Fix Pydantic model handling with PrivateAttr

agents/conversation_agent.py

@@ -1,17 +1,23 @@
-from typing import Dict, List
+from typing import Dict, List, Optional
 from crewai import Agent, Task
 import logging
 from utils.log_manager import LogManager
+from pydantic import Field, BaseModel, PrivateAttr
 
 class ConversationAgent(Agent):
     """Agent specialized in therapeutic conversations"""
     
+    # Private attributes for non-pydantic fields
+    _log_manager: LogManager = PrivateAttr(default_factory=LogManager)
+    _logger: logging.Logger = PrivateAttr()
+    _model_config: Dict = PrivateAttr()
+    
     def __init__(self, model_config: Dict, **kwargs):
-        self.model_config = model_config
-        self.log_manager = LogManager()
-        self.logger = self.log_manager.get_agent_logger("conversation")
+        # Initialize private attributes
+        self._model_config = model_config
+        self._logger = self._log_manager.get_agent_logger("conversation")
         
-        # Initialize the CrewAI agent
+        # Initialize the CrewAI agent with required fields
         super().__init__(
             role="Therapeutic Conversation Specialist",
             goal="Guide therapeutic conversations and provide emotional support",
@@ -20,14 +26,15 @@ class ConversationAgent(Agent):
             appropriate boundaries and recognizing when to escalate to crisis intervention.""",
             verbose=True,
             allow_delegation=False,
-            tools=[]  # Tools will be added as needed
+            tools=[],  # Tools will be added as needed
+            **kwargs
         )
         
-        self.logger.info("Conversation Agent initialized")
+        self._logger.info("Conversation Agent initialized")
         
     def execute_task(self, task: Task) -> str:
         """Execute a task assigned to the agent"""
-        self.logger.info(f"Executing task: {task.description}")
+        self._logger.info(f"Executing task: {task.description}")
         
         try:
             # Process the task description as a message
@@ -35,16 +42,16 @@ class ConversationAgent(Agent):
             return result["message"]
             
         except Exception as e:
-            self.logger.error(f"Error executing task: {str(e)}")
+            self._logger.error(f"Error executing task: {str(e)}")
             return "I apologize, but I encountered an error processing your request."
         
     def process_message(self, message: str, context: Dict = None) -> Dict:
         """Process a message and return a therapeutic response"""
-        self.logger.info("Processing message")
+        self._logger.info("Processing message")
         context = context or {}
         
         try:
-            # For now, return a simple response since we haven't set up the LLM
+            # Generate therapeutic response
             response = self._generate_therapeutic_response(message, context)
             
             return {
@@ -54,7 +61,7 @@ class ConversationAgent(Agent):
             }
             
         except Exception as e:
-            self.logger.error(f"Error processing message: {str(e)}")
+            self._logger.error(f"Error processing message: {str(e)}")
             return {
                 "message": "I apologize, but I encountered an error. Let me try a different approach.",
                 "agent_type": "conversation",