- 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 connector OAuth popup posted the session token to window.opener with
a '*' target origin, so any page that opened the popup received it. An
attacker with an account on a multi-user deployment could start a flow for
their own pending session, get a victim to finish the provider consent, and
receive a token backed by the victim's Drive/SharePoint/Confluence tokens.
- Post popup results only to allowed frontend origins: the callback origin,
OIDC_FRONTEND_URL, the new CONNECTOR_ALLOWED_ORIGINS, and localhost:5173
when the callback runs on a loopback host.
- Render the success page from the callback itself so the token never
appears in a URL; callback-status ignores session_token/user_email params.
- ConnectorAuth accepts messages only from the popup it opened, on the
callback origin reported by /api/connectors/auth.
- /api/connectors/disconnect requires auth and only deletes the caller's
session.
- /api/connectors/sync and /api/remote reject session tokens the caller
does not own.
Fixes#2766
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.
- docsgpt api binds 127.0.0.1 by default, like gunicorn and uvicorn do;
--host 0.0.0.0 exposes it. The docs say so.
- The embedded Milvus and LanceDB defaults derive from the data home, so
they follow DOCSGPT_HOME like the faiss indexes and uploads do. A checkout
run from its root and the Docker image resolve to the same paths as before.
- The docs and the pyproject comment describe the CPU torch install as two
steps (torch and torchvision from the PyTorch CPU index first, then the
docling extra): pip picks the highest version across indexes, so
--extra-index-url only yields the CPU build while that index keeps pace
with PyPI.
- AGENTS.md separates DOCSGPT_HOME (moves the data home) from
DOCSGPT_ENV_FILE (selects the .env file); the docs example uses a password
placeholder.
pip install docsgpt (extras: docling, milvus) installs the backend with a
docsgpt command: api, worker, migrate, prefetch-models, verify-offline,
reembed. Second step of the PyPI work after the package rename.
- hatchling build; the version comes from docsgpt/version.py. The wheel is
the docsgpt package with the data it reads at runtime (prompts, model
catalogs, seed config, alembic.ini and migrations) and without the
Dockerfile, the exported requirements, the sample index and local runtime
data. The application import alias stays checkout-only. uv sync installs
the package editable now that [tool.uv] package = false is gone.
- docsgpt/cli.py: api (gunicorn + BoundedDrainUvicornWorker with the image's
flags, --reload for uvicorn), worker (Celery worker with beat embedded,
--no-beat/-Q/--concurrency/--pool, solo pool on macOS), migrate, and
argument pass-through to the maintenance scripts. --help imports no app.
- docsgpt/core/paths.py: runtime data lives in a data home (DOCSGPT_HOME,
else the checkout, else cwd); DOCSGPT_ENV_FILE overrides the env file.
Settings, the dotenv load, LocalStorage and the internal upload route use
it instead of "three directories above this file", which is site-packages
for an installed package. A checkout and the Docker image behave as before.
- [project] dependencies are compatible ranges so the package installs next
to other packages; uv.lock resolves to the same versions and the exported
requirements files are unchanged.
- package-build.yml builds and checks the wheel on PRs and installs it into
a clean venv; pypi-publish.yml publishes on a published release through
trusted publishing (environment pypi), or to TestPyPI on a manual run.
- Docs: Deploying -> Install with pip. AGENTS.md notes the package.
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