The chunker caches only a model's tokenizer.json in the embeddings cache.
FastEmbed counts any cached snapshot as the model, so it never downloaded
the ONNX graph and every load failed with NO_SUCHFILE. The loader now
checks the files FastEmbed needs and fetches them first when they are
missing; offline it leaves them for FastEmbed to report.
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.
About 85 call sites read a setting as getattr(settings, "NAME", fallback),
each carrying its own copy of the default. Every one of those names is a
field with a default on the model, so the fallback could never apply to
the real settings object; it only masked drift. Two had drifted:
- OPENAI_PROMPT_CACHE_KEY defaults to True on the model but the reader
fell back to False, and two test stubs relied on that.
- SharePoint's MICROSOFT_AUTHORITY fallback to
https://login.microsoftonline.com/<tenant> never fired, because the
attribute always exists (as None), so MSAL got authority=None. The
connector now derives the tenant authority when the setting is unset,
as its test always assumed.
Four places read EMBEDDINGS_KEY straight from os.environ, skipping the
"None"/"" normalisation the model applies; they read the setting now.
Test stubs that replaced a module's settings with a SimpleNamespace list
every setting the code under test reads.
- Ship tiktoken's cl100k_base inside the package and build the encoding
from it, so token counting never downloads anything.
- Default EMBEDDINGS_CACHE_DIR to <data home>/models instead of FastEmbed's
temp dir, and read tokenizer.json and repo metadata from that cache, so
a model downloads once and survives reboots.
- TTS_PROVIDER=none and STT_PROVIDER=none switch the speech features off:
the endpoints return 404, audio files fail to ingest with a clear
message, /api/config reports tts_available/stt_available, and the UI
hides the Speak and microphone buttons.
- Drop the Google Fonts Roboto import from the web UI.
- prefetch-models fills the cache the app reads; verify-offline checks the
packaged encoding.
- Docs: new Air-Gapped Deployment guide, settings and cache notes.
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.
arc53-machine