update

app.py

@@ -17,8 +17,6 @@ if hf_token:
 else:
     logger.error("HF_TOKEN not found in environment variables")
 
-SAMPLE_NUM = 10
-
 # Set up logging
 logging.basicConfig(level=logging.INFO,
                     format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
@@ -79,19 +77,14 @@ def save_session_data(username, data):
         with open(temp_file_path, 'w') as f:
             f.write(json_data)
 
-        logger.info(f"Data uploaded to Hugging Face Data Space:\n{data}")
-
-        if data['current_index'] < SAMPLE_NUM:
-            pass 
-        else:
-            # Upload the file to a separate Hugging Face Space dedicated to data storage
-            api = HfApi()
-            api.upload_file(
-                path_or_fileobj=temp_file_path,
-                path_in_repo=f"session_data_pref/{file_name}",
-                repo_id="luulinh90s/Tabular-LLM-Study-Data",
-                repo_type="space",
-            )
+        # Upload the file to a separate Hugging Face Space dedicated to data storage
+        api = HfApi()
+        api.upload_file(
+            path_or_fileobj=temp_file_path,
+            path_in_repo=f"session_data_pref/{file_name}",
+            repo_id="luulinh90s/Tabular-LLM-Study-Data",
+            repo_type="space",
+        )
 
         # Remove the temporary file
         os.remove(temp_file_path)
@@ -158,14 +151,14 @@ def load_samples(methods):
 
 def select_balanced_samples(samples):
     try:
-        # Ensure we have at least N unique samples
+        # Ensure we have at least 10 unique samples
         unique_samples = list({(s['category'], s['file']) for s in samples})
 
-        if len(unique_samples) < SAMPLE_NUM:
+        if len(unique_samples) < 10:
             logger.warning(f"Not enough unique samples. Only {len(unique_samples)} available.")
             selected_samples = unique_samples
         else:
-            selected_samples = random.sample(unique_samples, SAMPLE_NUM)
+            selected_samples = random.sample(unique_samples, 10)
 
         logger.info(f"Unique sampled samples:\n{selected_samples}")