cohorta/backend/app/services/autonomous_conversation_controller.py

"""
Autonomous Conversation Controller
Orchestrates the autonomous conversation flow for focus groups using LLM decision making.
"""

from typing import Dict, Any, Optional, List
import asyncio
import time
from datetime import datetime, timedelta, timezone
import logging

from app.services.conversation_decision_service import ConversationDecisionService, ConversationDecisionError
from app.services.focus_group_response_service import generate_persona_response, FocusGroupResponseError
from app.services.ai_moderator_service import AIModeratorService
from app.models.focus_group import FocusGroup  # Now fully async
from app.models.persona import Persona


class AutonomousConversationController:
    """Controller for managing autonomous conversation flow."""
    
    def __init__(self, focus_group_id: str, logger: Optional[logging.Logger] = None):
        self.focus_group_id = focus_group_id
        self.logger = logger or logging.getLogger(__name__)
        self.is_running = False
        self.conversation_state = "idle"  # idle, running, paused, completed, error
        self.is_generating = False  # Track when actively generating responses
        self.last_action_time = None
        self.action_count = 0
        self.max_actions_per_session = 500  # Safety limit
        
        # Timing configuration
        self.min_delay_between_actions = 3  # seconds
        self.max_delay_between_actions = 10  # seconds
        self.response_timeout = 30  # seconds
        
        # Edge case tracking
        self.consecutive_silence_count = 0
        self.max_consecutive_silence = 3
        self.participant_dominance_threshold = 0.4  # 40% of messages
        
        # Reasoning history tracking
        self.reasoning_history = []  # List of recent AI decisions with reasoning
        self.max_reasoning_history = 20  # Keep last 20 decisions
        
        # Initialize state from database on construction
        self._initialize_state_from_database()
    
    def _initialize_state_from_database(self):
        """Initialize the controller's state with defaults (database check happens during start)."""
        # Set default state - actual database check will happen when start_autonomous_conversation is called
        self.is_running = False
        self.conversation_state = "idle"
        self.logger.debug(f"Initialized controller with default state - database state will be checked on start")
        
    async def start_autonomous_conversation(self, initial_prompt: Optional[str] = None) -> Dict[str, Any]:
        """
        Start the autonomous conversation flow.
        
        Args:
            initial_prompt: Optional initial prompt to start the conversation
            
        Returns:
            Dictionary containing the start result
        """
        try:
            if self.is_running:
                # If conversation is already running, reset it and restart
                self.logger.info(f"Conversation already running for focus group {self.focus_group_id}, resetting state and restarting")
                await self.stop_conversation("restart")
                # Reset the running state to allow restart
                self.is_running = False
                self.conversation_state = "stopped"
            
            # Validate focus group exists (using async model)
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if not focus_group:
                return {"error": "Focus group not found"}
            
            # Check if focus group has participants
            participants = focus_group.get('participants', [])
            if not participants:
                return {"error": "Focus group has no participants"}
            
            # Update focus group status (using async model)
            await FocusGroup.update(self.focus_group_id, {
                'status': 'ai_mode',
                'autonomous_started_at': datetime.now(timezone.utc)
            })
            
            self.is_running = True
            self.conversation_state = "running"
            self.action_count = 0
            self.consecutive_silence_count = 0
            
            self.logger.info(f"Starting autonomous conversation for focus group {self.focus_group_id}")
            
            # Add initial prompt if provided
            if initial_prompt:
                await self._add_moderator_message(initial_prompt, "question")
            
            # Start the conversation loop and run it to completion
            # (This will now run in background thread from the API route)
            result = await self._run_conversation_loop()
            
            return {
                "message": "Autonomous conversation started",
                "focus_group_id": self.focus_group_id,
                "state": self.conversation_state,
                "conversation_result": result
            }
            
        except Exception as e:
            self.logger.error(f"Error starting autonomous conversation: {str(e)}")
            self.conversation_state = "error"
            return {"error": f"Failed to start autonomous conversation: {str(e)}"}
    
    async def stop_conversation(self, reason: str = "manual_stop") -> Dict[str, Any]:
        """
        Stop the autonomous conversation.
        
        Args:
            reason: Reason for stopping the conversation
            
        Returns:
            Dictionary containing the stop result
        """
        try:
            self.is_running = False
            self.conversation_state = "completed"
            
            # Update focus group status (using async model)
            status = 'completed' if reason in ['completed', 'discussion_guide_completed', 'natural_completion'] else 'active'
            await FocusGroup.update(self.focus_group_id, {
                'status': status,
                'autonomous_ended_at': datetime.now(timezone.utc),
                'completion_reason': reason
            })
            
            # GPT-5 fix: Emit AI status update to notify frontend of completion
            # The FocusGroup.update() will trigger the websocket event automatically
            
            # Mode events are now handled by AIModeratorService.end_session_with_concluding_statement()
            # to prevent duplicate mode event indicators
            
            self.logger.info(f"Stopped autonomous conversation for focus group {self.focus_group_id}: {reason}")
            
            # Add completion message only for certain reasons (not manual_stop)
            completion_messages = {
                "natural_completion": "We've reached the end of our discussion guide. Thank you everyone for your valuable insights.",
                "discussion_guide_completed": "We've covered all topics in our discussion guide. Thank you everyone for your valuable insights and participation.",
                "time_limit": "We've reached our scheduled time limit. Thank you for your participation in this focus group.",
                "error": "The session has been ended due to a technical issue. Thank you for your participation."
            }
            
            # Only add completion message for specific reasons (skip manual_stop)
            if reason in completion_messages:
                # Use the AI moderator service to properly end the session with mode events
                from app.services.ai_moderator_service import AIModeratorService
                
                ending_result = await AIModeratorService.end_session_with_concluding_statement(
                    self.focus_group_id, reason
                )
                
                if "error" in ending_result:
                    self.logger.error(f"Error ending session with concluding statement: {ending_result['error']}")
                    # Fallback to simple message
                    completion_message = completion_messages[reason]
                    await self._add_moderator_message(completion_message, "system")
                else:
                    self.logger.info(f"Successfully ended session with concluding statement: {ending_result.get('concluding_statement', '')[:100]}...")
            elif reason == "manual_stop":
                # For manual stops, add a mode event to indicate AI session concluded
                mode_event_id = await FocusGroup.add_mode_event(
                    focus_group_id=self.focus_group_id,
                    event_type='ai_session_concluded'
                )
                if mode_event_id:
                    self.logger.info(f"🎯 Added AI session concluded mode event for manual stop: {mode_event_id}")
                else:
                    self.logger.warning(f"Failed to add AI session concluded mode event for manual stop")
            
            # For discussion guide completion, ensure all items are marked as completed (100% progress)
            if reason in ["discussion_guide_completed", "natural_completion"]:
                await self._mark_all_questions_completed()
            
            return {
                "message": "Autonomous conversation stopped",
                "focus_group_id": self.focus_group_id,
                "state": self.conversation_state,
                "reason": reason,
                "action_count": self.action_count
            }
            
        except Exception as e:
            self.logger.error(f"Error stopping conversation: {str(e)}")
            return {"error": f"Failed to stop conversation: {str(e)}"}
    
    async def _run_conversation_loop(self) -> Dict[str, Any]:
        """
        Main conversation loop that makes decisions and executes actions.
        
        Returns:
            Dictionary containing the loop result
        """
        try:
            while self.is_running and self.action_count < self.max_actions_per_session:
                # Check if we should continue
                if not await self._should_continue_conversation():
                    break
                
                # Make a decision about the next action
                decision = await self._make_conversation_decision()
                
                if not decision:
                    self.consecutive_silence_count += 1
                    if self.consecutive_silence_count >= self.max_consecutive_silence:
                        self.logger.warning("Too many consecutive silent decisions, ending conversation")
                        await self.stop_conversation("excessive_silence")
                        break
                    continue
                
                # Execute the decision
                result = await self._execute_decision(decision)
                
                # Update reasoning history with execution result
                reasoning_id = decision.get('reasoning_id')
                await self._update_reasoning_execution(reasoning_id, result)
                
                if result.get("error"):
                    self.logger.error(f"Error executing decision: {result['error']}")
                    continue
                
                # Reset silence count on successful action
                self.consecutive_silence_count = 0
                self.action_count += 1
                self.last_action_time = datetime.now(timezone.utc)
                
                # GPT-5 fix: Yield to eventlet hub after each action to flush WebSocket frames
                await self._yield_to_eventlet()
                
                # Wait before next action
                await self._wait_between_actions()
                
                # Check for session end conditions
                if decision.get("action") == "end_session":
                    await self.stop_conversation("natural_completion")
                    break
            
            # Handle loop exit conditions
            if self.action_count >= self.max_actions_per_session:
                await self.stop_conversation("action_limit_reached")
            
            return {
                "message": "Conversation loop completed",
                "action_count": self.action_count,
                "state": self.conversation_state
            }
            
        except Exception as e:
            self.logger.error(f"Error in conversation loop: {str(e)}")
            self.conversation_state = "error"
            await self.stop_conversation("error")
            return {"error": f"Conversation loop error: {str(e)}"}
    
    async def _should_continue_conversation(self) -> bool:
        """Check if the conversation should continue based on various conditions."""
        try:
            # Check focus group status (using async model)
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if not focus_group:
                return False
            
            current_status = focus_group.get('status', '')
            
            # Check if autonomous mode should stop - any status other than 'ai_mode' means stop
            if current_status != 'ai_mode':
                self.is_running = False
                self.logger.info(f"Autonomous conversation stopping due to status change: {current_status}")
                return False
            
            # Check if discussion guide is completed
            if await self._is_discussion_guide_completed(focus_group):
                await self.stop_conversation("discussion_guide_completed")
                return False
            
            # Note: Time limits are now informational only and don't stop conversations
            # Users can see elapsed time in the UI but it won't auto-stop the session
            
            return True
            
        except Exception as e:
            self.logger.error(f"Error checking conversation continuation: {str(e)}")
            return False
    
    async def _is_discussion_guide_completed(self, focus_group: Dict[str, Any]) -> bool:
        """
        Check if the discussion guide has been completed.
        
        Args:
            focus_group: The focus group data
            
        Returns:
            True if the discussion guide is completed, False otherwise
        """
        try:
            discussion_guide = focus_group.get('discussionGuide', {})
            
            # Handle legacy markdown format - never auto-complete for legacy guides
            if isinstance(discussion_guide, str):
                return False
            
            # If no structured guide, don't auto-complete
            if not discussion_guide or 'sections' not in discussion_guide:
                return False
            
            # Get current moderator position
            moderator_position = focus_group.get('moderator_position', {
                'section_index': 0,
                'item_index': 0,
                'item_type': 'activity'
            })
            
            sections = discussion_guide['sections']
            section_index = moderator_position.get('section_index', 0)
            item_index = moderator_position.get('item_index', 0)
            item_type = moderator_position.get('item_type', 'activity')
            
            # Check if we're past the last section
            if section_index >= len(sections):
                return True
            
            # Check if we're in the last section and past all items
            if section_index == len(sections) - 1:
                last_section = sections[section_index]
                
                # Get the total number of items in the last section
                activities_count = len(last_section.get('activities', []))
                questions_count = len(last_section.get('questions', []))
                
                # If we're past all activities and questions, guide is complete
                if item_type == 'activity' and item_index >= activities_count:
                    # Check if there are questions to move to
                    if questions_count > 0:
                        return False  # Still have questions to cover
                    else:
                        return True  # No questions, guide complete
                elif item_type == 'question' and item_index >= questions_count:
                    return True  # Past all questions in last section
            
            return False
            
        except Exception as e:
            self.logger.error(f"Error checking discussion guide completion: {str(e)}")
            return False
    
    async def _make_conversation_decision(self) -> Optional[Dict[str, Any]]:
        """
        Make a decision about the next conversation action using the LLM.
        
        Returns:
            Dictionary containing the decision (with reasoning_id added), or None if no decision could be made
        """
        try:
            decision = await ConversationDecisionService.decide_next_action(
                self.focus_group_id,
                temperature=0.7,
                mode='ai'
            )
            
            self.logger.info(f"LLM Decision: {decision['action']} - {decision['reasoning']}")
            
            # Store reasoning in history for UI display and get the database ID
            reasoning_id = await self._store_reasoning(decision)
            
            # Add the reasoning_id to the decision for later use
            decision['reasoning_id'] = reasoning_id
            
            return decision
            
        except ConversationDecisionError as e:
            self.logger.error(f"Error making conversation decision: {str(e)}")
            return None
        except Exception as e:
            self.logger.error(f"Unexpected error in decision making: {str(e)}")
            return None
    
    async def _store_reasoning(self, decision: Dict[str, Any]) -> Optional[str]:
        """
        Store reasoning from AI decision for UI display.
        
        Args:
            decision: The decision dictionary from ConversationDecisionService
            
        Returns:
            The ID of the stored reasoning entry, or None if failed
        """
        try:
            reasoning_entry = {
                'timestamp': datetime.now(timezone.utc).isoformat(),
                'action': decision.get('action', 'unknown'),
                'reasoning': decision.get('reasoning', 'No reasoning provided'),
                'details': decision.get('details', {}),
                'execution_status': 'pending',
                'execution_result': None
            }
            
            # Store to database for persistence
            reasoning_id = await FocusGroup.add_reasoning_entry(self.focus_group_id, reasoning_entry)
            
            # Also keep in memory for quick access during active session
            reasoning_entry['_id'] = reasoning_id  # Add the database ID
            self.reasoning_history.insert(0, reasoning_entry)
            
            # Maintain max history size in memory
            if len(self.reasoning_history) > self.max_reasoning_history:
                self.reasoning_history = self.reasoning_history[:self.max_reasoning_history]
            
            return reasoning_id
                
        except Exception as e:
            self.logger.error(f"Error storing reasoning: {str(e)}")
            return None
    
    async def _update_reasoning_execution(self, reasoning_id: Optional[str], execution_result: Dict[str, Any]) -> None:
        """
        Update the reasoning entry with execution results.
        
        Args:
            reasoning_id: The ID of the reasoning entry to update
            execution_result: The result from executing the decision
        """
        try:
            # Update the database record
            if reasoning_id:
                await FocusGroup.update_reasoning_execution(self.focus_group_id, reasoning_id, execution_result)
            
            # Also update in memory for quick access during active session
            if self.reasoning_history:
                latest_entry = self.reasoning_history[0]
                latest_entry['execution_status'] = 'success' if not execution_result.get('error') else 'error'
                latest_entry['execution_result'] = execution_result
                
        except Exception as e:
            self.logger.error(f"Error updating reasoning execution: {str(e)}")
    
    
    async def _execute_decision(self, decision: Dict[str, Any]) -> Dict[str, Any]:
        """
        Execute a conversation decision.
        
        Args:
            decision: The decision to execute
            
        Returns:
            Dictionary containing the execution result
        """
        try:
            action = decision["action"]
            details = decision["details"]
            
            self.logger.info(f"Executing decision: {action}")
            self.logger.debug(f"Decision details: {details}")
            
            # For moderator_speak actions, update position FIRST so creative review detection works correctly
            if action == "moderator_speak":
                # Update position before creating message so current position is correct for image detection
                self.logger.debug(f"Updating discussion guide position BEFORE moderator_speak execution")
                await self._update_discussion_guide_position(decision)
                result = await self._execute_moderator_speak(details)
            
            elif action == "participant_respond":
                result = await self._execute_participant_respond(details)
                # Update position after other actions
                if not result.get("error"):
                    self.logger.debug(f"Updating discussion guide position after successful {action}")
                    await self._update_discussion_guide_position(decision)
                else:
                    self.logger.warning(f"Skipping position update due to action error: {result.get('error')}")
            
            elif action == "participant_interaction":
                result = await self._execute_participant_interaction(details)
                # Update position after other actions
                if not result.get("error"):
                    self.logger.debug(f"Updating discussion guide position after successful {action}")
                    await self._update_discussion_guide_position(decision)
                else:
                    self.logger.warning(f"Skipping position update due to action error: {result.get('error')}")
            
            elif action == "probe_trigger":
                result = await self._execute_probe_trigger(details)
                # Update position after other actions
                if not result.get("error"):
                    self.logger.debug(f"Updating discussion guide position after successful {action}")
                    await self._update_discussion_guide_position(decision)
                else:
                    self.logger.warning(f"Skipping position update due to action error: {result.get('error')}")
            
            elif action == "end_session":
                result = await self._execute_end_session(details)
                # Update position after other actions
                if not result.get("error"):
                    self.logger.debug(f"Updating discussion guide position after successful {action}")
                    await self._update_discussion_guide_position(decision)
                else:
                    self.logger.warning(f"Skipping position update due to action error: {result.get('error')}")
            
            else:
                error_msg = f"Unknown action type: {action}"
                self.logger.error(error_msg)
                return {"error": error_msg}
            
            self.logger.debug(f"Action {action} execution result: {result}")
            
            return result
                
        except Exception as e:
            error_msg = f"Decision execution error: {str(e)}"
            self.logger.error(f"❌ Error executing decision: {error_msg}")
            import traceback
            self.logger.error(f"❌ Full traceback: {traceback.format_exc()}")
            return {"error": error_msg}
    
    async def _execute_moderator_speak(self, details: Dict[str, Any]) -> Dict[str, Any]:
        """Execute moderator speak action."""
        try:
            content = details["content"]
            message_type = details.get("message_type", "question")
            
            # Add moderator message  
            message_id = await self._add_moderator_message(content, message_type)
            
            return {
                "message": "Moderator message added",
                "message_id": message_id,
                "content": content
            }
            
        except Exception as e:
            return {"error": f"Error in moderator speak: {str(e)}"}
    
    async def _execute_participant_respond(self, details: Dict[str, Any]) -> Dict[str, Any]:
        """Execute participant respond action."""
        try:
            self.is_generating = True  # Mark as generating
            
            participant_id = details["participant_id"]
            topic_context = details["topic_context"]
            
            
            # Generate participant response
            result = await self._generate_participant_response(participant_id, topic_context)
            
            
            return result
            
        except Exception as e:
            error_msg = f"Error in participant respond: {str(e)}"
            self.logger.error(f"❌ {error_msg}")
            import traceback
            self.logger.error(f"❌ Full traceback: {traceback.format_exc()}")
            return {"error": error_msg}
        finally:
            self.is_generating = False  # Always clear generating state
    
    async def _execute_participant_interaction(self, details: Dict[str, Any]) -> Dict[str, Any]:
        """Execute participant interaction action."""
        try:
            self.is_generating = True  # Mark as generating
            
            participant_ids = details["participant_ids"]
            moderator_prompt = details["moderator_prompt"]
            
            # Add moderator prompt for interaction
            await self._add_moderator_message(moderator_prompt, "question")
            
            # Generate responses from both participants
            results = []
            for participant_id in participant_ids:
                result = await self._generate_participant_response(participant_id, moderator_prompt)
                results.append(result)
            
            return {
                "message": "Participant interaction executed",
                "participant_responses": results
            }
            
        except Exception as e:
            return {"error": f"Error in participant interaction: {str(e)}"}
        finally:
            self.is_generating = False  # Always clear generating state
    
    async def _execute_probe_trigger(self, details: Dict[str, Any]) -> Dict[str, Any]:
        """Execute probe trigger action."""
        try:
            probe_question = details["probe_question"]
            
            # Add probe question
            message_id = await self._add_moderator_message(probe_question, "probe")
            
            return {
                "message": "Probe trigger executed",
                "message_id": message_id,
                "probe_question": probe_question
            }
            
        except Exception as e:
            return {"error": f"Error in probe trigger: {str(e)}"}
    
    async def _execute_end_session(self, details: Dict[str, Any]) -> Dict[str, Any]:
        """Execute end session action."""
        try:
            closing_message = details["closing_message"]
            completion_reason = details["completion_reason"]
            
            # Add closing message
            await self._add_moderator_message(closing_message, "system")
            
            # Advance position past current item so final question shows as completed
            try:
                advance_result = await AIModeratorService.advance_discussion(self.focus_group_id)
                if advance_result.get('error'):
                    self.logger.info(f"Could not advance past final item when ending session: {advance_result['error']}")
                else:
                    self.logger.info("Advanced moderator position past final item - session complete")
            except Exception as e:
                self.logger.info(f"Error advancing position when ending session: {str(e)}")
            
            # Stop the conversation
            await self.stop_conversation(completion_reason)
            
            return {
                "message": "Session ended",
                "completion_reason": completion_reason
            }
            
        except Exception as e:
            return {"error": f"Error ending session: {str(e)}"}
    
    async def _generate_participant_response(self, participant_id: str, topic: str) -> Dict[str, Any]:
        """Generate a response from a participant."""
        try:
            
            # Get participant data
            persona = await Persona.find_by_id(participant_id)
            if not persona:
                error_msg = f"Participant {participant_id} not found"
                self.logger.error(error_msg)
                return {"error": error_msg}
            
            
            # Get focus group data
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if not focus_group:
                error_msg = "Focus group not found"
                self.logger.error(error_msg)
                return {"error": error_msg}
            
            
            # Get discussion guide
            discussion_guide = focus_group.get('discussionGuide', '')
            
            # Get the LLM model and GPT-5 parameters for this focus group
            llm_model = focus_group.get('llm_model')
            reasoning_effort = focus_group.get('reasoning_effort', 'medium')
            verbosity = focus_group.get('verbosity', 'medium')
            self.logger.info(f"🤖 Autonomous conversation using model: {llm_model or 'default (gemini-3-pro-preview)'} for focus group {self.focus_group_id}")
            
            # Get recent messages
            messages = await FocusGroup.get_messages(self.focus_group_id)
            recent_messages = messages[-20:] if len(messages) > 20 else messages
            
            # Generate response
            try:
                response_text = await generate_persona_response(
                    persona=persona,
                    current_topic=topic,
                    previous_messages=recent_messages,
                    temperature=0.7,
                    focus_group_id=self.focus_group_id,
                    llm_model=llm_model,
                    reasoning_effort=reasoning_effort,
                    verbosity=verbosity
                )
            except Exception as e:
                self.logger.error(f"Error in generate_persona_response: {str(e)}")
                import traceback
                self.logger.error(f"❌ Full traceback: {traceback.format_exc()}")
                raise
            
            # Save message
            message_data = {
                "text": response_text,
                "type": "response",
                "senderId": participant_id
            }
            
            message_id = await FocusGroup.add_message(self.focus_group_id, message_data)
            
            # GPT-5 fix: Yield after database write to flush WebSocket events
            await self._yield_to_eventlet()
            
            if not message_id:
                error_msg = "Failed to save message to database - no message ID returned"
                self.logger.error(error_msg)
                return {"error": error_msg}
            
            success_result = {
                "message": "Participant response generated",
                "participant_id": participant_id,
                "response": response_text,
                "message_id": message_id
            }
            return success_result
            
        except FocusGroupResponseError as e:
            error_msg = f"Error generating participant response: {str(e)}"
            self.logger.error(f"❌ FocusGroupResponseError: {error_msg}")
            return {"error": error_msg}
        except Exception as e:
            error_msg = f"Unexpected error generating response: {str(e)}"
            self.logger.error(f"❌ Unexpected error: {error_msg}")
            import traceback
            self.logger.error(f"❌ Full traceback: {traceback.format_exc()}")
            return {"error": error_msg}
    
    async def _get_item_by_position_id(self, position_id: str) -> Optional[Dict[str, Any]]:
        """Get a discussion guide item by its position ID."""
        try:
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if not focus_group:
                return None
                
            discussion_guide = focus_group.get('discussionGuide')
            if not discussion_guide or not isinstance(discussion_guide, dict):
                return None
                
            sections = discussion_guide.get('sections', [])
            
            # Search through all sections and subsections for the item
            for section in sections:
                # Check activities in main section
                for activity in section.get('activities', []):
                    if activity.get('id') == position_id:
                        return activity
                        
                # Check questions in main section  
                for question in section.get('questions', []):
                    if question.get('id') == position_id:
                        return question
                        
                # Check subsections
                for subsection in section.get('subsections', []):
                    # Check activities in subsection
                    for activity in subsection.get('activities', []):
                        if activity.get('id') == position_id:
                            return activity
                            
                    # Check questions in subsection
                    for question in subsection.get('questions', []):
                        if question.get('id') == position_id:
                            return question
                            
            return None
            
        except Exception as e:
            self.logger.warning(f"Error getting item by position ID {position_id}: {e}")
            return None
    
    async def _add_moderator_message(self, content: str, message_type: str) -> Optional[str]:
        """Add a moderator message to the conversation."""
        try:
            # Initialize image detection variables
            attached_assets = []
            activates_visual_context = False
            display_reference = None
            
            # Check if current discussion guide item has image attachments
            try:
                from app.services.ai_moderator_service import AIModeratorService
                from app.services.focus_group_response_service import extract_asset_filename_from_content
                
                print(f"🔍 Checking current discussion guide item for image attachments")
                
                moderator_status = await AIModeratorService.get_moderator_status(self.focus_group_id)
                current_item = None
                
                if moderator_status and 'moderator_position' in moderator_status:
                    focus_group = await FocusGroup.find_by_id(self.focus_group_id)
                    if focus_group:
                        discussion_guide = focus_group.get('discussionGuide')
                        if discussion_guide and isinstance(discussion_guide, dict):
                            sections = discussion_guide.get('sections', [])
                            pos = moderator_status['moderator_position']
                            section_idx = pos.get('section_index', 0)
                            item_idx = pos.get('item_index', 0)
                            item_type = pos.get('item_type', 'activity')
                            subsection_idx = pos.get('subsection_index')
                            
                            if section_idx < len(sections):
                                section = sections[section_idx]
                                
                                # Get current item from subsection or section
                                if subsection_idx is not None and section.get('subsections'):
                                    subsections = section['subsections']
                                    if subsection_idx < len(subsections):
                                        subsection = subsections[subsection_idx]
                                        items = subsection.get('questions' if item_type == 'question' else 'activities', [])
                                        if item_idx < len(items):
                                            current_item = items[item_idx]
                                else:
                                    # Section level
                                    items = section.get('questions' if item_type == 'question' else 'activities', [])
                                    if item_idx < len(items):
                                        current_item = items[item_idx]
                
                # Check if current item has visual asset metadata
                if current_item:
                    print(f"🔍 Current item: {current_item.get('content', '')[:50]}...")
                    
                    metadata = current_item.get('metadata', {})
                    visual_asset = metadata.get('visual_asset')
                    
                    if visual_asset:
                        # Found image in metadata - use it
                        asset_filename = visual_asset.get('filename')
                        display_reference = visual_asset.get('display_reference')
                        
                        print(f"🎨 Found image in current item metadata: {display_reference} -> {asset_filename}")
                        
                        attached_assets = [asset_filename]
                        activates_visual_context = True
                        
                        # Generate AI description and enhance the content
                        try:
                            from app.services.image_description_service import ImageDescriptionService, ImageDescriptionError
                            
                            print(f"🎨 AI MODE: Generating description for {asset_filename}")
                            description = await ImageDescriptionService.generate_description(self.focus_group_id, asset_filename)
                            
                            # Enhance the content with the description using display reference if available
                            if display_reference:
                                enhanced_content = ImageDescriptionService.enhance_creative_review_question_with_display_reference(
                                    content, display_reference, description
                                )
                            else:
                                # Fallback to old method for legacy content
                                enhanced_content = ImageDescriptionService.enhance_creative_review_question(
                                    content, asset_filename, description
                                )
                            
                            # Update the content to use enhanced version
                            content = enhanced_content
                            
                            print(f"✅ AI MODE: Enhanced moderator message with image description")
                            
                        except ImageDescriptionError as desc_error:
                            print(f"⚠️  AI MODE: Failed to generate image description: {desc_error}")
                            self.logger.warning(f"Failed to generate image description in autonomous mode: {desc_error}")
                            # Continue with original content
                    else:
                        # No visual asset metadata, try legacy content parsing
                        activity_content = current_item.get('content', '')
                        asset_filename = extract_asset_filename_from_content(activity_content)
                        
                        if asset_filename:
                            print(f"🔍 Legacy: Found asset filename in content: {asset_filename}")
                            attached_assets = [asset_filename]
                            activates_visual_context = True
                        else:
                            print(f"🔍 No image attachments found for current item")
                else:
                    print(f"🔍 No current discussion guide item found")
            except Exception as e:
                self.logger.warning(f"Error checking for creative review activity: {e}")
                print(f"⚠️  Error checking creative review: {e}")
            
            print(f"🔍 FINAL RESULT: attached_assets={attached_assets}, activates_visual_context={activates_visual_context}")
            
            # Create visual asset metadata for frontend display
            visual_asset_metadata = None
            if activates_visual_context and attached_assets and len(attached_assets) > 0:
                # Create visual asset metadata that frontend expects
                visual_asset_metadata = {
                    "filename": attached_assets[0],  # Use first asset
                    "displayReference": display_reference or attached_assets[0]  # Use display reference or filename as fallback
                }
            
            # Create message data with visual context information
            message_data = {
                "text": content,
                "type": message_type,
                "senderId": "moderator",
                "attached_assets": attached_assets,
                "activates_visual_context": activates_visual_context,
                "visual_asset": visual_asset_metadata  # Frontend needs this for image display
            }
            
            message_id = await FocusGroup.add_message(self.focus_group_id, message_data)
            
            # GPT-5 fix: Yield after database write to flush WebSocket events
            await self._yield_to_eventlet()
            
            # Visual context activation is handled automatically by FocusGroup.add_message()
            # when activates_visual_context=True and attached_assets are present
            if activates_visual_context and attached_assets:
                self.logger.info(f"✅ Added moderator message with visual context activation: {attached_assets}")
                print(f"✅ VISUAL CONTEXT ACTIVATED: {attached_assets}")
            
            return message_id
            
        except Exception as e:
            self.logger.error(f"Error adding moderator message: {str(e)}")
            return None
    
    async def _update_discussion_guide_position(self, decision: Dict[str, Any]) -> None:
        """Update moderator position based on LLM decision."""
        try:
            # Check if LLM provided discussion guide position mapping
            position_id = decision.get('discussion_guide_position_id')
            action = decision.get('action', 'unknown')
            
            if position_id:
                # Validate that the position ID exists
                section_id, item_id = await self._validate_position_id(position_id)
                if section_id and item_id:
                    # LLM specified valid position - set it precisely
                    try:
                        result = await AIModeratorService.set_moderator_position(self.focus_group_id, section_id, item_id)
                        position_desc = f"position '{position_id}'"
                        
                        if result.get('error'):
                            self.logger.warning(f"Failed to set LLM-specified position to {position_desc}: {result['error']}")
                            self.logger.info("🔄 Continuing with current position - next LLM decision will try again")
                        else:
                            self.logger.debug(f"Successfully set moderator position to LLM-specified {position_desc} (from {action} action)")
                    except Exception as e:
                        self.logger.warning(f"Error setting LLM-specified position: {str(e)}")
                        self.logger.info("🔄 Continuing with current position - next LLM decision will try again")
                else:
                    # Invalid position ID
                    self.logger.warning(f"🚫 LLM specified invalid position '{position_id}', continuing with current position")
                    self.logger.info("🔄 Next LLM decision will try again with valid position mapping")
            else:
                # LLM didn't specify a position - continue with current position
                self.logger.info(f"🔄 LLM didn't specify position for {action} action, continuing with current position")
                self.logger.debug("Next LLM decision should include position mapping for better tracking")
                
        except Exception as e:
            self.logger.error(f"Error updating discussion guide position: {str(e)}")
    
    async def _validate_position_id(self, position_id: str) -> tuple[Optional[str], Optional[str]]:
        """Validate that the position ID exists and return the section_id and item_id it maps to."""
        try:
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if not focus_group:
                return None, None
                
            discussion_guide = focus_group.get('discussionGuide', {})
            
            # Handle legacy format
            if isinstance(discussion_guide, str):
                self.logger.debug(f"Legacy discussion guide format, cannot validate position ID: {position_id}")
                return None, None
            
            # Handle structured format
            if isinstance(discussion_guide, dict) and 'sections' in discussion_guide:
                sections = discussion_guide['sections']
                
                # Search through all sections for the position ID
                for section in sections:
                    section_id = section.get('id')
                    
                    # Check in top-level activities
                    if section.get('activities'):
                        for activity in section['activities']:
                            if activity.get('id') == position_id:
                                return section_id, position_id
                    
                    # Check in top-level questions
                    if section.get('questions'):
                        for question in section['questions']:
                            if question.get('id') == position_id:
                                return section_id, position_id
                    
                    # Check in subsections
                    if section.get('subsections'):
                        for subsection in section['subsections']:
                            # Check subsection activities
                            if subsection.get('activities'):
                                for activity in subsection['activities']:
                                    if activity.get('id') == position_id:
                                        return section_id, position_id
                            
                            # Check subsection questions
                            if subsection.get('questions'):
                                for question in subsection['questions']:
                                    if question.get('id') == position_id:
                                        return section_id, position_id
                
                # Position ID not found - log available IDs for debugging
                available_positions = []
                for section in sections:
                    # Collect from top-level activities and questions
                    if section.get('activities'):
                        available_positions.extend([a.get('id', 'no-id') for a in section['activities']])
                    if section.get('questions'):
                        available_positions.extend([q.get('id', 'no-id') for q in section['questions']])
                    
                    # Collect from subsections
                    if section.get('subsections'):
                        for subsection in section['subsections']:
                            if subsection.get('activities'):
                                available_positions.extend([a.get('id', 'no-id') for a in subsection['activities']])
                            if subsection.get('questions'):
                                available_positions.extend([q.get('id', 'no-id') for q in subsection['questions']])
                
                self.logger.warning(f"Position ID '{position_id}' not found. Available positions: {available_positions}")
                return None, None
            
            self.logger.debug(f"No structured discussion guide found, cannot validate position ID: {position_id}")
            return None, None
            
        except Exception as e:
            self.logger.error(f"Error validating position ID '{position_id}': {str(e)}")
            return None, None
    
    async def _fallback_advance_position(self) -> None:
        """Fallback method to advance position sequentially."""
        try:
            advance_result = await AIModeratorService.advance_discussion(self.focus_group_id)
            if advance_result.get('error'):
                self.logger.warning(f"Sequential advancement failed: {advance_result['error']}")
            else:
                self.logger.info(f"Sequential advancement successful: {advance_result.get('message', 'Success')}")
        except Exception as e:
            self.logger.warning(f"Failed to advance moderator position sequentially: {str(e)}")
    
    async def _yield_to_eventlet(self):
        """Yield control to allow other tasks to run and flush WebSocket frames."""
        try:
            # Use asyncio sleep instead of socketio.sleep since we're in async context
            await asyncio.sleep(0)  # Yield to other tasks
        except Exception as e:
            self.logger.warning(f"Could not yield to event loop: {e}")
    
    async def _wait_between_actions(self):
        """Wait an appropriate amount of time between actions."""
        import random
        
        # Random delay between min and max
        delay = random.uniform(self.min_delay_between_actions, self.max_delay_between_actions)
        await asyncio.sleep(delay)
    
    async def get_conversation_status(self) -> Dict[str, Any]:
        """Get the current status of the autonomous conversation."""
        try:
            # Check the actual database state to determine if autonomous mode is truly running
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if focus_group:
                db_status = focus_group.get('status', 'unknown')
                
                # Determine if autonomous mode is actually running based on database state
                is_ai_mode = db_status == 'ai_mode'
                
                # Update instance variables to match database state
                if is_ai_mode:
                    self.is_running = True
                    self.conversation_state = "running"
                else:
                    self.is_running = False
                    self.conversation_state = "idle"
                
                self.logger.debug(f"Status check - DB status: {db_status}, is_running: {self.is_running}")
            else:
                self.logger.warning(f"Focus group {self.focus_group_id} not found during status check")
                
        except Exception as e:
            self.logger.error(f"Error checking database status: {str(e)}")
            # Keep existing instance state if database check fails
        
        # Load reasoning history from database to ensure it persists across controller instances
        reasoning_history = await FocusGroup.get_reasoning_history(self.focus_group_id, self.max_reasoning_history)
        
        return {
            "focus_group_id": self.focus_group_id,
            "is_running": self.is_running,
            "conversation_state": self.conversation_state,
            "is_generating": self.is_generating,
            "action_count": self.action_count,
            "last_action_time": self.last_action_time.isoformat() if self.last_action_time else None,
            "consecutive_silence_count": self.consecutive_silence_count,
            "reasoning_history": reasoning_history  # Now loads from database
        }
    
    async def _mark_all_questions_completed(self) -> None:
        """
        Mark all questions and activities in the discussion guide as completed by setting
        the moderator position to indicate 100% completion.
        """
        try:
            focus_group = await FocusGroup.find_by_id(self.focus_group_id)
            if not focus_group:
                self.logger.error("Focus group not found when marking all questions completed")
                return
            
            discussion_guide = focus_group.get('discussionGuide', {})
            
            # Handle legacy format - no position tracking needed
            if isinstance(discussion_guide, str):
                self.logger.debug("Legacy discussion guide format, no position update needed")
                return
            
            # Handle structured format
            if not discussion_guide or 'sections' not in discussion_guide:
                self.logger.debug("No structured discussion guide found, no position update needed")
                return
            
            sections = discussion_guide['sections']
            if not sections:
                self.logger.debug("No sections in discussion guide, no position update needed")
                return
            
            # Set moderator position to indicate all items are completed
            # Position it past the last section to show 100% completion
            last_section_index = len(sections) - 1
            last_section = sections[last_section_index]
            
            # Calculate the position that would indicate all items are done
            # We set it past the last item in the last section
            total_activities = len(last_section.get('activities', []))
            total_questions = len(last_section.get('questions', []))
            
            # Position it past all items to indicate completion
            if total_questions > 0:
                # If there are questions, position past the last question
                completion_position = {
                    'section_index': last_section_index,
                    'item_index': total_questions,  # Past the last question
                    'item_type': 'question'
                }
            elif total_activities > 0:
                # If there are only activities, position past the last activity
                completion_position = {
                    'section_index': last_section_index,
                    'item_index': total_activities,  # Past the last activity
                    'item_type': 'activity'
                }
            else:
                # Empty section, position past the section
                completion_position = {
                    'section_index': last_section_index + 1,
                    'item_index': 0,
                    'item_type': 'activity'
                }
            
            # Update the focus group with the completion position
            await FocusGroup.update(self.focus_group_id, {
                'moderator_position': completion_position
            })
            
            self.logger.info(f"Marked all questions completed - set position to: {completion_position}")
            
        except Exception as e:
            self.logger.error(f"Error marking all questions completed: {str(e)}")