5 Commits
Author SHA1 Message Date
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 e6fb46560c fix: minor graph rag improvements 2026-08-20 13:33:06 +01:00
Alex 0b36257202 feat: parser improvements and fixes 2026-08-19 23:49:26 +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
Alex 9fdaea6cd2 Pass selected run-scoped documents to workflow agent nodes natively
An agent node can list input_documents (short refs like A1, a literal "*" for all
inputs, or state variables holding refs produced by an upstream node). The engine
resolves each through the run-scoped artifact gate and feeds it to the node's LLM
natively when the model supports the format (PDFs included via the provider's
image synthesis), otherwise extracts it to text with Docling. A file_passing
policy (auto/native/extract) and per-node count + per-file byte caps bound cost;
the native decision uses the same supported-types source the provider handler
uses, so a document is never silently dropped. Bytes never enter run state.
2026-06-25 11:35:29 +01:00