mentalwellness_space/agents/conversation_agent.py

from typing import Dict, List
from crewai import Agent
import logging
from utils.log_manager import LogManager

class ConversationAgent:
    """Agent specialized in therapeutic conversations"""
    
    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 the CrewAI agent
        self.agent = Agent(
            role="Therapeutic Conversation Specialist",
            goal="Guide therapeutic conversations and provide emotional support",
            backstory="""I am an AI agent specialized in therapeutic conversation techniques. 
            I use evidence-based approaches to provide emotional support and guidance while maintaining 
            appropriate boundaries and recognizing when to escalate to crisis intervention.""",
            verbose=True,
            allow_delegation=False,
            tools=[]  # Tools will be added as needed
        )
        
        self.logger.info("Conversation Agent initialized")
        
    def process_message(self, message: str, context: Dict = None) -> Dict:
        """Process a message and return a therapeutic response"""
        self.logger.info("Processing message")
        context = context or {}
        
        try:
            # For now, return a simple response since we haven't set up the LLM
            response = "I understand and I'm here to help. Could you tell me more about how you're feeling?"
            
            return {
                "message": response,
                "agent_type": "conversation",
                "task_type": "therapeutic_dialogue"
            }
            
        except Exception as 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",
                "task_type": "error_recovery"
            }
            
    def get_status(self) -> Dict:
        """Get the current status of the agent"""
        return {
            "type": "conversation",
            "ready": True,
            "tools_available": len(self.agent.tools)
        }