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95 commits
| Author | SHA1 | Message | Date | |
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yujonglee
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574fcea691
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fix(redis): share one native circuit breaker between RedisCache and the Rust stores (#50473)
* 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> |
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tessellark
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b5a72c2042
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fix(router): pin /v1/responses requests for prompt caching affinity (#50321)
* 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> |
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yujonglee
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b1b236826a
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feat(redis): serve the proxy's common Redis call with Rust stores (#50170)
* 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> |
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Kerry Lu
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8ac9da84f7
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fix(router): drop supports_web_search false deployments for Anthropic web_search_* and Gemini googleSearch tools (#50275)
* fix(router): drop supports_web_search false deployments for Anthropic web_search_* and Gemini googleSearch tools * test(integration): build the web search filter proxy config without mutating the shared config --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Kerry Lu
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3f13c1ca34
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fix(router): write the prompt caching pin when turn_off_message_logging is on (#50276)
* fix(router): write the prompt caching pin when turn_off_message_logging is on The success event PromptCachingDeploymentCheck reads had its messages redacted in place by turn_off_message_logging before any callback ran, so the pin was keyed off redacted-by-litellm, never written, and every follow-up bounced across the group. Callbacks that route on the request and never log it now opt out of that redaction and get the request messages back, while every other callback and the spend log keep the redacted payload. * fix(logging): type the request-messages payload helper as dict[str, object] The bare dict return grew the LIT001 count past the merge base and left the returned fields unchecked * test(integration): type the pin rig's Redis client as Redis[bytes] The untyped generic grew the basedpyright reportUnknownMemberType count past the merge base * test(integration): quote the Redis[bytes] annotation so the rig collects at runtime redis.Redis is not generic at runtime, so the unquoted subscript raised TypeError on import * fix(logging): read the request messages once as object in the exempt payload helper Two partially unknown reads of self.messages grew the basedpyright reportUnknownMemberType count past the merge base --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Nate Armstrong
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e011a4ea9b
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fix(router): do not cool down a deployment on a 404 from a response id lookup (#50262)
The Rust core records every attempt failure against the routed deployment, so a client GET, DELETE, cancel or input_items call on a response id that the provider answers with 404 counted toward cooldown. The removed Python core never saw these failures. Exempt them in failure_exits next to the background poll 404 and video lookup exits. |
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Nate Armstrong
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067f93340f
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refactor(router): delete the python router core, the rust core is the only core (#50178) | ||
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Nate Armstrong
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9752869d84
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feat(router): add the Rust router core with the host as its only boundary (#49513)
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. |
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zoveki
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784754ca48
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fix(azure)!: answer 401 when Entra rejects the deployment's credential (#49863)
* fix(azure): answer 401 when Entra rejects the deployment's credential A ClientAuthenticationError from the Entra token provider (wrong, expired or rotated client secret) used to surface as a retryable 500 carrying the app's client id and Entra trace ids. Map it to a 401 AuthenticationError that keeps the AADSTS code and first sentence with GUIDs redacted, on both the direct token fetch and the provider handed to the OpenAI SDK client. Network failures stay 500. * fix(azure): keep network failures to Entra a retryable 500 azure-identity wraps a transport failure in ClientAuthenticationError, so the 401 mapping now skips errors whose cause chain holds ServiceRequestError or ServiceResponseError * fix(azure): cover async token providers and Entra 5xx, and scope caller-sent Entra credentials * fix(azure): map only AADSTS-coded Entra rejections to 401 and keep caller credential failures out of cooldown An Entra ClientAuthenticationError now answers 401 only when its message carries an AADSTS code, its HTTP status is not 429 or 5xx, and the code is not the AADSTS50196 throttle, so a chained credential's outage or throttle stays a retryable error. Caller-sent Entra fields no longer change the deployment id; a 401 from a value the caller sent skips the shared deployment's cooldown instead. The Azure AI Foundry agent token fetch maps the same rejection, and the A2A endpoint answers it with HTTP 401. * fix(router): count router default_litellm_params as configured Entra credentials when deciding cooldown * fix(azure): keep transient Entra codes retryable and scope 401 handling to Entra rejections ClientSecretCredential drops Entra's HTTP status, so throttling and transient codes (AADSTS50033, 50196, 90006, 90024, 90033, 90055) now stay retryable instead of mapping to 401. The A2A endpoint answers 401 only for an AuthenticationError caused by an Entra token rejection, and the router skips cooldown for a caller-sent Entra field only on Azure-family deployments. The azure/ Decisions route and the Bing grounding search tool now map an environment-credential rejection to the same 401. * fix(azure): map only known Entra credential rejections to 401 and cover the OIDC token exchange Unlisted AADSTS codes keep the retryable 500, the router skips the 401 cooldown only when an Entra rejection caused it, and a federated token Entra rejects answers the same 401 on Azure chat, Responses and A2A agents * fix(azure): answer 401 for Entra rejections on the /azure passthrough and token counting The fallback hop skips cooldown when Entra rejected a credential the caller sent, Prometheus counts a deployment's own Entra rejection as a deployment failure again, and an OIDC exchange error keeps Entra's headers so Retry-After reaches the router. * fix(azure): keep a no-op caller Entra field from skipping cooldown and redact the passthrough 401 message A caller-sent Entra field now skips the deployment's cooldown only when it differs from the deployment, its named credential, the router defaults, the AZURE_* environment variables and the default scope. An empty value counts as unset, so a deployment whose own secret is wrong still cools down when the caller's field changes nothing about the token request. The /azure passthrough's Entra 401 message goes through the same internal hostname redaction as other client-facing errors. * fix(router): compare a caller's Entra field with the value the deployment uses A caller-sent Entra field skipped the cooldown only when it matched no configured source, so a value equal to an environment default the deployment overrides (a stale AZURE_CLIENT_SECRET, say) counted as the deployment's own and let a caller's rejected credential cool down a working deployment. The check now resolves the value the deployment would use without the caller, in order from the router defaults, the deployment, its named credential, the AZURE_* environment variables and the default scope, and skips the cooldown only when the caller's value differs from it. * fix(azure): follow the settings merge for empty Entra fields and keep non-rejection OIDC exchange errors unchanged * fix(azure): count only the failed attempt's Entra rejection and ignore a non-callable token provider * fix(azure): keep the streaming Entra rejection inside the failed attempt --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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zoveki
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baddc67041
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fix(anthropic)!: carry prompt_cache_breakpoint to cache_control on chat completions to Claude (#49783)
* fix(anthropic): carry prompt_cache_breakpoint to cache_control on chat completions to Claude
A content part carrying OpenAI's prompt_cache_breakpoint on a /v1/chat/completions request to Claude (Anthropic, Bedrock Invoke and Converse, Vertex AI, Azure AI) now reaches Claude as cache_control {"type": "ephemeral"} on the same block, so prompt caching works for OpenAI-shaped clients instead of the marker being stripped.
Only parts OpenAI accepts the marker on are translated, a client cache_control on the same block wins, and Converse translates only for models that take cache points. A 30m ttl or a malformed marker answers UnsupportedParamsError without drop_params and becomes a default 5m mark or no mark with it.
* fix(anthropic): hold translated prompt_cache_breakpoint marks to the 4-breakpoint cap
Marks past Claude's 4 cache breakpoints now answer 400 without drop_params and
keep the earliest under it, counting the client's own message, tool, and
top-level cache_control marks. The ttl and malformed-marker errors name
drop_params for proxy users too and no longer name a single provider.
* fix(bedrock): count Converse tool cache points in the breakpoint cap and gate unmapped models
A client tool cache_control or a tool_config injection point becomes a Converse tool
cachePoint, so it now takes one of the 4 slots before a translated marker does.
Converse only translates prompt_cache_breakpoint for a model the cost map says takes
prompt caching. An unmapped model such as an application inference profile ARN opts in
through model_info supports_prompt_cache_breakpoint, so a marker sent to every model of a
mixed fleet no longer turns a non-caching profile's 200 into Bedrock's 403.
Router prompt-caching affinity now treats a marked block like a cache_control one, and
requests without a marker skip the translation after one pass over their messages.
* fix(bedrock): count only the tool cache points Converse sends against the breakpoint cap
* fix(anthropic,bedrock): cap only the cache breakpoints each provider sends, and drop marks Nova cannot take on tool results
* perf(anthropic,bedrock): find the breakpoint cut-off by binary search so trimming many marks stays fast
* fix(anthropic): drop the duplicate drop_params left by the main merge
* fix(bedrock): let an inference profile's cache breakpoint flag win over its base_model
* fix(anthropic): keep the first and last prompt_cache_breakpoint marks past the cap
Under drop_params the translated marks that fit the cap are now split between
the start and the end of the request, so the stable prefix and the newest turns
both stay cached. The cap count also includes a native tool search tool that
keeps its cache_control on the wire.
Bedrock Converse now translates the marker only for the Claude and Nova
families, which Bedrock documents as taking cache checkpoints, unless the
deployment sets supports_prompt_cache_breakpoint. A guarded user turn keeps its
cache mark when the request fits the cap.
* refactor(bedrock): decide guarded cache marks with a typed bool helper
* fix(bedrock): validate guarded blocks before reading their cache mark
* fix(anthropic): let injection points replace client marks and keep non-Claude routes untranslated
When a deployment sets cache_control_injection_points, the client's
prompt_cache_breakpoint marks are dropped on targets that do not read them, so
the operator's injection points decide every Claude breakpoint.
OpenCode Go models served over the Anthropic messages endpoint translate the
marker only for Claude, and guarded Converse text keeps a cache mark only on a
model known to take cache points.
* fix(anthropic): keep client marks unless a message injection point replaces them on a translating route
A tool_config-only injection point no longer strips client prompt_cache_breakpoint marks, a flagged Bedrock profile no longer counts as reading the marker natively, and guarded Converse text skips the tool count when no message carries a cache mark.
* fix(anthropic): keep Bedrock and Claude deployments flagged for the marker on cache_control injection
A supports_prompt_cache_breakpoint flag on a Bedrock profile or a Claude deployment made the injection hook write OpenAI markers and prompt_cache_options, which Bedrock answers 400 for. Routes that translate the marker now never take the OpenAI dialect.
* fix(bedrock): reserve only the tool cache points Converse sends when trimming Claude cache marks under drop_params
* fix(anthropic): name the marker's accepted ttl values in the malformed prompt_cache_breakpoint 400
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
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tessellark
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ff91b89b8d
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fix(router): keep encrypted reasoning when a fallback hops between same-key deployments with no api_base (#49396)
* fix(router): keep encrypted reasoning on a hop between same-key deployments on the provider's default endpoint * test(router): type the default-endpoint boundary test helpers * fix(guardrails): restore the google_text_moderation embeddings fix an earlier main merge dropped * fix(router): match encryption boundaries on the key, account, and region the request really uses A deployment's named credential now fills only the values the deployment leaves out, through the same helper the request path uses, so the boundary names the key and base the request sends. A deployment with no api_key takes the provider's default key, the boundary carries the OpenAI organization and project a deployment sends, and a Bedrock Mantle region named in the model routes through the provider resolver before the Responses URL builder * fix(router): keep header-signed accounts apart on a shared boundary and skip boundary work no reasoning needs Headers the request logger masks as secrets (Authorization, api-key, x-api-key) now join the boundary's account scope, with extra_headers overriding headers the way the request merges them, so deployments that sign in through a header on one base never share encrypted reasoning. Target boundaries are built only when a reasoning item from another deployment needs the comparison, and the Responses input strip asks only about encrypted reasoning items, so a pinned turn or fallback hop with nothing to compare makes no secret-manager reads. * fix(router): resolve default boundaries only for openai and drop the unsent organization param Aggregators and Bedrock Mantle serve several vendors on one key, so a missing key or base there no longer yields a shared boundary. The Responses request never sends the organization param, so it no longer splits the boundary, while a Cookie header now does. * fix(router): match explicit pairs as on main and key default boundaries by model An explicit api_base plus api_key pair is the whole boundary again, so tag headers no longer split deployments that main kept together. The default OpenAI boundary now carries the model, since one OPENAI_BASE_URL can front several vendors, and a deployment that declares another provider gets no boundary before any secret lookup. * fix(router): match an explicit key and the environment key on one api_base A deployment with an explicit api_base and api_key now shares a boundary with one on the same api_base that takes the same key from OPENAI_API_KEY, when the model and account headers also match. Two explicit pairs still match on base and key alone, as on main. * fix(router): skip a deployment whose params cannot be read in boundary checks A named credential with a value of the wrong type, or an extra header whose name is not a string, made the boundary check raise and fail the whole request. That deployment now has no boundary, so the others still keep the reasoning they can decrypt. Two explicit api_base plus api_key pairs also compare without resolving the provider, so they read no secrets, as on main. * fix(router): ask a secret manager for default boundaries at most once a minute per deployment * fix(router): resolve a changed named credential at once in the cached boundary and take an injected clock --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Nate Armstrong
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22d0b1e443
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fix(router): restore four base behaviors the RoutingContext refactor changed (#49395) | ||
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Nate Armstrong
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c43a1addf2
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refactor(router): extract PythonCore behind RouterCore and pass the router its config (#49119)
* refactor(router): move litellm/router.py to litellm/router_python_core.py A pure rename with no content change, so git and review tools track the router body as a move. The next commit turns it into PythonCore and adds the Router facade back at litellm/router.py * refactor(router): extract PythonCore behind RouterCore and pass the router its config The routing logic moves unchanged from litellm/router.py into PythonCore in litellm/router_python_core.py. Router becomes a facade that builds a RouterConfig, picks a RouterCore with make_core and delegates every member to it. The core no longer reads or writes litellm.* directly: process settings come from RouterDynamicConfig, and inference calls, sleeps, callback lists and the global cache go through PythonHost. A CI check bans litellm.* in the router modules, and the proxy's construction sites build the config outside the router Settings are static: the constructor arguments and changeset values are copied when the router is built or the change applied, and a write to a setting attribute becomes apply(ChangeSet(assign=...)). A Router subclass's core class also subclasses the facade, so an override's super(Sub, self) works, and an instance-level patch of a core method is kept on the facade so nested patches unwind. tests/unit/test_router/core tests the core in isolation: ScriptedHost serves every host operation (scripted inference answers, recorded sleeps, settings, callbacks, cache), and make_core runs each test once per core in CORE_BUILDERS |
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Nate Armstrong
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87d91d78b7
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refactor(router): route the router family through RoutingContext and close the outside surface (#49118)
Strategies, pre-call checks, cooldown and fallback helpers, and the auto, complexity and quality sub-routers now take a RoutingContext instead of the Router, and read the router only through registry(), settings(), health() and the context's forwarding methods. Router-free helpers move from router_utils to litellm_core_utils, outside callers of router state switch to entry points, and the surface allowlist shrinks to the endpoint methods plus the entry points |
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quietjules
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d302096b5a
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feat(lite): offer each model group's reasoning efforts in pi, OpenCode and Codex (#48949)
* feat(lite): offer each model group's reasoning efforts in pi, OpenCode and Codex lite pi, lite opencode and lite codex now read supported_reasoning_efforts from /model_group/info and write them into each client's model config. pi gets reasoning and a thinkingLevelMap, OpenCode gets reasoning_options plus one variant per effort, and Codex fallback entries get supported_reasoning_levels with a default level. The proxy-served Codex catalog on /v1/models?client_version= offers the same levels Codex before 0.138.0 fails the whole catalog on an effort it cannot name, so those releases, and an unreadable version, get only the six efforts every release parses. A group with unknown efforts keeps today's output, and a group with none is written as non-reasoning The strength order and nearest_declared_reasoning_effort move to an SDK-free module so the lite CLI, which loads without initializing the SDK, can import the Codex catalog * fix(lite): describe team models by their public name and keep Codex's none default /model_group/info now looks up a team's own deployments when the caller's team serves the requested name, so a team model reports its reasoning levels. Codex fallback entries default to none when the group lists it, and the proxy builds the Codex catalog in a worker thread * fix(lite): round Codex's default level down and describe a team's shared-name model from its own deployments Move the reasoning strength helper to litellm_core_utils so lite and the Codex catalog import it without the SDK or the router, and let make lint-format-check-changed diff the working tree so a staged rename passes. * fix(lite): keep pi's system role on reasoning model groups pi switches its system prompt to the developer role for any model marked reasoning, so an operator's cache_control_injection_points entry for role system stopped matching on Claude groups. lite pi now sets compat.supportsDeveloperRole false on those entries, so pi sends system as it did before. * fix(codex): treat a client_version too long to parse as an old Codex and keep undescribed stock levels A client_version past Python's integer digit limit made the Codex catalog answer 500. It now gets the levels every Codex parses. A stock Codex level with no description validates again, as on base, and lite codex treats undecodable codex --version output as an unknown version * fix(lite): keep REASONING_EFFORT_STRENGTH_ORDER importable from router_utils and skip the Codex sync on undecodable debug models output --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Nate Armstrong
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a659e8be70
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refactor(router): add router entry points and keep the old members as a deprecated mixin (#48840)
Router gains eight entry points (registry, settings, health, select, apply/aapply, observe, register_plugin, retire) in litellm/router_api.py. The 123 public members outside code used become DeprecatedRouterMembers (litellm/router_deprecated.py): same signatures and results, a DeprecationWarning naming the replacement and a use counter for callers outside the router. Router internals move to _core_ names; subclass overrides of old members are still called by the router. |
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Mateo Wang
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6cdb9959df
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feat(router): opt in to non-chat deployment filtering (#46257)
* feat(proxy): reject chat routes on models declared non-chat via model_info.supported_endpoints A model whose every deployment sets a non-chat model_info.mode and a supported_endpoints list with no chat endpoint now answers /v1/chat/completions, /v1/messages and /v1/responses with a 400 before any provider call. Models without both fields keep today's behavior. * fix(proxy): let fallbacks answer and cover more chat routes in the non-chat model check The check now steps aside when a request, key, team or router fallback would answer, skips such models in the rate-limit fallback loop, ignores mode and supported_endpoints copied from the cost map by old Admin UI saves, treats a blank mode as unset, and also covers /v1/completions, the Responses WebSocket, Gemini generateContent and /v1beta/interactions * fix(proxy): only step aside for fallbacks that can answer chat, gate the Responses WebSocket after alias resolution, and compare declarations to the loaded catalog * fix(proxy): gate the Responses WebSocket with the router after aliases resolve, and ignore client-set internal fallback flags * fix(proxy): walk fallback groups breadth first and release reservations on a rejected WebSocket Each fallback group is looked up once however often the request repeats it, and a WebSocket closed by the endpoint gate runs the failure hook so rate-limit reservations are released * fix(proxy): walk fallback layers without recursion and gate the compact Responses route The fallback walk now folds one layer at a time, so the recursion check passes, and /v1/responses/compact on a model declared non-chat gets the same 400 as the other chat-shaped routes * fix(proxy): keep chat on rows whose cost map entry serves chat A row that carries the cost map key of an entry that serves chat counts as declaring nothing, so a catalog edit that adds a chat path never turns old Admin UI copies into 400s * fix(proxy): check chat sent to a deployment id or backend model name * fix(proxy): check a model the read-through loads from the database * fix(proxy): step aside for fallbacks the check cannot follow and wildcards that serve a backend name A fallback target with no deployments of its own, a client routing stamp, and a wildcard that does not match the requested backend name no longer turn a working request into a 400 * fix(proxy): ignore a client model_group that is not a string when building rate-limit headers A client metadata.model_group sent as an int or a list crashed the error handler with a 500 once the embedding-only check rejected the call before routing. The header helper now treats a non-string stamp as no model group. Drops the pattern clause in the backend-name lookup, since the group lookup already returns wildcard matches. Adds the third audit round's routing-stamp cells. * fix(proxy): keep a non-string client model_group out of spend rows * fix(proxy): validate standard fallbacks before the typed fallback-group lookup * feat(router): opt in to non-chat deployment filtering * fix(router): skip unresolved local rate-limit fallbacks * fix(router): ignore caller-provided endpoint selector values * fix(router): normalize declared chat endpoint prefixes * test(router): cover preflight error-value behavior * test(router): derive replay metadata defaults from model info * fix(router): preserve fallback aliases and check synchronous text calls * test(routing): rewrite the WebSocket model with a pre-call callback, since main no longer runs guardrails at socket admission * test(routing): keep the endpoint gate's owned proxies on the worker's database * fix(router): keep the endpoint gate on model_info patches that omit it and on same-group stream retries A partial PATCH of model_info reset a stored enforce_supported_endpoints true back to false, because the field defaulted to False and the update merges model_dump(exclude_none=True). The field now defaults to None so an omitted flag keeps the stored value The same-group retry of a stream dropped before content called the provider without the endpoint selection context, so it could land on an enforced embedding-only deployment of the same group. It now runs inside endpoint_selection like every other router attempt * fix(router): probe rate-limit fallbacks through get_routable_deployments so the router surface does not grow Main's router fence lets code outside the router use only listed Router members and router_utils modules. The proxy's fallback probe now calls the listed get_routable_deployments with the request's call type, and the gate's 400 moves to litellm.exceptions as EndpointNotSupportedByModelError. It stays separate from main's UnsupportedEndpointError, which the router retries on the group's other deployments, while the gate refuses the whole group * test(responses): cover the WebSocket error frame for a model that refuses the endpoint * fix(proxy): let the rate-limit fallback probe try a fallback this worker has not loaded yet The probe now skips a fallback only when the endpoint check removed every deployment it has, so a model added on another worker still reaches route_request and its database lookup * fix(proxy): keep key router settings off the Responses WebSocket, read unrooted or single-string endpoint lists, and add status to the refusal frame * fix(router): warn when enforce_supported_endpoints has no usable list and match chat endpoints regardless of case, trailing slash, or Gemini path * test(router): type the load-warning test's caplog and router * test(routing): match the endpoint gate's integration tests to base fallback behavior on unloaded fallbacks and the Responses WebSocket --------- Co-authored-by: Mateo <mateo@Mateos-MBP-2.localdomain> |
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Mateo Wang
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0cf2bb7296
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fix(openai): warn when the GPT-5 reasoning effort gate drops a level under drop_params (#47761)
* fix(openai): warn when the GPT-5 reasoning effort gate drops a level under drop_params A GPT-5 request whose reasoning_effort the model map does not enable for that model lost the effort with no log line under drop_params. An Azure deployment name missing from the cost map lost reasoning_effort none this way and ran at the model's default effort. The gate now logs a warning naming the model, the level, the map entry it checked, and the model_info.base_model and model_info.reasoning_effort_levels fixes. * fix(openai): warn when the Responses route or a deployment's declared levels drop a reasoning effort The /v1/responses gate dropped a row-disabled GPT-5 effort, and reasoning for an OpenAI model without supports_reasoning, with no log line, and the router logged a declared-level drop only at INFO. Both Responses drops now log a WARNING and the router logs its drop at WARNING. The warning now leads with model_info.reasoning_effort_levels, since base_model only helps a deployment named differently from its underlying model. * fix: warn only when a reasoning level is actually dropped, and on generic reasoning_effort drops * fix: warn when thinking or a Bedrock Converse reasoning level is dropped, and name the router drop a reasoning level * fix: skip the drop warning when a non-reasoning model is asked for no reasoning, and honor declared levels on Bedrock Responses * fix: stay silent when reasoning is turned off on /v1/responses and warn on the Bedrock Responses fallback drop * fix(reasoning): warn when any reasoning-off request is dropped and give each route only the advice it honors A request to turn reasoning off on a model name the catalog lacks now warns on every route, since it may be a reasoning model. Chat suggests model_info.reasoning_effort_levels and, for a name with no catalog entry, model_info.base_model. OpenAI Responses suggests declared levels only where the config honors them, and Bedrock suggests neither. The Bedrock and Mantle Responses forwarding of declared levels is reverted until it can be proven live. * fix(reasoning): suggest reasoning_effort_levels and base_model only where the route reads them The chat gate suggested model_info.reasoning_effort_levels on routes that never pass declared levels (github_copilot, chatgpt and other OpenAIConfig delegates) and model_info.base_model on OpenAI and Azure AI chat, whose gate looks up the deployment name rather than base_model. /v1/responses/compact suggested levels it never reads either. Declared levels are now None when a caller passes none, so the advice appears only when a caller fed them, and the base_model advice is limited to the Azure chat gate, the one that looks up base_model. The openai row of the chat warning test now expects no base_model advice, the Responses warning test goes through get_optional_params_responses_api the way /v1/responses and compact call it, and the Azure direct-config test passes declared levels the way get_optional_params does. Long test lines are wrapped. * fix: read only the built-in catalog when choosing the reasoning drop warning |
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Nate Armstrong
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7650f766b0
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refactor(router): fence the router surface and document the router-core boundary (#48839)
Add rustdoc overviews for a new litellm-router-core crate and for litellm-model-catalog, a module docstring on litellm/router.py, and a shrink-only allowlist of the Router members and router_utils modules used outside the router, checked in CI by router_surface_check.py. Move the router-free helpers out of litellm/router_utils: batch_utils to litellm_core_utils, and the auto-router naming contract, tuning baseline and baseline request next to the auto-router plugin. No behaviour change. |
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Kerry Lu
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96fe78f96e
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fix(router): reject string fallback targets at Router init (LIT-10238) (#48943)
* fix(router): reject string fallback targets at Router init (LIT-10238) * fix(router): keep direct target fallback entries when rejecting string targets * test(router): set string fallbacks after init in cooldown tolerance tests --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Kerry Lu
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84c4c5aa5c
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fix(router): cool down failing deployments when fallbacks use string targets (LIT-10238) (#48913)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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shrey
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a45c2023ce
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fix(audio): return 400 for unsupported transcription providers (#47971) | ||
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simonp9
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78d6c1aa82
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fix(router): pass lifecycle events through on background OpenAI responses streams that cannot fall back (#48817)
* fix(router): pass lifecycle events through on background OpenAI responses streams that cannot fall back The Router held response.created, response.queued and response.in_progress until the first output event on every /v1/responses stream, so a background run showed the client no response id while it was queued or reasoning. A native OpenAI stream whose upstream echoes background: true now releases those events as they arrive when no fallback, order level or weighted failover could replace it, and once the id is out a later pre-output error is raised instead of starting a second run behind it. * test(router): type background stream test params and wait on the upstream pause instead of a clock * fix(router): keep the content-policy note on a released background stream error * fix(responses): return the routed id from cancel and add the router note only before output acancel_responses and cancel_responses now re-encode the reply id with the deployment, like get. The released stream's content-policy note follows the held path, which adds it only before output text. Renames _anthropic_messages_order_levels to _stream_order_levels. --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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tin-berri
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8e2e99670d
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fix(router): continue Responses mid-stream fallbacks on models without assistant prefill (#47672)
* fix(router): avoid assistant prefill in Responses fallbacks * fix(router): keep prefill for Claude fallbacks that take it and skip constrained continuations A Responses fallback to a Claude model that takes assistant prefill now gets the partial response as prefill again, so it continues mid-word without the prompt-shape drift. Every other fallback keeps the request to continue. A stream cut after text no longer continues when the request constrains its output (a json_schema or json_object text format, or a forced tool_choice), since a continued JSON document or tool call would not parse. The client gets the primary's error, as on the chat path. The fallback's re-sent leading space at the seam is dropped, and the prefill shaping runs per deployment after the encrypted reasoning strip, so stripped reasoning is never replayed. * fix(router): guard SDK text_format, narrow forced tool_choice, read Claude base_model, and cap Responses continuation output Cut Responses streams that asked for structured output through the SDK's text_format now surface the primary's error instead of stitching two models' JSON. Only a required or named tool_choice counts as forced, so allowed_tools in auto mode and hosted tool choices still continue. A Claude deployment named only through base_model keeps its prefill continuation, and the continuation's max_output_tokens is lowered by what the cut stream already emitted. * fix(router): quote the partial's ending in the continue request and surface the primary's error after a cut tool call * fix(router): stop Responses fallbacks from continuing content-filter cuts and client-run tool calls A content filter that cuts a /v1/responses stream mid-answer now returns its error, as on chat, instead of letting a content_policy_fallbacks backup finish the filtered text. Shell, apply_patch, computer, local_shell, and MCP approval items count as a started tool call. Chat continuation goes back to treating any tool_choice object as constraining, as on main * fix(responses): count a stream of tool arguments as a started tool call * fix(router): let Responses fallbacks continue under allowed_tools auto and after server-run tool calls A Responses tool_choice of allowed_tools in auto mode no longer blocks the continuation, since the model may still answer in text. Hosted MCP calls and the bridge's server-run tool search no longer count as a started client tool call. --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Aidan Singh
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b97fcf1af0
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fix(router): let affinity pins yield to deployments that already failed this request (#32309)
* fix(router): apply weighted-failover exclusion before deployment-affinity callback * fix(router): let affinity pins yield to deployments that already failed this request Moving the weighted failover exclusion ahead of the affinity check also changed what tag, order, plugin and managed-file filters saw. Restore the original filter order and have the affinity check ignore session and API key pins that point at a deployment already excluded or retry-skipped in this request. previous_response_id pins still win. * fix(router): release affinity pins on deployments that failed this request Delete a session or API key pin whose deployment already failed the request, so the deployment that serves it claims the pin. Prompt caching pins skip failed deployments too, and the proxy strips the internal failed-id fields from client bodies. * fix(router): keep affinity pins in place and skip failed origins in encrypted content affinity A pin now only yields for the request whose pinned deployment failed. Deleting it moved pins after one 429 or a request-caused 400 and added a Redis call on the routing path. Encrypted content affinity also ignores deployments that failed this request, so a failed origin takes the strip-and-dispatch path. * fix(router): keep encrypted reasoning when a retry can only go back to its origin The encrypted content check now drops failed deployments the way the router does: a weighted failover exclusion always holds, and a retry skip that would leave nothing falls back to the whole group. The proxy also drops client-sent metadata._failover_excluded_ids, and the encrypted content tests use a real Router * fix(router): keep encrypted reasoning when previous_response_id binds the failed origin --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Max Azatian
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ff65785717
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fix(router)!: count an explicit allowed_fails of 3 and keep fallback deployments out of cooldown (#46183)
* fix(router): count an explicit allowed_fails equal to the default as set Router(allowed_fails=3) stored the same value as an unset Router, so _is_allowed_fails_set_on_router treated it as "not set" and kept the rate-based cooldown logic. Keep the passed value in explicit_allowed_fails, like _explicit_timeout, and count it as set. * chore(router): drop the comment on explicit_allowed_fails * fix(router): keep the fallback deployment out of cooldown when no deployment can be picked When every deployment of the requested model is in cooldown, the router raises "No deployments available" and schedules the failure callbacks on the request's logging object. By the time they run, the fallback has already written its own deployment into that object, so the 429 counted as a failure of the healthy fallback deployment and cooled it down too, leaving the model group with nothing to serve. Tag the selection error and skip cooldown accounting for it, the same way advisor orchestration failures are skipped. * test(router): annotate the new cooldown test variables with Final * test(router): pin that a saved allowed_fails of 3 stays unset and type the fallback helper * test(router): use a fixed start time in the fallback helper * test(router): cover a fallback group staying up after the primary's selection fails --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Kerry Lu
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8f31c7171d
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fix(router): keep a lone deployment warm under router allowed_fails unless the policy names the exception (#48644)
* fix(router): keep a lone deployment warm under router allowed_fails unless the policy names the exception Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(router): give cooldown fixtures a sibling deployment so allowed_fails=0 still forces a cooldown * fix(router): keep benching a lone deployment that has a fallback group or an empty deployment policy * fix(router): accept dictionary fallback targets in the lone deployment check Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mateo Wang
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14193435b8
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refactor(anthropic): rename llms/anthropic/pass_through to llms/anthropic/messages (#48510)
* refactor(anthropic): rename llms/anthropic/pass_through to llms/anthropic/messages Move the unified /v1/messages code out of a directory called pass_through, since it is not the passthrough feature. The inner messages sub-package becomes native, and the Vertex AI partner model experimental_pass_through package becomes messages. The old packages stay as import shims that warn once and alias every submodule in sys.modules, so old deep imports still resolve Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(anthropic): keep Final variables out of loops in the rename shim Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(anthropic): match the warning text in the rename shim test Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(anthropic): resolve old pass_through imports lazily through a meta path finder Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(anthropic): mark the alias loader spec restore for the type discipline gate Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(anthropic): format the renamed package shim Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(anthropic): keep the rebind-ok marker on the spec restore line Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(anthropic): carry the new package search path on alias specs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(anthropic): declare the shim test locals Final 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> |
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Mateo Wang
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7e14638001
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refactor(llms): rename model-version transformation files to family names (#48509)
gpt_5_transformation.py becomes gpt_reasoning_transformation.py (OpenAI and Azure), the Bedrock anthropic_claude3_transformation.py files become anthropic_claude_transformation.py, anthropic_claude2_transformation.py becomes anthropic_legacy_text_completions_transformation.py, and vertex_ai_partner_models/llama3 becomes vertex_ai_partner_models/llama. Class and symbol names are unchanged. Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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moe-berri
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55479821e2
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feat(router): add opt-in session repinning after successful failover (#48206)
* feat(router): add opt-in session repinning after successful failover * fix(router): respect shared session pins and split metadata * fix(router): preserve session routing during Redis failures * test(router): inject the delayed Redis reader |
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Mateo Wang
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820725661e
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fix(router): log each dropped /v1/messages attempt through its own logging copy and open the retry without its usage (#45194)
* fix(proxy): keep a retried /v1/messages stream's spend log by logging the superseded attempt as a failure A /v1/messages stream the router retries before any content shares one logging object across both attempts. The superseded attempt's end-of-stream logging ran as a success (a usage-only or placeholder result) and claimed the request's one-shot success log, so the recovered stream's spend row was either missing or written under the superseded attempt's message id. The passthrough logging path now logs an Anthropic stream whose frames carry an `event: error` as a failure with whatever usage the provider reported, the way a dropped stream already does, and the router closes the superseded stream before it opens the retry so that logging is queued first. * fix(proxy): log a provider error frame through an attempt-scoped logging copy The error-frame failure stashed the superseded attempt's usage on the logging object the retry shares, so the retry's success log carried the failed attempt's token counts. The failure now logs through a copy of the logging object with its own model_call_details, and the helper moves into the Anthropic passthrough logging handler so the proxy streaming handler only routes by endpoint type. * fix(proxy): scope the error-frame failure log to streams closed at the frame A stream that ran to its end at the provider's error frame kept logging through the success route before this PR, and the attempt-scoped failure log is now taken only for a stream the router closed at that frame, with the copy made at the close so the retry's deployment never reaches it * fix(router): log each dropped /v1/messages attempt through its own logging copy and open the retry without its usage A /v1/messages stream dropped after message_start and retried in its model group shares one Logging object across attempts, so the retry's success log inherited the dropped attempt's stashed usage and exception, and a second drop never reached the failure handlers because the first had already marked the object as logged. The dropped attempt now dispatches its failure handlers through an attempt-scoped copy, and the router discards the stashed usage right before it opens the next attempt, on same-group retries and on every fallback hop, so a request that runs out of attempts still bills the last attempt's partial usage. * fix(router): dispatch chat stream failures through the attempt-scoped logging copy The router now clears a dropped attempt's stashed usage before every fallback hop, so the chat stream wrapper's queued failure log must read that usage from its own copy of the logging object, like the /v1/messages path already does. The stash test asserts through a real success log, the cooldown test reads a real Router's cooldown list, and the integration helpers carry full types. * test(vertex): give the stream wrapper's logging stub an attempt_scoped_copy * test: route the pass-through logging mock's attempt copy to itself and read the callback sink through a reader The pass-through failure test stubbed dispatch_failure_handlers on a spec'd MagicMock, which the attempt-scoped copy no longer reached, so the logging worker never finished. The integration tests kept earlier sink batches in a caller-owned list the helper mutated; a small reader keeps them instead. * test(router): use real Logging in fallback cooldown test Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(router): preserve superseded retry usage for billing Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): bill retry input after prior stream usage Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): track retry dispatch for terminal billing Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(router): use deterministic retry timestamp Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(router): avoid real clock in fallback tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tests): remove duplicate streaming logger import Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): retain error-frame usage for exhausted retries * test(proxy): fix retry billing expectations and helper annotations * fix(proxy): preserve failure estimate without carried usage Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(proxy): audit retry helpers and fixtures Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): fix retry fixture timestamps Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): observe retry stash at attempt boundary Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): keep terminal failure attribution when dropped attempts log on copies Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): publish a dropped attempt's payload only while it is still the current attempt Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): cover spend-log encoding error propagation Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(anthropic): skip adapter failure dispatch when the wrapped stream already logged it Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(router): cool down the final fallback attempt when its failure callbacks were blocked Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(anthropic): import Final in adapter regression Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): drop spend-log encoding expectation superseded by main's poison isolation Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(anthropic): finish the wrapped stream's failure log before surfacing the error Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(anthropic): wait for the wrapped stream's failure log to finish like the inline dispatch did Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(anthropic): wait for the executor-run sync failure callback separately from the async caller boundary Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): pin pass-through stream fixture start times Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): publish failed attempt payload before awaiting failure callbacks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): publish failed attempt payload from the failure handler after baseline invalidation Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(logging): drop unused discard_partial_usage_for_failure 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> |
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Kerry Lu
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0c6731eb5c
|
fix(router): price cost-based routing through model_info.base_model (#47617)
* fix(router): price cost-based routing through model_info.base_model * fix(router): keep cost-based routing pricing helpers fully typed * fix(router): drop typing.cast from cost-based routing pricing helpers * fix(router): read the cost map through a typed accessor in cost-based routing * fix(router): avoid a Final rebind inside the cost-based routing loop * refactor(router): share deployment_pricing_models across spend, listing and cost-based routing * refactor(router): keep the /v1/models listing key inline, share pricing models for spend and routing * refactor(router): inline the deployment pricing-model wrapper in cost-based routing * refactor(router): read deployment pricing models through one shared helper deployment_pricing_models(deployment) now owns the model_info.base_model / litellm_params.base_model / litellm_params.model unpacking, used by cost-based routing and the /v1/models listing. pricing_models(base_model, model) stays for the failure-row spend estimate, which already holds the two names * refactor(router): share the str-keyed mapping validator with cost-based routing * ci: re-run after flaky test_aiohttp_transport read timeout in llms-providers --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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joshua-berri
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6564a490f4
|
fix(batches): retry confirmed pre-accounting failures (#47625)
* fix(batches): retry confirmed pre-accounting failures * fix(batches): avoid promising retries for unknown accounting outcomes * test(batches): exercise real spend writer during retry recovery * fix(budgets): charge retried batches once per router budget * test(budgets): cover shared batch charge helpers --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> |
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Kerry Lu
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c38b86cc93
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fix(router): skip non-dict tool entries in the prompt caching affinity key instead of raising (#47565)
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Vincent Gimenes
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808333682e
|
feat(embeddings): enforce per-request input batch limit (#44574)
* feat(embeddings): add max_batch_inputs pre-call validation Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> * add unit tests for max embedding batch size Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> * feat(embeddings): enforce batch limit on extra_body input override Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> * chore(dashboard): update schema.d.ts for embedding batch size model field Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> * fix(embeddings): close Bedrock batch bypass and satisfy ruff PT012 Count max(top-level input, extra_body.input) for batch limits so providers that ignore extra_body cannot bypass max_embedding_batch_size. Add router tests and refactor pytest.raises blocks for ruff-tests. Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> * fix(embeddings): drop unchecked casts in router batch-size check Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> * fix(embeddings): route oversized batches to a group deployment that admits them * fix(embeddings): count extra_body input for any top-level input and prefer admitting deployments before cooldown * fix(embeddings): log cap rejections to failure callbacks and scope batch routing to embedding calls * fix(embeddings): apply the batch cap after tag and pre-call filters and fall back on cap rejections * fix(router): keep embedding cap rejections out of deployment health and hold only for routable cooling deployments * fix(router): clear the embedding cap rejection mark before a fallback's provider call A fallback or retry shares the request's logging object, so the mark a rejected attempt set made telemetry skip the fallback deployment's real call. Unit tests now pass a fixed logging start time instead of reading the clock. * fix(router): log embedding batch rejections once, before a fallback runs * refactor(router): drop docstrings that restate the code --------- Signed-off-by: Vincent Gimenes <vincent.gimenes@gmail.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Mateo Wang
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d698106ed7
|
fix(router)!: schedule default_priority requests once and reject a malformed priority (#47498)
* fix(router): schedule default_priority requests once and reject a non-integer priority A router configured with default_priority failed every request that carried no priority with a 500 naming a missing 'priority' argument, and an explicit priority re-entered acompletion and hit the same error. acompletion now resolves the priority once (the request's integer, else the default, with 0 kept as a real priority) and schedules through _schedule_factory directly, while schedule_acompletion delegates to acompletion so the two paths share one queue pass. A non-integer priority answers 400 naming the param, or is dropped under drop_params, instead of leaking to the provider or crashing the scheduler. * fix(router): honor router-level drop_params and schedule prompt-management models under a priority * fix(router): drop a non-integer priority when the model's deployments set drop_params * fix(router): resolve the drop_params deployment scope for team routes and deployment ids * fix(router): read the request and router drop_params flags without a loop-assigned Final * refactor(router): type the prompt-management wrapper's return and mock the provider in its test * perf(router): consult drop_params for the priority only when it is not an integer * test(integration): assert the new priority contract for non-integer and zero priorities * docs(router): describe default_priority as the priority every request without one takes * fix(router): parse default_priority once and apply it to text completions and the queue route A digit string default is taken and any other non-integer default is ignored with a warning instead of failing every request. atext_completion and /queue/chat/completions resolve the priority the way acompletion does: a request without one takes the default, an integer queues once, and a non-integer answers 400 or takes the default under drop_params. Integration cells cover every default-priority surface on an owned two-instance rig. * fix(router): type the priority dispatch so the lint budgets hold * fix(router): read priority like the scheduler did, require a priority on the queue route, and keep litellm's drop_params order * fix(router): drop a priority named in additional_drop_params and report the queued priority on streamed queue responses * fix(router): serve deployment-id requests without waiting behind the queue and ignore a boolean default_priority A request whose model is a deployment id now counts that deployment as healthy in the scheduler, since routing by id already ignores cooldown. Before, the scheduler found no healthy deployment for an id, so the request waited behind every entry ahead of it. A boolean default_priority (true, or YAML off) is ignored at startup with a warning, like any other value that is not a whole number. The scheduler integration tests now share worker state for the defaulted pair, cool a group through /v1/responses so no stale in-memory queue is left behind, and use "high" instead of "1" for the non-integer cases. The concurrent burst test no longer asserts that the queue drains, matching the explicit-priority burst test, since the scheduler's read-modify-write queue can race across workers. * test(router): keep the queue drain check as a BUG-skipped integration test * fix(router): queue default_priority chat requests once instead of failing them * test(router): open with the default_priority regression tests alone * fix(router): honor deployment drop_params for a malformed priority on a request routed by provider model name |
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Mateo Wang
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96f1bc02d8
|
feat(router)!: apply each deployment's reasoning_effort_levels on every provider and route (#46601)
* feat(router): apply each deployment's reasoning_effort_levels on every provider and route A deployment's declared reasoning_effort_levels now decide the effort sent upstream on /v1/chat/completions, /v1/messages and /v1/responses for every provider. Requests round up by default, litellm.reasoning_effort_rounding and model_info.reasoning_effort_rounding switch to down, a declaration lets providers like azure_ai accept reasoning_effort, and each remap logs one INFO line with structured fields. * fix(router): round reasoning effort only on a deployment's own declared levels Cost map levels no longer round requests or force-allow reasoning_effort, so undeclared sibling deployments and catalog-only models behave as on main. A declaring deployment lets azure_ai accept any level the resolver sends, and a hosted_vllm chat thinking budget is rounded too. * fix(router): drop undeclared reasoning effort under drop_params and round native /v1/messages effort Under drop_params a level outside the deployment's reasoning_effort_levels is dropped instead of sent. Providers that take /v1/messages natively now round output_config.effort onto the deployment's declaration. The rounding setting ignores case and surrounding spaces. * fix(router): strip line breaks from every field in the reasoning effort remap log * fix(router): round thinking-budget efforts onto a declaring deployment on every provider * fix(router): keep the caller's thinking display when rounding a thinking budget on adaptive Claude Warn on a reasoning_effort_rounding value other than up or down instead of silently rounding up * test(integration): cover deployment reasoning_effort_levels rounding on chat, messages and responses Wire cells assert the exact body each provider receives when a deployment declares reasoning_effort_levels, plus undeclared controls, malformed input, drop_params, rounding settings, fallbacks, model groups, live updates and the response cache. Chaos cells cover a killed worker, a proxy restart, an upstream outage, a slow stream and the INFO remap log. * test(integration): cut held streams when the upstream stops in the reasoning effort chaos cell The upstream-stop cell waited for the held streams before stopping the upstream, so they only ended on a client or proxy timeout and the result depended on which fired first. The upstream now stops while the streams are held, and each cut stream must carry an error and no answer * fix(router): round thinking budgets only on declaring deployments and round Converse output_config An undeclared hosted_vllm deployment serving a Claude model name now maps a thinking budget the same as any other undeclared hosted_vllm deployment. A model_info that echoes a cost map key no longer borrows that entry's levels. A non-numeric thinking.budget_tokens answers 400, or is dropped under drop_params, where main answered 500. A declaring Bedrock Converse Claude deployment now rounds output_config.effort, which /v1/messages sends for Claude Code * test(integration): cover output_config rounding and non-numeric thinking budgets in the reasoning effort cells * test(integration): keep an explicit reasoning_effort winning over a malformed thinking budget on hosted_vllm * test(integration): cover output_config rounding on openai, azure and azure_ai chat * fix(hosted_vllm): let an explicit effort win over a malformed budget and reject one on /v1/messages An explicit reasoning_effort beside a non-numeric thinking.budget_tokens keeps main's behavior again. A declared hosted_vllm deployment with a Claude model name maps a budget through the generic table instead of the adaptive Claude one. /v1/messages to a non-Claude target hands a malformed budget to completion(), which answers 400 or drops it under drop_params, where it answered 500 * fix(router): drop thinking beside an explicit effort when a declaring deployment's provider cannot read it * test(integration): cover malformed thinking budgets on /v1/messages to non-Claude targets * fix(anthropic): answer 400 for a malformed thinking budget on /v1/messages to any non-Claude model, or drop it under drop_params * test(integration): cover an explicit effort beside thinking on azure_ai and drop_params on the /v1/messages bridges * fix(anthropic): answer 400 for a malformed thinking budget through adapter_completion without drop_params * fix(anthropic): type the adapter_completion request so the drop_params read adds no unknown argument * fix(router): a default effort beside a thinking budget sends no effort on chat Chat now leaves the budget-derived effort out when the caller's effort resolves to none or asks output_config for one, matching /v1/messages. The chat thinking decision moves into resolve_chat_reasoning so completion() stays under basedpyright's complexity limit. * test: type respx_mock and mark the adapter result Final in the reasoning effort tests * fix(router): keep the caller's thinking beside a kept effort and the budget effort beside a dropped one A non-default output_config.effort beside a thinking budget now leaves the thinking as sent, so Bedrock Invoke keeps display updates. A level drop_params drops counts as never sent, so the budget still sets the effort. output_config.effort replaces a thinking budget the provider cannot read, and a non-numeric string budget on adaptive Claude answers 400 in place of 500, or drops under drop_params. * fix(router): send a kept output_config effort as reasoning_effort where the provider cannot read thinking On a declaring hosted_vllm or azure_ai deployment, a thinking budget goes out as reasoning_effort. An output_config.effort beside it now takes that slot, rounded onto the declared levels, instead of leaving only output_config, which those backends ignore. * fix(reasoning-effort): honor global drop_params for a non-numeric budget and keep the budget effort beside a dropped /v1/messages level * fix(reasoning-effort): send a level a gpt-5 deployment declares even where the cost map does not list it * fix(reasoning): apply declared levels on azure_ai gpt-5 and reject a bool thinking budget on adaptive Claude * fix(router): drop a thinking budget's effort that a deployment declaring no ranked levels excludes A deployment declaring [] or ["none"] skipped the budget check, so adaptive Claude still sent the budget-derived output_config.effort under drop_params on chat, Bedrock Converse, and native /v1/messages. The adaptive thinking now goes out without that effort * fix(anthropic): reject a false, null or empty thinking budget on adaptive Claude |
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Yassin Kortam
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d56ff281de
|
fix(router): key prompt caching affinity on tools and the /v1/messages system prompt (#46411)
* fix(router): key prompt caching affinity on tools and the /v1/messages system prompt Co-authored-by: nuernber <benjamin.nuernberger@jpl.nasa.gov> Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(router): read a 1h tool cache_control nested under function for the pin ttl --------- Co-authored-by: nuernber <benjamin.nuernberger@jpl.nasa.gov> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mrunmayee Daware
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2196943195
|
fix(proxy): match partial wildcards against prefix-stripped model ids (#46390)
* fix(proxy): match partial wildcards against prefix-stripped model ids (issue #46384) Refactor model checks to improve filtering logic and type hints. * test(proxy): partial wildcard listing regression coverage (issue #46384) * fix(proxy): drop unneeded annotation on suffix list (LIT001) * fix(proxy): annotate suffix list with reasoned mutable-ok (basedpyright) Change suffix_appended_wildcard_models to a typed list. * Add lock timeout before creating telemetry report table Set local lock timeout to 10 seconds before creating the telemetry report table. * fix(proxy): list alias wildcards as routable ids, not raw catalog ids An alias whose suffix collides with a catalog sub-prefix (e.g. public "cloudflare/@cf/*" over deployment "cloudflare/*") took the partial-filter branch and listed raw catalog ids. Routing substitutes the captured suffix into the deployment pattern, so those listed ids routed to targets that do not exist. Only use filter semantics when the deployment repeats the wildcard suffix (or no deployment is available); aliases prepend their prefix to provider-stripped catalog ids so every listed id routes back to a real catalog model. Addresses Greptile review on #46390. * fix(proxy): derive partial wildcard listings from the deployment's routing pattern List an id for a partial wildcard only when routing it through the deployment's pattern lands on a catalog model, so aliases, catch-alls, and key filters over a wildcard deployment list ids that answer when called. /model/info expands a bare * row the same way /v1/models does. * fix(proxy): drop fragment ids for a catch-all over a partial wildcard and route bare aliases through the deployment pattern A * catch-all over a partial deployment now lists no catalog ids, a bare alias like my-cf/* over cloudflare/@cf/* names ids by the deployment pattern, an alias whose wildcard count differs from its deployment lists nothing, and /model/info rows show the model each listed id routes to * fix(proxy): keep listed ids on /model/info alias rows and clean up test-registered models * fix(proxy): list catalog models through routing-prefix wildcard deployments * fix(proxy): keep namespace and bare catch-all wildcards on routable listings A leading deployment segment the model name repeats, or the provider name itself, is no longer read as a routing segment, so same-name namespace wildcards and a key filter over `*` -> `openai/*` stop listing ids that route to no model. A bare `*` deployment under a prefixed name keeps the legacy listing. `*` over a partial deployment now lists the names that route through it, dropping empty ids. * fix(proxy): list nothing for a catch-all over a mid-word wildcard deployment * fix(proxy): list only wildcard ids that route back to their deployment and catalog model A listed id now has to round-trip through the alias pattern to the catalog model it names, and the router's wildcard match for it has to pick this deployment, so an id a more specific sibling wildcard serves is no longer listed under the catch-all on /v1/models or /model/info * fix(proxy): list wildcard aliases that route at a word boundary and ids a sibling serves with the same model --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Mateo Wang
|
6c4c134f23
|
fix(secret_managers)!: resolve oidc/file and oidc/env refs in admin-configured api_key per request (#47341)
* fix(secret_managers): resolve oidc/file and oidc/env refs in admin-configured api_key per request An api_key set to oidc/file/<path> or oidc/env/<VAR> in a credential_list entry or a deployment's litellm_params was sent upstream as literal text, so every call answered 401. The SDK client wrapper now reads the referenced file or env var on each call and never writes the token back, so a rotated token is used on the next call. The existing server-owned federation gates treat an oidc/ api_key as server-owned by value, so a request body, a non-admin credential or model write, user_config, fallback targets and routing tier params can never carry or name one. Other oidc/ kinds answer 400 * fix(secret_managers): strip only the leading oidc/ from a secret reference A token file under a directory named oidc resolved to the wrong path, because every oidc/ in the reference was removed * fix(auth): refuse oidc/ api_key refs in advisor tools and scope the route gates to them The advisor tool's own api_key now answers a 400 when it holds an oidc/ reference, since its sub-call runs through the client wrapper that resolves one. Stored fallback targets, auto-router tiers and user_config refuse only an oidc/ api_key, inline or through the credential they name, so their workload identity federation handling stays as it was. Provider model discovery for a wildcard deployment resolves the reference before calling the provider. * fix(auth): allow admin oidc api_key on deployment writes, resolve refs on discovery, batch probe and realtime health, refuse client api_base on oidc deployments * fix(utils): resolve oidc api_key refs only from admin-configured sources Mark an oidc/ api_key read from a proxy-level deployment or a stored credential, and resolve only that marked value. Team deployments, prompt templates, nested configs and a direct SDK api_key send the text as written. An unsupported reference kind raises a 401 so the router fails over to the group's next deployment. * fix(utils): send a credential's oidc token only to its own api_base host A stored credential's oidc/ api_key now resolves only for the scheme, host and port of the credential's own api_base or base_url, so a team model or vector store that names the credential with another api_base gets a 401 and that host gets nothing. Saving a team model with an inline oidc/ api_key answers 400, since team rows never resolve one. * fix(proxy): send an admin oidc api_key only to the hosts configured beside it Every admin oidc/ reference now carries the origins of the host params set beside it, checked for api_base, base_url and the Bedrock, S3, SageMaker and deployment_url params. Token counting reads the reference only when it calls the provider, answering 401 when it cannot, and pass-through 401s redact internal paths. * fix(proxy): redact the token path from token count auth errors * test(security): cover token count, Bedrock endpoint, api_base update and pass-through path redaction for oidc api_key refs * fix(proxy): redact the token path from secret reference errors where they are raised * fix(proxy): keep the secret reference's path out of the error a caller sees The 401 for an unreadable oidc api_key or pass-through credential now names only the reference kind and a fixed reason, so a token path under /run/secrets or a custom credential dir never reaches the caller, while the server log keeps the full reference for the operator * fix(secret_managers): strip line breaks from the logged secret reference A reference holding a newline can no longer forge a server log line * fix(secret_managers): label an unknown oidc reference kind instead of echoing it An api_key such as oidc/env_MY_VAR (a typo for oidc/env/MY_VAR) came back in full in the caller's 401 and in the spend log, since the kind was whatever text followed oidc/. A kind get_secret does not know now reads oidc/<unknown kind>. The relative-path hint uses oidc/file//<absolute path>, which the client-message redaction on chat routes leaves whole. * test(health): run the real model auth check in the oidc test connection test * test(secret_managers): read an oidc/file token stored under a directory named oidc * fix(secret_managers): count a URL in the model name as an upstream host for oidc api_key references A huggingface/* wildcard call could name its own endpoint URL as the model and receive the resolved token. The origin check now treats a URL in the model as a host the reference must allow. The integration contract also reads the proxy's own database instead of the pytest worker's. * fix(secret_managers): treat a default port as explicit when matching an oidc api_key origin A credential on https://api.mistral.ai refused a call to https://api.mistral.ai:443, though both reach the same server. The origin check now compares scheme, host and effective port, as assert_same_origin does, and an unparseable api_base is refused instead of raising. The advisor test sets the real proxy flag instead of replacing our own helpers. * test: type the oidc request-body helpers and drive the tier test through mock_response * fix(secret_managers): refuse an oidc api_key reference whose call drops the configured host |
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yucheng-berri
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3e18a4b55d
|
fix(router): record cooled deployments on the all-cooled failure row (#47120)
* fix(router): record cooled deployments on the all-cooled failure row A RouterRateLimitError now carries the cooled deployments of the route the request resolves to for the caller's team (model group, alias, wildcard or team route), each with its masked api_base. get_error_information copies them into error_information.error_cooldown_deployments so the SpendLogs failure row and every logging callback can tell which deployments were cooling * fix(router): name cooled deployments from the router's own resolved route Use the deployments the router resolved for the request, before health and cooldown filtering, instead of re-deriving the route. Alias chains, the provider-model fallback, wildcards and team filtering now match routing by construction. A routing-strategy refusal records null. * fix(router): name only the cooled deployments tag and region routing allow The refusal's cooled-deployment list now leaves out deployments the request's tags or the end user's allowed region keep it from, so a tenant's refusal row no longer shows another tenant's api_base * fix(router): keep failure logging working for refusal subclasses that skip init A RouterRateLimitError subclass that never calls its parent init now logs a null cooled-deployment list instead of breaking the failure payload * test(router): call the refusal routing helpers directly The router coverage check needs each router function called by name from a unit test --------- Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com> |
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Paul El Khoury
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d7620c77a1
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fix(openai): drop unsupported reasoning effort for gpt-6.1-sol (#43935)
* fix(openai): drop unsupported reasoning effort for gpt-6.1-sol gpt-6.1-sol accepts low, medium, high, xhigh, and max. none and minimal were still forwarded, because chat completions ignored an explicit supports_none_reasoning_effort=false and the Responses mapper never applied that contract. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(openai): mark the stripped reasoning object as outgoing JSON Co-authored-by: Cursor <cursoragent@cursor.com> * Fix Azure responses reading the OpenAI effort map gpt-6-astra on Azure accepts reasoning.effort none. The responses gate was checking the OpenAI entry, which rejects it. Signed-off-by: Paul El Khoury <82139421+pOpO1-9@users.noreply.github.com> Co-authored-by: Cursor <cursoragent@cursor.com> * fix(openai): gate every reasoning_effort level from the cost map on chat and Responses One gate reads the model's cost-map row for whatever effort level a request asks for, on Chat Completions and the Responses API, for OpenAI and Azure. xhigh stays opt-in on chat (Azure also keeps none opt-in); every other level is refused only when its supports_<level>_reasoning_effort flag is false. A refused level is dropped under drop_params or answered with a local 400, and Responses keeps the rest of the reasoning object when it drops effort. The guards that follow judge temperature by the level the provider will see. Tests move into the mapped test files and derive the expected outcome for each level from the map row, so a new GPT-6 model needs only its row. * test(openai): pin gpt-6.1-sol's refused effort levels and prove the row flags alone drive the gate * fix(cost-map): azure gpt-6-astra refuses none and honors max on Responses, as live calls show * test(reasoning_effort): pin the astra max and none flips through the adapter and Foundry paths * fix(reasoning_effort): keep max out of the route gates and correct the gpt-5.3-codex rows The same model honors max on Responses and refuses it on Chat Completions, so one row flag cannot gate it on either route. The gates now skip max, the Azure gpt-6-astra rows keep max off so the /v1/messages adapter degrades to xhigh and /model_group/info stops short of it as on main, and chat still forwards max for the Responses bridge. The gpt-5.3-codex rows said none and xhigh off and minimal on; the live model answers the other way round (2026-10-01), and an opt-out gate would have dropped the levels Codex CLI sends. * fix(reasoning_effort): bridge function tools to Responses when the chat gate drops none * docs(reasoning_effort): correct the max advertisement note * fix(azure_ai): read the Foundry row on the Responses effort gate and turn none off for Azure gpt-6.1-sol * fix(azure): gate a prefixed Foundry deployment's Responses effort off its row litellm.responses(model="azure_ai/<deployment>", api_base=<Foundry host>) is re-routed to the azure provider with the azure_ai/ prefix intact, so the Azure Responses config saw a prefixed name, skipped it as another provider's pass-through, and forwarded none and minimal to Azure even under drop_params. The Azure gpt-5 resolver also read no row at all for a prefixed name. The Azure Responses gate now detects the family the way the Azure chat gate does, and an azure_ai/ name on the Azure OpenAI configs reads its azure_ai/ row when the map has one, else the azure/ twin, the rule the Foundry chat config already applies to the same deployment. * fix(cost-map): turn none off on azure/eu/gpt-6-astra like its sibling rows * docs(reasoning_effort): say how each gate reads none and shorten the module docstring * fix(azure_ai): call the public effort-level check from the Foundry Responses gate * test(reasoning_effort): fold the Foundry Responses tests into the mapped file and type the row helpers --------- Signed-off-by: Paul El Khoury <82139421+pOpO1-9@users.noreply.github.com> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> |
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devin-ai-integration[bot]
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f8f6a01cae
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feat(ui): show kubernetes pods on the model page (#44666)
Show discovered Kubernetes pods on the model page for admins Resolves LIT-9168 Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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f85926a652
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feat(router): keep a session on one kubernetes pod (#44393)
Requests with an explicit session id stick to one discovered pod via rendezvous hashing Requests without a session id keep round robin Pod routing records are included in logs, spend logs, and traces Resolves LIT-9168 Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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6fc60bc00d
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feat(router): discover kubernetes pods behind a headless service api_base (#44342)
Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mateo Wang
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7e6fb09da3
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fix(streaming)!: map stream read timeouts to litellm.Timeout on chat, messages, and responses (#47198)
* fix(streaming): map stream read timeouts to litellm.Timeout * revert(streaming): move the timeout mapping to a later commit * fix(streaming): map stream read timeouts to litellm.Timeout on chat, messages, and responses * fix(streaming): keep stream fallback and cooldown unchanged for transport timeouts A chat stream served through the Responses bridge now keeps mid-stream fallback on a stall, because the fallback exemption also covers a litellm.Timeout whose cause is an httpx transport timeout. The Responses stream hands the raw transport error to failure callbacks again, so router cooldown sees a stall as it did before. The 408 deployment info now lists stream_timeout. * test(integration): cover a stalled hosted_vllm stream on chat, Responses, and Messages with its spend log row * fix(router): keep a fallback deployment whose stream stalled out of cooldown * test(integration): cover bridged chat, fallback and cooldown for stalled hosted_vllm streams |
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yuneng-jiang
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1e3641a52a
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fix(router): read an application profile's base model from metadata on a cache hit (#47144)
* fix(router): read an application profile's base model from metadata on a cache hit The 1h prompt-cache pin check read base_model only from the top level of litellm_params. On a response-cache hit the params it sees carry the base model only under metadata.model_info, so an application-profile ARN resolved to itself and the pin was written for 5 minutes while the wire carried a 1h TTL. Read it through get_base_model_from_metadata, which also checks metadata.model_info * test(router): pin top-level base_model precedence over metadata model_info |
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devin-ai-integration[bot]
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46ae68021e
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fix(anthropic): carry safeguard_results and stop_details in synthesized message_delta events (#46096)
* fix(anthropic): carry safeguard_results and stop_details in synthesized message_delta events When the proxy renders a complete Anthropic Messages response as an SSE stream for a client that asked to stream, the message_delta event carried only stop_reason and stop_sequence. A real Anthropic stream puts safeguard_results and stop_details inside message_delta.delta, so a client such as Claude Code auto mode lost the server-side classifier verdict and a refusal lost its stop_details. Both stream builders now copy those keys from the source response through one shared helper when they are present. * fix(guardrails): keep safeguard_results and stop_details when re-emitting a rewritten Anthropic stream A post-call guardrail that rewrites an Anthropic stream (presidio, bedrock, tool permission, model armor) now carries the upstream message_delta safeguard_results and stop_details into the re-emitted stream. The router fallback message_start no longer leaks those final fields early * fix(guardrails): keep stop_details and safeguard_results in rewritten Anthropic streams without explanations A guardrail that rewrites a /v1/messages stream now carries stop_details (type and category) and the dangerous_tool_use verdicts for the tool calls it still delivers, with every explanation dropped so a masked stream never echoes the unmasked text through those fields. * fix(guardrails): copy only upstream stop_details and forward-compatible safeguard_results into rewritten Anthropic streams A rewritten stream now takes stop_details and safeguard_results from the upstream message_delta alone, so a refusal the upstream sent without stop_details is never given one by the OpenAI round trip. Unknown safeguard types, statuses, reasons and extra fields pass through, a verdict follows a tool call only when its input is unchanged, and tool_permission keeps the explanations since it rewrites no text. * fix(guardrails): apply the safeguard_results and stop_details rules to policy pipeline stream rewrites * fix(router): deliver a refused stream built from a finished agentic turn instead of falling back Websearch, MCP and advisor streams replay a complete reply whose tools already ran, so a refusal fallback would run every tool again. Also give the recovered response's message_start a null stop_details as the API sends it, drop safeguard_results a masking rewrite cannot read, and add the audit cells for synthesized streams. * test(router): annotate the finished-turn refusal stream test locals with Final --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Mateo Wang
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4a58784fa2
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fix(cost): price exact cost-map names before price-free capability rules, and fix SCIM and MCP integration tests on CircleCI (#47037)
* fix(test-harness): preserve sibling auth modules in isolated worker configs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): expect servers in MCP connect-flow descriptions Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): expect ptu_hours in daily activity metrics after #43043 Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): kill every serving worker once the SCIM push blocks on the row lock * fix(cost): price exact cost-map names before price-free capability rule matches * test(streaming): price a priced alias stream at its deployment model and keep the unpriceable case unmapped Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(cost): price an explicit base_model under its own provider after candidate reordering Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(cost): retain priced generalized candidates and skip explicit-pricing lookups Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): assert custom pricing makes no remote model-info requests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(cost): keep the per-candidate pricing provider final Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(router): pin a Bedrock application profile prompt for the one-hour ttl its base model sends Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): assert the Nova Sonic tool-call argument delta carries the full arguments * fix(cost): sort cost candidates from the static cost map and rules, without provider lookups * test(integration): bill route-priced Bedrock chat streams and responses, and pin application profiles for an hour on messages and cache hits --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: Yuneng Jiang <yuneng@berri.ai> |
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Mateo Wang
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d76ec3a47e
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fix(proxy)!: answer 400 for malformed tools on count_tokens instead of crashing (#46583)
* fix(proxy): answer 400 for malformed tools on count_tokens instead of crashing A non-list tools value crashed the vector store lookup during auth and the built-in tool cost lookup in the failure logging path, so the proxy answered an unhandled 500 and closed the keep-alive connection. count_tokens now answers a 400 invalid_request_error for a malformed body, drops malformed tools when drop_params is on, and both lookups skip values of the wrong shape. * fix(proxy): skip non-list tools in the tool allowlist check Also validate the count_tokens body without recursion, which the recursion detector rejects. * test(integration): restore the int tools case on count_tokens The proxy now answers a non-list tools value with a 400, so the case is deterministic again. * fix(proxy): reject malformed tools at the LLM route entry and keep vector store checks on malformed ids * fix(proxy): apply drop_params like core when dropping malformed tools, and reject malformed tool vector store ids Check tools after request setup so the Claude Code default and the logged call type apply, read the request, global, and model group drop_params the way core does, drop tool_choice and friends with tools, cover Gemini generateContent, and answer 400 for a malformed tools[].vector_store_ids with the strict flag off * fix(proxy): keep the request's call type when logging a gate rejection after request setup The body-shape fallback relabeled a /v1/messages rejection as acompletion and a list-input /v1/responses rejection as aembedding, so it now only applies when the logging object carries no known call type * fix(proxy): share the malformed tools check across tool routes and honor drop_params per entry * fix(proxy): accept null vector_store_ids, read every named store id in auth, check the responses websocket * refactor(proxy): leave the responses websocket out of the request-level tool check * fix(proxy): let a request's additional_drop_params replace the deployment list and keep compact's call type on rejections * fix(proxy): read router default drop lists and deployment ids in the malformed tools check * fix(proxy): leave malformed tools to the router when it can pick another deployment Fallbacks, auto-routers, model strings, comma batches and team model names let the router pick a deployment after the proxy checks the request, so the proxy now forwards a malformed tools field there as main does, and only rejects it when the deployment it checks is the one that serves. Token counting never reroutes, so count_tokens and input_tokens keep reading the group they count with. additional_drop_params names are read the way core reads them, so a list with a non-string entry still names its strings. * test(integration): cover malformed tools on reroutable models, router defaults and deployment ids * fix(proxy): resolve malformed tools at the deployment the router picks * fix(proxy): keep provider-repaired tool schemas, honor fallback_on_unsupported_params, skip cooldown on malformed tools Empty schemas and JSON-string schemas pass the tools check the way litellm's provider paths already read them. The rejection is a BadRequestError subclass carrying the deployment's provider, so fallback_on_unsupported_params: false keeps the 400, and the router never cools a deployment down for a request litellm rejected before calling it. Adds the audit's pre_call guardrail and cross-provider bridge cells. * test(integration): expect a 400 for an empty-string tools field on /v1/messages Real Anthropic rejects tools "" with a 400 on main too, so the case joins the malformed tools test * fix(router): keep web search routing for tools passed as a tuple * fix(router): keep a deployment's own tools when drop_params drops a malformed request tools * test(router): list _merged_tools as covered through the deployment tools merge tests * fix(router): drop the request's tool settings with its malformed tools when deployment tools replace them * fix(router): skip a tool whose type is not a string in the web search filter instead of raising TypeError * fix(prometheus): keep deployment health metrics clean on a malformed tools rejection * test: type the new malformed tools tests * test: mark new test locals Final and type kwargs dicts |