Move GET /api/events, the remote-device command stream and artifact
downloads from Flask to Starlette routes mounted ahead of the Flask
catch-all. On Flask each held an a2wsgi threadpool slot for as long as
its response stayed open, and because uvicorn drops writes after a
client disconnects, a closed tab never released it.
- asgi_auth: one JWT/OIDC gate for Starlette routes; the chat reconnect
reader uses it too
- ClosingStreamingResponse closes the body iterator and releases the
SSE slot or file handle even when the client leaves before the first
frame
- AsyncTopic liveness probe replaces the sync client's socket_timeout
guard against half-open pub/sub sockets
- ASYNC_REDIS_MAX_CONNECTIONS sizes the async Redis pool; every open
stream holds a connection and redis-py defaults to 100
pip install docsgpt now brings the web UI with it: `docsgpt api` serves the
API and the UI on one port.
- scripts/build_frontend.sh builds the frontend into docsgpt/static
(gitignored) the way the frontend image does: .env.development as the
production baseline, and index.html loading /config.js ahead of the
bundle. hatch admits the directory into the wheel and the sdist through
`artifacts`; the package workflows run the script before `uv build` and
fail if the wheel lacks the UI. The backend image keeps ignoring it.
- docsgpt/ui.py serves the build in front of Flask: files as they are,
hashed assets immutable, Flask's own path prefixes (taken from its URL map,
so new blueprints need no registration) passed through, every other GET
rendered as index.html for the client-side router. /config.js is generated
per request with VITE_API_HOST and VITE_BASE_URL set to the page's origin,
VITE_* environment variables winning. SERVE_UI=false leaves the API alone.
- docsgpt api configures gunicorn in code (gunicorn.app.base.Application)
instead of rewriting sys.argv, so the SIGUSR2 re-exec that gunicorn uses
for zero-downtime upgrades runs the docsgpt console script again and
works; verified with a live handover.
- Docs: the pip page says the UI is included, that DOCSGPT_HOME and
DOCSGPT_ENV_FILE are process environment variables rather than .env
entries, and the settings page describes SERVE_UI.
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