- check_usage treats a request through a keyless (draft) agent as agent
traffic, matching how its usage rows are bucketed and the headless rule
- dashboard edits carry the stored enabled flag instead of re-enabling the
policy; disabled policies are labelled in the Quotas tab and the editor
- quota 429s send x-should-retry: false so OpenAI SDK clients do not retry
a refusal that cannot succeed before the reset
- cached-input and cache-write rates for Anthropic, OpenRouter and Groq
gpt-oss-120b; refresh OpenRouter deepseek-v3.2 list prices
- UsageQuota reuses usagePercent; docs note that a user override needs an
existing user
- A tool continuation refused for usage now releases the resume claim it
took; before, retries got a 409 until the stale claim was reverted.
- Agent traffic is any row with an agent key or an agent id, so keyless
agents and workflow nodes count toward the agent bucket, not direct.
- The user quota modal discards responses for a previously opened user.
- The usage meter shows every limited bucket, not only 'all'.
- Restore the class separator on the analytics stat card that a formatter
run removed, and align the OpenRouter DeepSeek description with its rates.
check_usage now checks the billable user's quota on every request, before
the per-agent 24h limits, which keep applying to traffic through an agent.
Until now a request without an agent key skipped every limit. A refusal is
a 429 with Retry-After and a body naming the budget, usage, limit, the
layer the limit came from and when it resets.
Headless runs check the agent owner's quota before starting. A refused
scheduled run is recorded as budget_exceeded; a refused webhook run returns
a quota_exceeded result instead of raising, so Celery does not retry it.
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.
The sources list used to start with a fake "Default" entry that had no id
and, at run time, meant "no source, skip retrieval". The agent form
pre-selected it, snapped back to it when the last source was deselected,
and refused to publish without it, so a new agent always looked like it
had a knowledge base when it had none.
Backend
- /api/sources returns only ingested sources; no placeholder row.
- Publishing an agent no longer requires a source on create or update.
The legacy "default" value is still accepted and maps to NULL.
Frontend
- The agent source picker starts empty, can be cleared, and shows a hint
that a source-less agent answers from the model and its tools only.
- The picker groups sources into "Your sources" and "Shared with team"
when any team-shared source exists, shows "N sources selected" for a
multi-selection, and gets the same "Go to Sources" / "Upload new"
footer as the chat picker. A source uploaded from the form is selected
when it lands.
- Source selection serialisation and the picker id live in one helper
shared with the chat picker; the four copies in the form are gone.
- The client no longer seeds a placeholder source in the store, and the
dead auto-select of a "default" document is removed.
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