Update app.py

app.py

@@ -3,6 +3,7 @@ from pydantic import BaseModel
 import json
 import gradio as gr
 import pandas as pd
+import io
 
 class ValidationStatus(BaseModel):
     is_valid: bool
@@ -47,14 +48,45 @@ def parse_execution_results_to_dataframe(execution_results):
         print(f"Error parsing results: {e}")
         return None
 
+def create_excel_file(df):
+    """Create an Excel file from DataFrame and return the file path"""
+    if df is None or df.empty:
+        return None
+    
+    try:
+        # Create a BytesIO buffer
+        output = io.BytesIO()
+        
+        # Write DataFrame to Excel
+        with pd.ExcelWriter(output, engine='openpyxl') as writer:
+            df.to_excel(writer, index=False, sheet_name='Query Results')
+            
+            # Get the worksheet
+            worksheet = writer.sheets['Query Results']
+            
+            # Auto-adjust column widths
+            for idx, col in enumerate(df.columns):
+                max_length = max(
+                    df[col].astype(str).apply(len).max(),
+                    len(str(col))
+                )
+                worksheet.column_dimensions[chr(65 + idx)].width = min(max_length + 2, 50)
+        
+        output.seek(0)
+        return output.getvalue()
+        
+    except Exception as e:
+        print(f"Error creating Excel file: {e}")
+        return None
+
 def generate_sql_query(api_key, user_query):
     """Generate SQL query from natural language using GROQ API"""
     try:
         if not api_key:
-            return "Error: Please enter your GROQ API key", "", "", "", None, ""
+            return "Error: Please enter your GROQ API key", "", "", "", None, None, ""
         
         if not user_query:
-            return "Error: Please enter a query description", "", "", "", None, ""
+            return "Error: Please enter a query description", "", "", "", None, None, ""
         
         client = Groq(api_key=api_key)
         
@@ -130,21 +162,25 @@ Optimization Notes:
         # Convert execution results to DataFrame
         results_df = parse_execution_results_to_dataframe(sql_query_generation.execution_results)
         
+        # Create Excel file
+        excel_file = create_excel_file(results_df) if results_df is not None else None
+        
         return (
             sql_query_generation.query,
             metadata,
             sql_query_generation.table_schema,
             sql_query_generation.sample_data,
             results_df,
+            excel_file,
             validation_text
         )
         
     except Exception as e:
         error_msg = f"Error: {str(e)}"
-        return error_msg, "", "", "", None, ""
+        return error_msg, "", "", "", None, None, ""
 
 # Create Gradio interface
-with gr.Blocks(title="SQL Query Generator", theme=gr.themes.Ocean()) as demo:
+with gr.Blocks(title="SQL Query Generator", theme=gr.themes.Soft()) as demo:
     gr.Markdown(
         """
         # 🗄️ Natural Language to SQL Query Generator
@@ -216,15 +252,24 @@ with gr.Blocks(title="SQL Query Generator", theme=gr.themes.Ocean()) as demo:
             )
     
     with gr.Row():
-        execution_output = gr.Dataframe(
-            label="📊 Execution Results",
-            headers=None,
-            datatype="str",
-            row_count=10,
-            col_count=None,
-            wrap=True,
-            interactive=False
-        )
+        with gr.Column():
+            execution_output = gr.Dataframe(
+                label="📊 Execution Results",
+                headers=None,
+                datatype="str",
+                row_count=10,
+                col_count=None,
+                wrap=True,
+                interactive=False
+            )
+    
+    with gr.Row():
+        with gr.Column():
+            download_btn = gr.File(
+                label="📥 Download Excel File",
+                type="binary",
+                interactive=False
+            )
     
     generate_btn.click(
         fn=generate_sql_query,
@@ -235,6 +280,7 @@ with gr.Blocks(title="SQL Query Generator", theme=gr.themes.Ocean()) as demo:
             schema_output,
             sample_data_output,
             execution_output,
+            download_btn,
             validation_output
         ]
     )
@@ -246,14 +292,16 @@ with gr.Blocks(title="SQL Query Generator", theme=gr.themes.Ocean()) as demo:
         1. Enter your GROQ API key (get one from [console.groq.com](https://console.groq.com))
         2. Type your natural language query description
         3. Click "Generate SQL Query" to see the results
+        4. Download the execution results as an Excel file
         
         The app will provide:
         - A validated SQL query
         - Table schema and sample data
         - Execution results in Excel-style table format
+        - Downloadable Excel file with results
         - Optimization suggestions
         """
     )
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch(share=False, server_name="0.0.0.0", server_port=7860)