mirror of
https://github.com/danswer-ai/danswer.git
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108 lines
3.6 KiB
Plaintext
108 lines
3.6 KiB
Plaintext
[supervisord]
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nodaemon=true
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user=root
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logfile=/var/log/supervisord.log
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# Indexing is the heaviest job, also requires some CPU intensive steps
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# Cannot place this in Celery for now because Celery must run as a single process (see note below)
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# Indexing uses multi-processing to speed things up
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[program:document_indexing]
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environment=CURRENT_PROCESS_IS_AN_INDEXING_JOB=true
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command=python danswer/background/update.py
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stdout_logfile=/var/log/document_indexing.log
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stdout_logfile_maxbytes=16MB
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redirect_stderr=true
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autorestart=true
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# Background jobs that must be run async due to long time to completion
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# NOTE: due to an issue with Celery + SQLAlchemy
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# (https://github.com/celery/celery/issues/7007#issuecomment-1740139367)
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# we must use the threads pool instead of the default prefork pool for now
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# in order to avoid intermittent errors like:
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# `billiard.exceptions.WorkerLostError: Worker exited prematurely: signal 11 (SIGSEGV)`.
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#
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# This means workers will not be able take advantage of multiple CPU cores
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# on a system, but this should be okay for now since all our celery tasks are
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# relatively compute-light (e.g. they tend to just make a bunch of requests to
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# Vespa / Postgres)
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[program:celery_worker_primary]
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command=celery -A danswer.background.celery.celery_run:celery_app worker
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--pool=threads
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--concurrency=4
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--prefetch-multiplier=1
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--loglevel=INFO
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--hostname=primary@%%n
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-Q celery
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stdout_logfile=/var/log/celery_worker_primary.log
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stdout_logfile_maxbytes=16MB
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redirect_stderr=true
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autorestart=true
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startsecs=10
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stopasgroup=true
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[program:celery_worker_light]
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command=bash -c "celery -A danswer.background.celery.celery_run:celery_app worker \
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--pool=threads \
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--concurrency=${CELERY_WORKER_LIGHT_CONCURRENCY:-24} \
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--prefetch-multiplier=${CELERY_WORKER_LIGHT_PREFETCH_MULTIPLIER:-8} \
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--loglevel=INFO \
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--hostname=light@%%n \
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-Q vespa_metadata_sync,connector_deletion"
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stdout_logfile=/var/log/celery_worker_light.log
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stdout_logfile_maxbytes=16MB
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redirect_stderr=true
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autorestart=true
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startsecs=10
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stopasgroup=true
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[program:celery_worker_heavy]
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command=celery -A danswer.background.celery.celery_run:celery_app worker
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--pool=threads
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--concurrency=4
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--prefetch-multiplier=1
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--loglevel=INFO
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--hostname=heavy@%%n
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-Q connector_pruning
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stdout_logfile=/var/log/celery_worker_heavy.log
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stdout_logfile_maxbytes=16MB
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redirect_stderr=true
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autorestart=true
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startsecs=10
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stopasgroup=true
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# Job scheduler for periodic tasks
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[program:celery_beat]
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command=celery -A danswer.background.celery.celery_run:celery_app beat
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stdout_logfile=/var/log/celery_beat.log
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stdout_logfile_maxbytes=16MB
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redirect_stderr=true
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startsecs=10
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stopasgroup=true
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# Listens for Slack messages and responds with answers
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# for all channels that the DanswerBot has been added to.
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# If not setup, this will just fail 5 times and then stop.
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# More details on setup here: https://docs.danswer.dev/slack_bot_setup
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[program:slack_bot]
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command=python danswer/danswerbot/slack/listener.py
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stdout_logfile=/var/log/slack_bot.log
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stdout_logfile_maxbytes=16MB
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redirect_stderr=true
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autorestart=true
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startretries=5
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startsecs=60
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# Pushes all logs from the above programs to stdout
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# No log rotation here, since it's stdout it's handled by the Docker container logging
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[program:log-redirect-handler]
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command=tail -qF
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/var/log/celery_beat.log
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/var/log/celery_worker_primary.log
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/var/log/celery_worker_light.log
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/var/log/celery_worker_heavy.log
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/var/log/document_indexing.log
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/var/log/slack_bot.log
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stdout_logfile=/dev/stdout
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stdout_logfile_maxbytes = 0 # must be set to 0 when stdout_logfile=/dev/stdout
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autorestart=true
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