8 Commits
Author SHA1 Message Date
Alex 15bdda8554 fix(worker): know you are in a worker from any thread, not only the task's
Celery records the executing task on the thread that runs it, so a thread that
task starts sees none. The embeddings client and read_document both decided
"am I in a worker?" from that alone, and from any other thread took the
web-process branch: dispatch to the worker they were running in and block on
the result. Celery refuses that get() ("Never call result.get() within a
task!"), so the embed failed and latched the 30s dispatch cooldown for every
caller after it; with joins allowed, read_document would instead wait on a
parsing queue only its own busy process serves.

Threads inside tasks are not hypothetical: per-source retrieval fans out to a
pool, so a scheduled or webhook agent searching several sources embedded from
pool threads. Graph extraction did too, which failed every chunk of a build.

in_worker() in celery_init answers for the whole process. Celery's
task_join_will_block is process-wide and set for every blocking pool (prefork,
solo, threads) -- exactly the condition under which dispatch-and-wait goes
wrong; eventlet/gevent leave it unset, so the task's own thread still counts
through current_worker_task. Verified with real workers on each blocking pool:
from a thread a task started, the old check dispatched and hit the error, the
new one embedded locally.
2026-09-19 14:07:42 +01:00
Alex 574f96341e refactor: rename the application package to docsgpt
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.
2026-09-07 10:20:43 +01:00
Alex 82ac2dcee9 fix: refactors and optimisations 2026-08-20 13:56:37 +01:00
Alex 0b36257202 feat: parser improvements and fixes 2026-08-19 23:49:26 +01:00
Alex 94a845aa82 fix: more artefact hardening 2026-07-04 11:42:27 +02:00
Alex b144265094 fix: workflow security pass 2026-06-29 19:21:35 +02:00
Alex 636f299e67 Default the code and artifact tools; scope read_document to workflows
Enable code_executor and artifact_generator by default in chats (added to
DEFAULT_CHAT_TOOLS) — they load via the synthetic-id path user- and
conversation-scoped like scheduler, and persist artifacts (no user_tools FK).
Make read_document an internal agent-builtin flagged workflow_only so it appears
only in the workflow builder, not the classic agent picker or the Add-Tool
catalog (reuses the builtin synthetic-id path; still run-scoped and authz-gated).

Per decision, default-on code_executor runs sandboxed code without an approval
prompt (the sandbox is the trust boundary); this is documented in settings and
the threat model, and multi-tenant deployments should add per-tenant isolation
(Daytona / gVisor / egress policy).
2026-06-25 18:37:04 +01:00
Alex 37d93cbd86 Parse documents on a Celery parsing worker via a read_document tool
Replace the sandbox Docling extractor with read_document, backed by the in-process
backend parser (the same one ingestion uses) and offloaded to a dedicated
'parsing' Celery queue so it can run on GPU-capable workers with predictable RAM.
The tool resolves the input ref under the run-scoped gate, enqueues the parse,
and awaits it with a timeout (degrading to an error rather than hanging); the
worker independently re-resolves the artifact through the same gate and never
trusts a raw path. Untrusted files get the upload path's safeguards (extension
whitelist, size cap, sanitized temp file, cleanup). Options: output
(markdown/text/structured/chunks), ocr, pages, engine, max_chars, include_tables,
persist, json_schema. The workflow native-file 'extract' fallback now uses the
same worker path, so document parsing no longer needs the sandbox and works on
every backend.

Also fixes the branch's periodic-task test (the sandbox reaper made it 12) and
points the dev and e2e Celery workers at the parsing queue.
2026-06-25 13:24:12 +01:00