Update app.py

app.py

@@ -238,6 +238,44 @@ def handle_custom_question(question):
         buf.seek(0)
         return "Here is the forecasted revenue for the next 2 quarters.", Image.open(buf)
 
+    if "financial health" in question.lower():
+        df["year"] = df["ddate"].dt.year
+        latest_year = df["year"].max()
+
+        # Extract required metrics
+        revenue = df[df["tlabel"].str.contains("revenue", case=False, na=False)]
+        net_income = df[df["tlabel"].str.contains("net income", case=False, na=False)]
+        assets = df[df["tlabel"].str.contains("total assets", case=False, na=False)]
+        liabilities = df[df["tlabel"].str.contains("total liabilities", case=False, na=False)]
+        equity = df[df["tlabel"].str.contains("equity", case=False, na=False)]
+
+        rev_latest = revenue[revenue["year"] == latest_year]["value"].sum()
+        net_income_latest = net_income[net_income["year"] == latest_year]["value"].sum()
+        assets_latest = assets[assets["year"] == latest_year]["value"].sum()
+        liabilities_latest = liabilities[liabilities["year"] == latest_year]["value"].sum()
+        equity_latest = equity[equity["year"] == latest_year]["value"].sum()
+
+        # Calculate ratios
+        profit_margin = (net_income_latest / rev_latest * 100) if rev_latest > 0 else 0
+        debt_to_equity = (liabilities_latest / equity_latest) if equity_latest > 0 else 0
+        roa = (net_income_latest / assets_latest * 100) if assets_latest > 0 else 0
+
+        # Classification logic
+        if profit_margin > 15 and debt_to_equity < 1 and roa > 5:
+            health = "Healthy"
+        elif profit_margin > 5 and debt_to_equity < 2:
+            health = "Watchlist"
+        else:
+            health = "Risky"
+
+        return (
+            f"For {latest_year}, Apple is classified as **{health}** based on:\n"
+            f"- Profit Margin: {profit_margin:.2f}%\n"
+            f"- Debt-to-Equity: {debt_to_equity:.2f}\n"
+            f"- Return on Assets (ROA): {roa:.2f}%",
+            None
+        )
+        
     return None, None
 
 def ask_question(history, question):