912 lines
No EOL
45 KiB
Python
912 lines
No EOL
45 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
|
|
|
|
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": get_utc_timestamp(),
|
|
"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": get_utc_timestamp(),
|
|
"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": get_utc_timestamp(),
|
|
"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": get_utc_timestamp(),
|
|
"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": get_utc_timestamp(),
|
|
"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': [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 hasattr(result, 'documents') and result.documents else 0,
|
|
'documents': result.documents if hasattr(result, 'documents') and result.documents else []
|
|
}
|
|
for i, result in enumerate(action_results)
|
|
]
|
|
}
|
|
)
|
|
# 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': 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)}
|
|
|
|
# --- 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 hasattr(first_doc, 'documentData') and isinstance(first_doc.documentData, dict):
|
|
action.result = first_doc.documentData.get("result", "")
|
|
elif hasattr(first_doc, 'documentData') and 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):
|
|
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"
|
|
})
|
|
|
|
# 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 if hasattr(result, 'documents') else []
|
|
|
|
# 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")
|
|
|
|
# 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": get_utc_timestamp(),
|
|
"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
|
|
|
|
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 hasattr(first_doc, 'documentData') and isinstance(first_doc.documentData, dict):
|
|
return first_doc.documentData.get("result", "")
|
|
elif hasattr(first_doc, 'documentData') and isinstance(first_doc.documentData, str):
|
|
return first_doc.documentData
|
|
else:
|
|
return "" |