mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-04 16:13:23 +00:00
Alex
adb6963523
- CI installs the backend requirements from docsgpt/; the old cd into
application/ silently installed nothing.
- The root .dockerignore re-admits only application/__init__.py. An upgraded
checkout may still hold gitignored application/{inputs,indexes,vectors,.env}
from the old layout, and the directory rule shipped them into the image.
- The compose files keep the host bind mounts on application/{indexes,inputs,
vectors}, so an upgrade does not start with empty data. The move comes with
the packaging work, together with an upgrade note.
- The alias loader puts the real docsgpt spec back on the shared module object
after import (the import machinery stamped the alias spec on it, which made
importlib.reload rename the module and skip re-execution) and delegates
get_code/get_source/get_filename to the target loader, so
python -m application.<name> runs.
- Each legacy application.* task name is registered as its own task object,
a subclass carrying the old name. Registering the same object under two
keys made Celery's tracer log every run under whichever name it built last.
- The redbeat key prefix stays redbeat:docsgpt:; the three schedule_syncs
entries get stable names instead. redbeat tracks its static entries and
deletes the ones that vanish from beat_schedule at start-up, and rewrites the
task path of named entries in place, so neither a prefix bump nor a cleanup
pass is needed (checked against redbeat 2.4.2 with a seeded Redis).
70 lines
2.9 KiB
Python
70 lines
2.9 KiB
Python
from kombu import Queue
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from docsgpt.core.settings import settings
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# Pydantic loads .env into ``settings`` but does not inject values into
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# ``os.environ`` — read directly from settings so beat startup (which
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# imports this module before any explicit env load) sees a real URL.
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broker_url = settings.CELERY_BROKER_URL
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result_backend = settings.CELERY_RESULT_BACKEND
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task_serializer = 'json'
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result_serializer = 'json'
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accept_content = ['json']
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# Autodiscover tasks
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imports = (
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'docsgpt.api.user.tasks',
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'docsgpt.vectorstore.embeddings_tasks',
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)
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# Project-scoped queue so a stray sibling worker on the same broker
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# (other repo, same default ``celery`` queue) can't grab DocsGPT tasks.
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task_default_queue = "docsgpt"
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task_default_exchange = "docsgpt"
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task_default_routing_key = "docsgpt"
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# Route document parsing to a dedicated queue so a parse enqueued from inside a
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# Celery worker (headless/scheduled agent) is served by a separate parsing worker
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# and never self-deadlocks the awaiting worker. The tool also passes the queue at
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# apply_async time, so this routing is the default for any other enqueuer.
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# Query embedding gets its own queue for the same reason parsing does: a query
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# waiting behind a multi-minute ingest is a query that has timed out. A bare
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# worker still consumes it, but its concurrency is shared -- run a separate
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# ``-Q embeddings`` worker to actually isolate query latency from ingest.
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task_routes = {
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"docsgpt.api.user.tasks.parse_document": {"queue": settings.DOCUMENT_PARSE_QUEUE},
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"docsgpt.vectorstore.embeddings_tasks.embed_texts": {"queue": settings.EMBEDDINGS_QUEUE},
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}
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# Declare every queue so a bare ``celery worker`` (no -Q) consumes ALL of them —
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# the default worker does the whole job, parsing included. Operators who want
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# heavy OCR isolated run one worker with ``-Q docsgpt`` and another with
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# ``-Q parsing``. (dict.fromkeys dedupes if DOCUMENT_PARSE_QUEUE == "docsgpt".)
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task_queues = tuple(
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Queue(name)
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for name in dict.fromkeys(
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["docsgpt", settings.DOCUMENT_PARSE_QUEUE, settings.EMBEDDINGS_QUEUE]
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)
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)
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beat_scheduler = "redbeat.RedBeatScheduler"
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redbeat_redis_url = broker_url
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redbeat_key_prefix = "redbeat:docsgpt:"
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redbeat_lock_timeout = 90
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# Survive worker SIGKILL/OOM without silently dropping in-flight tasks.
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task_acks_late = True
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task_reject_on_worker_lost = True
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worker_prefetch_multiplier = settings.CELERY_WORKER_PREFETCH_MULTIPLIER
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broker_transport_options = {"visibility_timeout": settings.CELERY_VISIBILITY_TIMEOUT}
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result_expires = 86400 * 7
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task_track_started = True
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# Recycle the prefork worker child to bound native-heap growth from
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# docling/torch parsing. Left unset (Celery's unlimited default) when 0.
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if settings.CELERY_WORKER_MAX_MEMORY_PER_CHILD > 0:
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worker_max_memory_per_child = settings.CELERY_WORKER_MAX_MEMORY_PER_CHILD
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if settings.CELERY_WORKER_MAX_TASKS_PER_CHILD > 0:
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worker_max_tasks_per_child = settings.CELERY_WORKER_MAX_TASKS_PER_CHILD
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