The azure row of test_get_model_info_falls_back_from_dated_snapshot_to_undated_entry used gpt-5.6-luna-2026-07-09, which main's cost map carries as an exact azure key, so the lookup returned the dated key and the required misc test job failed on main. All three dated snapshot tests now use a 2099-01-01 snapshot date, so they keep exercising the strip path whatever real snapshots the map gains
DeepSeek charges half the listed rate outside 01:00-04:00 and 06:00-10:00 UTC
Monday to Friday, so every deepseek-flash, deepseek-v4-flash,
deepseek-v4-flash-vision-exp, and deepseek-v4-pro entry now carries an
off_peak_pricing block with those windows and the halved input, output, and
cache-hit rates. The generated cost map schema picks up the block, and the
regression tests pin the peak and off-peak cost of one call at fixed moments.
The S3 Vectors ingestion embedded every chunk with the request's
embedding.model or the default, never the embedding_model the store was
registered with, while search on the same store embeds with the
registered model. A registered store uploaded to by id alone therefore
embedded with the wrong model and AWS rejected the vectors on the
dimension mismatch. The store's embedding model now wins for S3 Vectors
ingestion through a helper next to the one search already uses
Hosted Responses API tools with no Chat Completions equivalent were forwarded
verbatim, so Codex 0.140+ got a 400 from the provider on every turn. The bridge
now drops tool_search and local_shell the same way it drops computer_use,
image_generation, and shell, and also drops parallel_tool_calls when no chat
tools remain, since chat completions only accepts it alongside tools
A "bucket:" or ":index" id split into an empty name, so ingestion silently
generated a fresh index and search sent the empty name to AWS. Both sides now
raise the existing format error through the shared helper.
A registered S3 Vectors store usually carries only its "bucket:index" id,
and the previous commit stopped forwarding the caller's bucket and index for
a managed store, so ingesting into one raised KeyError 'vector_bucket_name'.
The ingestion now derives both from vector_store_id with the rule the search
side already uses, explicit keys still winning. The caller's
litellm_credential_name is dropped for a managed store too, since it expands
into api_key and api_base, and max_embedding_requests_per_min joins the
per-upload options a caller may still set.
The cost tracking callback f-stringed chosen_metadata, litellm_metadata,
and old_metadata into the failed_tracking_spend alert on every failure,
at every log level, so one 250-byte request produced a 23 KB alert
carrying the client's metadata, headers, and key-auth reprs four times
over. The alert now carries the exception, the traceback, the model, and
the call type; the metadata keys are logged once at debug level through
lazy formatting, so nothing is built at warning level
With store_prompts_in_spend_logs on, the persisted request body kept the client's model string even when the row's model, model_group, and error text had been replaced by the unknown-model placeholder. The body's model now takes the same placeholder on those rows. Also annotates the new test locals with Final and wraps the four test lines that ran past 120 characters.
A bulk item that carried only tags reached the DB with max_budget, team_id,
and budget_id as explicit nulls, wiping the key's budget and detaching it
from its team. The per-key update is now built from the fields the item
actually set, so a field left out keeps its value and an explicit null still
clears it, the same as /key/update. Items carrying a field the bulk path
cannot apply (object_permission and the like) are rejected with 422 instead
of being silently dropped.
Guardrails created through POST /guardrails on older releases have api_version "v1" saved in the database, because the writer persists every default. Azure Content Safety never accepts that value, so those guardrails kept answering 404 after the default moved to None. The Azure base now resolves "v1" to 2024-09-01 the same way it resolves a missing value. Also restores the OpenAPI snapshot line that a Python 3.14 regeneration had dedented
When a deployment priced one OCR batch family and the other still needed a
published rate, a failed cost-map lookup returned zero for the whole line and
discarded the deployment rate that was already resolved. Those pages were
billed as free. The lookup failure now only logs, and the families the
deployment prices are billed at the configured rate
