gateway/modules/chat/handling/handlingTasks.py

1362 lines
No EOL
67 KiB
Python

# 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 modules.shared.timezoneUtils import get_utc_timestamp
from .executionState import TaskExecutionState
from .promptFactory import (
createTaskPlanningPrompt,
createActionDefinitionPrompt,
createResultReviewPrompt
)
from modules.chat.documents.documentGeneration import DocumentGenerator
import uuid
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)
# Set initial workflow context
self.service.setWorkflowContext(round_number=1, task_number=0, action_number=0)
# Check workflow status before calling AI service
self._checkWorkflowStopped()
# Create proper context object for task planning
# For task planning, we need to create a minimal TaskStep since TaskContext requires it
from modules.interfaces.interfaceChatModel import TaskStep
planning_task_step = TaskStep(
id="planning",
objective=userInput,
dependencies=[],
success_criteria=[],
estimated_complexity="medium"
)
task_planning_context = TaskContext(
task_step=planning_task_step,
workflow=workflow,
workflow_id=workflow.id,
available_documents=available_docs,
available_connections=[],
previous_results=[],
previous_handover=None,
improvements=[],
retry_count=0,
previous_action_results=[],
previous_review_result=None,
is_regeneration=False,
failure_patterns=[],
failed_actions=[],
successful_actions=[]
)
prompt = await self.service.callAiTextAdvanced(
createTaskPlanningPrompt(task_planning_context, self.service)
)
# 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
)
# Set workflow totals for progress tracking
total_tasks = len(tasks)
self.service.setWorkflowTotals(total_tasks=total_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 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 ===")
# PHASE 3: Create chat message containing the task plan
await self.createTaskPlanMessage(task_plan, workflow)
return task_plan
except Exception as e:
logger.error(f"Error in generateTaskPlan: {str(e)}")
raise
async def createTaskPlanMessage(self, task_plan: TaskPlan, workflow):
"""Create a chat message containing the task plan with user-friendly messages"""
try:
# Build task plan summary
task_summary = f"📋 **Task Plan Generated**\n\n"
task_summary += f"**Overview:** {task_plan.overview}\n\n"
task_summary += f"**Total Tasks:** {len(task_plan.tasks)}\n\n"
# Add each task with its user message
for i, task in enumerate(task_plan.tasks):
task_summary += f"**Task {i+1}:** {task.objective}\n"
if task.userMessage:
task_summary += f" 💬 {task.userMessage}\n"
if task.success_criteria:
criteria_str = ', '.join(task.success_criteria)
task_summary += f" ✅ Success Criteria: {criteria_str}\n"
task_summary += "\n"
# Get overall user message from task plan if available
overall_message = task_plan.userMessage
if overall_message:
task_summary += f"**Plan Summary:** {overall_message}\n\n"
# Create workflow message
message_data = {
"workflowId": workflow.id,
"role": "assistant",
"message": task_summary,
"status": "step",
"sequenceNr": len(workflow.messages) + 1,
"publishedAt": get_utc_timestamp(),
"documentsLabel": "task_plan",
"documents": [],
# Add workflow context fields
"roundNumber": 1, # Task plan is always round 1
"taskNumber": 0, # Task plan is before individual tasks
"actionNumber": 0
}
message = self.chatInterface.createWorkflowMessage(message_data)
if message:
workflow.messages.append(message)
logger.info(f"Task plan message created with {len(task_plan.tasks)} tasks")
else:
logger.error("Failed to create task plan message")
except Exception as e:
logger.error(f"Error creating task plan message: {str(e)}")
async def createDocumentContextMessage(self, documents: List, workflow):
"""Create a chat message with enhanced document context and workflow labeling"""
try:
from .promptFactory import createDocumentContextPrompt
# Get user language from service
user_language = self.service.user.language if self.service and self.service.user else 'en'
# Get current workflow context and stats
workflow_context = self.service.getWorkflowContext()
workflow_stats = self.service.getWorkflowStats()
# Build context for the document context prompt
context = {
'documents': documents,
'workflow_context': {
'currentRound': workflow_context.get('currentRound', 1),
'totalTasks': workflow_stats.get('totalTasks', 0),
'currentTask': workflow_context.get('currentTask', 0),
'totalActions': workflow_stats.get('totalActions', 0),
'currentAction': workflow_context.get('currentAction', 0),
'workflowStatus': workflow_stats.get('workflowStatus', 'unknown'),
'workflowId': workflow_stats.get('workflowId', 'unknown')
},
'user_language': user_language
}
# Generate enhanced document context using AI
prompt = createDocumentContextPrompt(context)
response = await self.service.callAiTextAdvanced(prompt)
# Parse the AI response
try:
json_start = response.find('{')
json_end = response.find('}') + 1
if json_start != -1 and json_end > 0:
json_str = response[json_start:json_end]
doc_context = json.loads(json_str)
# Build message from AI response
message_text = f"📄 **Document Context**\n\n"
message_text += f"**Summary:** {doc_context.get('documentSummary', 'No summary available')}\n\n"
message_text += f"**Workflow Progress:** {doc_context.get('workflowProgress', 'No progress info')}\n\n"
# Add workflow context information
current_round = workflow_context.get('currentRound', 1)
current_task = workflow_context.get('currentTask', 0)
total_tasks = workflow_stats.get('totalTasks', 0)
current_action = workflow_context.get('currentAction', 0)
total_actions = workflow_stats.get('totalActions', 0)
message_text += f"**Workflow Context:**\n"
message_text += f"- Round: {current_round}\n"
if total_tasks > 0:
message_text += f"- Task: {current_task}/{total_tasks}\n"
else:
message_text += f"- Task: {current_task}\n"
if total_actions > 0:
message_text += f"- Action: {current_action}/{total_actions}\n"
else:
message_text += f"- Action: {current_action}\n"
message_text += f"- Status: {workflow_stats.get('workflowStatus', 'unknown')}\n\n"
# Add overall user message if available
overall_message = doc_context.get('overallUserMessage')
if overall_message:
message_text += f"💬 {overall_message}\n\n"
# Add document details
document_details = doc_context.get('documentDetails', [])
if document_details:
message_text += "**Document Details:**\n"
for doc_detail in document_details:
message_text += f"- {doc_detail.get('workflowLabel', 'Unknown')}: {doc_detail.get('fileName', 'Unknown file')}\n"
user_msg = doc_detail.get('userMessage')
if user_msg:
message_text += f" 💬 {user_msg}\n"
message_text += "\n"
else:
# Fallback if AI response parsing fails
message_text = f"📄 **Document Context**\n\n"
message_text += f"**Total Documents:** {len(documents)}\n\n"
# Add workflow context information even in fallback
current_round = workflow_context.get('currentRound', 1)
current_task = workflow_context.get('currentTask', 0)
total_tasks = workflow_stats.get('totalTasks', 0)
current_action = workflow_context.get('currentAction', 0)
total_actions = workflow_stats.get('totalActions', 0)
message_text += f"**Workflow Context:**\n"
message_text += f"- Round: {current_round}\n"
if total_tasks > 0:
message_text += f"- Task: {current_task}/{total_tasks}\n"
else:
message_text += f"- Task: {current_task}\n"
if total_actions > 0:
message_text += f"- Action: {current_action}/{total_actions}\n"
else:
message_text += f"- Action: {current_action}\n"
message_text += f"- Status: {workflow_stats.get('workflowStatus', 'unknown')}\n\n"
message_text += "Document context information is available for processing."
except Exception as e:
logger.error(f"Error parsing document context AI response: {str(e)}")
# Fallback message with workflow context
message_text = f"📄 **Document Context**\n\n"
message_text += f"**Total Documents:** {len(documents)}\n\n"
# Add workflow context information in fallback
current_round = workflow_context.get('currentRound', 1)
current_task = workflow_context.get('currentTask', 0)
total_tasks = workflow_stats.get('totalTasks', 0)
current_action = workflow_context.get('currentAction', 0)
total_actions = workflow_stats.get('totalActions', 0)
message_text += f"**Workflow Context:**\n"
message_text += f"- Round: {current_round}\n"
if total_tasks > 0:
message_text += f"- Task: {current_task}/{total_tasks}\n"
else:
message_text += f"- Task: {current_task}\n"
if total_actions > 0:
message_text += f"- Action: {current_action}/{total_actions}\n"
else:
message_text += f"- Action: {current_action}\n"
message_text += f"- Status: {workflow_stats.get('workflowStatus', 'unknown')}\n\n"
message_text += "Document context information is available for processing."
# Create workflow message
message_data = {
"workflowId": workflow.id,
"role": "assistant",
"message": message_text,
"status": "step",
"sequenceNr": len(workflow.messages) + 1,
"publishedAt": get_utc_timestamp(),
"documentsLabel": "document_context",
"documents": documents,
# Add workflow context fields
"roundNumber": workflow_context.get('currentRound', 1),
"taskNumber": workflow_context.get('currentTask', 0),
"actionNumber": workflow_context.get('currentAction', 0)
}
message = self.chatInterface.createWorkflowMessage(message_data)
if message:
workflow.messages.append(message)
logger.info(f"Document context message created with {len(documents)} documents")
else:
logger.error("Failed to create document context message")
except Exception as e:
logger.error(f"Error creating document context message: {str(e)}")
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()
# Create proper context object for action definition
if enhanced_context and isinstance(enhanced_context, TaskContext):
# Use existing TaskContext if provided
action_context = TaskContext(
task_step=enhanced_context.task_step,
workflow=enhanced_context.workflow,
workflow_id=enhanced_context.workflow_id,
available_documents=enhanced_context.available_documents or available_docs,
available_connections=enhanced_context.available_connections or available_connections,
previous_results=enhanced_context.previous_results or previous_results or [],
previous_handover=enhanced_context.previous_handover,
improvements=enhanced_context.improvements or [],
retry_count=enhanced_context.retry_count or 0,
previous_action_results=enhanced_context.previous_action_results or [],
previous_review_result=enhanced_context.previous_review_result,
is_regeneration=enhanced_context.is_regeneration or False,
failure_patterns=enhanced_context.failure_patterns or [],
failed_actions=enhanced_context.failed_actions or [],
successful_actions=enhanced_context.successful_actions or []
)
else:
# Create new context from scratch
action_context = TaskContext(
task_step=task_step,
workflow=workflow,
workflow_id=workflow.id,
available_documents=available_docs,
available_connections=available_connections,
previous_results=previous_results or [],
previous_handover=None,
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(action_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, action_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.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,
# Extract user-friendly message if available
"userMessage": a.get('userMessage', None)
}) 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} ===")
# Update workflow context for this task
if task_index is not None:
self.service.setWorkflowContext(task_number=task_index)
self.service.incrementWorkflowContext('task')
# 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": get_utc_timestamp(),
"documentsLabel": f"task_{task_index}_start",
"documents": [],
# Add workflow context fields
"roundNumber": 1, # Task start is always round 1
"taskNumber": task_index,
"actionNumber": 0
}
# Add user-friendly message if available
if task_step.userMessage:
task_start_message["message"] += f"\n\n💬 {task_step.userMessage}"
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()
# Update retry context with current attempt information
if retry_context:
retry_context.retry_count = attempt + 1
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")
# Set workflow action total for this task
self.service.setWorkflowTotals(total_actions=total_actions)
# Create document context message if documents are available
available_docs = self.service.getAvailableDocuments(workflow)
if available_docs:
await self.createDocumentContextMessage(available_docs, workflow)
action_results = []
for action_idx, action in enumerate(actions):
# Check workflow status before each action execution
self._checkWorkflowStopped()
# Update workflow context for this action
action_number = action_idx + 1
self.service.setWorkflowContext(action_number=action_number)
self.service.incrementWorkflowContext('action')
# Log action start in format expected by frontend
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": get_utc_timestamp(),
"documentsLabel": f"action_{action_number}_start",
"documents": []
}
# Add user-friendly message if available
if action.userMessage:
action_start_message["message"] += f"\n\n💬 {action.userMessage}"
# Add workflow context fields
action_start_message.update({
"roundNumber": 1, # Action start is always round 1
"taskNumber": task_index,
"actionNumber": action_number
})
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": get_utc_timestamp(),
"documentsLabel": f"task_{task_index}_completion",
"documents": [],
# Add workflow context fields
"roundNumber": 1, # Task completion is always round 1
"taskNumber": task_index,
"actionNumber": 0
}
# Add user-friendly message if available
if task_step.userMessage:
task_completion_message["message"] += f"\n\n💬 {task_step.userMessage}"
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()
# Update retry context with retry information
if retry_context:
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": get_utc_timestamp(),
"actionId": None,
"actionMethod": "task",
"actionName": "task_retry",
"documentsLabel": None,
"documents": [],
# Add workflow context fields
"roundNumber": 1, # Task retry is always round 1
"taskNumber": task_index,
"actionNumber": 0
}
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": get_utc_timestamp(),
"actionId": None,
"actionMethod": "task",
"actionName": "task_failure",
"documentsLabel": None,
"documents": [],
# Add workflow context fields
"roundNumber": 1, # Task failure is always round 1
"taskNumber": task_index,
"actionNumber": 0
}
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()
# Create proper context object for result review
review_context = ReviewContext(
task_step=task_step,
task_actions=task_actions,
action_results=action_results,
step_result={
'successful_actions': sum(1 for result in action_results if result.success),
'total_actions': len(action_results),
'results': [self._extractResultText(result) for result in action_results if result.success],
'errors': [result.error for result in action_results if not result.success],
'documents': [
{
'action_index': i,
'documents_count': len(result.documents) if result.documents else 0,
'documents': result.documents if result.documents else []
}
for i, result in enumerate(action_results)
]
},
workflow_id=workflow.id,
previous_results=[]
)
# Check workflow status before calling AI service
self._checkWorkflowStopped()
# Use promptFactory for review prompt
prompt = createResultReviewPrompt(review_context, self.service)
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),
# Extract user-friendly message if available
userMessage=review.get('userMessage', None)
)
# 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
status = review_result.status if review_result else 'unknown'
met = review_result.met_criteria if review_result and review_result.met_criteria else []
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(),
'workflow_id': workflow.id,
'handover_time': get_utc_timestamp()
}
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)}
def createTaskAction(self, actionData: Dict[str, Any]) -> 'TaskAction':
"""Creates a new task action."""
try:
# Ensure ID is present
if "id" not in actionData or not actionData["id"]:
actionData["id"] = f"action_{uuid.uuid4()}"
# Ensure required fields
if "status" not in actionData:
actionData["status"] = TaskStatus.PENDING
if "execMethod" not in actionData:
logger.error("execMethod is required for task action")
return None
if "execAction" not in actionData:
logger.error("execAction is required for task action")
return None
if "execParameters" not in actionData:
actionData["execParameters"] = {}
# Create action in database
createdAction = self.chatInterface.db.recordCreate("taskActions", actionData)
# Convert to TaskAction model
return TaskAction(
id=createdAction["id"],
execMethod=createdAction["execMethod"],
execAction=createdAction["execAction"],
execParameters=createdAction.get("execParameters", {}),
execResultLabel=createdAction.get("execResultLabel"),
expectedDocumentFormats=createdAction.get("expectedDocumentFormats"),
status=createdAction.get("status", TaskStatus.PENDING),
error=createdAction.get("error"),
retryCount=createdAction.get("retryCount", 0),
retryMax=createdAction.get("retryMax", 3),
processingTime=createdAction.get("processingTime"),
timestamp=float(createdAction.get("timestamp", get_utc_timestamp())),
result=createdAction.get("result"),
resultDocuments=createdAction.get("resultDocuments", [])
)
except Exception as e:
logger.error(f"Error creating task action: {str(e)}")
return None
# --- 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()
# Extract result text from documents if available, otherwise use empty string
action.result = ""
if result.documents and len(result.documents) > 0:
# Try to get text content from the first document
first_doc = result.documents[0]
if isinstance(first_doc.documentData, dict):
action.result = first_doc.documentData.get("result", "")
elif isinstance(first_doc.documentData, str):
action.result = first_doc.documentData
# Preserve the action's execResultLabel for document routing
# Action methods should NOT return resultLabel - this is managed by the action handler
if not action.execResultLabel:
logger.warning(f"Action {action.execMethod}.{action.execAction} has no execResultLabel set")
# Always use the action's execResultLabel for message creation to ensure proper document routing
message_result_label = action.execResultLabel
await self.createActionMessage(action, result, workflow, message_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):
logger.info(f" {i+1}. {doc.fileName}")
# Log document details for debugging
logger.info("Document details:")
for i, doc in enumerate(created_documents):
logger.info(f" Doc {i+1}: fileName={doc.fileName}, type={type(doc)}")
logger.info(f" ID: {doc.id}")
logger.info(f" File ID: {doc.fileId}")
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"
})
# Log action summary
logger.info(f"=== TASK {task_num} ACTION {action_num} COMPLETED ===")
# Preserve the original documents field from the method result
# This ensures the standard document format is maintained
original_documents = result.documents
# Extract result text from documents if available
result_text = self._extractResultText(result)
return ActionResult(
success=result.success,
documents=original_documents, # Preserve original documents field from method result
resultLabel=action.execResultLabel, # Always use action's execResultLabel
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,
documents=[], # Empty documents for error case
resultLabel=action.execResultLabel,
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")
# Get current workflow context and stats
workflow_context = self.service.getWorkflowContext()
workflow_stats = self.service.getWorkflowStats()
# 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 for doc in created_documents[:3]]
if len(created_documents) > 3:
doc_names.append(f"... and {len(created_documents) - 3} more")
# Enhanced message with workflow context
message_text = f"✅ **Task {task_index or '?'} - Action {action.execMethod}.{action.execAction} Completed**\n\n"
message_text += f"**Objective:** {task_objective}\n\n"
message_text += f"**Generated {len(created_documents)} document(s):** {', '.join(doc_names)}\n\n"
message_text += f"**Result Label:** {result_label}\n"
# Add comprehensive workflow context
current_round = workflow_context.get('currentRound', 1)
current_task = workflow_context.get('currentTask', 0)
total_tasks = workflow_stats.get('totalTasks', 0)
current_action = workflow_context.get('currentAction', 0)
total_actions = workflow_stats.get('totalActions', 0)
message_text += f"**Workflow Context:**\n"
message_text += f"- Round: {current_round}\n"
if total_tasks > 0:
message_text += f"- Task: {current_task}/{total_tasks}\n"
else:
message_text += f"- Task: {current_task}\n"
if total_actions > 0:
message_text += f"- Action: {current_action}/{total_actions}\n"
else:
message_text += f"- Action: {current_action}\n"
message_text += f"- Status: {workflow_stats.get('workflowStatus', 'unknown')}"
else:
message_text = f"✅ **Task {task_index or '?'} - Action {action.execMethod}.{action.execAction} Completed**\n\n"
message_text += f"**Objective:** {task_objective}\n\n"
message_text += "**Action executed successfully**\n\n"
message_text += f"**Result Label:** {result_label}\n"
# Add comprehensive workflow context
current_round = workflow_context.get('currentRound', 1)
current_task = workflow_context.get('currentTask', 0)
total_tasks = workflow_stats.get('totalTasks', 0)
current_action = workflow_context.get('currentAction', 0)
total_actions = workflow_stats.get('totalActions', 0)
message_text += f"**Workflow Context:**\n"
message_text += f"- Round: {current_round}\n"
if total_tasks > 0:
message_text += f"- Task: {current_task}/{total_tasks}\n"
else:
message_text += f"- Task: {current_task}\n"
if total_actions > 0:
message_text += f"- Action: {current_action}/{total_actions}\n"
else:
message_text += f"- Action: {current_action}\n"
message_text += f"- Status: {workflow_stats.get('workflowStatus', 'unknown')}"
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\n"
message_text += f"**Objective:** {task_objective}\n\n"
message_text += f"**Error:** {error_details}\n\n"
message_text += f"**Result Label:** {result_label}\n"
# Add comprehensive workflow context
current_round = workflow_context.get('currentRound', 1)
current_task = workflow_context.get('currentTask', 0)
total_tasks = workflow_stats.get('totalTasks', 0)
current_action = workflow_context.get('currentAction', 0)
total_actions = workflow_stats.get('totalActions', 0)
message_text += f"**Workflow Context:**\n"
message_text += f"- Round: {current_round}\n"
if total_tasks > 0:
message_text += f"- Task: {current_task}/{total_tasks}\n"
else:
message_text += f"- Task: {current_task}\n"
if total_actions > 0:
message_text += f"- Action: {current_action}/{total_actions}\n"
else:
message_text += f"- Action: {current_action}\n"
message_text += f"- Status: {workflow_stats.get('workflowStatus', 'unknown')}\n\n"
message_text += "Please check the connection and try again."
message_data = {
"workflowId": workflow.id,
"role": "assistant",
"message": message_text,
"status": "step",
"sequenceNr": len(workflow.messages) + 1,
"publishedAt": get_utc_timestamp(),
"actionId": action.id,
"actionMethod": action.execMethod,
"actionName": action.execAction,
"documentsLabel": result_label,
"documents": created_documents,
# Add workflow context fields
"roundNumber": workflow_context.get('currentRound', 1),
"taskNumber": task_index,
"actionNumber": workflow_context.get('currentAction', 0)
}
# Add user-friendly message if available
if action.userMessage:
if result.success:
message_data["message"] += f"\n\n💬 {action.userMessage}"
else:
message_data["message"] += f"\n\n💬 Action was intended to: {action.userMessage}"
# 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('round'):
logger.error(f"Action {i} result label must start with 'round': {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
def _extractResultText(self, result: ActionResult) -> str:
"""Extract result text from ActionResult documents"""
if not result.success or not result.documents:
return ""
# Try to get text content from the first document
first_doc = result.documents[0]
if isinstance(first_doc.documentData, dict):
return first_doc.documentData.get("result", "")
elif isinstance(first_doc.documentData, str):
return first_doc.documentData
return ""