Update app.py

app.py

@@ -123,36 +123,55 @@ def process_nl_query(api_key, natural_query):
         output_text += "### Step 1: Understanding User Intent\n"
         output_text += f"**User Query:** {natural_query}\n\n"
         
-        # Call Groq API for SQL generation
+        # Call Groq API for SQL generation - FIXED: Added "JSON" to system message
         response = client.chat.completions.create(
-            model="moonshotai/kimi-k2-instruct-0905",
+            model="mixtral-8x7b-32768",
             messages=[
                 {
                     "role": "system",
-                    "content": "You are a SQL expert. Generate structured SQL queries from natural language descriptions with proper syntax validation and metadata. Use standard SQL syntax compatible with SQLite.",
+                    "content": """You are a SQL expert. Generate structured SQL queries from natural language descriptions with proper syntax validation and metadata. 
+                    
+                    Return your response in JSON format with the following structure:
+                    {
+                        "query": "SQL query string",
+                        "query_type": "SELECT/INSERT/UPDATE/DELETE",
+                        "tables_used": ["table1", "table2"],
+                        "estimated_complexity": "low/medium/high",
+                        "execution_notes": ["note1", "note2"],
+                        "validation_status": {
+                            "is_valid": true/false,
+                            "syntax_errors": []
+                        }
+                    }
+                    
+                    Use standard SQL syntax compatible with SQLite. Always use proper JOINs, WHERE clauses, and GROUP BY when needed.""",
+                },
+                {
+                    "role": "user", 
+                    "content": f"Convert this natural language query to SQL and return as JSON: {natural_query}"
                 },
-                {"role": "user", "content": natural_query},
             ],
             response_format={
                 "type": "json_object"
-            }
+            },
+            temperature=0.3
         )
         
         # Parse the response
         response_content = response.choices[0].message.content
         sql_data = json.loads(response_content)
         
-        # Try to map to our Pydantic model
+        # Try to map to our Pydantic model with better error handling
         try:
             sql_query_gen = SQLQueryGeneration(**sql_data)
-        except:
+        except Exception as e:
             # If response doesn't match exact schema, create it manually
             sql_query_gen = SQLQueryGeneration(
-                query=sql_data.get('query', ''),
+                query=sql_data.get('query', sql_data.get('sql_query', '')),
                 query_type=sql_data.get('query_type', 'SELECT'),
-                tables_used=sql_data.get('tables_used', []),
+                tables_used=sql_data.get('tables_used', sql_data.get('tables', [])),
                 estimated_complexity=sql_data.get('estimated_complexity', 'medium'),
-                execution_notes=sql_data.get('execution_notes', []),
+                execution_notes=sql_data.get('execution_notes', sql_data.get('notes', [])),
                 validation_status=ValidationStatus(
                     is_valid=sql_data.get('validation_status', {}).get('is_valid', True),
                     syntax_errors=sql_data.get('validation_status', {}).get('syntax_errors', [])
@@ -187,7 +206,10 @@ def process_nl_query(api_key, natural_query):
         else:
             output_text += "✅ **Query executed successfully!**\n\n"
             output_text += "**📈 SQL Execution Result:**\n\n"
-            output_text += result_df.to_markdown(index=False)
+            if len(result_df) > 0:
+                output_text += result_df.to_markdown(index=False)
+            else:
+                output_text += "*No results found matching the criteria*"
             result_table = result_df
         
         conn.close()