# handlingTasks.py
# Refactored for clarity and consolidation

import asyncio
import logging
import json
import time
from typing import Dict, Any, Optional, List, Union
from datetime import datetime, UTC
from modules.interfaces.interfaceChatModel import (
    TaskStatus, TaskStep, TaskContext, TaskAction, ReviewResult, TaskPlan, WorkflowResult, TaskResult, ReviewContext, ActionResult
)
from .executionState import TaskExecutionState
from .promptFactory import createTaskPlanningPrompt, createActionDefinitionPrompt, createResultReviewPrompt
from modules.chat.documents.documentGeneration import DocumentGenerator

logger = logging.getLogger(__name__)

class WorkflowStoppedException(Exception):
    """Exception raised when a workflow is stopped by the user."""
    pass

class HandlingTasks:
    def __init__(self, chatInterface, service, workflow=None):
        self.chatInterface = chatInterface
        self.service = service
        self.workflow = workflow
        self.documentGenerator = DocumentGenerator(service)
    
    def _checkWorkflowStopped(self):
        """
        Check if workflow has been stopped by user and raise exception if so.
        This function centralizes all workflow stop checking logic to avoid code duplication.
        """
        try:
            # Get the current workflow status from the database to avoid stale data
            current_workflow = self.chatInterface.getWorkflow(self.service.workflow.id)
            if current_workflow and current_workflow.status == "stopped":
                logger.info("Workflow stopped by user, aborting execution")
                raise WorkflowStoppedException("Workflow was stopped by user")
        except WorkflowStoppedException:
            # Re-raise the WorkflowStoppedException immediately
            raise
        except Exception as e:
            # If we can't get the current status due to other database issues, fall back to the in-memory object
            logger.warning(f"Could not check current workflow status from database: {str(e)}")
            if self.service.workflow.status == "stopped":
                logger.info("Workflow stopped by user (from in-memory object), aborting execution")
                raise WorkflowStoppedException("Workflow was stopped by user")

    async def generateTaskPlan(self, userInput: str, workflow) -> TaskPlan:
        """Generate a high-level task plan for the workflow."""
        try:
            # Check workflow status before generating task plan
            self._checkWorkflowStopped()
            
            logger.info(f"Generating task plan for workflow {workflow.id}")
            available_docs = self.service.getAvailableDocuments(workflow)

            
            # Check workflow status before calling AI service
            self._checkWorkflowStopped()
            
            prompt = await self.service.callAiTextAdvanced(
                createTaskPlanningPrompt({
                    'user_request': userInput,
                    'available_documents': available_docs,
                    'workflow_id': workflow.id
                })
            )
            # Inline _parseTaskPlanResponse logic
            try:
                json_start = prompt.find('{')
                json_end = prompt.rfind('}') + 1
                if json_start == -1 or json_end == 0:
                    raise ValueError("No JSON found in response")
                json_str = prompt[json_start:json_end]
                task_plan_dict = json.loads(json_str)
                if 'tasks' not in task_plan_dict:
                    raise ValueError("Task plan missing 'tasks' field")
            except Exception as e:
                logger.error(f"Error parsing task plan response: {str(e)}")
                task_plan_dict = {'tasks': []}
            
            if not self._validateTaskPlan(task_plan_dict):
                logger.error("Generated task plan failed validation")
                logger.error(f"AI Response: {prompt}")
                logger.error(f"Parsed Task Plan: {json.dumps(task_plan_dict, indent=2)}")
                raise Exception("AI-generated task plan failed validation - AI is required for task planning")
            
            tasks = []
            for task_dict in task_plan_dict.get('tasks', []):
                # Map old 'description' field to new 'objective' field
                if 'description' in task_dict and 'objective' not in task_dict:
                    task_dict['objective'] = task_dict.pop('description')
                tasks.append(TaskStep(**task_dict))
            task_plan = TaskPlan(
                overview=task_plan_dict.get('overview', ''),
                tasks=tasks
            )
            
            logger.info(f"Task plan generated successfully with {len(tasks)} tasks")
            
            # Log the generated tasks
            for i, task in enumerate(tasks):
                logger.info(f"  Task {i+1}: {task.objective}")
                if hasattr(task, 'success_criteria') and task.success_criteria:
                    logger.info(f"    Success criteria: {task.success_criteria}")
            
            # Log the complete task plan
            logger.info("=== GENERATED TASK PLAN ===")
            logger.info(f"Overview: {task_plan.overview}")
            logger.info(f"Total tasks: {len(tasks)}")
            
            # Log the RAW AI-generated task plan JSON for debugging
            logger.info("=== RAW AI TASK PLAN JSON ===")
            logger.info(f"AI Response with task plan: {prompt}")
            logger.info("=== END RAW AI TASK PLAN JSON ===")
            
            return task_plan
        except Exception as e:
            logger.error(f"Error in generateTaskPlan: {str(e)}")
            raise

    async def generateTaskActions(self, task_step, workflow, previous_results=None, enhanced_context=None) -> List[TaskAction]:
        """Generate actions for a given task step."""
        try:
            # Check workflow status before generating actions
            self._checkWorkflowStopped()
            
            logger.info(f"Generating actions for task: {task_step.objective}")
            
            available_docs = self.service.getAvailableDocuments(workflow)
            available_connections = self.service.getConnectionReferenceList()

            
            context = enhanced_context or TaskContext(
                task_step=task_step,
                workflow=workflow,
                workflow_id=workflow.id,
                available_documents=available_docs,
                previous_results=previous_results or [],
                improvements=[],
                retry_count=0,
                previous_action_results=[],
                previous_review_result=None,
                is_regeneration=False,
                failure_patterns=[],
                failed_actions=[],
                successful_actions=[]
            )
            # Check workflow status before calling AI service
            self._checkWorkflowStopped()
            
            prompt = await self.service.callAiTextAdvanced(
                await createActionDefinitionPrompt(context, self.service)
            )
            # Inline parseActionResponse logic here
            json_start = prompt.find('{')
            json_end = prompt.rfind('}') + 1
            if json_start == -1 or json_end == 0:
                raise ValueError("No JSON found in response")
            json_str = prompt[json_start:json_end]
            try:
                action_data = json.loads(json_str)
            except Exception as e:
                logger.error(f"Error parsing action response JSON: {str(e)}")
                action_data = {}
            if 'actions' not in action_data:
                raise ValueError("Action response missing 'actions' field")
            actions = action_data['actions']
            if not self._validateActions(actions, context):
                logger.error("Generated actions failed validation")
                raise Exception("AI-generated actions failed validation - AI is required for action generation")
            
            # Convert to TaskAction objects
            task_actions = [self.chatInterface.createTaskAction({
                "execMethod": a.get('method', 'unknown'),
                "execAction": a.get('action', 'unknown'),
                "execParameters": a.get('parameters', {}),
                "execResultLabel": a.get('resultLabel', ''),
                "expectedDocumentFormats": a.get('expectedDocumentFormats', None),
                "status": TaskStatus.PENDING
            }) for a in actions]
            
            valid_actions = [ta for ta in task_actions if ta]
            logger.info(f"Generated {len(valid_actions)} actions for task: {task_step.objective}")
            
            # Log the generated actions
            for i, action in enumerate(valid_actions):
                logger.info(f"  Action {i+1}: {action.execMethod}.{action.execAction}")
                if action.expectedDocumentFormats:
                    logger.info(f"    Expected formats: {action.expectedDocumentFormats}")
                if action.execParameters.get('documentList'):
                    logger.info(f"    Input documents: {action.execParameters['documentList']}")
            
            # Log the complete action plan
            logger.info("=== GENERATED ACTION PLAN ===")
            logger.info(f"Task: {task_step.objective}")
            logger.info(f"Total actions: {len(valid_actions)}")
            
            # Log the RAW AI-generated action plan JSON for debugging
            logger.info("=== RAW AI ACTION PLAN JSON ===")
            logger.info(f"AI Response with parsed actions: {prompt}")
            logger.info("=== END RAW AI ACTION PLAN JSON ===")
            
            return valid_actions
        except Exception as e:
            logger.error(f"Error in generateTaskActions: {str(e)}")
            return []

    async def executeTask(self, task_step, workflow, context, task_index=None, total_tasks=None) -> TaskResult:
        """Execute all actions for a task step, with state management and retries."""
        logger.info(f"=== STARTING TASK {task_index or '?'}: {task_step.objective} ===")
        
        # Create database log entry for task start in format expected by frontend
        if task_index is not None:
            if total_tasks is not None:
                self.chatInterface.createWorkflowLog({
                    "workflowId": workflow.id,
                    "message": f"Executing task {task_index}/{total_tasks}",
                    "type": "info"
                })
            else:
                self.chatInterface.createWorkflowLog({
                    "workflowId": workflow.id,
                    "message": f"Executing task {task_index}/?",
                    "type": "info"
                })
            
            # Create a task start message for the user
            task_progress = f"{task_index}/{total_tasks}" if total_tasks is not None else str(task_index)
            task_start_message = {
                "workflowId": workflow.id,
                "role": "assistant",
                "message": f"🚀 Starting Task {task_progress}\n\nObjective: {task_step.objective}",
                "status": "step",
                "sequenceNr": len(workflow.messages) + 1,
                "publishedAt": datetime.now(UTC).isoformat(),
                "documentsLabel": f"task_{task_index}_start",
                "documents": []
            }
            
            message = self.chatInterface.createWorkflowMessage(task_start_message)
            if message:
                workflow.messages.append(message)
                logger.info(f"Task start message created for task {task_index}")
        
        state = TaskExecutionState(task_step)
        retry_context = context
        max_retries = state.max_retries
        for attempt in range(max_retries):
            logger.info(f"Task execution attempt {attempt+1}/{max_retries}")
            
            # Check workflow status before starting task execution
            self._checkWorkflowStopped()
            
            actions = await self.generateTaskActions(task_step, workflow, previous_results=retry_context.previous_results, enhanced_context=retry_context)
            if not actions:
                logger.error("No actions defined for task step, aborting task execution")
                break
            
            # Log total actions count for this task
            total_actions = len(actions)
            logger.info(f"Task {task_index or '?'} has {total_actions} actions")
            
            action_results = []
            for action_idx, action in enumerate(actions):
                # Check workflow status before each action execution
                self._checkWorkflowStopped()
                
                # Log action start in format expected by frontend
                action_number = action_idx + 1
                logger.info(f"Task {task_index} - Starting action {action_number}/{total_actions}")
                
                # Create database log entry for action start
                self.chatInterface.createWorkflowLog({
                    "workflowId": workflow.id,
                    "message": f"Task {task_index} - Starting action {action_number}/{total_actions}",
                    "type": "info"
                })
                
                # Create an action start message for the user
                action_start_message = {
                    "workflowId": workflow.id,
                    "role": "assistant",
                    "message": f"⚡ Task {task_index} - Action {action_number}/{total_actions}\n\nMethod: {action.execMethod}.{action.execAction}",
                    "status": "step",
                    "sequenceNr": len(workflow.messages) + 1,
                    "publishedAt": datetime.now(UTC).isoformat(),
                    "documentsLabel": f"action_{action_number}_start",
                    "documents": []
                }
                
                message = self.chatInterface.createWorkflowMessage(action_start_message)
                if message:
                    workflow.messages.append(message)
                    logger.info(f"Action start message created for action {action_number}")
                
                # Pass action index to executeSingleAction with task context
                result = await self.executeSingleAction(action, workflow, task_step, task_index, action_number, total_actions)
                action_results.append(result)
                if result.success:
                    state.addSuccessfulAction(result)
                else:
                    state.addFailedAction(result)
            
            # Check workflow status before review
            self._checkWorkflowStopped()
            
            review_result = await self.reviewTaskCompletion(task_step, actions, action_results, workflow)
            success = review_result.status == 'success'
            feedback = review_result.reason
            error = None if success else review_result.reason
            if success:
                logger.info(f"=== TASK {task_index or '?'} COMPLETED SUCCESSFULLY: {task_step.objective} ===")
                
                # Create database log entry for task completion
                if total_tasks is not None:
                    self.chatInterface.createWorkflowLog({
                        "workflowId": workflow.id,
                        "message": f"🎯 Task {task_index}/{total_tasks} completed",
                        "type": "success"
                    })
                else:
                    self.chatInterface.createWorkflowLog({
                        "workflowId": workflow.id,
                        "message": f"🎯 Task {task_index}/? completed",
                        "type": "success"
                    })
                
                # Create a task completion message for the user
                task_progress = f"{task_index}/{total_tasks}" if total_tasks is not None else str(task_index)
                task_completion_message = {
                    "workflowId": workflow.id,
                    "role": "assistant",
                    "message": f"🎯 Task {task_progress} Completed Successfully!\n\nObjective: {task_step.objective}\n\nFeedback: {feedback or 'Task completed successfully'}",
                    "status": "step",
                    "sequenceNr": len(workflow.messages) + 1,
                    "publishedAt": datetime.now(UTC).isoformat(),
                    "documentsLabel": f"task_{task_index}_completion",
                    "documents": []
                }
                
                message = self.chatInterface.createWorkflowMessage(task_completion_message)
                if message:
                    workflow.messages.append(message)
                    logger.info(f"Task completion message created for task {task_index}")
                
                return TaskResult(
                    taskId=task_step.id,
                    status=TaskStatus.COMPLETED,
                    success=True,
                    feedback=feedback,
                    error=None
                )
            elif review_result.status == 'retry' and state.canRetry():
                logger.warning(f"Task step '{task_step.objective}' requires retry: {review_result.improvements}")
                state.incrementRetryCount()
                retry_context.retry_count = state.retry_count
                retry_context.improvements = review_result.improvements
                retry_context.previous_action_results = action_results
                retry_context.previous_review_result = review_result
                retry_context.is_regeneration = True
                retry_context.failure_patterns = state.getFailurePatterns()
                retry_context.failed_actions = state.failed_actions
                retry_context.successful_actions = state.successful_actions
                continue
            else:
                logger.error(f"=== TASK {task_index or '?'} FAILED: {task_step.objective} after {attempt+1} attempts ===")
                
                # Create user-facing error message for task failure
                error_message = f"❌ Task {task_index or '?'} - '{task_step.objective}' failed after {attempt+1} attempts\n\n"
                error_message += f"Objective: {task_step.objective}\n\n"
                
                # Add specific error details if available
                if error:
                    error_message += f"Error: {error}\n\n"
                
                # Add retry information
                error_message += f"Attempts: {attempt+1}\n"
                error_message += f"Status: Will retry automatically\n\n"
                error_message += "The system will attempt to retry this task. Please wait..."
                
                # Create workflow message for user
                message_data = {
                    "workflowId": workflow.id,
                    "role": "assistant",
                    "message": error_message,
                    "status": "step",
                    "sequenceNr": len(workflow.messages) + 1,
                    "publishedAt": datetime.now(UTC).isoformat(),
                    "actionId": None,
                    "actionMethod": "task",
                    "actionName": "task_retry",
                    "documentsLabel": None,
                    "documents": []
                }
                
                try:
                    message = self.chatInterface.createWorkflowMessage(message_data)
                    if message:
                        workflow.messages.append(message)
                        logger.info(f"Created user-facing retry message for failed task: {task_step.objective}")
                    else:
                        logger.error(f"Failed to create user-facing retry message for failed task: {task_step.objective}")
                except Exception as e:
                    logger.error(f"Error creating user-facing retry message: {str(e)}")
                
                return TaskResult(
                    taskId=task_step.id,
                    status=TaskStatus.FAILED,
                    success=False,
                    feedback=feedback,
                    error=error
                )
        logger.error(f"=== TASK {task_index or '?'} FAILED AFTER ALL RETRIES: {task_step.objective} ===")
        
        # Create user-facing error message for task failure
        error_message = f"❌ Task {task_index or '?'} - '{task_step.objective}' failed after all retries\n\n"
        error_message += f"Objective: {task_step.objective}\n\n"
        
        # Add specific error details if available
        if error and error != "Task failed after all retries.":
            error_message += f"Error: {error}\n\n"
        
        # Add retry information
        error_message += f"Retries attempted: {retry_context.retry_count if retry_context else 'Unknown'}\n"
        error_message += f"Status: Task failed permanently\n\n"
        error_message += "Please check the connection and try again, or contact support if the issue persists."
        
        # Create workflow message for user
        message_data = {
            "workflowId": workflow.id,
            "role": "assistant",
            "message": error_message,
            "status": "step",
            "sequenceNr": len(workflow.messages) + 1,
            "publishedAt": datetime.now(UTC).isoformat(),
            "actionId": None,
            "actionMethod": "task",
            "actionName": "task_failure",
            "documentsLabel": None,
            "documents": []
        }
        
        try:
            message = self.chatInterface.createWorkflowMessage(message_data)
            if message:
                workflow.messages.append(message)
                logger.info(f"Created user-facing error message for failed task: {task_step.objective}")
            else:
                logger.error(f"Failed to create user-facing error message for failed task: {task_step.objective}")
        except Exception as e:
            logger.error(f"Error creating user-facing error message: {str(e)}")
        
        return TaskResult(
            taskId=task_step.id,
            status=TaskStatus.FAILED,
            success=False,
            feedback="Task failed after all retries.",
            error="Task failed after all retries."
        )

    async def reviewTaskCompletion(self, task_step, task_actions, action_results, workflow):
        try:
            # Check workflow status before reviewing task completion
            self._checkWorkflowStopped()
            
            review_context = ReviewContext(
                task_step=task_step,
                action_results=action_results,
                workflow=workflow,
                step_result={
                    'successful_actions': sum(1 for result in action_results if result.success),
                    'total_actions': len(action_results),
                    'results': [result.data.get('result', '') for result in action_results if result.success],
                    'errors': [result.error for result in action_results if not result.success]
                }
            )
            # Check workflow status before calling AI service
            self._checkWorkflowStopped()
            
            # Use promptFactory for review prompt
            prompt = await createResultReviewPrompt(review_context)
            response = await self.service.callAiTextAdvanced(prompt)
            # Inline parseReviewResponse logic here
            json_start = response.find('{')
            json_end = response.rfind('}') + 1
            if json_start == -1 or json_end == 0:
                raise ValueError("No JSON found in review response")
            json_str = response[json_start:json_end]
            try:
                review = json.loads(json_str)
            except Exception as e:
                logger.error(f"Error parsing review response JSON: {str(e)}")
                review = {}
            if 'status' not in review:
                raise ValueError("Review response missing 'status' field")
            review.setdefault('status', 'unknown')
            review.setdefault('reason', 'No reason provided')
            review.setdefault('quality_score', 5)
            
            # Ensure improvements is a list
            improvements = review.get('improvements', [])
            if isinstance(improvements, str):
                # Split string into list if it's a single improvement
                improvements = [improvements.strip()] if improvements.strip() else []
            elif not isinstance(improvements, list):
                improvements = []
            
            # Ensure all list fields are properly typed
            met_criteria = review.get('met_criteria', [])
            if not isinstance(met_criteria, list):
                met_criteria = []
                
            unmet_criteria = review.get('unmet_criteria', [])
            if not isinstance(unmet_criteria, list):
                unmet_criteria = []
            
            review_result = ReviewResult(
                status=review.get('status', 'unknown'),
                reason=review.get('reason', 'No reason provided'),
                improvements=improvements,
                quality_score=review.get('quality_score', 5),
                missing_outputs=[],
                met_criteria=met_criteria,
                unmet_criteria=unmet_criteria,
                confidence=review.get('confidence', 0.5)
            )
            
            # Enhanced validation logging
            logger.info(f"VALIDATION RESULT - Task: '{task_step.objective}' - Status: {review_result.status.upper()}, Quality: {review_result.quality_score}/10")
            if review_result.status == 'success':
                logger.info(f"VALIDATION SUCCESS - Task completed successfully")
                if review_result.met_criteria:
                    logger.info(f"Met criteria: {', '.join(review_result.met_criteria)}")
            elif review_result.status == 'retry':
                logger.warning(f"VALIDATION RETRY - Task requires retry: {review_result.improvements}")
                if review_result.unmet_criteria:
                    logger.warning(f"Unmet criteria: {', '.join(review_result.unmet_criteria)}")
            else:
                logger.error(f"VALIDATION FAILED - Task failed: {review_result.reason}")
            
            return review_result
        except Exception as e:
            logger.error(f"Error in reviewTaskCompletion: {str(e)}")
            return ReviewResult(
                status='failed',
                reason=str(e),
                quality_score=0
            )

    async def prepareTaskHandover(self, task_step, task_actions, review_result, workflow):
        try:
            # Check workflow status before preparing task handover
            self._checkWorkflowStopped()
            
            # Log handover status summary
            if hasattr(review_result, 'status'):
                status = review_result.status
                if hasattr(review_result, 'met_criteria'):
                    met = review_result.met_criteria
                else:
                    met = []
                
                
            
            handover_data = {
                'task_id': task_step.id,
                'task_description': task_step.objective,
                'actions': [action.to_dict() for action in task_actions],
                'review_result': review_result.to_dict() if hasattr(review_result, 'to_dict') else review_result,
                'workflow_id': workflow.id,
                'handover_time': datetime.now(UTC).isoformat()
            }
            logger.info(f"Prepared handover for task {task_step.id} in workflow {workflow.id}")
            return handover_data
        except Exception as e:
            logger.error(f"Error in prepareTaskHandover: {str(e)}")
            return {'error': str(e)}

    # --- Helper action handling methods ---

    async def executeSingleAction(self, action, workflow, task_step, task_index=None, action_index=None, total_actions=None):
        """Execute a single action and return ActionResult with enhanced document processing"""
        try:
            # Check workflow status before executing action
            self._checkWorkflowStopped()
            
            # Use passed indices or fallback to '?'
            task_num = task_index if task_index is not None else '?'
            action_num = action_index if action_index is not None else '?'
            
            logger.info(f"=== TASK {task_num} ACTION {action_num}: {action.execMethod}.{action.execAction} ===")
            
            # Log input parameters
            input_docs = action.execParameters.get('documentList', [])
            input_connections = action.execParameters.get('connections', [])
            logger.info(f"Input documents: {input_docs} (type: {type(input_docs)})")
            if input_connections:
                logger.info(f"Input connections: {input_connections}")
            
            # Log all action parameters for debugging
            logger.info(f"All action parameters: {action.execParameters}")
            
            enhanced_parameters = action.execParameters.copy()
            if action.expectedDocumentFormats:
                enhanced_parameters['expectedDocumentFormats'] = action.expectedDocumentFormats
                logger.info(f"Expected formats: {action.expectedDocumentFormats}")
            
            # Check workflow status before executing the action
            self._checkWorkflowStopped()
            
            result = await self.service.executeAction(
                methodName=action.execMethod,
                actionName=action.execAction,
                parameters=enhanced_parameters
            )
            result_label = action.execResultLabel
            
            # Process documents from the action result
            created_documents = []
            if result.success:
                created_documents = self.documentGenerator.createDocumentsFromActionResult(result, action, workflow)
                action.setSuccess()
                action.result = result.data.get("result", "")
                action.execResultLabel = result_label
                await self.createActionMessage(action, result, workflow, result_label, created_documents, task_step, task_index)
                
                # Log action results
                logger.info(f"✓ Action completed successfully")
                
                # Create database log entry for action completion
                if total_actions is not None:
                    self.chatInterface.createWorkflowLog({
                        "workflowId": workflow.id,
                        "message": f"✅ Task {task_num} - Action {action_num}/{total_actions} completed",
                        "type": "success"
                    })
                else:
                    self.chatInterface.createWorkflowLog({
                        "workflowId": workflow.id,
                        "message": f"✅ Task {task_num} - Action {action_num}/? completed",
                        "type": "success"
                    })
                
                if created_documents:
                    logger.info(f"Output documents ({len(created_documents)}):")
                    for i, doc in enumerate(created_documents):
                        if hasattr(doc, 'filename'):
                            logger.info(f"  {i+1}. {doc.filename}")
                        elif isinstance(doc, dict) and 'filename' in doc:
                            logger.info(f"  {i+1}. {doc['filename']}")
                        else:
                            logger.info(f"  {i+1}. {type(doc).__name__}")
                    
                    # Log document details for debugging
                    logger.info("Document details:")
                    for i, doc in enumerate(created_documents):
                        if hasattr(doc, 'filename'):
                            logger.info(f"  Doc {i+1}: filename={doc.filename}, type={type(doc)}")
                            if hasattr(doc, 'id'):
                                logger.info(f"    ID: {doc.id}")
                            if hasattr(doc, 'fileId'):
                                logger.info(f"    File ID: {doc.fileId}")
                        elif isinstance(doc, dict):
                            logger.info(f"  Doc {i+1}: dict with keys: {list(doc.keys())}")
                else:
                    logger.info("Output: No documents created")
            else:
                action.setError(result.error or "Action execution failed")
                logger.error(f"✗ Action failed: {result.error}")
                
                # ⚠️ IMPORTANT: Create error message for failed actions so user can see what went wrong
                await self.createActionMessage(action, result, workflow, result_label, [], task_step, task_index)
                
                # Create database log entry for action failure
                if total_actions is not None:
                    self.chatInterface.createWorkflowLog({
                        "workflowId": workflow.id,
                        "message": f"❌ Task {task_num} - Action {action_num}/{total_actions} failed: {result.error}",
                        "type": "error"
                    })
                else:
                    self.chatInterface.createWorkflowLog({
                        "workflowId": workflow.id,
                        "message": f"❌ Task {task_num} - Action {action_num}/? failed: {result.error}",
                        "type": "error"
                    })
            
            # Extract document filenames for the ActionResult
            document_filenames = []
            for doc in created_documents:
                if hasattr(doc, 'filename'):
                    document_filenames.append(doc.filename)
                elif isinstance(doc, dict) and 'filename' in doc:
                    document_filenames.append(doc['filename'])
            
            # Also include the original documents from the service result for validation
            original_documents = result.data.get("documents", [])
            
            # Log action summary
            logger.info(f"=== TASK {task_num} ACTION {action_num} COMPLETED ===")
            
            return ActionResult(
                success=result.success,
                data={
                    "result": result.data.get("result", ""),
                    "documents": created_documents,  # Include actual document objects in data
                    "actionId": action.id,
                    "actionMethod": action.execMethod,
                    "actionName": action.execAction,
                    "resultLabel": result_label
                },
                documents=document_filenames,  # Keep as filenames for the documents field
                metadata={
                    "actionId": action.id,
                    "actionMethod": action.execMethod,
                    "actionName": action.execAction,
                    "resultLabel": result_label
                },
                validation={},
                error=result.error or ""
            )
        except Exception as e:
            logger.error(f"Error executing single action: {str(e)}")
            action.setError(str(e))
            return ActionResult(
                success=False,
                data={
                    "actionId": action.id,
                    "actionMethod": action.execMethod,
                    "actionName": action.execAction,
                    "documents": []
                },
                metadata={
                    "actionId": action.id,
                    "actionMethod": action.execMethod,
                    "actionName": action.execAction
                },
                validation={},
                error=str(e)
            )

    async def createActionMessage(self, action, result, workflow, result_label=None, created_documents=None, task_step=None, task_index=None):
        """Create and store a message for the action result in the workflow with enhanced document processing"""
        try:
            # Check workflow status before creating action message
            self._checkWorkflowStopped()
            
            if result_label is None:
                result_label = action.execResultLabel
            
            # Use provided documents or process them if not provided
            if created_documents is None:
                created_documents = self.documentGenerator.createDocumentsFromActionResult(result, action, workflow)
            
            # Log delivered documents
            if created_documents:
                logger.info(f"Result label: {result_label} - {len(created_documents)} documents")
            else:
                logger.info(f"Result label: {result_label} - No documents")
            
            # Create a more meaningful message that includes task context
            task_objective = task_step.objective if task_step else 'Unknown task'
            
            # Build a user-friendly message based on success/failure
            if result.success:
                if created_documents and len(created_documents) > 0:
                    doc_names = [doc.filename if hasattr(doc, 'filename') else str(doc) for doc in created_documents[:3]]
                    if len(created_documents) > 3:
                        doc_names.append(f"... and {len(created_documents) - 3} more")
                    
                    message_text = f"✅ Task {task_index or '?'} - Action {action.execMethod}.{action.execAction} completed\n\nObjective: {task_objective}\n\nGenerated {len(created_documents)} document(s): {', '.join(doc_names)}"
                else:
                    message_text = f"✅ Task {task_index or '?'} - Action {action.execMethod}.{action.execAction} completed\n\nObjective: {task_objective}\n\nAction executed successfully"
            else:
                # ⚠️ FAILURE MESSAGE - Show error details to user
                error_details = result.error if result.error else "Unknown error occurred"
                message_text = f"❌ Task {task_index or '?'} - Action {action.execMethod}.{action.execAction} failed\n\nObjective: {task_objective}\n\nError: {error_details}\n\nPlease check the connection and try again."
            
            message_data = {
                "workflowId": workflow.id,
                "role": "assistant",
                "message": message_text,
                "status": "step",
                "sequenceNr": len(workflow.messages) + 1,
                "publishedAt": datetime.now(UTC).isoformat(),
                "actionId": action.id,
                "actionMethod": action.execMethod,
                "actionName": action.execAction,
                "documentsLabel": result_label,
                "documents": created_documents
            }
            
            # Add debugging for error messages
            if not result.success:
                logger.info(f"Creating ERROR message: {message_text}")
                logger.info(f"Message data: {message_data}")
            
            message = self.chatInterface.createWorkflowMessage(message_data)
            if message:
                workflow.messages.append(message)
                logger.info(f"Message created: {action.execMethod}.{action.execAction}")
            else:
                logger.error(f"Failed to create workflow message for action {action.execMethod}.{action.execAction}")
        except Exception as e:
            logger.error(f"Error creating action message: {str(e)}")

    # --- Helper validation methods ---

    def _validateTaskPlan(self, task_plan: Dict[str, Any]) -> bool:
        try:

            
            if not isinstance(task_plan, dict):
                logger.error("Task plan is not a dictionary")
                return False
                
            if 'tasks' not in task_plan or not isinstance(task_plan['tasks'], list):
                logger.error(f"Task plan missing 'tasks' field or not a list. Found: {type(task_plan.get('tasks', 'MISSING'))}")
                return False
                
            # First pass: collect all task IDs to validate dependencies
            task_ids = set()
            for task in task_plan['tasks']:
                if not isinstance(task, dict):
                    logger.error(f"Task is not a dictionary: {type(task)}")
                    return False
                if 'id' not in task:
                    logger.error(f"Task missing 'id' field: {task}")
                    return False
                task_ids.add(task['id'])
            
            # Second pass: validate each task
            for i, task in enumerate(task_plan['tasks']):
    
                
                if not isinstance(task, dict):
                    logger.error(f"Task {i} is not a dictionary: {type(task)}")
                    return False
                    
                required_fields = ['id', 'objective', 'success_criteria']
                missing_fields = [field for field in required_fields if field not in task]
                if missing_fields:
                    logger.error(f"Task {i} missing required fields: {missing_fields}")
                    return False
                    
                # Check for duplicate IDs (shouldn't happen after first pass, but safety check)
                if task['id'] in task_ids and list(task_plan['tasks']).count(task['id']) > 1:
                    logger.error(f"Task {i} has duplicate ID: {task['id']}")
                    return False
                
                dependencies = task.get('dependencies', [])
                if not isinstance(dependencies, list):
                    logger.error(f"Task {i} dependencies is not a list: {type(dependencies)}")
                    return False
                    
                for dep in dependencies:
                    if dep not in task_ids and dep != 'task_0':
                        logger.error(f"Task {i} has invalid dependency: {dep} (available: {list(task_ids) + ['task_0']})")
                        return False
                        
            logger.info(f"Task plan validation successful with {len(task_ids)} tasks")
            return True
            
        except Exception as e:
            logger.error(f"Error validating task plan: {str(e)}")
            return False

    def _validateActions(self, actions: List[Dict[str, Any]], context) -> bool:
        try:
            if not isinstance(actions, list):
                logger.error("Actions must be a list")
                return False
            if len(actions) == 0:
                logger.warning("No actions generated")
                return False
            for i, action in enumerate(actions):
                if not isinstance(action, dict):
                    logger.error(f"Action {i} must be a dictionary")
                    return False
                required_fields = ['method', 'action', 'parameters', 'resultLabel']
                missing_fields = []
                for field in required_fields:
                    if field not in action or not action[field]:
                        missing_fields.append(field)
                if missing_fields:
                    logger.error(f"Action {i} missing required fields: {missing_fields}")
                    return False
                result_label = action.get('resultLabel', '')
                if not result_label.startswith('task'):
                    logger.error(f"Action {i} result label must start with 'task': {result_label}")
                    return False
                parameters = action.get('parameters', {})
                if not isinstance(parameters, dict):
                    logger.error(f"Action {i} parameters must be a dictionary")
                    return False
            logger.info(f"Successfully validated {len(actions)} actions")
            return True
        except Exception as e:
            logger.error(f"Error validating actions: {str(e)}")
            return False