Files
sientia-dataops-laborious-l…/laborious/worker/worker.py
vitor-aignosi 98ea2a7f75 SIENTIAPDE-1110
Update dependencies and enhance logging in activities; bump version in requirements and values.yaml
2025-06-27 09:17:24 -03:00

105 lines
3.3 KiB
Python

from temporalio import workflow, client
from temporalio.worker import Worker
with workflow.unsafe.imports_passed_through():
import os
import sys
import asyncio
from laborious.workflows.predictions_batch import PredictionsBatch
from laborious.workflows.sub_workflows.prediction_process import PredictionProcess
from laborious.workflows.sub_workflows.format_and_export_prediction import \
FormatAndExportPrediction
from laborious.activities.activities import Activities
from laborious.utils.connectors_config import (
build_postgres_config,
build_mlflow_config,
build_opc_config
)
from sientia_do.notifications.handlers import NotificationHandler
from sientia_do.temporal.utils.logger import get_logger
async def main():
host = os.getenv('TEMPORAL_HOST', 'localhost:7233')
logger = get_logger(__name__)
logger.info('Starting Worker...')
logger.info('Starting Notification Handler...')
notification_handler = NotificationHandler(
servers=os.getenv('KAFKA_BOOTSTRAP_SERVERS', 'http://localhost:9092'),
logger=logger,
project_name=os.getenv('PROJECT_NAME', 'laborious'),
)
logger.info('Starting Activities...')
activities = Activities(
postgres_config=build_postgres_config(),
mlflow_config=build_mlflow_config(),
opc_config=build_opc_config(),
logger=logger,
notification_handler=notification_handler
)
logger.info('Starting Temporal Client...')
temporal_client = await client.Client.connect(
target_host=host,
namespace=os.getenv('TEMPORAL_NAMESPACE', 'default')
)
logger.info('Starting Workers...')
workers = [
Worker(
temporal_client,
task_queue='predictions_batch-queue',
workflows=[PredictionsBatch, PredictionProcess,
FormatAndExportPrediction],
activities=[
# MLFlow
activities.request_predict,
activities.request_transform,
# Gates
activities.input_gate,
activities.mlflow_response_gate,
activities.mlflow_content_gate,
activities.format_prediction,
activities.format_default_prediction,
activities.get_last_timestamp,
# OPC
activities.write_opc_data,
# Postgres
activities.load_custom_query,
activities.repeat_last_prediction,
activities.export_data_to_postgres
]
)
]
handlers = []
for w in workers:
handlers.append(w.run())
logger.info('Workers started successfully')
try:
# This will run the workers and wait for them to complete.
# If an exception occurs in any of the worker handlers, it will be propagated here.
await asyncio.gather(*handlers)
except BaseException as e:
logger.error(f"An unhandled exception occurred: {e}")
finally:
if notification_handler:
notification_handler.shutdown()
if activities:
activities.shutdown()
# Exit with a non-zero status code to indicate failure to Kubernetes
sys.exit(1)
if __name__ == '__main__':
asyncio.run(main())