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.

.devcontainer/devc-welcome.md

@@ -19,17 +19,17 @@ Run the full app under uvicorn (serves `/mcp` and the async SSE reconnect
 routes, and matches production):
 
 ```bash
-uvicorn application.asgi:asgi_app --host 0.0.0.0 --port 7091 --reload
+uvicorn docsgpt.asgi:asgi_app --host 0.0.0.0 --port 7091 --reload
 ```
 
-`flask --app application/app.py run --host=0.0.0.0 --port=7091` is faster but
+`flask --app docsgpt/app.py run --host=0.0.0.0 --port=7091` is faster but
 serves only the WSGI Flask app — it omits `/mcp` and the reconnect reader
 `GET /api/messages/<id>/events`, so a dropped stream won't auto-resume.
 
 ### Celery (Task Queue)
 
 ```bash
-celery -A application.app.celery worker -l INFO -Q docsgpt,parsing,embeddings
+celery -A docsgpt.app.celery worker -l INFO -Q docsgpt,parsing,embeddings
 ```
 
 The `parsing` queue serves document parsing (the `read_document` tool / workflow

.devcontainer/post-create-command.sh

@@ -22,8 +22,8 @@ fi
 
 
 # The embedding model is fetched on first use and cached, so nothing to download
-# here. For an offline container, run `python -m application.scripts.prefetch_models`
+# here. For an offline container, run `python -m docsgpt.scripts.prefetch_models`
 # after the install below.
-pip install -r application/requirements.txt
+pip install -r docsgpt/requirements.txt
 cd frontend
 npm install --include=dev