780 lines
35 KiB
Python
780 lines
35 KiB
Python
from typing import Dict, Any, List, Optional
|
|
import logging
|
|
from datetime import datetime, UTC
|
|
import uuid
|
|
import asyncio
|
|
|
|
from modules.datamodels.datamodelChat import (
|
|
UserInputRequest,
|
|
ChatMessage,
|
|
ChatWorkflow,
|
|
ChatDocument,
|
|
WorkflowResult
|
|
)
|
|
from modules.datamodels.datamodelWorkflow import TaskItem, TaskStatus, TaskContext
|
|
from modules.workflows.processing.workflowProcessor import WorkflowProcessor, WorkflowStoppedException
|
|
from modules.shared.timezoneUtils import get_utc_timestamp
|
|
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
class WorkflowManager:
|
|
"""Manager for workflow processing and coordination"""
|
|
|
|
def __init__(self, services):
|
|
self.services = services
|
|
self.workflowProcessor = None
|
|
|
|
# Exported functions
|
|
|
|
async def workflowStart(self, userInput: UserInputRequest, workflowId: Optional[str] = None, workflowMode: str = "React") -> ChatWorkflow:
|
|
"""Starts a new workflow or continues an existing one, then launches processing."""
|
|
try:
|
|
# Debug log to check workflowMode parameter
|
|
logger.info(f"WorkflowManager received workflowMode: {workflowMode}")
|
|
currentTime = self.services.utils.getUtcTimestamp()
|
|
|
|
if workflowId:
|
|
workflow = self.services.workflow.getWorkflow(workflowId)
|
|
if not workflow:
|
|
raise ValueError(f"Workflow {workflowId} not found")
|
|
|
|
# Store workflow in services for reference (don't overwrite the workflow service)
|
|
self.services.currentWorkflow = workflow
|
|
|
|
if workflow.status == "running":
|
|
logger.info(f"Stopping running workflow {workflowId} before processing new prompt")
|
|
workflow.status = "stopped"
|
|
workflow.lastActivity = currentTime
|
|
self.services.workflow.updateWorkflow(workflowId, {
|
|
"status": "stopped",
|
|
"lastActivity": currentTime
|
|
})
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflowId,
|
|
"message": "Workflow stopped for new prompt",
|
|
"type": "info",
|
|
"status": "stopped",
|
|
"progress": 100
|
|
})
|
|
await asyncio.sleep(0.1)
|
|
|
|
newRound = workflow.currentRound + 1
|
|
self.services.workflow.updateWorkflow(workflowId, {
|
|
"status": "running",
|
|
"lastActivity": currentTime,
|
|
"currentRound": newRound,
|
|
"workflowMode": workflowMode # Update workflow mode for existing workflows
|
|
})
|
|
|
|
workflow = self.services.workflow.getWorkflow(workflowId)
|
|
if not workflow:
|
|
raise ValueError(f"Failed to reload workflow {workflowId} after update")
|
|
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflowId,
|
|
"message": f"Workflow resumed (round {workflow.currentRound}) with mode: {workflowMode}",
|
|
"type": "info",
|
|
"status": "running",
|
|
"progress": 0
|
|
})
|
|
|
|
# CRITICAL: Update the workflow object's workflowMode attribute for immediate use
|
|
workflow.workflowMode = workflowMode
|
|
else:
|
|
workflowData = {
|
|
"name": "New Workflow",
|
|
"status": "running",
|
|
"startedAt": currentTime,
|
|
"lastActivity": currentTime,
|
|
"currentRound": 0,
|
|
"currentTask": 0,
|
|
"currentAction": 0,
|
|
"totalTasks": 0,
|
|
"totalActions": 0,
|
|
"mandateId": self.services.user.mandateId,
|
|
"messageIds": [],
|
|
"workflowMode": workflowMode,
|
|
"maxSteps": 5 if workflowMode == "React" else 1, # Set maxSteps for React mode
|
|
"stats": {
|
|
"processingTime": None,
|
|
"tokenCount": None,
|
|
"bytesSent": None,
|
|
"bytesReceived": None,
|
|
"successRate": None,
|
|
"errorCount": None
|
|
}
|
|
}
|
|
|
|
workflow = self.services.workflow.createWorkflow(workflowData)
|
|
logger.info(f"Created workflow with mode: {getattr(workflow, 'workflowMode', 'NOT_SET')}")
|
|
logger.info(f"Workflow data passed: {workflowData.get('workflowMode', 'NOT_IN_DATA')}")
|
|
workflow.currentRound = 1
|
|
self.services.workflow.updateWorkflow(workflow.id, {"currentRound": 1})
|
|
self.services.workflow.updateWorkflowStats(workflow.id, bytesSent=0, bytesReceived=0)
|
|
|
|
# Store workflow in services for reference (don't overwrite the workflow service)
|
|
self.services.currentWorkflow = workflow
|
|
|
|
# Start workflow processing asynchronously
|
|
asyncio.create_task(self._workflowProcess(userInput, workflow))
|
|
|
|
return workflow
|
|
except Exception as e:
|
|
logger.error(f"Error starting workflow: {str(e)}")
|
|
raise
|
|
|
|
async def workflowStop(self, workflowId: str) -> ChatWorkflow:
|
|
"""Stops a running workflow."""
|
|
try:
|
|
workflow = self.services.workflow.getWorkflow(workflowId)
|
|
if not workflow:
|
|
raise ValueError(f"Workflow {workflowId} not found")
|
|
|
|
workflow.status = "stopped"
|
|
workflow.lastActivity = self.services.utils.getUtcTimestamp()
|
|
self.services.workflow.updateWorkflow(workflowId, {
|
|
"status": "stopped",
|
|
"lastActivity": workflow.lastActivity
|
|
})
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflowId,
|
|
"message": "Workflow stopped",
|
|
"type": "warning",
|
|
"status": "stopped",
|
|
"progress": 100
|
|
})
|
|
return workflow
|
|
except Exception as e:
|
|
logger.error(f"Error stopping workflow: {str(e)}")
|
|
raise
|
|
|
|
# Main processor
|
|
|
|
async def _workflowProcess(self, userInput: UserInputRequest, workflow: ChatWorkflow) -> None:
|
|
"""Process a workflow with user input"""
|
|
try:
|
|
# Store the current user prompt in services for easy access throughout the workflow
|
|
self.services.rawUserPrompt = userInput.prompt
|
|
self.services.currentUserPrompt = userInput.prompt
|
|
self.workflowProcessor = WorkflowProcessor(self.services, workflow)
|
|
message = await self._sendFirstMessage(userInput, workflow)
|
|
task_plan = await self._planTasks(userInput, workflow)
|
|
workflow_result = await self._executeTasks(task_plan, workflow)
|
|
await self._processWorkflowResults(workflow, workflow_result, message)
|
|
|
|
except WorkflowStoppedException:
|
|
self._handleWorkflowStop(workflow)
|
|
|
|
except Exception as e:
|
|
self._handleWorkflowError(workflow, e)
|
|
|
|
# Helper functions
|
|
|
|
async def _sendFirstMessage(self, userInput: UserInputRequest, workflow: ChatWorkflow) -> ChatMessage:
|
|
"""Send first message to start workflow"""
|
|
try:
|
|
self.workflowProcessor._checkWorkflowStopped(workflow)
|
|
|
|
# Create initial message using interface
|
|
# For first user message, include round info in the user context label
|
|
round_num = workflow.currentRound
|
|
task_num = 0
|
|
action_num = 0
|
|
context_label = f"round{round_num}_usercontext"
|
|
|
|
messageData = {
|
|
"workflowId": workflow.id,
|
|
"role": "user",
|
|
"message": userInput.prompt,
|
|
"status": "first",
|
|
"sequenceNr": 1,
|
|
"publishedAt": self.services.utils.getUtcTimestamp(),
|
|
"documentsLabel": context_label,
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "pending",
|
|
"actionProgress": "pending"
|
|
}
|
|
|
|
# Create message first to get messageId
|
|
message = self.services.workflow.createMessage(messageData)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Clear trace log for new workflow session
|
|
self.workflowProcessor.clearTraceLog()
|
|
|
|
# Add documents if any, now with messageId
|
|
if userInput.listFileId:
|
|
# Process file IDs and add to message data
|
|
documents = await self._processFileIds(userInput.listFileId, message.id)
|
|
message.documents = documents
|
|
# Update the message with documents in database
|
|
self.services.workflow.updateMessage(message.id, {"documents": [doc.to_dict() for doc in documents]})
|
|
|
|
# Analyze the user's input to extract intent and offload bulky context into documents
|
|
try:
|
|
analyzerPrompt = (
|
|
"You are an input analyzer. Split the user's message into:\n"
|
|
"1) intent: the user's core request in one concise paragraph, normalized to the user's language.\n"
|
|
"2) contextItems: supportive data to attach as separate documents if significantly larger than the intent. "
|
|
"Include large literal data blocks, long lists/tables, code/JSON blocks, quoted transcripts, CSV fragments, or detailed specs. "
|
|
"Keep URLs in the intent unless they include large pasted content.\n\n"
|
|
"Rules:\n"
|
|
"- If total content length (intent + data) is less than 10% of the model's max tokens, do not extract; "
|
|
"return an empty contextItems and keep a compact, self-contained intent.\n"
|
|
"- If content exceeds that, move bulky parts into contextItems, keeping the intent short and clear.\n"
|
|
"- Preserve critical references (URLs, filenames) in the intent.\n"
|
|
"- Normalize the intent to the detected language. If mixed-language, use the primary detected language and normalize.\n\n"
|
|
"Output JSON only (no markdown):\n"
|
|
"{\n"
|
|
" \"detectedLanguage\": \"en\",\n"
|
|
" \"intent\": \"Concise normalized request...\",\n"
|
|
" \"contextItems\": [\n"
|
|
" {\n"
|
|
" \"title\": \"User context 1\",\n"
|
|
" \"mimeType\": \"text/plain\",\n"
|
|
" \"content\": \"Full extracted content block here\"\n"
|
|
" }\n"
|
|
" ]\n"
|
|
"}\n\n"
|
|
f"User message:\n{userInput.prompt}"
|
|
)
|
|
|
|
# Call AI analyzer
|
|
aiResponse = await self.services.ai.callAi(prompt=analyzerPrompt)
|
|
|
|
detectedLanguage = None
|
|
intentText = userInput.prompt
|
|
contextItems = []
|
|
|
|
# Parse analyzer response (JSON expected)
|
|
try:
|
|
import json
|
|
jsonStart = aiResponse.find('{') if aiResponse else -1
|
|
jsonEnd = aiResponse.rfind('}') + 1 if aiResponse else 0
|
|
if jsonStart != -1 and jsonEnd > jsonStart:
|
|
parsed = json.loads(aiResponse[jsonStart:jsonEnd])
|
|
detectedLanguage = parsed.get('detectedLanguage') or None
|
|
if parsed.get('intent'):
|
|
intentText = parsed.get('intent')
|
|
contextItems = parsed.get('contextItems') or []
|
|
except Exception:
|
|
contextItems = []
|
|
|
|
# Update services state
|
|
if detectedLanguage and isinstance(detectedLanguage, str):
|
|
self._setUserLanguage(detectedLanguage)
|
|
self.services.currentUserPrompt = intentText or userInput.prompt
|
|
|
|
# Telemetry (sizes and counts)
|
|
try:
|
|
inputSize = len(userInput.prompt.encode('utf-8')) if userInput and userInput.prompt else 0
|
|
outputSize = len(aiResponse.encode('utf-8')) if aiResponse else 0
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflow.id,
|
|
"message": f"User prompt analyzed (input {inputSize} bytes, output {outputSize} bytes, items {len(contextItems)})",
|
|
"type": "info",
|
|
"status": "running",
|
|
"progress": 0
|
|
})
|
|
except Exception:
|
|
pass
|
|
|
|
# Create and attach documents for context items
|
|
if contextItems and isinstance(contextItems, list):
|
|
created_docs = []
|
|
for idx, item in enumerate(contextItems):
|
|
try:
|
|
title = item.get('title') if isinstance(item, dict) else None
|
|
mime = item.get('mimeType') if isinstance(item, dict) else None
|
|
content = item.get('content') if isinstance(item, dict) else None
|
|
if not content:
|
|
continue
|
|
fileName = (title or f"user_context_{idx+1}.txt").strip()
|
|
mimeType = (mime or "text/plain").strip()
|
|
|
|
# Create file in component storage
|
|
content_bytes = content.encode('utf-8')
|
|
file_item = self.services.interfaceDbComponent.createFile(
|
|
name=fileName,
|
|
mimeType=mimeType,
|
|
content=content_bytes
|
|
)
|
|
# Persist file data
|
|
self.services.interfaceDbComponent.createFileData(file_item.id, content_bytes)
|
|
|
|
# Collect file info
|
|
file_info = self.services.workflow.getFileInfo(file_item.id)
|
|
from modules.datamodels.datamodelChat import ChatDocument as _ChatDocument
|
|
doc = _ChatDocument(
|
|
messageId=message.id,
|
|
fileId=file_item.id,
|
|
fileName=file_info.get("fileName", fileName) if file_info else fileName,
|
|
fileSize=file_info.get("size", len(content_bytes)) if file_info else len(content_bytes),
|
|
mimeType=file_info.get("mimeType", mimeType) if file_info else mimeType
|
|
)
|
|
# Persist document record
|
|
self.services.interfaceDbChat.createDocument(doc.to_dict())
|
|
created_docs.append(doc)
|
|
except Exception:
|
|
continue
|
|
|
|
if created_docs:
|
|
# Attach to message and persist
|
|
if not message.documents:
|
|
message.documents = []
|
|
message.documents.extend(created_docs)
|
|
# Ensure label is user_context for discoverability
|
|
message.documentsLabel = context_label
|
|
self.services.workflow.updateMessage(message.id, {
|
|
"documents": [d.to_dict() for d in message.documents],
|
|
"documentsLabel": context_label
|
|
})
|
|
except Exception as e:
|
|
logger.warning(f"Prompt analysis failed or skipped: {str(e)}")
|
|
|
|
return message
|
|
else:
|
|
raise Exception("Failed to create first message")
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error sending first message: {str(e)}")
|
|
raise
|
|
|
|
async def _planTasks(self, userInput: UserInputRequest, workflow: ChatWorkflow):
|
|
"""Generate task plan for workflow execution"""
|
|
handling = self.workflowProcessor
|
|
# Generate task plan first (shared for both modes)
|
|
task_plan = await handling.generateTaskPlan(userInput.prompt, workflow)
|
|
if not task_plan or not task_plan.tasks:
|
|
raise Exception("No tasks generated in task plan.")
|
|
workflow_mode = getattr(workflow, 'workflowMode', 'Actionplan')
|
|
logger.info(f"Workflow object attributes: {workflow.__dict__ if hasattr(workflow, '__dict__') else 'No __dict__'}")
|
|
logger.info(f"Executing workflow mode={workflow_mode} with {len(task_plan.tasks)} tasks")
|
|
return task_plan
|
|
|
|
async def _executeTasks(self, task_plan, workflow: ChatWorkflow) -> WorkflowResult:
|
|
"""Execute all tasks in the task plan"""
|
|
handling = self.workflowProcessor
|
|
total_tasks = len(task_plan.tasks)
|
|
all_task_results: List = []
|
|
previous_results: List[str] = []
|
|
|
|
for idx, task_step in enumerate(task_plan.tasks):
|
|
current_task_index = idx + 1
|
|
logger.info(f"Task {current_task_index}/{total_tasks}: {task_step.objective}")
|
|
|
|
# Build TaskContext (mode-specific behavior is inside WorkflowProcessor)
|
|
task_context = TaskContext(
|
|
task_step=task_step,
|
|
workflow=workflow,
|
|
workflow_id=workflow.id,
|
|
available_documents=None,
|
|
available_connections=None,
|
|
previous_results=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=[],
|
|
criteria_progress={
|
|
'met_criteria': set(),
|
|
'unmet_criteria': set(),
|
|
'attempt_history': []
|
|
}
|
|
)
|
|
|
|
task_result = await handling.executeTask(task_step, workflow, task_context, current_task_index, total_tasks)
|
|
handover_data = await handling.prepareTaskHandover(task_step, [], task_result, workflow)
|
|
all_task_results.append({
|
|
'task_step': task_step,
|
|
'task_result': task_result,
|
|
'handover_data': handover_data
|
|
})
|
|
if task_result.success and task_result.feedback:
|
|
previous_results.append(task_result.feedback)
|
|
|
|
return WorkflowResult(
|
|
status="completed",
|
|
completed_tasks=len(all_task_results),
|
|
total_tasks=total_tasks,
|
|
execution_time=0.0,
|
|
final_results_count=len(all_task_results)
|
|
)
|
|
|
|
async def _processWorkflowResults(self, workflow: ChatWorkflow, workflow_result: WorkflowResult, initial_message: ChatMessage) -> None:
|
|
"""Process workflow results and create appropriate messages"""
|
|
try:
|
|
try:
|
|
self.workflowProcessor._checkWorkflowStopped(workflow)
|
|
except WorkflowStoppedException:
|
|
logger.info(f"Workflow {workflow.id} was stopped during result processing")
|
|
|
|
# Create final stopped message
|
|
stopped_message = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": "🛑 Workflow stopped by user",
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": self.services.utils.getUtcTimestamp(),
|
|
"documentsLabel": "workflow_stopped",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "stopped",
|
|
"actionProgress": "stopped"
|
|
}
|
|
message = self.services.workflow.createMessage(stopped_message)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Update workflow status to stopped
|
|
workflow.status = "stopped"
|
|
workflow.lastActivity = self.services.utils.getUtcTimestamp()
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "stopped",
|
|
"lastActivity": workflow.lastActivity
|
|
})
|
|
return
|
|
|
|
if workflow_result.status == 'stopped':
|
|
# Create stopped message
|
|
stopped_message = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": "🛑 Workflow stopped by user",
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": self.services.utils.getUtcTimestamp(),
|
|
"documentsLabel": "workflow_stopped",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "stopped",
|
|
"actionProgress": "stopped"
|
|
}
|
|
message = self.services.workflow.createMessage(stopped_message)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Update workflow status to stopped
|
|
workflow.status = "stopped"
|
|
workflow.lastActivity = self.services.utils.getUtcTimestamp()
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "stopped",
|
|
"lastActivity": workflow.lastActivity,
|
|
"totalTasks": workflow.totalTasks,
|
|
"totalActions": workflow.totalActions
|
|
})
|
|
|
|
# Add stopped log entry
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflow.id,
|
|
"message": "Workflow stopped by user",
|
|
"type": "warning",
|
|
"status": "stopped",
|
|
"progress": 100
|
|
})
|
|
return
|
|
elif workflow_result.status == 'failed':
|
|
# Create error message
|
|
error_message = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": f"Workflow failed: {workflow_result.error or 'Unknown error'}",
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": self.services.utils.getUtcTimestamp(),
|
|
"documentsLabel": "workflow_failure",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "fail",
|
|
"actionProgress": "fail"
|
|
}
|
|
message = self.services.workflow.createMessage(error_message)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Update workflow status to failed
|
|
workflow.status = "failed"
|
|
workflow.lastActivity = self.services.utils.getUtcTimestamp()
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "failed",
|
|
"lastActivity": workflow.lastActivity,
|
|
"totalTasks": workflow.totalTasks,
|
|
"totalActions": workflow.totalActions
|
|
})
|
|
|
|
# Add failed log entry
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflow.id,
|
|
"message": f"Workflow failed: {workflow_result.error or 'Unknown error'}",
|
|
"type": "error",
|
|
"status": "failed",
|
|
"progress": 100
|
|
})
|
|
return
|
|
|
|
# For successful workflows, send detailed completion message
|
|
await self._sendLastMessage(workflow)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error processing workflow results: {str(e)}")
|
|
# Create error message
|
|
error_message = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": f"Error processing workflow results: {str(e)}",
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": self.services.utils.getUtcTimestamp(),
|
|
"documentsLabel": "workflow_error",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "fail",
|
|
"actionProgress": "fail"
|
|
}
|
|
message = self.services.workflow.createMessage(error_message)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Update workflow status to failed
|
|
workflow.status = "failed"
|
|
workflow.lastActivity = self.services.utils.getUtcTimestamp()
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "failed",
|
|
"lastActivity": workflow.lastActivity,
|
|
"totalTasks": workflow.totalTasks,
|
|
"totalActions": workflow.totalActions
|
|
})
|
|
|
|
async def _sendLastMessage(self, workflow: ChatWorkflow) -> None:
|
|
"""Send last message to complete workflow (only for successful workflows)"""
|
|
try:
|
|
# Safety check: ensure this is only called for successful workflows
|
|
if workflow.status in ['stopped', 'failed']:
|
|
logger.warning(f"Attempted to send last message for {workflow.status} workflow {workflow.id}")
|
|
return
|
|
|
|
# Generate feedback
|
|
feedback = await self._generateWorkflowFeedback(workflow)
|
|
|
|
# Create last message using interface
|
|
messageData = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": feedback,
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": self.services.utils.getUtcTimestamp(),
|
|
"documentsLabel": "workflow_feedback",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "success",
|
|
"actionProgress": "success"
|
|
}
|
|
|
|
# Create message using interface
|
|
message = self.services.workflow.createMessage(messageData)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Update workflow status to completed
|
|
workflow.status = "completed"
|
|
workflow.lastActivity = self.services.utils.getUtcTimestamp()
|
|
|
|
# Update workflow in database
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "completed",
|
|
"lastActivity": workflow.lastActivity
|
|
})
|
|
|
|
# Add completion log entry
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflow.id,
|
|
"message": "Workflow completed",
|
|
"type": "success",
|
|
"status": "completed",
|
|
"progress": 100
|
|
})
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error sending last message: {str(e)}")
|
|
raise
|
|
|
|
async def _generateWorkflowFeedback(self, workflow: ChatWorkflow) -> str:
|
|
"""Generate feedback message for workflow completion"""
|
|
try:
|
|
self.workflowProcessor._checkWorkflowStopped(workflow)
|
|
|
|
# Count messages by role
|
|
user_messages = [msg for msg in workflow.messages if msg.role == 'user']
|
|
assistant_messages = [msg for msg in workflow.messages if msg.role == 'assistant']
|
|
|
|
# Generate summary feedback
|
|
feedback = f"Workflow completed.\n\n"
|
|
feedback += f"Processed {len(user_messages)} user inputs and generated {len(assistant_messages)} responses.\n"
|
|
|
|
# Add final status
|
|
if workflow.status == "completed":
|
|
feedback += "All tasks completed successfully."
|
|
elif workflow.status == "partial":
|
|
feedback += "Some tasks completed with partial success."
|
|
else:
|
|
feedback += f"Workflow status: {workflow.status}"
|
|
|
|
return feedback
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error generating workflow feedback: {str(e)}")
|
|
return "Workflow processing completed."
|
|
|
|
def _handleWorkflowStop(self, workflow: ChatWorkflow) -> None:
|
|
"""Handle workflow stop exception"""
|
|
logger.info("Workflow stopped by user")
|
|
|
|
# Update workflow status to stopped
|
|
workflow.status = "stopped"
|
|
workflow.lastActivity = get_utc_timestamp()
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "stopped",
|
|
"lastActivity": workflow.lastActivity,
|
|
"totalTasks": workflow.totalTasks,
|
|
"totalActions": workflow.totalActions
|
|
})
|
|
|
|
# Create final stopped message
|
|
stopped_message = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": "🛑 Workflow stopped by user",
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": get_utc_timestamp(),
|
|
"documentsLabel": "workflow_stopped",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "pending",
|
|
"actionProgress": "pending"
|
|
}
|
|
message = self.services.workflow.createMessage(stopped_message)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Add log entry
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflow.id,
|
|
"message": "Workflow stopped by user",
|
|
"type": "warning",
|
|
"status": "stopped",
|
|
"progress": 100
|
|
})
|
|
|
|
def _handleWorkflowError(self, workflow: ChatWorkflow, error: Exception) -> None:
|
|
"""Handle workflow error exception"""
|
|
logger.error(f"Workflow processing error: {str(error)}")
|
|
|
|
# Update workflow status to failed
|
|
workflow.status = "failed"
|
|
workflow.lastActivity = get_utc_timestamp()
|
|
self.services.workflow.updateWorkflow(workflow.id, {
|
|
"status": "failed",
|
|
"lastActivity": workflow.lastActivity,
|
|
"totalTasks": workflow.totalTasks,
|
|
"totalActions": workflow.totalActions
|
|
})
|
|
|
|
# Create error message
|
|
error_message = {
|
|
"workflowId": workflow.id,
|
|
"role": "assistant",
|
|
"message": f"Workflow processing failed: {str(error)}",
|
|
"status": "last",
|
|
"sequenceNr": len(workflow.messages) + 1,
|
|
"publishedAt": get_utc_timestamp(),
|
|
"documentsLabel": "workflow_error",
|
|
"documents": [],
|
|
# Add workflow context fields
|
|
"roundNumber": workflow.currentRound,
|
|
"taskNumber": 0,
|
|
"actionNumber": 0,
|
|
# Add progress status
|
|
"taskProgress": "fail",
|
|
"actionProgress": "fail"
|
|
}
|
|
message = self.services.workflow.createMessage(error_message)
|
|
if message:
|
|
workflow.messages.append(message)
|
|
|
|
# Add error log entry
|
|
self.services.workflow.createLog({
|
|
"workflowId": workflow.id,
|
|
"message": f"Workflow failed: {str(error)}",
|
|
"type": "error",
|
|
"status": "failed",
|
|
"progress": 100
|
|
})
|
|
|
|
raise
|
|
|
|
async def _processFileIds(self, fileIds: List[str], messageId: str = None) -> List[ChatDocument]:
|
|
"""Process file IDs from existing files and return ChatDocument objects"""
|
|
documents = []
|
|
for fileId in fileIds:
|
|
try:
|
|
# Get file info from unified workflow service
|
|
fileInfo = self.services.workflow.getFileInfo(fileId)
|
|
if fileInfo:
|
|
# Create document directly with all file attributes
|
|
document = ChatDocument(
|
|
id=str(uuid.uuid4()),
|
|
messageId=messageId or "", # Use provided messageId or empty string as fallback
|
|
fileId=fileId,
|
|
fileName=fileInfo.get("fileName", "unknown"),
|
|
fileSize=fileInfo.get("size", 0),
|
|
mimeType=fileInfo.get("mimeType", "application/octet-stream")
|
|
)
|
|
documents.append(document)
|
|
logger.info(f"Processed file ID {fileId} -> {document.fileName}")
|
|
else:
|
|
logger.warning(f"No file info found for file ID {fileId}")
|
|
except Exception as e:
|
|
logger.error(f"Error processing file ID {fileId}: {str(e)}")
|
|
return documents
|
|
|
|
def _setUserLanguage(self, language: str) -> None:
|
|
"""Set user language for the service center"""
|
|
self.services.user.language = language
|