Update agents.py

agents.py

@@ -615,7 +615,79 @@ Design practice questions:"""
         except Exception as e:
             logger.error(f"Q&A Design error: {e}")
             return ""
-    
+
+    def process(
+        self,
+        user_input: str,
+        conversation_history: str = "",
+        thinking_prompts: str = "",
+        tool_img_output: str = "",
+        tool_context: str = ""
+    ) -> str:
+        """
+        Unified process method - runs thinking agents based on active prompts.
+        
+        Args:
+            user_input: User's query
+            conversation_history: Formatted conversation history string
+            thinking_prompts: Newline-separated list of thinking prompts to activate
+            tool_img_output: HTML output from visualization tool
+            tool_context: Context from tool usage
+            
+        Returns:
+            str: Combined thinking context from all activated agents
+        """
+        thinking_outputs = []
+        
+        # Convert history string to list format for agent methods
+        history_list = []
+        if conversation_history and conversation_history != "No previous conversation":
+            for line in conversation_history.split('\n'):
+                if ':' in line:
+                    role, content = line.split(':', 1)
+                    history_list.append({'role': role.strip(), 'content': content.strip()})
+        
+        # Determine which thinking agents to run based on prompts
+        prompt_list = [p.strip() for p in thinking_prompts.split('\n') if p.strip()]
+        
+        # Math Thinking
+        if any('MATH' in p.upper() for p in prompt_list):
+            math_output = self.math_thinking(
+                user_query=user_input,
+                conversation_history=history_list,
+                tool_context=tool_context
+            )
+            if math_output:
+                thinking_outputs.append(f"[Mathematical Reasoning]\n{math_output}")
+        
+        # Q&A Design Thinking
+        if any('PRACTICE' in p.upper() or 'QUESTION' in p.upper() for p in prompt_list):
+            qa_output = self.qa_design_thinking(
+                user_query=user_input,
+                conversation_history=history_list,
+                tool_context=tool_context
+            )
+            if qa_output:
+                thinking_outputs.append(f"[Practice Question Design]\n{qa_output}")
+        
+        # General Reasoning (fallback or when no specific thinking needed)
+        if not thinking_outputs or any('REASONING' in p.upper() for p in prompt_list):
+            general_output = self.general_reasoning(
+                user_query=user_input,
+                conversation_history=history_list,
+                tool_context=tool_context
+            )
+            if general_output:
+                thinking_outputs.append(f"[General Reasoning]\n{general_output}")
+        
+        # Combine all thinking outputs
+        combined_thinking = "\n\n".join(thinking_outputs) if thinking_outputs else ""
+        
+        if combined_thinking:
+            logger.info(f"✓ Thinking complete: {len(combined_thinking)} chars from {len(thinking_outputs)} agents")
+        
+        return combined_thinking
+        
     def general_reasoning(
         self,
         user_query: str,