in_worker() read task_join_will_block, which eventlet and gevent leave unset,
and the task's current_worker_task, which they scope to one greenlet -- so a
greenlet a task spawned in those pools still took the web-process branch and
dispatched to its own worker, where it could queue behind its parent and time
out.
The worker's own startup now records it: worker_init fires in every worker's
main process before the pool starts (where solo, threads, eventlet and gevent
run tasks, and what prefork children fork from), and worker_process_init in
each prefork child. worker_ready would be too late -- prefork children are
forked before it fires. The two existing checks stay for anything that runs
tasks without that startup.
Celery records the executing task on the thread that runs it, so a thread that
task starts sees none. The embeddings client and read_document both decided
"am I in a worker?" from that alone, and from any other thread took the
web-process branch: dispatch to the worker they were running in and block on
the result. Celery refuses that get() ("Never call result.get() within a
task!"), so the embed failed and latched the 30s dispatch cooldown for every
caller after it; with joins allowed, read_document would instead wait on a
parsing queue only its own busy process serves.
Threads inside tasks are not hypothetical: per-source retrieval fans out to a
pool, so a scheduled or webhook agent searching several sources embedded from
pool threads. Graph extraction did too, which failed every chunk of a build.
in_worker() in celery_init answers for the whole process. Celery's
task_join_will_block is process-wide and set for every blocking pool (prefork,
solo, threads) -- exactly the condition under which dispatch-and-wait goes
wrong; eventlet/gevent leave it unset, so the task's own thread still counts
through current_worker_task. Verified with real workers on each blocking pool:
from a thread a task started, the old check dispatched and hit the error, the
new one embedded locally.
- The post-task reclaim skip recognises the legacy application.* embed name,
so query embeds queued by the previous release do not pay a full collect.
- The Azure compose file mounts host data on /app/{indexes,inputs,vectors},
where the process actually reads and writes; it mounted /app/application/...
before the rename and /app/docsgpt/... after it, and nothing wrote to either.
- The offline image check triggers on docsgpt/requirements*.txt again;
dependabot's pip entry points at docsgpt/.
- install_hint() and its docstring name docsgpt/requirements-<extra>.txt;
the test asserts the full path.
- application/vectors/ stays ignored: the compose files still mount it.
- The durability QA script quiets the docsgpt logger tree.
- Upgrade note: the three renamed source-sync entries start their timers
from the upgrade.
- 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).
The backend import package is now docsgpt, the name it will carry on PyPI;
application was far too generic to install into anyone's site-packages.
git mv plus a mechanical rewrite of every import, dotted string and path
reference: 734 Python files, the compose files, Dockerfile, workflows, docs,
setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage
config, .gitignore. Behaviour is unchanged.
Kept for one release:
- A top-level application package whose meta-path finder resolves
application.x.y to the already-imported docsgpt.x.y object, so old imports
and entry points (celery -A application.app.celery,
uvicorn application.asgi:asgi_app) keep working with a FutureWarning.
- Celery registers every application.* task name as an alias of its
docsgpt.* task on start-up, so messages queued by the previous release still
run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries
the previous release wrote are left unread instead of firing twice.
The backend image builds from the repository root (docker build -f
docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore
allow-lists docsgpt/ and application/ and keeps caches, local data, .env
files, the sample index files and the Dockerfile out. Compose and the image
workflows point at the new context.
Alex