* refactor(model-cost): move the cost map inputs, fetch and register_model overlay into Rust
* fix(model-cost): keep main's compat helpers pure and move network tests to integration
ModelCostMapReloaded.model_cost_map now returns the alias-sharing table, so an alias registration after adopting a reload still reprices the owner. _finalize_model_cost_map reads a caller's map without size limits and installs nothing, through the new NativeModelCostMap.finalize. The unit tests that started a local server or a child interpreter now live in tests/integration/sdk/test_model_cost_fetch_sdk.py, and run_isolated gets direct tests for joining its blocking pool and leaving the fork gate alone.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* feat(rust): add litellm-s3 crate, AwsCredentialsProvider and cost map fetch
* fix(model-catalog-refresh): time each read instead of the whole cost map download
The 5 s fetch timeout covered the full body, so a slow but steady link failed every attempt where httpx and boto3 would finish. Each read now gets its own 5 s, matching main.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix(router): let a retry leave a pinned deployment after a retryable failure
The retry loop only recorded a failed deployment for non-retryable statuses,
so encrypted_content_affinity re-pinned the failing origin on every 5xx, 429
or connection-error retry. Track every deployment the request failed on and
hand that list to the callback filters, leaving selection's skip list alone.
Fixes#47607
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(router): carry failed deployments through stream retries too
retry_stream started each retry with no failed ids, so an affinity pin on a
stream that failed early stayed on the deployment it failed on. Seed the list
with the stream's deployment and add each retry that fails. Drop the 429
python case, whose RateLimitError mock cannot be deep-copied by the router.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* style(router): cargo fmt
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): leave out deployments that failed the request when affinity strips
When the origin had failed this request and no boundary peer existed, the
affinity check stripped the reasoning and returned every candidate, the failed
origin included. Later retries then carried no marker and re-picked the failed
deployment one time in three. Return the untried candidates instead.
---------
Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic-messages): apply additional_drop_params before the unsupported-param gates
* fix(anthropic-messages): apply additional_drop_params before the unsupported param checks
Share the tolerant drop list parser between the Python handler and the Rust host route, clear listed params before the Rust gate, and keep the prompt cache baseline body in step with the real request
* fix(anthropic-messages): leave additional_drop_params keys out of the Rust host body
* test(anthropic-messages): annotate the new test locals with Final
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Python stores a unary messages response from a background cache write task that runs after the router stamps _hidden_params, so the entry carries model_id and the router headers and a later hit returns x-litellm-cache-key. The native path stored the entry inside the native call, before the router saw the response. The async unary store is now deferred until the route encodes its public response and is handed to Python's own cache write task
When the client disconnects mid-stream, the native adapter now logs success for the chunks it delivered before teardown, so spend, SpendLogs and the key's budget and tpm reservations settle the same way they do on the Python path
The proxy records a client disconnect, with its 499 error information, in the stream generator's cleanup. The native teardown billed the stream before that cleanup, so the row had empty error information. A proxy stream torn down by cancellation now bills from the task's done callback, after the disconnect is recorded
A stream whose upstream body ends mid-frame reached proxy callers as a mapped APIConnectionError with status 500. Python's transport raises an unmapped httpx error at that point. The native body read now records a body cut and the host raises the same exception the active transport would
Python wraps a connect, DNS, TLS or reset failure in a synthesized 500 AnthropicError, which maps to InternalServerError. The native path surfaced these as APIConnectionError with the bug-report footer, which also changed cooldown decisions
The proxy bills the estimated prompt of a failed call only when the Timeout was caused by an httpx ReadTimeout. The native timeout now chains the same httpx timeout Python's client raises, so its failure row bills the prompt
Python rebuilds an upstream error response from the decoded body without content-encoding and content-length. The native failure now drops those wire headers, and a failure raised without an HTTP response states no headers at all, like Python
Python's messages transform takes any JSON object from a 200 response and only adds stop_sequence, so a provider answering 200 with an error object reaches the client as 200 and the router counts a success. The native decoder turned it into a 500 APIConnectionError and a router failure. A JSON object that is not a message now passes through unchanged
A non-string extra_headers or deployment header value surfaced from the native handler as an APIConnectionError. It is now refused as an invalid request when the headers are collected, before the provider request is built or logged, so the caller gets a 400 BadRequestError naming the header and its type
Python logs the requested optional params, taken before the provider transform, as model_parameters. The native handler logged the transformed body, so a reasoning_effort request was logged as thinking and output_config. The request context now carries the requested params
Python updates model_call_details with the transformed request body before pre_call, so the logged messages are what was sent. The native adapter kept the caller's messages and compared params as JSON values, so an int 0 logged as 0.0
Python only records custom_llm_provider in model_call_details. The native adapter also wrote it into litellm_params, and the proxy reuses one logger across router hops, so a fallback hop's pre_call log showed the provider where Python shows null
Python only stamps cache_hit when a result came from the cache. The native adapter wrote False on every provider result
Python calls pre_call with the request body as a json user message, and a stream's spend-log cache_key is computed over that input. The native adapter logged the string Messages, so a streamed call's cache_key differed
* fix(messages): log native messages success once, after the proxy releases it
The proxy defers non-stream success logging past post-call guardrails, but the native host parked its log in its own slot and the release only ran for OCR, so a unary /v1/messages call served by Rust logged no success event, no SpendLogs row and no key, team, user or end-user spend. A deferred native success now parks in enqueue_deferred_logging with deferred_success_result, the same slots Python uses, so the proxy releases it like any other call and its guardrail step pruning and cost preparation see it too
Python runs sync success callbacks inside the deferred logging closure, so a post-call hook that blocks the response drops them. A parked native success now carries its sync callbacks and runs them on release
A refused first attempt and its fallback share one logger. Python logs the async success once, for the first attempt, so the native adapter now claims the async success log once across fallback attempts. Like Python, an attempt that loses the claim runs its sync callbacks only when logging is not deferred, and an internal call logs nothing
* test(messages): cover the deferred native success park and release
python-bridge now installs ring in its pymodule_init, matching the gateway's
startup install. redis-connect no longer sets the process default as a side
effect of connecting, so a dependency that calls ClientConfig::builder()
without a provider cannot panic on the Python host depending on whether Redis
has connected yet
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
The Rust credential source passed gcp_service_account straight into the
IAM credentials URL, so a bare email got a 404 and the stores fell back
to per-worker memory. Address it as projects/-/serviceAccounts/<email>
when it is not already a resource name, like the Python gRPC path did.
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix(proxy): report live key and team spend to budget gauges within the key cache TTL
* fix(prometheus): carry live spend for the user, org and customer budget gauges too
The remaining budget gauges for users, orgs and customers read the same cached rows as the key and
team gauges, so they read high for about a minute after a charge. Auth now carries the live counter
for each budgeted entity in one snapshot that only the gauges read, floored at the spend auth loaded.
The x-litellm-key-spend header and logging spend fields keep their current values.
* fix(prometheus): show committed spend in the remaining budget gauges
Reads twin counters that take only charged cost, so a worst-case budget hold
never shows as spent and a request that finishes last cannot set a gauge back.
The twins exist only while the Prometheus logger is registered, and every path
that resets a spend counter drops them. Failed requests now set the org gauge
from the carried org row and committed spend, not the cached org row.
* fix(prometheus): count a charge the cached customer row already holds once
* fix(prometheus): keep committed spend only for budgeted entities and drop it on spend resets
Auth now reads committed spend through the admission MGET and names the counters a charge
may move, so the master key and unbudgeted entities get no twin. Organization spend edits
and the global spend reset drop their twins, and a long request no longer reads as charged.
* fix(prometheus): read the committed org spend on failed requests without the auth object
* test(prometheus): cover a failed request with no carried org
* fix(prometheus): move the committed counters for charges with no auth on the row
A billed background response is charged from its creator's stored attribution, after the request's auth is gone. Its charge moved the live counters but not the committed ones, so every gauge read one charge behind. It now moves the committed counters that already exist, and its own gauge adds its cost to them.
* fix(prometheus): keep the gauges right for pass-through rows, overlapping charges and slow DB spend writes
Pass-through rows carry the auth object, so a cold committed counter gets seeded there too. The gauges read a
charge still waiting in the post-call pipeline as not counted, whatever other charges reached the counter. Committed
counters outlive two DB spend writes. Cold seeds read the DB once per worker, and the global spend reset reads keys
and teams in bounded pages.
* fix(prometheus): count a charged failure's own cost in the org gauge
A stream cut mid-response still charges for what it delivered, and that charge is usually still queued when the failure logs. The failure path passed a cost of 0, so the org gauge left that charge out until the worker's next request
* fix(prometheus): skip twins for window-named ids, drop twins on delete, keep auth out of PostHog
* fix(prometheus): keep the auth object off pass-through rows and drop user twins on every user delete
Pass-through rows now carry only the committed spend in litellm_params, so loggers that dump the row's metadata never get the auth object. Every user delete path, SCIM and bulk delete included, drops the deleted users' committed spend twins
* fix(prometheus): keep committed spend values out of logger dumps of pass-through rows
CommittedBudgetSpend fields are repr=False, so Athina's payload, Sentry breadcrumbs and debug logs that str() a pass-through row's litellm_params show no spend values
* fix(prometheus): keep the gauge fallback on a slow committed read and refresh committed twin TTLs on cluster
The success-path committed read now gets half the per-request budget, so a slow Redis falls back to stored spend before the outer timeout cancels the gauges. Post-call charges refresh a committed twin's TTL on Redis Cluster too, so a twin never expires while its charges are still on their way to the DB. Also applies cargo fmt to the PR's Rust files
* fix(proxy): key the global reset's committed-spend page queries so the Prisma span check reads them
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(cost-map): read alias_of pointer rows in the catalog and the loader
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost-map): keep alias_of rows out of alias lists and add them to the registry schema
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost-map): let alias lists win over alias_of rows in both loaders and never serve a malformed pointer
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(redis): share one native circuit breaker between RedisCache and the Rust stores
RedisCache and the native Redis client each kept their own breaker, so once
the cache learned the coordination Redis was wedged, a spend-counter write
through the native store still paid a full socket timeout. Every Redis target
now has one Rust breaker, looked up by NativeRedisBreaker.shared and injected
into both the RedisCache guard and the native client. The Python FSM is gone.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* style(rust): cargo fmt the shared breaker
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(redis): close the breaker when the recovery probe gets a Redis reply error
A command error such as WRONGTYPE means Redis answered, but the probe was left
unsettled and its drop reopened the breaker for another recovery timeout. Both
the RedisCache guard and the native client now settle such a probe as a success.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* test(redis): pass a NativeRedisBreaker and isolate the shared breaker per test
The sensitive routing test still passed RedisBreakerSettings as the store breaker, and the session affinity fixture reused one Redis URL, so a breaker an earlier test opened leaked into the next. Also make the RUF043 match pattern raw.
* fix(redis): key the shared breaker by server and close the three audit gaps
The breaker registry now keys on the Redis server (host and port, unix socket,
cluster node set or sentinel service) instead of the full connection target, so
caches that differ only in db, credentials or url spelling share one breaker.
A READONLY reply from a replica mid-failover no longer counts as Redis answering,
so it can't reset a run of failures. A new RedisCache refreshes the breaker state
gauge, which the deleted Python breaker did at construction. A shared native client
is only reused by a store that passes the same breaker.
* refactor(redis): split redis-types into modules and drop redundant pyo3 attribute annotations
lib.rs now only declares modules and re-exports, with resolution, target, tls,
auth and endpoint each in their own file. Derived FromPyObject already reads a
struct field as the attribute of the same name, so #[pyo3(attribute)] on the
breaker and store settings did nothing.
* refactor(redis): drop redundant pyo3 attribute annotations in the stores and let PyO3 build the cooldown snapshot
Derived FromPyObject already reads each field as the attribute of the same name.
The cooldown snapshot returns an IndexMap, which PyO3 turns into the same dict in
the same order.
* refactor(redis): return a HashMap from the three memory-tier snapshots
The snapshots read cache-memory's HashMap, so there is no order to keep.
PyO3 builds the same dict from a std HashMap, which replaces the hand-written
PyDict loops in the spend counter and router usage stores and the IndexMap in
the cooldown store. The rate-limit slot registry keeps IndexMap because it
hands back a Python dict in the order Python wrote it.
* refactor(redis): share Redis breakers and clients through one RedisHosts per host
redis-connect's RedisHosts now owns the per-server breaker and the shared clients
that python-bridge kept in two process-wide statics. A client takes breaker
settings and admits through its server's breaker, so no caller can pair a client
with a breaker of its own, and clients are keyed by Resolution alone. This drops
RedisClient::guarded_by and Breaker::same.
python-bridge keeps one RedisHosts per process and calls it with the GIL released.
The gateway builds one per connect, so its coordination and response cache on the
same server now share a breaker. RedisStoreSettings.breaker is back to breaker
settings, as on main.
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix(router): pin /v1/responses requests for prompt caching affinity
* fix(router): pin previous_response_id turns and keep native tools in the Responses pin key
A Responses turn that continues a stored response now goes to the deployment
that answered it, unless that deployment already failed this request. Native
Responses tools are hashed into the pin key as sent instead of converted, so
two requests with different native tools no longer share a pin and a native
request no longer logs a false dropped-tool warning. The pin keeps its
cacheable deployment ids in a sorted tuple so loggers can serialize request
metadata.
* fix(router): leave a Responses request with a malformed tool to the provider
* fix(router): keep the Responses prompt cache pin out of logged metadata
The pre-call check now keeps the pin in a router-owned in-flight store and
puts only a random token in litellm_metadata, so loggers that ship metadata
never see the routing key or deployment ids. The store is shared across check
instances, so turning prompt_caching off and on at runtime keeps pinning, and
a retry drops its previous attempt's token. The skipped-input debug log now
names only the error type.
* fix(router): apply the prompt caching pin after tag, region and pre-call filters, and leave it on retries
The prompt caching check no longer narrows the candidates inside the callback
filters. It names the deployment it prefers, and the router core applies that
preference at the pinned deployment step, after tag, region, pre-call and plugin
filters, only when the deployment is still a candidate. A pin can no longer
send a request to a deployment its tags do not allow.
A retry skips the pin when the pinned deployment was already tried in this
request, read from the retry breadcrumbs in both metadata buckets and the
excluded and retry-skipped ids. When the retry count outruns the breadcrumbs
the check stands down, so a pinned deployment that keeps failing is not
retried on every attempt.
* test(router): list the prompt caching check as an in-memory cache caller
The check's in-flight Responses pins live in a process-local InMemoryCache, so it opens no Redis span and needs no key family, like the other in-memory callers
* fix(router): pin a lone healthy deployment, free every in-flight Responses pin, and clear a reused metadata dict's retry records
* test(router): lift test cooldowns through the cooldown store's evict_local
* fix(router): key Responses tools like their chat twin and drop the pin token after success
A Responses function tool now hashes only the function fields it sent, so a chat request and a Responses request with the same tool share one pin. The success event also removes the pin token from the caller's metadata dict.
* test(router): cover untyped tool parameters and custom tool grammars in the Responses pin key
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
RouterEvent and the types it carries (FailureKind, Blocked, MockFailure,
RetryCause, PickError) now serialize, so a host can log or forward events as
JSON instead of parsing their Debug text. Events are tagged by "event",
durations are seconds, failure kinds use litellm's exception class names
* feat(redis): route the router, rate limiters and auth through the native store families
* style(redis): satisfy the python lint gates
Format the rate limit store, sort its __all__ and give the routing read batch and two tests concrete list and dict types.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(router): give the registry's default usage store a memory-only handle
RouterUsageStore now takes a handle, so the default passed None and any usage read before RustCore swapped in its store raised AttributeError.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* test(redis): build stores from native handles and wait for router tasks
Tests still used the pre-refactor store constructors (Store(None), handle= factories, NativeIncrement, tuple scopes). The router outcome tests counted 20 loop ticks, too few now that the allowed-fails increment resolves on the native runtime, so settle() waits for the scheduled tasks instead.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Reworks the redis-client, connect, resolve and testing crates, adds python-compat json loads and
TTL seconds, replaces the redis-store memory tier with a DualCache plus a shared failure log, and
gives the Python side the Redis timeout log throttle and a request OTEL parent span for service events
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
A bare model name that no team pattern matches as spelled is now tried again as provider/model against the caller's team pattern routers, as PatternMatchRouter.get_pattern did in the Python core, with the routed deployment's model filled from the prefixed name.
* feat(gateway): forward HTTP requests to the Python proxy
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(gateway): preserve required forwarding headers and separate upgrades
* test(gateway): clarify hash compatibility and relocate forwarding docs
* test(gateway): define URL fragment forwarding behavior
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Adds the litellm-router-core crate, its step-driven PyO3 bridge
(RouterCoreHandle / RouterCall) and RustCore (litellm/router_rust/),
served behind LITELLM_RUST through the ROUTER route rule. The host
call-out is the only boundary: every attempt goes through Host::invoke,
there is no native executor path, and RustCore never builds, wraps or
forwards to PythonCore, so router_python_core.py stays deletable.
Attempt preparation lives in litellm/router_attempt.py so it outlives
router_python_core.py.
RustCore matches PythonCore's behavior, including its known bugs (fixed
in follow-up PRs). Routing decisions (strategy picks, routing groups,
PTU, pre-routing, pre-call checks, fallback walk, health routing, access
groups, weights, cooldowns, allowed fails, usage) live in the crate;
work that needs live Python objects (request shaping, endpoints,
streaming, model info facts, callbacks, alerting, prompt management)
lives in the host-side litellm/router_rust/ package (steps/, invoke/,
surface/) driven by Rust steps.
The crate owns the registry. It runs the deployment build loop (secret
references, ids, organization fan-out, install order) and asks the host
for what needs Python, one deployment at a time so errors surface where
Python raised them: secrets, validate, provider and added steps. It
holds the model list, the index maps and the pattern routers with the
Python core's history rules (host_index.rs), and answers the registry
lookups (lookup.rs). The Python views of that state in
litellm/router_rust/surface/ (model_list, index(), names(), patterns())
read the handle, and every write to them becomes a changeset. Model
info, deployment model info, configured limits and model group info are
merged in the crate (model_info.rs, group_info.rs) from catalog rows and
facts the host answers on a model_info step asked at query time, so
price reloads and register_model stay visible. The usage cache key
format is defined once, in the crate.
The crate records each attempt's outcome itself rather than through
litellm callbacks. A streamed attempt is deferred: it counts its
request when the stream opens, and the host's stream wrappers report
the success with the final usage, or a failure after the first chunk,
when the stream ends, as the Python core's callbacks do.
tests/unit/test_router/core characterizes PythonCore's public behavior
and runs every test on both cores, with nothing pending; only the names
of the Python core's own outcome callbacks are asserted on Python alone.
litellm.Router is now final: subclassing it raises TypeError at the class statement, and the
machinery that kept subclass overrides working is gone. The Rust core never honoured subclass
overrides, so they would have silently stopped running there. Custom routing goes through
register_plugin(), settings through apply() and outcomes through observe(). This is a breaking
change for anyone subclassing Router.
Fuzz parity fixes on top of the rebase: the Rust core keeps num_retries,
max_fallbacks, allowed_fails, retry_after, timeout, the tag settings,
routing_strategy_args and the fallback lists as given (the crate reads
them as numbers, update_settings casts as Python does); a deprecated
`model_list = [...]` write reaches the Rust core; a failed set_model_list
is all or nothing on both cores (the deployments served before the call
are put back and the error raised); config_deployments() is a generator and `del` of a plain
attribute works on the Rust core. Least-busy pick reservations from
main now work on the Rust core: its selectors share one reservation
store, routed calls reserve and free their unstarted picks, and
select() and batch cancel do not reserve. On the Python core a dropped
upsert takes its name back off deployment_names, and
get_deployment_order reads every numeric spelling as one int so mixed
orders no longer raise TypeError.
Rulings on the remaining differences, the Python core changed where it
was the odd one out: sync picks and picks by deployment id apply the
team filter as async picks do, so another team's deployment is refused;
the fallback lists and default_litellm_params in RouterSettings are
copies, so an in-place edit is ignored and settings change only through
apply(); one health record with an unreadable timestamp drops out alone;
an empty fallback entry is skipped; a bool cooldown_time is refused at
construction, a bool or string cooldown_time on a deployment or a call
falls back to the router default, and a failure status that no HTTP
status can be is recorded as 500; an infinite or NaN cost and a whole
number wider than 64 bits (ptu_shares) are refused on both cores with
the same error (litellm/router_utils/deployment_numbers.py); and a
/v1/messages stream whose provider iterator raises cools the deployment
and retries like a non-stream call, with the Rust core waiting for that
cooldown before its retry picks.
Differences the proxy parity fuzz and its regression tests found on the
Rust core: a file upload or a batch on an uploaded file falls back only
within its own model group, as on the Python core, since the file lives
with one provider (the host sends same_group_fallbacks_only and the walk
skips targets in other groups); Decisions calls drop deployments whose
provider has no Decisions config, and deployments that refuse the audio
or videos a call carries, unless that would leave none, as the Python
core does, while the retry count still reads the whole group; a file
upload that fails on one order level is created on the next level's
deployments rather than the first level again; and a response that
cannot be converted (a text_completion body without a message) reports
only its own traceback, so a rate limit handled by the attempt before it
no longer turns the error into a 429, and both cores return 500.
* fix(auth): align cloud credential loading and expiry with the Python SDKs
* feat(auth): resolve consumer-scoped default identities for AWS and Azure
AwsAuthService::default_chain_credentials and AzureAuthService::identity_token give a consumer the SDK's own default identity without LiteLLM's Bedrock or Azure OpenAI settings. Moved here from #49510 so every shared auth crate change lives in one PR
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(auth): include identity hints in secret snapshots
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* feat(model-catalog): add regional_processing_uplift_multiplier_fedramp
* refactor(model-catalog): make the FedRAMP uplift its own fedramp_uplift_multiplier key
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(realtime): support latest OpenAI audio models
* fix(transcription): type SDK stream duration metadata explicitly
* fix(realtime): preserve transport settings and translation duration
* refactor(realtime): reuse SDK client initialization
* fix(audio): bill finalized streams and authorize transcription models
* refactor(audio): keep transcription pricing selection together
* fix(realtime): reconcile model metadata and test contracts
* fix(realtime): preserve provider duration and model capabilities
* fix(realtime): keep transcription validation compatible with cost map guard
* fix(realtime): address transcription and billing review findings
* fix(realtime): preserve input usage and provider routing
* fix(realtime): bill retained output and route Azure aliases
* fix(realtime): reject malformed provider durations
* fix(realtime): preserve batch cache rates and Azure v1 routes
* fix(transcription): reject nonfinite provider durations
* refactor(realtime): align annotations with current lint rules
* fix(realtime): preserve translation deployment pricing and input usage
* test(transcription): verify synchronous stream finalization
* fix(realtime): retain missing translation input usage at close
* fix(transcription): reject streams that bypass output guardrails
* fix(realtime): reconcile audio protocols billing and current CI
* fix(realtime): trust confirmed formats and authorize default models
* fix(realtime): preserve absent models and reject unsupported guardrails
* fix(realtime): reject translation policy pipelines
* chore(ci): rerun transient infrastructure timing failure
* fix(realtime): reconcile audio protocols with current upstream
* fix(audio): validate provider responses at SDK boundaries
* fix(realtime): preserve minimum OpenAI SDK compatibility
* fix(realtime): preserve deferred Live session authorization
* fix(realtime): preserve upstream authentication and transcription behavior
* fix(audio): scope provider duration precedence to configured models
* fix(typing): avoid Final declarations inside transcription cost loop
* refactor(audio): reuse transcription mapping and duration resolution
* fix(realtime): enforce model budgets and preserve translation routing
* fix(audio): log streamed transcripts whose done event reports detected languages
* fix(audio): pass stream, languages and keywords through unchecked for non-OpenAI transcription providers
Providers without a streaming transcription handler got UnsupportedParamsError
for stream=True, languages and keywords, where the merge base forwarded them as
provider-specific params. Only openai and azure validate them now.
* fix(audio): bill streamed gpt-transcribe from the provider's reported duration
The stream path computed cost after logging had replaced the transcription's
duration usage, so it fell back to the measured file length while the
unstreamed call billed the provider's seconds.
* fix(transcription): log streamed transcription usage from the provider response
The stream logging path built the spend payload from the response after
its duration usage was transformed away, so whisper-1 with stream=true and
streamed gpt-transcribe logged an empty usage object. Bill and log from the
provider's TranscriptionResponse in both the sync and async paths.
* fix(realtime): keep main's routing, protocol and transport behavior around the new translation routes
- Send OpenAI realtime and translation client_secrets and calls through litellm's httpx client again, so ssl_verify and custom CA settings apply and upstream errors keep main's shape
- Use the input transcription model as the session model only for transcription sessions
- Drop the new /openai/v1 translation aliases and record each lazy feature's own routes, so the /openai pass-through and the MCP routes resolve as on main
- Let a configured Azure realtime_protocol win for every model, with GA as the default only when none is set
- Return x-litellm headers on streamed transcriptions and mark the request done
- Refuse translation sessions before connecting upstream when realtime guardrails apply or the provider is not OpenAI or Azure
- Accept json and text for gpt-transcribe, and drop other formats under drop_params instead of failing
- Bill translation sessions on output audio seconds only, at the single published rate
- Document the 201 SDP answer on the translation calls routes and the transcription 200 response
* fix(realtime): restore main behavior for guardrails, Azure transcription, and realtime clients
Streamed transcription runs unstreamed when a deployment post_call guardrail applies, so the
guardrail still sees the transcript. Azure transcription maps v1, latest and preview to the
default dated version on the deployments route for every model. The SDK client secret keeps
session.model ahead of model, realtime WebSockets connect to api_base again, realtime metadata
keeps only guardrails, and managed agents need an explicit transcription model. Reverts the two
unrelated streamed Responses error codes and the duplicate cached_tokens_details field, and the
gpt-transcribe format check only reads the request provider's cost map entry.
* fix(realtime): keep main's transcription, client secret and route behavior where the PR changed it
Transcription reaches every provider as on main again, sends stream only when asked, forwards language and
languages together, keeps form key order, bills provider seconds only when above zero, honors base_model for the
new flags, keeps main's Azure api_version on the proxy path, and streams carry chat's headers, an error event on a
mid-stream failure, and a spend row when the stream ends early. Translation cost reads both per-second rates from
one source and spend rows carry the billed seconds.
Realtime transcription WebSockets keep model in the upstream URL outside OpenAI's hosts, client secrets forward
explicit nulls, accept conversation and delay, and answer 400 on a malformed body, the /openai translation paths
are back to main, translation refuses only for guardrails realtime sessions run, nested aliases resolve and later
session.update models are authorized, translation client secrets run per-model auth, beta clients bridged to GA
get beta-shaped session events, and transcription sessions send the deployment model in both shapes.
* fix(realtime): address review findings on transcription billing, streaming and realtime auth
Per-second pricing replaces token billing only when the priced entry sets no token rates, translation rates fall back per key to the cost map, transcription cache keys include languages and keywords, a stream request a post_call guardrail forces unstreamed comes back as redacted SSE, Azure beta clients are bridged only for GA-only deployments, nested transcription models on the realtime WebSocket are checked against the key, and translation spend carries key and team metadata
* fix(azure): pick the GA realtime protocol for deployments whose model_info.base_model is GA-only
* fix(realtime): preserve prior merge resolutions after rebase
* fix(realtime): enforce translation policies and normalize Azure transcription URLs
* fix(cookbook): stop translation once output idles after the upload ends
* fix(realtime): bill translation on input audio and drop pre-read stream cost headers
Translation spend now uses the input audio seconds the session sent, priced
through input_cost_per_second, instead of the translated output duration.
A streamed transcription no longer returns cost headers before the stream is
read, since the cost is only known after the last event. Also removes an
unused realtime guardrail helper.
* fix(realtime): drop top-level session nulls, bill dropped transcription streams, and bridge beta response fields
Client secret, translation and transcription session bodies drop top-level nulls again, as main did, while nested nulls such as turn_detection still pass through. Transcription client secrets send the deployment model as session.model. A streamed transcription the client drops still runs its success callbacks, and the stream ends with data: [DONE] like OpenAI's. The beta to GA bridge maps max_response_output_tokens, speed and noise reduction, remaps response.create, and drops temperature under drop_params. The Entra token for realtime HTTP routes is fetched off the event loop
* test(e2e): cover realtime translation, live transcription, client secrets, and streamed transcription
* fix(realtime): close review gaps in translation billing, transcription streams, and Azure GA
Bill translation sessions from the deployment's own per-second rates, add per-second prices for
Azure gpt-4o transcribe models, keep stream-scoped guardrails seeing the caller's stream flag, map
mid-stream transcription errors to LiteLLM exceptions with a [DONE] frame, map GA responses back to
the beta shape for bridged beta clients, honor the minting key's guardrail opt-out on translation
calls, restore the Azure transcription session URL, and flag GA-only Azure realtime models
* fix(realtime): bill a translation rate the deployment omits from the session model
* test(e2e): check translated speech is not English instead of exact French wording
* fix(realtime): keep main's behavior for non-bridged backends, stream error frames, gateway URLs and Azure transcribe prices
Remap beta events to GA only for bridged beta clients and translation sessions, bridge beta clients on GA-pinned Azure deployments, log error-only upstream sessions as failures, flag dated Azure GA realtime models, drop the unpublished Azure per-second transcribe rates, log a mid-stream transcription failure once, keep main's SSE error frame outside transcription, drop unsupported transcription params under drop_params, keep the caller's Azure auth headers, keep a gateway /v1 path, let key opt-outs release string-callback guardrails on translation, and keep the cookbook waiting while a long upload is still sending
* fix(realtime): keep the proxy's realtime session gate off translation sessions
A key that opts out of a legacy callback guardrail now gets a working translation session, since the transcription-guardrail gate no longer sends a realtime session.update the translation upstream rejects
* fix(realtime): keep websocket model limits, bill measured transcription length, route transcription sessions on the allowed model
A WebSocket opened without a query model now authorizes as an empty model, transcription cost prefers the measured upload length over the provider's reported seconds, transcription sessions overwrite nested models with the authorized top-level model again, and a non-boolean transcription stream value answers 400 or is dropped under drop_params.
* fix(ci): copy the rust bridge extension into the openapi docs gate's base worktree
* fix(model-catalog): accept the realtime translation endpoints in the cost map
* fix(cookbook): close the translation session and read until session.closed
* fix(realtime): treat an empty transcription stream as unset and pass the cost-map guard
An empty `stream` form value runs the transcription unstreamed again, as
OpenAI does, instead of answering 400. The four translate cost-map entries
drop the translation routes from supported_endpoints until the main
branch's catalog parser accepts them, and the nested transcription model
lookup uses the router registry entry point.
* test(proxy): drop the mid-stream error frame pin that main's error shape change replaced
* fix(transcription): bill uploaded seconds when a stream fails mid-transcript
* fix(proxy): bill uploaded seconds when a streamed transcription breaks mid-stream
* fix(audio): keep transcription's positional arguments and redact streamed error details
- Move the new languages, keywords and stream options to the end of transcription's parameters, so a prompt or format passed by position keeps its meaning
- Redact internal hostnames, paths and tracebacks from a streamed transcription's mid-stream error event, as chat streams already do
- Move the CA-bundle check for the realtime HTTP routes, which serves real TLS on loopback, from the unit suite to the SDK integration suite
* fix(audio): stream the guarded transcript to SDK callers that asked for a stream
* fix(logging): keep a streamed transcript out of callbacks that turned off message logging
A streamed transcription's assembled response reached success callbacks with its text intact under turn_off_message_logging or a callback's message_logging=False, because the shared streaming redactor had no transcription branch. It now redacts the text, as the unstreamed call already does
* fix(proxy): stream a transcription the deployment streamed when the client sent no stream field
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(model-catalog): declare the thinking_on_by_default key
The cost map guard runs main's catalog on a PR's cost map, so the key has to be declared on main before a PR can set it on the Claude 5 rows
* chore(model-catalog): keep the attribute list sorted and document thinking_on_by_default
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(count_tokens): count grok-4-1, grok-4.3 and DeepSeek V4.1 tool requests like their chat templates
Render grok-4-1, grok-4.3 and DeepSeek V4.1 tool schemas the way each chat
template does, and add a per-deployment token_count_tool_framing next to
token_count_framing for the hidden tool preamble a host bills. The Azure AI
Foundry grok-4-1, xAI grok-4.3 and Fireworks DeepSeek V4.1 cost map rows carry
the measured framing, overridable in model_info
* fix(count_tokens): count Azure grok-4-1 Responses requests with their own framing and use the tool framing in place of the base framing
* fix(count_tokens): keep operator framing on tool and Responses counts, frame bridged Responses like chat, follow base_model for tool rendering, count grok tool_choice
* fix(token_counter): count Azure Responses strict default, skip false strict and built-in-only tools, per-kind operator framing
* fix(token_counter): count an explicit null strict like false on Azure Responses
* fix(count_tokens): follow the chat completions bridge flag and Azure's strict default on azure/ deployments
Keep Azure grok-4-1 chat tool counts at or over the bill by raising its tool framing to 302
* fix(token_counter): keep strict false for non-grok templates, coerce the bridge flag, frame DeepSeek API counts
* fix(proxy): frame Responses counts for the api_base router defaults send inference to
* fix(proxy): keep the api_base helper's name so main's /v1/messages count caller resolves
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(model-catalog): declare the tool and Responses token count framing keys
* fix(model-catalog): read token count framings as strict integers
The cost map guard read the framing keys as lax counts, so a text "214"
or a true passed while litellm's reader drops both and falls back to the
plain framing. Read all four framing keys as plain u64, matching the reader
* fix(model-catalog): accept whole-float token count framings the way the Python reader does
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(anthropic): sync the beta header allowlist with what anthropic, vertex_ai, and azure_ai accept
* test(e2e): send the azure_ai beta check without the code execution tool
* test(anthropic): require a vertex_ai and azure_ai decision for every anthropic beta
* fix(anthropic): forward the betas Claude Code sends that anthropic, vertex_ai, and azure_ai accept
* test(e2e): send Vertex's header-only betas in the beta acceptance case
* fix(anthropic): keep forwarding Vertex computer-use betas and point beta tests at platforms that still lack them
A live probe found each Claude 4.5 and 4.6 model on Vertex needs one of the two
computer-use betas for the computer tool, so dropping both broke it. The e2e
acceptance test leaves those two out of its all-at-once Vertex call, and the
integration and unit tests that relied on a beta being dropped now use one
the platform still lacks.
* test(anthropic): point unsupported-beta tests at betas the platforms still drop
The Azure AI handler test used claude-code-20250219 as the beta Azure drops, and the
Rust parse test used it as an unknown value. This PR forwards it on Azure AI and maps it,
so both now use values that stay dropped or unknown.
* fix(anthropic): add computer-use-2025-11-24 for the computer_20251124 tool
The computer_20251124 tool fell through to the default computer-use-2024-10-22 beta, which the
provider rejects for that tool version. Map it to computer-use-2025-11-24, which the beta map now
forwards on anthropic and azure_ai
* fix(anthropic): send no computer use beta for an unknown computer tool version
An unknown computer tool version fell back to computer-use-2024-10-22, which the anthropic and azure_ai columns now forward. It now gets no beta, as every platform effectively sent before. Every computer tool version also skips defer_loading and allowed_callers, computer_20251124 included
* test(azure_ai): read the branch's beta map in the auto-injected beta wire test
* fix(anthropic): keep defer_loading and allowed_callers on the computer_20251124 chat tool
* test(anthropic): read the branch's beta map in the azure_ai safeguards beta wire test
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* docs(model-catalog): explain meter, band, channel and When
Add a Concepts section to the model-catalog AGENTS.md with worked key
breakdowns, doc comments on the undocumented litellm-cost price types,
and a cost AGENTS.md that points to the concepts.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* docs(model-catalog): write concepts as nested lists
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* docs(model-catalog): spell out band rules and channel fallbacks
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix(anthropic): map pause_turn and return refusal explanations on chat and responses
pause_turn now maps to finish_reason length (Python and Rust) and keeps the raw
stop_reason in provider_specific_fields. Responses reports a paused turn as
incomplete with max_output_tokens and shows the unrun server search as an
in_progress web_search_call instead of a client function_call.
A refusal's stop_details.explanation now fills message.refusal and the final
stream delta.refusal on chat, and becomes a refusal content part on Responses,
streamed or not.
* fix(anthropic): let a chat client resend a paused turn so Claude continues it
* fix(anthropic): replay a paused chat turn without its thinking blocks, and drop its unrun search before a new message
Chat cannot say where Claude wrote each thinking block in a paused web search turn, and
Anthropic answers 400 when one moves but accepts the turn without them. A new message after
a paused turn also 400s on a server_tool_use with no result, so that unrun search is dropped.
* fix(responses): send the streamed refusal part's type and text in content_part.added
* fix(anthropic): keep pause_turn and Claude refusal explanations out of the Messages adapter's text
A paused Claude turn now ends on stop_reason pause_turn instead of max_tokens, streamed or not. A Claude refusal keeps its explanation in stop_details with Claude's category and no longer repeats it as a text block, so a guardrail mask on a streamed refusal is delivered. A paused turn sent back with list content drops its thinking blocks like string content does
* fix(anthropic): replay a paused turn with one unrun search and no thinking on chat and Responses
* fix(responses): report a paused Claude turn as completed so Codex and the Agents SDK keep going
* fix(responses): mark a paused turn's message item completed
* fix(responses): mark every item of a paused turn completed
* fix(responses): keep a refusal's explanation when a refused turn is sent back
A refusal part in a Responses input message now goes to the model as text, so the assistant turn is no longer dropped from the history. The integration test now expects a paused Claude turn on Responses to report completed, and the paused-turn test helper is typed
* fix(responses): scan refusal parts in Responses guardrails
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* refactor(proxy): inject database repositories through per-repository dependencies
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* test(proxy): model Prisma client cleanup
* test(rust): include NativeDatabase in bridge API surface
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(vertex_ai): forward and auto-add the compact-2026-09-04 beta on Claude routes
* test(vertex_ai): prove the compact-2026-09-04 beta reaches the wire through both Claude handlers
* fix(vertex_ai): move a client-sent body compact-2026-09-04 beta to the request header
* refactor(vertex_ai): build the Claude beta set without mutation and inject the client in the messages wire test
* fix(vertex_ai): keep client body betas in the body and answer 400 on a malformed anthropic_beta
* fix(rust): allow the compact-2026-09-04 beta on vertex_ai in the Rust beta table
The beta header config now maps compact-2026-09-04 for vertex_ai, so the Rust
table that mirrors it must stop rejecting that beta there, and the Rust Vertex
messages route adds it for a compaction request like the Python route does.
* fix(vertex_ai): keep client body betas out of the Vertex body next to litellm betas, honor drop_params, and send the compaction beta on count_tokens
Litellm's own betas replace a client's body anthropic_beta again, as on main, so a body beta
Vertex rejects no longer turns a 200 into a 400. A malformed beta drops under drop_params and
names its field otherwise. inline-tools-2026-09-15 joins compact-2026-09-04 as header-only, since
Vertex rejects both in the body. Vertex count_tokens sends compact-2026-09-04 when the request
carries compaction.
* fix(logging): log and bill Anthropic messages compaction responses on the Rust route
The Rust route hands the served Anthropic body to the logger, which validates it
against AnthropicResponse. That model had no compaction content block and no
compaction stop reason, so a compaction reply raised and wrote no spend row.
* fix(vertex_ai,azure_ai): forward compact-2026-09-04 to Azure AI Foundry, merge Vertex body betas, and redact compaction summaries
Azure AI Foundry needs the compact-2026-09-04 header for compaction, a replayed compaction block, and count tokens, so the beta map, the native compaction providers, and the Rust beta table now allow it there. Vertex keeps a client's body betas next to the ones litellm adds, as the Anthropic route does, and turn_off_message_logging now redacts compaction summaries too
* fix(vertex_ai,azure_ai): auto-add thinking display and tool change betas, redact streamed compaction summaries
Folds the header changes from #44103 into this PR. Vertex AI and Azure AI Claude
routes now add thinking-display-updates-2026-08-18 when thinking.display is
"updates" and mid-conversation-tool-changes-2026-07-01 when a tool_addition
block is present, matching the Anthropic and Bedrock routes.
With turn_off_message_logging on, compaction summaries from streamed messages
and streamed chat completions are now redacted in spend logs and callback
payloads, like the non-streamed response already was.
* fix(vertex_ai,azure_ai,rust): add tool change betas on count tokens and Rust messages, bill Rust server tool replies
Vertex and Azure count tokens now add mid-conversation-tool-changes-2026-07-01 when the history carries a tool_addition or tool_removal block, through one shared helper with the compaction beta.
The Rust /v1/messages route adds thinking-display-updates-2026-08-18 and mid-conversation-tool-changes-2026-07-01 when a request uses them, on the providers that accept each beta.
Rust-route logging parses the served body with the Anthropic response parser, so web_search, pause_turn, mcp_tool_use and container_upload replies get a spend row.
Legacy enabled thinking keeps display updates on anthropic too, and the Vertex transform reads drop_params through drops_unsupported_params.
* style(rust): rewrap beta map test line with cargo fmt
* test(rust): expect the display beta on Databricks, which main's beta list now accepts
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix: openai exception mapper ignored status code for invalid_request_error
_map_openai_exception coerced anything whose body carried type
invalid_request_error into BadRequestError, guarded only by excluding the single
phrase Incorrect API key provided, and this ran before the status-code checks.
OpenAI and openai-compatible providers return 401 and 404 bodies with type
invalid_request_error, so an auth failure like Invalid API key mapped to a 400
instead of AuthenticationError, and a 404 mapped to BadRequestError instead of
NotFoundError. That changes the status returned to proxy clients and router
retry, cooldown, and fallback handling. Mirror the Azure mapper by only coercing
to BadRequestError when status_code is None or 400, so 401 and 404 fall through
to their existing handlers.
* fix(exceptions): map OpenAI-family invalid_request_error 404s to NotFoundError
Move the contributor's test to the mapped unit test file, assert the raised
class, status code and message, and cover the 400 and status-less cases that
must still raise BadRequestError
Add a regression test for the flow the bug was found on. Retrieving a missing
OpenAI vector store, sync or async, now raises NotFoundError with status 404
The router test that pinned an OpenAI 404 typed invalid_request_error as
BadRequestError now expects NotFoundError
* fix(a2a): answer a provider NotFoundError as JSON-RPC invalid params
* fix(exceptions)!: limit the invalid_request_error status guard to 401 and 404
Every other status keeps raising BadRequestError as on main, so 402-415, 429 and 5xx bodies typed invalid_request_error keep their class and router retry behavior. A2A goes back to main's mapping, which answers NotFoundError and AuthenticationError as JSON-RPC internal errors.
* fix(exceptions): keep the provider error fields on mapped 401 and 404 invalid_request_errors
Raise AuthenticationError and NotFoundError straight from the invalid_request_error
branch with the provider body, so code, param and type survive and the proxy's
error.type matches main. The Rust mapper copy skips 401 and 404 the same way.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(ocr): support outputContentFormat=markdown for Azure Document Intelligence
* fix(ocr): map only span endpoints when slicing Azure Markdown pages
* fix(ocr): accept any casing of outputContentFormat and report code point offsets
Azure reads outputContentFormat case-insensitively, so Markdown and TEXT
now map to the same values instead of returning 400. When the proxy asks
Azure for code point offsets to split Markdown pages, the response now
carries stringIndexType so callers know the unit of table and key-value
spans. Tests use rstest and the enum derives VariantArray per the Rust
workspace rules.
* fix(ocr): ask Azure for code point offsets only on prebuilt-layout and keep line-joined pages when spans are malformed
* fix(ocr): trim Azure DI outputContentFormat, accept output_content_format, and drop invalid values under drop_params
* fix(ocr): fall back to output_content_format when outputContentFormat is empty
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(bedrock): omit system prompt from audio transcription
* fix(bedrock): report Converse token usage on audio transcription
Bedrock transcriptions returned usage null and were billed at $0. Map
Converse inputTokens, outputTokens and totalTokens into the transcription
usage so spend uses the model's per-token price. input_token_details is
optional because Converse does not split audio and text tokens.
Also switch the updated request-shape test to rstest.
* fix(bedrock): default transcription temperature to 0 and price ap-southeast-2 Voxtral regionally
Voxtral wrapped some transcripts in quotes at its default sampling
temperature. In direct Converse calls in ap-southeast-2, 0 of 48 calls at
temperature 0 were framed against 7 of 72 at the default, and instruction
wording made no clear difference, so the request now sends temperature 0
when the caller sets none, matching OpenAI's transcription default.
Calls in ap-southeast-2 billed at the us-east-1 price. The cost map gains
bedrock/ap-southeast-2 Voxtral rows with all four service tiers, the Bedrock
transcription response carries the deployment region in its hidden params,
and the transcription token cost uses the region-resolved model key.
The bridge now builds the response with model_copy instead of assigning
usage after construction, and the native wheel test checks the usage the
compiled route returns.
* fix(bedrock): forward transcription language, reject unsupported formats, and bill env and Tokyo/London regions
get_optional_params_transcription had no Bedrock branch, so language,
response_format and timestamp_granularities were dropped before the Rust
transform ever saw them. Bedrock now forwards language, prompt and
temperature, accepts response_format json or text (the only shapes it can
return), and answers 400 for srt, vtt, verbose_json or
timestamp_granularities unless drop_params is set.
The billing region now falls back to AWS_REGION_NAME and then AWS_REGION
when aws_region_name is unset, the same order the Rust resolver uses to
pick the endpoint, so an env-configured region gets its regional price.
Adds ap-northeast-1 and eu-west-2 Voxtral rows (standard, batch, flex and
priority) from the AWS Bedrock offer files, the other two regions AWS
serves Voxtral audio in.
* fix(bedrock): send transcription temperature as a number and name the rejected param
The proxy keeps multipart form values as strings, so -F temperature=0.2
reached Converse as "0.2" and Bedrock answered 400. The Bedrock mapper now
converts temperature to a float and answers 400 (or drops it under
drop_params) when it is not a finite number.
get_optional_params_transcription copied prompt and temperature back from
the raw call after the Bedrock branch ran, which undid that conversion and
any drop. The Bedrock branch now owns every OpenAI transcription param.
An unsupported param such as timestamp_granularities now gets a 400 that
names it instead of the generic "user/encoding format" message.
* refactor(bedrock): return unsupported transcription params as a value and raise at the param step
* fix(bedrock): drop the retired max_tokens field from the regional voxtral price rows
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
