown(f"**📝 Summary:** {summaries[i]}")
             st.markdown("---")
+else:
+    st.info("Enter a brand or keyword and click 'Start Analysis 🚀' to begin.")