Update app.py

app.py

@@ -383,7 +383,7 @@ elif activities=="News Sentiment":
                             # url6
                            ])
     docs = loader.load()
-    st.write(docs)
+    # st.write(docs)
     st.divider()
 
     llm_prompt_template = """You are an expert Stock Market Trader specializing in stock market insights derived from fundamental analysis, analytical trends, profit-based evaluations, news indicators from different sites and detailed company financials. You will receive one or more news articles from TradingView’s India stock news feed. For each article, perform the following tasks:
@@ -425,6 +425,45 @@ elif activities=="News Sentiment":
     
     # res = stuff_chain.invoke(docs)
     res = stuff_chain.invoke({"input_documents": docs})
-    st.write(res["output_text"])
+    raw_text = res["output_text"]
+    # Remove markdown code block delimiters if present
+    if raw_text.startswith("```json"):
+        raw_text = raw_text[len("```json"):]
+    
+    if raw_text.endswith("```"):
+        raw_text = raw_text[:-3]
+    
+    # Also strip leading/trailing whitespace/newlines
+    raw_text = raw_text.strip()
+
+    # Parse JSON
+    parsed_data = json.loads(raw_text)
+    top_picks = parsed_data.get("top_picks", [])
+    
+    st.set_page_config(page_title="Stock Insights", layout="wide")
+    st.title("📊 Weekly Stock Insights from News")
+    
+    # Layout
+    for stock in top_picks:
+        col1, col2 = st.columns([3, 1])
+        with col1:
+            st.subheader(f"{stock['company']} ({stock['ticker']})")
+            st.markdown(f"**📰 Critical News:** {stock['critical_news']}")
+            st.markdown(f"**📈 Impact Summary:** {stock['impact_summary']}")
+            st.markdown(f"**💡 Reason for Top Pick:** {stock['reason']}")
+        with col2:
+            sentiment_color = {
+                "Bullish": "🟢 Bullish",
+                "Bearish": "🔴 Bearish",
+                "Neutral": "🟡 Neutral"
+            }.get(stock["sentiment"], stock["sentiment"])
+            st.metric(label="Sentiment", value=sentiment_color)
+            st.markdown(f"**🚦 Action:** `{stock['action']}`")
+    
+    st.divider()
+    st.caption("Data analyzed using LLM from TradingView India news feed.")
+
+
+
 else:
     pass