added together ai agent

python_code_executor_service.py

@@ -160,51 +160,104 @@ class PythonExecutor:
         # Return a dummy URL
         return f"https://example.com/charts/{filename}"
     
-    def process_response(self, response: CsvChatResult) -> str:
-        """
-        Process the CsvChatResult response and generate formatted output
+    # def process_response(self, response: CsvChatResult) -> str:
+    #     """
+    #     Process the CsvChatResult response and generate formatted output
         
-        Args:
-            response (CsvChatResult): Response from CSV analysis
+    #     Args:
+    #         response (CsvChatResult): Response from CSV analysis
             
-        Returns:
-            str: Formatted output with results and dummy image URLs
-        """
-        output_parts = []
+    #     Returns:
+    #         str: Formatted output with results and dummy image URLs
+    #     """
+    #     output_parts = []
         
-        # Add casual response
-        output_parts.append(response.casual_response)
+    #     # Add casual response
+    #     output_parts.append(response.casual_response)
         
-        # Process analysis operations
-        for operation in response.analysis_operations:
-            # Execute the code
-            result = self.execute_code(operation.code.code)
+    #     # Process analysis operations
+    #     for operation in response.analysis_operations:
+    #         # Execute the code
+    #         result = self.execute_code(operation.code.code)
             
-            # Add operation description
-            output_parts.append(f"\n{operation.description}:")
+    #         # Add operation description
+    #         output_parts.append(f"\n{operation.description}:")
             
-            # Add output or error
-            if result['error']:
-                output_parts.append(f"Error: {result['error']['message']}")
-            else:
-                output_parts.append(result['output'].strip())
+    #         # Add output or error
+    #         if result['error']:
+    #             output_parts.append(f"Error: {result['error']['message']}")
+    #         else:
+    #             output_parts.append(result['output'].strip())
         
-        # Process charts if they exist
-        if response.charts:
-            output_parts.append("\nVisualizations:")
+    #     # Process charts if they exist
+    #     if response.charts:
+    #         output_parts.append("\nVisualizations:")
             
-            for chart in response.charts:
-                if chart.code:
-                    # Execute the chart code
-                    result = self.execute_code(chart.code)
+    #         for chart in response.charts:
+    #             if chart.code:
+    #                 # Execute the chart code
+    #                 result = self.execute_code(chart.code)
                     
-                    if result['plots']:
-                        # Save each generated plot and get dummy URL
-                        for plot_data in result['plots']:
-                            dummy_url = self.save_plot_dummy(plot_data, chart.image_description)
-                            output_parts.append(f"\n{chart.image_description}")
-                            output_parts.append(f"![{chart.image_description}]({dummy_url})")
-                    elif result['error']:
-                        output_parts.append(f"\nError generating {chart.image_description}: {result['error']['message']}")
-        
-        return "\n".join(output_parts)
+    #                 if result['plots']:
+    #                     # Save each generated plot and get dummy URL
+    #                     for plot_data in result['plots']:
+    #                         dummy_url = self.save_plot_dummy(plot_data, chart.image_description)
+    #                         output_parts.append(f"\n{chart.image_description}")
+    #                         output_parts.append(f"![{chart.image_description}]({dummy_url})")
+    #                 elif result['error']:
+    #                     output_parts.append(f"\nError generating {chart.image_description}: {result['error']['message']}")
+        
+    #     return "\n".join(output_parts)
+    
+    def process_response(self, response: CsvChatResult) -> str:
+     """
+     Process the CsvChatResult response and generate formatted output
+     with markdown code blocks for structured data.
+     """
+     output_parts = []
+    
+     # Add casual response
+     output_parts.append(response.casual_response)
+    
+ # Process analysis operations
+     for operation in response.analysis_operations:
+         # Execute the code
+         result = self.execute_code(operation.code.code)
+        
+         # Add operation description
+         output_parts.append(f"\n{operation.description}:")
+        
+         # Add output or error with markdown wrapping
+         if result['error']:
+             output_parts.append("```python\n" + f"Error: {result['error']['message']}" + "\n```")
+         else:
+            output = result['output'].strip()
+            if self._looks_like_structured_data(output):  # New helper method
+                output_parts.append("```python\n" + output + "\n```")
+            else:
+                output_parts.append(output)
+    
+     # Process charts remains the same
+     if response.charts:
+        output_parts.append("\nVisualizations:")
+        for chart in response.charts:
+            if chart.code:
+                result = self.execute_code(chart.code)
+                if result['plots']:
+                    for plot_data in result['plots']:
+                        dummy_url = self.save_plot_dummy(plot_data, chart.image_description)
+                        output_parts.append(f"\n{chart.image_description}")
+                        output_parts.append(f"![{chart.image_description}]({dummy_url})")
+                elif result['error']:
+                    output_parts.append("```python\n" + f"Error generating {chart.image_description}: {result['error']['message']}" + "\n```")
+    
+     return "\n".join(output_parts)
+
+    def _looks_like_structured_data(self, output: str) -> bool:
+     """Helper to detect JSON-like or array-like output"""
+     output = output.strip()
+     return (
+        output.startswith('{') and output.endswith('}') or  # JSON object
+        output.startswith('[') and output.endswith(']') or  # Array
+        '\n' in output and '=' in output  # Python console output
+     )