refactor: read settings directly instead of getattr with a second default

About 85 call sites read a setting as getattr(settings, "NAME", fallback),
each carrying its own copy of the default. Every one of those names is a
field with a default on the model, so the fallback could never apply to
the real settings object; it only masked drift. Two had drifted:

- OPENAI_PROMPT_CACHE_KEY defaults to True on the model but the reader
  fell back to False, and two test stubs relied on that.
- SharePoint's MICROSOFT_AUTHORITY fallback to
  https://login.microsoftonline.com/<tenant> never fired, because the
  attribute always exists (as None), so MSAL got authority=None. The
  connector now derives the tenant authority when the setting is unset,
  as its test always assumed.

Four places read EMBEDDINGS_KEY straight from os.environ, skipping the
"None"/"" normalisation the model applies; they read the setting now.
Test stubs that replaced a module's settings with a SimpleNamespace list
every setting the code under test reads.

docsgpt/api/user/artifacts/download.py

@@ -154,7 +154,7 @@ async def download_artifact(request: Request) -> Response:
         # URL. If the active backend can't mint one, that's a config error:
         # surface a 500 rather than silently proxying bytes from a backend
         # the operator expected to be off the hot path.
-        if getattr(settings, "URL_STRATEGY", "backend") == "s3":
+        if settings.URL_STRATEGY == "s3":
             try:
                 url = await anyio.to_thread.run_sync(
                     partial(storage.generate_presigned_url, storage_path, expires_in=_PRESIGNED_URL_TTL)

docsgpt/api/user/base.py

@@ -235,7 +235,7 @@ def get_vector_store(source_id):
     store = VectorCreator.create_vectorstore(
         settings.VECTOR_STORE,
         source_id=source_id,
-        embeddings_key=os.getenv("EMBEDDINGS_KEY"),
+        embeddings_key=settings.EMBEDDINGS_KEY,
     )
     return store
 

docsgpt/api/user/tasks.py

@@ -346,9 +346,9 @@ def parse_timeout_for_size(size_bytes: Optional[int]) -> float:
     """
     from docsgpt.core.settings import settings
 
-    base = float(getattr(settings, "DOCUMENT_PARSE_TIMEOUT", 120) or 120)
-    per_mib = float(getattr(settings, "DOCUMENT_PARSE_TIMEOUT_PER_MB", 0) or 0)
-    ceiling = float(getattr(settings, "DOCUMENT_PARSE_TIMEOUT_MAX", base) or base)
+    base = float(settings.DOCUMENT_PARSE_TIMEOUT or 120)
+    per_mib = float(settings.DOCUMENT_PARSE_TIMEOUT_PER_MB or 0)
+    ceiling = float(settings.DOCUMENT_PARSE_TIMEOUT_MAX or base)
     size = float(size_bytes) if isinstance(size_bytes, (int, float)) else 0.0
     scaled = base + per_mib * max(size, 0.0) / (1024 * 1024)
     return min(ceiling, max(base, scaled))