Update eb_agent_module.py

eb_agent_module.py

@@ -338,7 +338,10 @@ class EmployerBrandingAgent:
 
         self.chat_history: List[Dict[str, str]] = []
         self.is_ready = False
-        
+
+        # Create charts directory
+        self.charts_dir = "./charts"
+        os.makedirs(self.charts_dir, exist_ok=True)        
         
         # Initialize PandasAI Agent
         self.pandas_agent = None
@@ -363,10 +366,14 @@ class EmployerBrandingAgent:
             
             # Set PandasAI configuration
             pai.config.set({
-                "llm": llm,
-                "temperature": 0.7,
-                "verbose": True,
-                "enable_cache": True
+            "llm": llm,
+            "temperature": 0.7,
+            "verbose": True,
+            "enable_cache": True,
+            "save_charts": True,  # Enable chart saving
+            "save_charts_path": "./charts",  # Directory to save charts
+            "open_charts": False,  # Don't auto-open charts in browser
+            "custom_whitelisted_dependencies": ["matplotlib", "seaborn", "plotly"]  # Allow plotting libraries
             })
             
             # Store dataframes for chat queries (we'll use them directly)
@@ -490,7 +497,7 @@ class EmployerBrandingAgent:
         ## Your Enhanced Capabilities:
         You now have advanced data analysis capabilities through PandasAI integration, allowing you to:
         - Directly query and analyze DataFrames with natural language
-        - Generate charts and visualizations automatically
+        - Generate charts and visualizations automatically (ALWAYS create charts when data visualization would be helpful)
         - Perform complex statistical analysis on LinkedIn employer branding data
         - Handle multi-DataFrame queries and joins seamlessly
         
@@ -587,15 +594,35 @@ class EmployerBrandingAgent:
                 dfs = list(self.pandas_dfs.values())
                 pandas_response = pai.chat(query, *dfs)
             
-            # Check if response is meaningful
-            if pandas_response and str(pandas_response).strip():
-                return str(pandas_response), True
-            else:
-                return "I couldn't generate a meaningful analysis for this query.", False
-                
-        except Exception as e:
-            logging.error(f"Error in PandasAI processing: {e}", exc_info=True)
-            return f"I encountered an error while analyzing the data: {str(e)}", False
+        # Handle different response types (text, charts, etc.)
+        response_text = ""
+        chart_info = ""
+        
+        # Check if a chart was generated
+        import os
+        charts_dir = "./charts"
+        if os.path.exists(charts_dir):
+            chart_files = [f for f in os.listdir(charts_dir) if f.endswith(('.png', '.jpg', '.jpeg', '.svg'))]
+            if chart_files:
+                # Get the most recent chart file
+                chart_files.sort(key=lambda x: os.path.getmtime(os.path.join(charts_dir, x)), reverse=True)
+                latest_chart = chart_files[0]
+                chart_path = os.path.join(charts_dir, latest_chart)
+                chart_info = f"\n\n📊 **Chart Generated**: {latest_chart}\nChart saved at: {chart_path}"
+                logging.info(f"Chart generated: {chart_path}")
+        
+        # Combine text response with chart info
+        if pandas_response and str(pandas_response).strip():
+            response_text = str(pandas_response).strip()
+        else:
+            response_text = "Analysis completed"
+        
+        final_response = response_text + chart_info
+        return final_response, True
+        
+    except Exception as e:
+        logging.error(f"Error in PandasAI processing: {e}", exc_info=True)
+        return f"I encountered an error while analyzing the data: {str(e)}", False
 
     async def _generate_enhanced_response(self, query: str, pandas_result: str = "", query_type: str = "general") -> str:
         """Generate enhanced response combining PandasAI results with RAG context"""