Update app.py

app.py

@@ -224,44 +224,53 @@ def display(x, y):
             leaderboard_df[column] = leaderboard_df[column].apply(remove_invalid_unicode)
 
     subset_df = leaderboard_df[COLS]
-    # Ensure the output directory exists
-    #output_dir = 'output'
-    #if not os.path.exists(output_dir):
-    #    os.makedirs(output_dir)
-#
-    ## Save JSON to a file in the output directory
-    #output_file_path = os.path.join(output_dir, 'output.json')
-    #with open(output_file_path, 'w') as file:
-    #    file.write(subset_df.to_json(orient='records'))
-
-    #first_50_rows = subset_df.head(50)
-    #print(first_50_rows.to_string())
-    #json_data = first_50_rows.to_json(orient='records')
-    #print(json_data)  # Print JSON representation
     return subset_df
 
 INTRODUCTION_TEXT = """
-This is a copied space from Open Source LLM leaderboard. Instead of displaying
-the results as table the space simply provides a gradio API interface to access
-the full leaderboard data easily.
-
-Example python on how to access the data:
-```python
+This is a copied space from Enterprise Scenarios Leaderboard. Instead of displaying
+the results as table this space was modified to simply provides a gradio API interface.
+Using the following python script below, users can access the full leaderboard data easily.
+Python on how to access the data:
+# Import dependencies
 from gradio_client import Client
-import json
-client = Client("https://felixz-open-llm-leaderboard.hf.space/")
 
-json_data = client.predict("","", api_name='/predict')
+# Initialize the Gradio client with the API URL
+client = Client("https://rodrigomasini-data-only-enterprise-scenarios-leaderboard.hf.space/")
+
+try:
+    # Perform the API call
+    response = client.predict("","", api_name='/predict')
+
+    # Check if response it's directly accessible
+    if len(response) > 0:
+        print("Response received!")
+        headers = response.get('headers', [])
+        data = response.get('data', [])
+
+        print(headers)
+
+        # Remove commenst if you want to download the dataset and save in csv format
+        # Specify the path to your CSV file
+        #csv_file_path = 'enterprise-scenarios-benchmark.csv'
+
+        # Open the CSV file for writing
+        #with open(csv_file_path, mode='w', newline='', encoding='utf-8') as file:
+        #    writer = csv.writer(file)
+
+            # Write the headers
+        #    writer.writerow(headers)
+
+            # Write the data
+        #    for row in data:
+        #        writer.writerow(row)
 
-with open(json_data, 'r') as file:
-    file_data = file.read()
+        #print(f"Results saved to {csv_file_path}")
 
-# Load the JSON data
-data = json.loads(file_data)
+    # If the above line prints a string that looks like JSON, you can parse it with json.loads(response)
+    # Otherwise, you might need to adjust based on the actual structure of `response`
 
-# Get the headers and the data
-headers = data['headers']
-data = data['data']
+except Exception as e:
+    print(f"An error occurred: {e}")
 ```
 
 """