Update app.py

app.py

@@ -3,6 +3,7 @@ from transformers import pipeline, set_seed
 import re
 import numpy as np
 import pandas as pd
+import os
 
 # Set a seed for reproducibility
 set_seed(42)
@@ -80,7 +81,7 @@ def extract_score(text):
         return min(max(score, 0), 100)
     return 0
 
-# Main benchmark function that runs all tests at once and saves results to a CSV file.
+# Main benchmark function that runs all tests at once and saves results automatically.
 def run_benchmark_all():
     results = []
     
@@ -125,21 +126,22 @@ def run_benchmark_all():
     # Create DataFrame and sort by Final Score.
     df = pd.DataFrame(results).sort_values(by="Final Score", ascending=False).reset_index(drop=True)
     
-    # Save results to CSV file.
+    # Automatically save results to a CSV file.
     csv_path = "benchmark_results.csv"
     df.to_csv(csv_path, index=False)
+    print(f"CSV file saved to {os.path.abspath(csv_path)}")
     
+    # Return both the DataFrame and the CSV file path for download.
     return gr.Dataframe(df), csv_path
 
-# Gradio UI using Blocks for a canvas layout.
+# Build the Gradio UI using Blocks for a canvas layout.
 with gr.Blocks(title="Premium Model Palindrome Benchmark") as demo:
     gr.Markdown("# Premium Model Palindrome Benchmark")
-    gr.Markdown("This benchmark runs automatically over 2 premium text-generation models across 5 languages (English, German, Spanish, French, Portuguese), and saves the results to a CSV file for later review.")
+    gr.Markdown("This benchmark runs automatically over 2 premium text-generation models across 5 languages (English, German, Spanish, French, Portuguese) and saves the results to a CSV file when done.")
     
     with gr.Row():
         run_button = gr.Button("Run All Benchmarks")
     
-    # The interface now outputs both a DataFrame and a File Download.
     output_table = gr.Dataframe(label="Benchmark Results")
     output_file = gr.File(label="Download CSV Results")