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.

docsgpt/parser/remote/reddit_loader.py

@@ -0,0 +1,89 @@
+import json
+from typing import Any, Iterable, List
+
+from docsgpt.parser.remote.base import BaseRemote
+from docsgpt.parser.schema.base import Document
+
+REQUIRED_FIELDS = ["client_id", "client_secret", "user_agent", "search_queries"]
+
+
+class RedditPostsLoaderRemote(BaseRemote):
+    """Load Reddit posts through praw.
+
+    Create an app at https://www.reddit.com/prefs/apps/ to obtain the
+    ``client_id`` and ``client_secret``.
+    """
+
+    def load_data(self, inputs) -> List[Document]:
+        """Load posts for every configured subreddit or user.
+
+        Args:
+            inputs: JSON string holding the praw credentials plus
+                ``search_queries``, and optionally ``mode``
+                (``subreddit``/``username``), ``categories`` and
+                ``number_posts``.
+
+        Returns:
+            One document per post, carrying the post body as text.
+        """
+        try:
+            data = json.loads(inputs)
+        except json.JSONDecodeError as e:
+            raise ValueError(f"Invalid JSON input: {e}")
+
+        missing_fields = [field for field in REQUIRED_FIELDS if field not in data]
+        if missing_fields:
+            raise ValueError(f"Missing required fields: {', '.join(missing_fields)}")
+
+        mode = data.get("mode", "subreddit")
+        if mode not in ("subreddit", "username"):
+            raise ValueError(
+                "mode not correct, please enter 'username' or 'subreddit' as mode"
+            )
+        categories = data.get("categories", ["new", "hot"])
+        search_queries = data.get("search_queries")
+        number_posts = data.get("number_posts", 10)
+
+        import praw
+
+        reddit = praw.Reddit(
+            client_id=data.get("client_id"),
+            client_secret=data.get("client_secret"),
+            user_agent=data.get("user_agent"),
+        )
+
+        documents: List[Document] = []
+        for search_query in search_queries:
+            for category in categories:
+                if mode == "subreddit":
+                    listing = reddit.subreddit(search_query)
+                else:
+                    listing = reddit.redditor(search_query).submissions
+                documents.extend(
+                    self._posts_to_documents(
+                        getattr(listing, category)(limit=number_posts), category
+                    )
+                )
+        return documents
+
+    @staticmethod
+    def _posts_to_documents(posts: Iterable[Any], category: str) -> List[Document]:
+        """Convert praw submissions into documents."""
+        documents = []
+        for post in posts:
+            documents.append(
+                Document(
+                    text=post.selftext,
+                    doc_id=post.id,
+                    extra_info={
+                        "post_subreddit": post.subreddit_name_prefixed,
+                        "post_category": category,
+                        "title": post.title,
+                        "post_score": post.score,
+                        "post_id": post.id,
+                        "source": post.url,
+                        "post_author": str(post.author),
+                    },
+                )
+            )
+        return documents