[supervisord]
nodaemon=true
user=root
logfile=/var/log/supervisord.log

# Indexing is the heaviest job, also requires some CPU intensive steps
# Cannot place this in Celery for now because Celery must run as a single process (see note below)
# Indexing uses multi-processing to speed things up
[program:document_indexing]
environment=CURRENT_PROCESS_IS_AN_INDEXING_JOB=true,LOG_FILE_NAME=document_indexing
command=python danswer/background/update.py
redirect_stderr=true
autorestart=true


# Background jobs that must be run async due to long time to completion
# NOTE: due to an issue with Celery + SQLAlchemy 
# (https://github.com/celery/celery/issues/7007#issuecomment-1740139367)
# we must use the threads pool instead of the default prefork pool for now
# in order to avoid intermittent errors like:
# `billiard.exceptions.WorkerLostError: Worker exited prematurely: signal 11 (SIGSEGV)`. 
#
# This means workers will not be able take advantage of multiple CPU cores 
# on a system, but this should be okay for now since all our celery tasks are
# relatively compute-light (e.g. they tend to just make a bunch of requests to 
# Vespa / Postgres)
[program:celery_worker]
command=celery -A danswer.background.celery.celery_run:celery_app worker 
    --pool=threads
    --concurrency=6 
    --loglevel=INFO 
    --logfile=/var/log/celery_worker_supervisor.log 
    -Q celery,vespa_metadata_sync,connector_deletion
environment=LOG_FILE_NAME=celery_worker
redirect_stderr=true
autorestart=true

# Job scheduler for periodic tasks
[program:celery_beat]
command=celery -A danswer.background.celery.celery_run:celery_app beat 
    --logfile=/var/log/celery_beat_supervisor.log
environment=LOG_FILE_NAME=celery_beat
redirect_stderr=true

# Listens for Slack messages and responds with answers
# for all channels that the DanswerBot has been added to.
# If not setup, this will just fail 5 times and then stop.
# More details on setup here: https://docs.danswer.dev/slack_bot_setup
[program:slack_bot]
command=python danswer/danswerbot/slack/listener.py
environment=LOG_FILE_NAME=slack_bot
redirect_stderr=true
autorestart=true
startretries=5
startsecs=60

# Pushes all logs from the above programs to stdout
# No log rotation here, since it's stdout it's handled by the Docker container logging
[program:log-redirect-handler]
command=tail -qF
    /var/log/document_indexing_info.log
    /var/log/celery_beat_supervisor.log
    /var/log/celery_worker_supervisor.log
    /var/log/celery_beat_debug.log
    /var/log/celery_worker_debug.log
    /var/log/slack_bot_debug.log
stdout_logfile=/dev/stdout
stdout_logfile_maxbytes=0
redirect_stderr=true
autorestart=true