A bare string or list under off_peak_pricing in YAML passed the truthy
guard and crashed _is_off_peak with AttributeError, breaking cost
calculation for that deployment. Malformed pieces of the block are
documented to not match rather than error, so guard the block itself the
same way and bill standard rates.
Since the Rust core handoff in #37241, BedrockConverseLLM.completion read
access_key, secret_key and token off the boto3 credentials before asking
the Rust gate whether it wanted the call. On a deployment that only sets
AWS_BEARER_TOKEN_BEDROCK boto3 resolves no credentials, so every Converse
call through /v1/chat/completions and /v1/responses failed with
"'NoneType' object has no attribute 'access_key'", with or without the
Rust opt-in
Bearer auth resolves no SigV4 principal at all, and both the Python and
the Rust path read the bearer token themselves, so only hand the
principal keys down when boto3 actually resolved one
get_request_headers now accepts credentials=None and raises botocore's
NoCredentialsError when neither a bearer token nor a principal exists
instead of handing SigV4Auth a None
Fixes#38579
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BFDpYC45u9p8eKd4aBATnS
* test(e2e/ui): cover creating, testing and deleting a guardrail
The Guardrails page had no browser coverage. The RC checklist covers it by
hand against a live Presidio, which is why it has always been skipped in CI.
These drive the LiteLLM content filter instead, which runs inside the proxy,
so the whole flow is exercised without a third-party moderation service. The
create test does not stop at the table row: it sends a prompt carrying the
keyword it just banned and asserts the gateway refuses it, then sends a clean
prompt through the same guardrail and asserts it is served.
* test(e2e/ui): delete the guardrails these tests create
Review caught the fixtures being left behind. Guardrails are database rows
that show up in the table and in the playground's list, so a run that leaves
them changes what the next run sees.
Also trims the comments that restated what the helpers already say.
* test(e2e/ui): fail the run when guardrail teardown does not delete
Review caught the afterEach discarding the DELETE response, so a failed
cleanup finished quietly and left the guardrail for the next run to trip on.
* test(e2e/ui): wait for a new guardrail to reach the request path
The wizard test drove one chat completion immediately after creating the
guardrail and required a 400. A trace from the deployed stack shows the
record is stored correctly (blocked_words, action BLOCK, block_on_violation)
and the call six seconds later is still served unguarded, so the first
request can land before the proxy picks the guardrail up.
Polls the same call to the same 400 instead, which keeps the assertion and
lets the refresh land. If it never blocks, this stays red, which is what we
want it to say.
---------
Co-authored-by: Claude <noreply@anthropic.com>
The router_code_coverage gate only counts calls made from test files with
router in the filename, so the helper needs direct unit tests beside the
other inheritance helpers in test_router_model_cost_isolation.py: fills
missing base rates from the builtin entry, leaves explicit rates alone,
and no-ops without a block or for an unmapped backend model.
* test(e2e/ui): cover the Budgets page create, edit and delete flows
The Budgets page had no browser coverage at all, so an admin creating or
editing a spend cap through the UI was only exercised by hand at RC time.
Each test reads the budget back from /budget/list, a different route from
the one the table renders, so a row that only exists in the table's cache
does not pass. The edit test pins the rate limits an unrelated spend-cap
edit has no business touching.
* test(e2e/ui): trim comments that restate the test steps
Review flagged the explanatory comments as restating ordinary setup rather
than explaining anything. Keeps the two that carry the regression rationale
for an assertion and drops the rest.
---------
Co-authored-by: Claude <noreply@anthropic.com>
Cost lookup selects the deployment-scoped cost map entry only when custom
pricing is detected and the entry carries a base pricing field. A deployment
whose model_info held nothing but off_peak_pricing failed both conditions, so
its schedule was silently ignored and every request billed at the shared
backend rate.
use_custom_pricing_for_model now also treats deployment-scoped pricing fields
in the metadata model_info as custom pricing, and the router inherits the
backend model's built-in base token rates onto such an entry at registration,
which also lets cache pricing inheritance apply. Regression tests cover the
registration, the detection, and the costed request end to end.
The custom-logger detail branch reads the payload from cold storage, which is
written independently of the spend-log table and can outlive its row. The DB
owner pre-check then has nothing to verify for an id lookup that matches no row,
so a foreign tenant's stored payload could be returned. Authorize the returned
payload against the owner recorded inside it (metadata user/team id), failing
closed when none is recorded. Also fold the three identical 403 raises into one
helper.
register_model inserted the first deployment's off_peak_pricing dict by
reference into the shared backend cost-map entry, and later deployments
sharing that backend merged their schedules into the same object,
corrupting the first deployment's schedule and polluting the built-in
entry. Nested dicts now merge copy-on-write, and off_peak_pricing stays
off the shared backend keys.
Access is confirmed on the Anthropic account, and all 11 cells pass live, so the
xfail marker would only hide real regressions.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This reverts commit 65a46a5f32 (#38113)
That change made two edits that combine into a hard failure for SDK
users. It dropped the null-router guard in
_select_search_tool_from_router, so a missing router now yields an empty
search_tools list instead of returning early, and it turned the no-match
case in _select_search_tool_from_list from a debug-logged fallback into
a raised ValueError. It also added a call site in
async_pre_call_deployment_hook that invokes the selection purely for the
side effect of raising, discarding the return value
Used together, any SDK caller that sets search_tool_name and sends a web
search tool now raises "Configured search tool '<name>' was not found"
on every request. There is no way to satisfy the check off the proxy,
because search_tools is only ever populated from the proxy router, so
the SDK path cannot register one
tests/pass_through_unit_tests/test_websearch_interception_e2e.py caught
this, but #38113 only updated the handler unit tests, so the break
landed on staging
Reverting restores the previous behavior while we work out a fix that
keeps the stricter validation on the proxy path, where a silently
substituted search provider is the real problem worth rejecting, without
turning the SDK path into an unconditional error
The chat-completions bridge emitted Responses output items whose item ids
were raw Anthropic tool ids (toolu_/srvtoolu_), which OpenAI rejects on
replay with "Expected an ID that begins with 'fc'", breaking router
fallback conversations from gpt-5 to claude models.
Four fixes, composable and independently useful:
- emission: bridge output items get fc_/ctc_-prefixed item ids while
call_id stays raw so tool_result pairing keeps working (streaming and
non-streaming share the same helpers)
- openai replay: request transformation drops tool call item ids that do
not match OpenAI's own shapes instead of forwarding them, gated to
OpenAI and Azure, since the API accepts the items with no id at all
- anthropic replay: a replayed srvtoolu_ call whose paired server tool
result is unavailable degrades to a plain client tool_use instead of a
dangling server_tool_use that 400s the client's tool_result
- tool-only turns no longer emit a message output item with output_text
text null, matching native OpenAI output
Adds claude-fable-5-1 cost map entries on the Anthropic API, Bedrock converse
(base, global, and us/eu geo inference profiles at the 10% regional premium),
Vertex AI, and Azure AI. Specs match Fable 5 (1M context, 128K output, $10/$50
per MTok, adaptive thinking always on, xhigh and max effort), except cache reads
land at $0.25 per MTok, a quarter of Fable 5's price and 0.025x base input
instead of the usual 0.1x.
Registers anthropic.claude-fable-5-1 in BEDROCK_CONVERSE_MODELS, lists the model
in the setup wizard, and extends the reasoning effort e2e grid. The partner cells
carry fail_reason markers until access on the CI accounts is confirmed.
Partner entries deliberately carry no deprecation_date: Anthropic publishes
retirement no sooner than 2027-09-01 for the first-party model, and the Foundry
and Vertex dates are not published yet.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
