Update app.py

app.py

@@ -631,7 +631,8 @@ with gr.Blocks() as demo:
             with gr.Column(scale=5):
                 gr.Textbox(value = portfolios_output, label="Generated Portfolios Example (Conservative, Growth, Balanced, & Agressive)", lines=40, interactive=False )
                     
-        
+    # Note: a portion of the Optimize Portfolio code was taken from Damian Boh open source code on Hugging Face and was rewritten for this application.    
+    
     with gr.Tab("Step 2: Optimize Portfolio"):
         gr.HTML(STEP3_TITLE)
         with gr.Blocks() as app:
@@ -706,7 +707,7 @@ with gr.Blocks() as demo:
                     expected_annual_return, annual_volatility, sharpe_ratio, fig_indiv_prices, fig_cum_returns])       
            
 
-    with gr.Tab("Step 3: Portfolio Analysis"): 
+    with gr.Tab("Step 3: Fine Tuning"): 
         gr.HTML(STEP2_TITLE)
         run_button_crewai = gr.Button(value="Run", variant="primary", scale=1)
         run_button_crewai.click(
@@ -716,18 +717,6 @@ with gr.Blocks() as demo:
         )
 
 
-        with gr.Row():        
-            fig_cum_returns_optimized = gr.Plot(label="Cumulative Returns of Optimized Portfolio (Starting Price of $100)")
-            weights_df = gr.DataFrame(label="Optimized Weights of Each Ticker")
-
-       
-        with gr.Row(visible=False):
-            fig_efficient_frontier = gr.Plot(label="Efficient Frontier")
-            fig_corr = gr.Plot(label="Correlation between Stocks")
-        
-        with gr.Row(visible=False):
-            fig_indiv_prices = gr.Plot(label="Price of Individual Stocks")
-            fig_cum_returns = gr.Plot(label="Cumulative Returns of Individual Stocks Starting with $100")
 
         
     # For future upgrade