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.
Workflows ship two expression languages in adjacent fields. Agent
`prompt_template` and end `output_template` are Jinja2, so `{{query}}` is
correct there. State and condition `expression` fields are bare CEL,
where the same string is a parse error.
Nothing told users this. docs/content/Agents/nodes.mdx documented the
pre-CEL Set State node with `{{variable_name}}` examples and Set /
Increment / Append operations that no longer exist — "CEL" appeared
nowhere in the docs. The builder's own placeholder was `input.foo + 1`,
referencing an `input` namespace that is not in workflow state, while the
panel beside it advertised `{{ agent.variable }}`.
There was also no validation anywhere: neither validateWorkflow nor
validate_workflow_structure looked at state nodes at all, and conditions
were only checked for a non-empty string. A workflow containing
`{{query}}` saved and published clean, then aborted on the first message
with a bare caret dump that sanitize_api_error collapsed into "An error
occurred … please try again later" — advice that sends the user round the
same loop, which is what the 2026-08-01 report shows.
Adds validate_cel_expression (compile-only, since state is built at run
time and unresolved names are not knowable when saving) and wires it into
the workflow save path for both node types, plus the half-configured
state operations the engine silently skips. `{{ }}` gets a targeted hint,
raised only after compilation has already failed so valid CEL that
contains braces — `x == "{{y}}"`, or a nested map literal — is not
rejected.
celpy errors are now summarized: undeclared-reference messages embed a
repr of the entire activation, thousands of characters including the
user's own query, and others interpolate the offending state value.
Quoted fragments that are not bare identifiers are redacted, since
config errors now bypass sanitize_api_error to reach the user, and a
shared agent's runner is not its owner.
Docs rewritten with a table of which field takes which syntax, CEL
examples for Set State, and the Condition node section that basics.mdx
has been linking to all along.
/api/models reports `display_provider` when a catalog YAML sets one
(`foundry`, `azure_foundry`, `cloudflare`), and the builder persists that
string as a node's `llm_name`. The engine passed it straight to
LLMCreator, which only knows the names in PROVIDERS_BY_NAME and raises
`No LLM class found for type <label>`.
That fails the node before any LLM call, so the turn ends in ~60ms with
an empty answer and no tokens generated. It hits the *default* path: the
platform-default model's label is stamped into every newly dragged agent
node and validateWorkflow requires an agent node, so a new user's
untouched workflow could not produce a token regardless of what they
typed. Ordinary chat was unaffected because it resolves the provider from
the model registry and never reads the stored name.
Adds `resolve_dispatch_provider`, which prefers a stored name that is a
real dispatch provider, then the registry lookup, then the parent agent.
Nodes already saved with a label are repaired at run time, so no
migration is needed. The api_key now resolves from the normalized name
too — `get_api_key_for_provider` falls back to settings.API_KEY for names
it does not recognize, which would have sent the deployment key to
whatever endpoint the label happened to select.
Alex