updated tabulate use

app.py

@@ -126,24 +126,26 @@ def process_data(file_obj, model_col: str, train_col: str, data_source: str) ->
         return f"An error occurred: {str(e)}", None, None, None, None, None, None
 
 
-def update_dropdowns(file_obj) -> Tuple[list, str]:
+def update_dropdowns(file_obj) -> Tuple[list, list, str]:
     """Updates dropdown choices based on the uploaded file."""
     if not file_obj:
-        return [], "No file uploaded."
+        return [], [], "No file uploaded."
 
-    file_path = file_obj.name
     try:
-        if file_path.endswith(".csv"):
-            df = pd.read_csv(file_path)
-        elif file_path.endswith(".json"):
-            df = pd.read_json(file_path)
+        file_name = getattr(file_obj, "name", "")
+        if file_name.endswith(".csv"):
+            df = pd.read_csv(file_obj)
+        elif file_name.endswith(".json"):
+            df = pd.read_json(file_obj)
         else:
-            return [], "Invalid file type."
+            return [], [], "Invalid file type. Only .csv and .json are supported."
+
         columns = df.columns.tolist()
         preview = df.head().to_markdown(index=False, numalign="left", stralign="left")
-        return columns, preview
+        return columns, columns, preview  # For two dropdowns + preview
+
     except Exception as e:
-        return [], f"Error reading file: {e}"
+        return [], [], f"Error reading file: {e}"
 
 
 def main_interface():
@@ -193,6 +195,14 @@ def main_interface():
         file_input = gr.File(
             file_types=[".csv", ".json"], label="Upload a CSV or JSON file"
         )
+        gr.Markdown(
+            """
+    📝 **Note:**  
+    - **Model Output Column**: Select the column that contains generated responses, completions, or predictions from your model.  
+    - **Training Data Column**: Select the column that may be used for future training or fine-tuning.  
+    This helps MADGuard simulate feedback loops by comparing lexical and semantic overlap between current output and future inputs.
+    """
+        )
 
         with gr.Row():
             model_col_input = gr.Dropdown(

requirements.txt

@@ -7,3 +7,4 @@ pandas
 scikit-learn
 sentence-transformers
 graphviz
+tabulate