Update app.py

app.py

@@ -113,6 +113,9 @@ def generate_large_synthetic_data(description, columns, num_rows=1000, rows_per_
     
     for i in tqdm(range(num_iterations)):
         generated_data = generate_synthetic_data(description, columns)
+
+print("Generated Data:\n", generated_data)  # Add this line to debug
+
         if "Error" in generated_data:
             return generated_data
         df_synthetic = process_generated_data(generated_data)
@@ -124,9 +127,26 @@ def generate_large_synthetic_data(description, columns, num_rows=1000, rows_per_
     return pd.concat(data_frames, ignore_index=True)
 
 def process_generated_data(csv_data):
-    data = StringIO(csv_data)
-    df = pd.read_csv(data)
-    return df
+    try:
+        # Check if the data is not empty and has valid content
+        if not csv_data.strip():
+            raise ValueError("Generated data is empty.")
+
+        data = StringIO(csv_data)
+        df = pd.read_csv(data)
+        print("DataFrame Shape:", df.shape)
+        print("DataFrame Head:\n", df.head())
+
+
+        # Check if the DataFrame is empty
+        if df.empty:
+            raise ValueError("Generated DataFrame is empty.")
+
+        return df
+    except Exception as e:
+        st.error(f"Error processing generated data: {e}")
+        return pd.DataFrame()  # Return an empty DataFrame on error
+
 
 # Streamlit app interface
 st.title("Synthetic Data Generator")