Update app.py

app.py

@@ -312,6 +312,53 @@ def build_custom_index(symbols_df: pd.DataFrame, index_type: str, exchange: str)
     
     return {"index_value": round(index_value, 2), "components": prices, "weights": weights}
 
+# ========== Index Calculator functions ==========
+def calculate_indices(df: pd.DataFrame):
+    """
+    Compute Laspeyres, Paasche, and Fisher indices from input dataframe.
+    Expected columns: Item, p0, q0, p1, q1
+    """
+    if df.empty:
+        return "Please enter data.", 0, 0, 0, go.Figure()
+    
+    # Convert to numeric, handle errors
+    try:
+        df['p0'] = pd.to_numeric(df['p0'], errors='coerce')
+        df['q0'] = pd.to_numeric(df['q0'], errors='coerce')
+        df['p1'] = pd.to_numeric(df['p1'], errors='coerce')
+        df['q1'] = pd.to_numeric(df['q1'], errors='coerce')
+    except Exception as e:
+        return f"Error converting data: {e}", 0, 0, 0, go.Figure()
+    
+    # Drop rows with NaN
+    df = df.dropna()
+    if df.empty:
+        return "No valid numeric data.", 0, 0, 0, go.Figure()
+    
+    # Calculate sums
+    sum_p0q0 = (df['p0'] * df['q0']).sum()
+    sum_p1q0 = (df['p1'] * df['q0']).sum()
+    sum_p0q1 = (df['p0'] * df['q1']).sum()
+    sum_p1q1 = (df['p1'] * df['q1']).sum()
+    
+    # Avoid division by zero
+    if sum_p0q0 == 0 or sum_p0q1 == 0:
+        return "Base period expenditure is zero, cannot compute indices.", 0, 0, 0, go.Figure()
+    
+    laspeyres = (sum_p1q0 / sum_p0q0) * 100
+    paasche = (sum_p1q1 / sum_p0q1) * 100
+    fisher = np.sqrt(laspeyres * paasche)
+    
+    # Create comparison chart
+    fig = go.Figure(data=[
+        go.Bar(name='Index Value', x=['Laspeyres', 'Paasche', 'Fisher'], 
+               y=[laspeyres, paasche, fisher])
+    ])
+    fig.update_layout(title="Price Index Comparison", yaxis_title="Index Value")
+    
+    result_text = f"**Laspeyres Index:** {laspeyres:.2f}\n**Paasche Index:** {paasche:.2f}\n**Fisher Index:** {fisher:.2f}"
+    return result_text, laspeyres, paasche, fisher, fig
+
 # ========== Comparison UI functions ==========
 def create_comparison_ui():
     """Return UI components for index comparison tab."""
@@ -361,7 +408,6 @@ with gr.Blocks(title="AI-Powered Index Analyst with Real-Time Data") as demo:
     """)
     
     with gr.Tab("💬 Conversational Assistant"):
-        # Remove type="messages" – use classic list-of-lists format
         chat_history = gr.Chatbot(label="Conversation", height=400)
         msg = gr.Textbox(
             label="Ask about stocks or indices",
@@ -469,11 +515,39 @@ with gr.Blocks(title="AI-Powered Index Analyst with Real-Time Data") as demo:
         )
     
     with gr.Tab("📊 Index Calculator"):
-        # Simplified placeholder – you can expand with actual calculations later
         gr.Markdown("""
-        ### Index Calculator
-        This tab is under construction. For now, use the Conversational Assistant to ask about index calculations.
+        ### Price Index Calculator
+        Enter items with base period prices (p0) and quantities (q0), and current period prices (p1) and quantities (q1).
+        The calculator will compute Laspeyres, Paasche, and Fisher indices.
         """)
+        
+        index_df = gr.Dataframe(
+            headers=["Item", "p0", "q0", "p1", "q1"],
+            datatype=["str", "number", "number", "number", "number"],
+            row_count=5,
+            col_count=5,
+            value=[["Item1", 10, 100, 12, 110],
+                   ["Item2", 20, 50, 22, 55],
+                   ["Item3", 30, 30, 33, 32],
+                   ["Item4", 40, 20, 44, 18],
+                   ["Item5", 50, 10, 55, 9]]
+        )
+        
+        calc_index_btn = gr.Button("Calculate Indices", variant="primary")
+        
+        with gr.Row():
+            laspeyres_out = gr.Number(label="Laspeyres Index")
+            paasche_out = gr.Number(label="Paasche Index")
+            fisher_out = gr.Number(label="Fisher Index")
+        
+        index_results = gr.Textbox(label="Detailed Results", lines=4)
+        index_plot = gr.Plot(label="Index Comparison Chart")
+        
+        calc_index_btn.click(
+            calculate_indices,
+            inputs=[index_df],
+            outputs=[index_results, laspeyres_out, paasche_out, fisher_out, index_plot]
+        )
     
     with gr.Tab("🔄 Index Comparison"):
         comp_ui = create_comparison_ui()