DocsGPT keeps three append-only journals -- auth_events, device_audit_log and
guardrail_events -- each readable only on its own terms, and the second of
those had an admin endpoint that no UI ever called. An operator reviewing an
incident wants one timeline, not three.
Adds GET /api/admin/activity: all three journals projected onto a common row
shape and merged, ordered newest first, with facets for journal, category,
event name, actor, affected user, a time window and free-text search over the
detail payload. A category filter that only one journal can satisfy drops the
others from the union rather than scanning and discarding them.
GET /api/admin/activity/events returns the distinct (event, category) pairs
the instance has actually recorded, so the filter UI can offer real choices
instead of asking an operator to type "oidc_login_denied" from memory.
GET /api/admin/activity/export streams the same filtered feed as CSV or
NDJSON. Streamed rather than buffered, and capped, so a compliance export of a
busy instance is bounded work.
guardrail_events.api_key (a raw agent key) and matched_value (unredacted
source text) are excluded from the projection, mirroring the exclusion the
per-agent guardrail view already makes. Admin-gating is not a reason to widen
what a list response carries.
auth_events.user_id was overloaded and meant something different per call
site: admin mutations filed the row under the target user and hid the acting
admin in metadata->>'by', team events filed it under the actor, and quota
events switched between the two depending on scope. The practical consequence
was that "show me everything admin X did" had no answer.
Adds actor_id (never NULL) and target_id (NULL when the event is not about a
user) alongside the existing column, which keeps its meaning as the per-user
feed key so nothing historical is rewritten. The backfill recovers the actor
from metadata for rows that predate the columns.
Also adds the indexes the cross-user admin feed needs. The only index was
(user_id, created_at DESC), so the global feed -- which orders by created_at
with no user predicate -- fell back to a sequential scan plus a sort on every
page.
The feed gains actor, multi-event, until and free-text search filters, plus a
distinct-event catalogue so the UI can offer what the instance recorded
instead of asking operators to type a name from memory.
Validation problems are returned as values rather than raised and echoed
with str(exc), and a huge integer limit is rejected as out of range instead
of overflowing. Tests no longer call mutating endpoints inside asserts.
The unpriced-model notice asked the live registry whether a model has a
price, so a priced model whose provider was later disabled showed up as
unpriced. It now lists models whose calls this period were all recorded at
$0. Token limits are serialized as integers.
Admins read and set the instance default, team allowances and user
overrides under /api/admin/quotas. A user's endpoint also returns the
limits those layers resolve to, the layer each came from and the usage
against them. The overview lists catalog models used this period that have
no price, since a cost limit cannot see them. Every write is audited.
GET /api/user/quota gives a user their own limited buckets, usage and reset
time without naming the policies behind them; any valid token may call it.
A resource restriction was checked on ids in the request, not on what the
addressed row pulls in or belongs to. Closed:
- Workflow writes for tokens restricted on sources, tools or prompts (a graph
names those inside its nodes), and attaching a workflow to an agent unless
the token is restricted on workflows too.
- Chat for tools-restricted tokens (chat executes tools; rejected at token
creation as well), and agent-less chat for tokens restricted on prompts or
workflows.
- conversation_id on chat: it must belong to the agent being run, or to no
agent for agent-less chat. Otherwise the server continued, appended to, or
resumed pending tool calls of another agent's conversation.
- Schedules for tokens restricted on anything but agents; schedule-id routes
for every restricted token.
- Conversations and analytics for every restricted token, not only
agent-restricted ones.
Also: create, first publish and adopt return the agent API key masked to a
token without agents:keys; token ids must be canonical UUIDs (urn:uuid: gave
a 500); an expired token is reported as expired; token creation takes a
per-user advisory lock so the cap cannot be raced; admin revoke-sessions
writes a pat_revoked event per token. The UI drops a row whose revoke returns
404 and does not offer a tools restriction next to chat:run.
Users list, create and revoke their own tokens under /api/user/tokens; the
plaintext is returned once at creation. Admins can list a user's tokens and
revoke any token, and the admin revoke-sessions action now revokes the user's
tokens too. Creation and revocation are written to auth_events.
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