Update app.py

app.py

@@ -22,6 +22,7 @@ from sklearn.linear_model import LinearRegression
 from sklearn.tree import DecisionTreeRegressor
 from sklearn.ensemble import RandomForestRegressor
 from sklearn.svm import SVR
+from sklearn.svm import SVC
 
 # Metrics
 from sklearn.metrics import (
@@ -68,6 +69,25 @@ def load_boston():
 # MAIN FUNCTION
 # =====================================================
 
+
+def save_report(results_df, best_model, task_type, dataset_name):
+    file_path = "model_report.txt"
+
+    with open(file_path, "w", encoding="utf-8") as f:
+        f.write("AI Model Comparison Report\n")
+        f.write("=" * 40 + "\n\n")
+
+        f.write(f"Task Type: {task_type}\n")
+        f.write(f"Dataset: {dataset_name}\n\n")
+
+        f.write("Results:\n")
+        f.write(results_df.to_string(index=False))
+        f.write("\n\n")
+
+        f.write(f"Best Model: {best_model}\n")
+
+    return file_path
+    
 def run_models(task_type, dataset_name):
 
     # =========================
@@ -194,7 +214,8 @@ def run_models(task_type, dataset_name):
             "Model"
         ]
 
-    return results_df, f"🏆 Best Model: {best_model}"
+    report_file = save_report(results_df, best_model, task_type, dataset_name)
+    return results_df, f"🏆 Best Model: {best_model}", report_file
 
 
 # =====================================================
@@ -262,10 +283,12 @@ with gr.Blocks() as demo:
 
     output_text = gr.Textbox()
 
+    output_file = gr.File(label="Download Report")
+
     run_button.click(
-        fn=run_models,
-        inputs=[task_type, dataset_name],
-        outputs=[output_table, output_text]
+    fn=run_models,
+    inputs=[task_type, dataset_name],
+    outputs=[output_table, output_text, output_file]
     )
 
 demo.launch()