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.

docs/content/Models/cloud-providers.mdx

@@ -33,7 +33,7 @@ DocsGPT offers direct, streamlined support for the following cloud LLM providers
 | Novita AI                    | `novita`       | (See Novita docs)           |
 | HuggingFace Inference API    | `huggingface`  | `meta-llama/Llama-3.1-8B-Instruct` |
 
-DocsGPT also ships a **model catalog** (`application/core/models/*.yaml`) that the in-app model picker reads, so common models from these providers — including DeepSeek — appear ready to select once the matching API key is set.
+DocsGPT also ships a **model catalog** (`docsgpt/core/models/*.yaml`) that the in-app model picker reads, so common models from these providers — including DeepSeek — appear ready to select once the matching API key is set.
 
 ## Connecting to OpenAI-Compatible Cloud APIs
 
@@ -75,4 +75,4 @@ See [App Configuration](/Deploying/DocsGPT-Settings) for the full settings refer
 
 ## Adding Support for Other Cloud Providers
 
-If you wish to connect to a cloud provider that is not explicitly listed above or doesn't offer OpenAI API compatibility, you can extend DocsGPT to support it. Within the DocsGPT repository, navigate to the `application/llm` directory. Here, you will find Python files defining the existing LLM integrations.  You can use these files as examples to create a new module for your desired cloud provider.  After creating your new LLM module, you will need to register it within the `llm_creator.py` file. This process involves some coding, but it allows for virtually unlimited extensibility to connect to any cloud-based LLM service with an accessible API.
+If you wish to connect to a cloud provider that is not explicitly listed above or doesn't offer OpenAI API compatibility, you can extend DocsGPT to support it. Within the DocsGPT repository, navigate to the `docsgpt/llm` directory. Here, you will find Python files defining the existing LLM integrations.  You can use these files as examples to create a new module for your desired cloud provider.  After creating your new LLM module, you will need to register it within the `llm_creator.py` file. This process involves some coding, but it allows for virtually unlimited extensibility to connect to any cloud-based LLM service with an accessible API.