The changed-test gate booted its stage-mirror stack without files_settings
or finetune_settings, so every raw upload with a custom_llm_provider hit a
500, and it exported the whole provider env into the gateways, so the
AWS_ROLE_NAME the assume-role test needs made the GovCloud deployment run
an AssumeRole with its static keys. The gate also deleted its pytest output,
so a red run left nothing to read. The mirror config now carries the
openai, azure, and vertex_ai file settings, gateways start without
AWS_ROLE_NAME, and the workflow uploads the pass logs and junit files with
every secret value, every field of a JSON-valued secret, and their
XML-escaped forms replaced before the raw files are removed.
The stored flag is the cluster's desired state and is what the form saves, so it
cannot also stand as proof that this process activated the callback: a pod that
lagged or failed to apply it would still read as on. Report the process's own
registration as a separate read-only field and warn on the page when the two
disagree, so a failed activation is visible instead of only logged.
Deriving enabled from whether this process has the callback registered makes a
pod that has not polled yet report off while the cluster runs it, and the next
save writes that off back for every pod. The stored flag is the cluster's own
answer, so prefer it and fall back to local registration only when none is
stored, which is the config-activated case that has no flag to read.
The managed files hook's content read looped the file's model mappings and asked each deployment for the file. A file LiteLLM stored itself maps every model to its storage url, so the read sent that internal id to the upstream server, failed, and the batch rate limiter failed open: a key's TPM limit did not apply to a LiteLLM-executed batch. The hook now returns the stored bytes from the file's storage backend before it consults any deployment
The last-known org copy was written only on get_org_object's DB-read path. The
virtual-key auth prefetch fills the same 5s org entry directly, so with keys and
JWTs of one org on the same worker the JWT lookup always hit the cache, never
wrote the copy, and a DB outage turned that JWT traffic into 503s again.
get_org_object_for_request now writes the copy itself whenever this worker holds
none, under the management-object TTL, and get_org_object is back to its shape
on main.
An explicit target_storage=litellm_db upload was accepted for any model, so an OpenAI model's litellm_db://<uuid> id was sent to OpenAI as input_file_id and a model-less upload left a content row nothing can read; it now answers 400 on target_storage. An explicit target_storage skips the files api probe and the purpose and single-target gates, which only decide whether LiteLLM keeps the file itself, so an azure_storage user_data upload for a vLLM model reaches the storage path again as it did before this branch. cancel_batch authorizes the model of every LiteLLM-managed batch id before it branches, the way retrieve_batch already does, so the LiteLLM-executed branch gets the check its provider sibling had. Restores the test_afile_delete_passes_trusted_model_credentials_to_router definition line an earlier commit dropped
Peer pods gate the settings poll on general_settings.supported_db_objects,
which validates against SupportedDBObjectType. Without a member for this
name an operator could not opt in, so a configured allowlist left every
pod but the one that served the write on stale settings.
Also types the dashboard's settings payload off the generated schema
instead of Record<string, any>.
Greptile flagged the unannotated list and append against the repository's
immutable-state and Final-local rules (LIT001/LIT010). Recording the call on an
AsyncMock removes the accumulator entirely and matches how the neighbouring
audit-log tests in this file read their captured arguments.
