Update app.py

app.py

@@ -65,6 +65,7 @@ def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
     profit_loss = final_value - initial_budget
     percentage_return = (profit_loss / initial_budget) * 100
 
+    # Create summary text
     results = f"""
     Ticker: {ticker}
     Trading Period: {start_date} to {end_date}
@@ -73,8 +74,13 @@ def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
     Total Profit/Loss: ${profit_loss:.2f}
     Percentage Return: {percentage_return:.2f}%
     """
-    
-    return plot_file, results
+
+    # Save results to a text file
+    results_file = "simulation_results.txt"
+    with open(results_file, "w") as f:
+        f.write(results)
+
+    return plot_file, results, results_file
 
 # Define Gradio interface components
 with gr.Blocks() as app:
@@ -96,6 +102,7 @@ with gr.Blocks() as app:
             with gr.Row():
                 portfolio_graph = gr.Image(label="Portfolio Value Over Time")
                 summary_text = gr.Textbox(label="Simulation Summary", lines=8)
+                download_button = gr.File(label="Download Results (.txt)")
 
         # Tab for Instructions
         with gr.Tab("Instructions"):
@@ -105,6 +112,7 @@ with gr.Blocks() as app:
             2. Specify the trading period (start and end dates).
             3. Select a stock ticker symbol (e.g., SPY, TSLA, GOOGL).
             4. Click "Run Simulation" to visualize the portfolio value over time and view a summary of results.
+            5. Download the results as a `.txt` file using the download button.
             
             ### Notes:
             - The 50-day and 150-day SMAs are used for buy and sell signals.
@@ -115,7 +123,7 @@ with gr.Blocks() as app:
     run_button.click(
         sma_crossover_strategy,
         inputs=[initial_budget, start_date, end_date, ticker],
-        outputs=[portfolio_graph, summary_text],
+        outputs=[portfolio_graph, summary_text, download_button],
     )
 
 # Launch the app