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139 commits
| Author | SHA1 | Message | Date | |
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tin-berri
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1f4acbb924
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feat(complexity_router): custom classifier plugins via classifier_type 'custom' (#37249)
* feat(complexity_router): custom classifier plugins via classifier_type 'plugin' Adds a third classification mode where an operator-supplied hook decides the tier instead of the heuristic scorer or the LLM classifier. The hook implements an async classify(context) returning a tier name (built-in value, tier_labels label, or tier_definitions name) or None to decline; failures, timeouts, and unknown tiers fall back exactly like a failed LLM classifier. The context carries the request messages and metadata, including caller identity, so a plugin can route by team, spend, or any business rule. The plugin resolves from a dotted path at proxy startup with a load-time check that classify is a coroutine function, and is closed off over HTTP like the routing plugins list. Routing decisions record the new classifier_plugin cause. tier_definitions now accepts classifier_type 'plugin' alongside 'llm'. * fix(proxy): resolve plugin dotted paths in _delete_deployment before hashing ids The db-sync reconcile re-reads the raw config and hashes litellm_params to compute which ids the config wants served, but the router's ids were hashed from the resolved params where plugin dotted paths are live instances. The mismatched ids made the reconcile evict every plugin-bearing auto-router one sync after startup, on any proxy with a database connected. This also affected the existing routing plugins list, not just the new classifier plugin. Resolving the plugins in _delete_deployment the same way load_config does makes both sides hash the same canonical form. A plugin module broken on disk at reconcile time skips cleanup instead of evicting valid deployments, matching how a get_config failure is handled * fix(complexity_router): treat non-string plugin verdicts as declines, centralize the empty-mapping sentinel A hook returning a non-string raised inside resolve_classified_tier outside the plugin exception boundary, failing the request instead of falling back. Also moves the read-only empty mapping to constants.py per repo convention and moves the classifier plugin product docs out of the package README for the docs repo * refactor(complexity_router): rename the plugin classifier mode to classifier_type 'custom' The mode value now names the operator's intent while classifier_plugin keeps naming the mechanism; routing decisions keep the classifier_plugin cause * refactor(proxy): pin plugin-bearing deployment ids from the raw params instead of resolving in the reconcile Replaces the previous approach of re-running plugin resolution inside _delete_deployment, which imported operator modules on every reconcile cycle and skipped the whole cleanup pass when any one module was broken on disk. load_config now stamps model_info.id from the raw litellm_params before resolution swaps dotted paths for live instances, so the reconcile's raw-config hash matches by construction and needs no resolution at all: a broken module cannot stall cleanup for unrelated models, and any future param-transforming resolution is covered by the same pin. _generate_model_id becomes a staticmethod so the pin can run before the Router exists; its statically dead non-string key branches are removed. Also documents candidate_models as an informational snapshot for classifier plugins, unlike the narrowing surface RoutingPlugin filters * fix(router): restore _generate_model_id key handling, align classifier context with the routing-plugin pattern The staticmethod conversion accidentally dropped the non-string-key branches from _generate_model_id, a silent hash change for any params with non-string keys; they are restored verbatim. The classifier plugin context now follows the Router-level routing-plugin recipe exactly: structured messages come from resolve_structured_messages over the raw messages, and the metadata key comes from the shared get_metadata_variable_name_from_kwargs helper, which also replaces the duplicated inline sniff in _pick_model_for_tier. This removes the raw-or-resolved fallback where a plugin could silently receive resolved messages when a call site forgot to pass the raw ones * refactor(router): make generate_model_id public, guard classifier context construction Two modules legitimately hash deployment ids with the same helper now (Router and the proxy's config-load pin), so the private name was lying about its audience and the cross-module call needed a pyright suppression; renaming it public restores the static safety net. The classifier plugin's RoutingContext construction moves inside the failure boundary, matching the LLM path where litellm-side prompt building also falls back rather than failing the request, and a prompt-only call with no message list is now covered by a test |
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Yuneng Jiang
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075781568d
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test: remove tests that never execute
Three groups, all verified by running the suite rather than by inspection. 18 files whose every test function carries an unconditional @pytest.mark.skip, 39 test functions in total. They are collected on every CI run and always skip, so they advertise coverage the suite does not have. Reasons on the marks include "AWS Suspended Account", "lakera deprecated their v1 endpoint" and "moved to using 'otel' for logging"; 26 of the marks predate 2025. 30 test functions with a byte-identical body and identical decorators to a sibling in the same file and class, differing only in name. Deleting one of each pair removes no coverage. Four further candidates were excluded because they override an inherited test, where deleting the override un-shadows the base class implementation instead of removing a duplicate. 9 test functions that a later definition of the same name shadows, so Python never binds them and pytest cannot collect them. One file that is a demo script rather than a test; its own docstring says to run it with python. Verification: collecting the 26 edited files gives 2,492 node IDs before and 2,462 after. The 30 duplicate deletions account for exactly 30 removals, the 9 shadowed deletions account for 0 (confirming at runtime that they were never collectable), nothing unexplained disappeared, and nothing new appeared. No other test or module imports any deleted symbol. |
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devin-ai-integration[bot]
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7a55ca811b
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fix(responses): init completed_response on bridge streaming iterator (#35413)
LiteLLMCompletionStreamingIterator overrides __init__ without calling super().__init__(), so completed_response was only set once the stream reached RESPONSE_COMPLETED. On a mid-stream provider error the router's _extract_partial_responses_usage read source_iterator.completed_response during fallback recovery and raised AttributeError, masking the real provider error (e.g. Anthropic 529) and bypassing configured retries and fallbacks. Initialize the attribute to None so recovery degrades to no partial usage instead of crashing. Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Deepanshu Lulla
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0580465384
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feat(router): add per-deployment allowed_fails_policy and cooldown_time override support (#34416)
* feat(router): add per-deployment allowed_fails_policy and cooldown_time override support
Three bugs fixed in the router cooldown system: (1) deployment-level allowed_fails and
allowed_fails_policy in model_info now take precedence over router-level settings in
_should_cooldown_deployment; (2) failed fallback deployments now get evaluated for
cooldown via _trigger_cooldown_for_failed_deployment, bypassing the Logging dedup gate;
(3) DualCache promotes Redis cooldown entries using default 600s TTL instead of true
remaining cooldown time -- _corrected_active_cooldown now evicts expired entries and
corrects stale in-memory TTLs on backfill. Adds ServiceUnavailableError, BadGatewayError,
and NotFoundError fields to AllowedFailsPolicy and cooldown_time to LiteLLMParamsTypedDict.
* fix(router): gate fallback cooldown trigger on has_logged_async_failure; use only litellm_metadata for deployment ID
* fix(router): use X | Y union syntax to fix UP007 strict lint gate
* test(router_utils): add coverage for _trigger_cooldown_for_failed_deployment and has_logged_async_failure gate
* test(router_utils): cover deployment cooldown override and exception swallow paths
* fix(router): add InternalServerError/ServiceUnavailableError/BadGatewayError/NotFoundError to router-level get_allowed_fails_from_policy
* fix(router): format router.py and add router-level policy tests
* test(router): add CI-visible coverage for per-deployment cooldown policy
Tests for `_get_deployment_cooldown_policy`, `_resolve_allowed_fails_from_policy`,
and `_should_cooldown_based_on_deployment_policy` (cooldown_handlers.py), the
`_corrected_active_cooldown` branches in CooldownCache, and the four new
exception-type branches in `Router.get_allowed_fails_from_policy` (router.py) --
all in `tests/test_litellm/` which the enterprise-routing CI job runs.
* fix(router): use is not None guard for cooldown_time_override in should_cooldown_based_on_allowed_fails_policy
A cooldown_time_override of 0 was previously treated as falsy and silently
fell through to the router-level cooldown_time value. Switched to an explicit
is not None check so that zero is honored as a valid override.
Added a regression test covering the zero case.
* fix(router): honor has_logged_async_failure and metadata for fallback cooldown; support both model_info and litellm_params locations
Manual verification against a live proxy surfaced that the fallback-cooldown-gap
trigger never actually fired: the has_logged_async_failure check read a plain
attribute that Logging never sets (the real flag lives in model_call_details),
and the deployment_id lookup only trusted litellm_metadata, which regular chat
completions never populate (only batch/thread/file endpoints do). Router
overwrites model_info on whichever key is present before every attempt, so
metadata is equally authoritative there, not caller-controlled as previously
assumed. Also let allowed_fails/allowed_fails_policy/cooldown_time be set under
either model_info or litellm_params, each preferring its own canonical location.
* fix(router): fix ContentPolicyViolationError policy shadowing and partial-policy zero-threshold
Two bugs from Greptile review on PR #34416:
- ContentPolicyViolationError subclasses BadRequestError, so listing
BadRequestError first in _EXCEPTION_POLICY_FIELDS made the isinstance
check always match BadRequestError for content-policy errors, using the
wrong allowed_fails threshold. Reordered so the subclass is checked first.
- A deployment with a partial allowed_fails_policy and no deployment-wide
allowed_fails forced allowed_fails_override=0 for any exception type its
policy didn't cover, cooling the deployment down on the first unrelated
failure. Now defers to router-level behavior for uncovered exception
types instead of forcing an immediate cooldown.
* fix(router): only trust a metadata/litellm_metadata bucket the router itself wrote deployment info into
veria-ai flagged that preferring litellm_metadata whenever present could pick up a
caller-supplied litellm_metadata.model_info.id (preserved via allow_client_pricing_override)
instead of the metadata bucket the router actually populated for a regular completion's
fallback attempt, naming an arbitrary "victim" deployment for cooldown.
Router._update_kwargs_with_deployment() always writes model_info and
deployment_model_name into the same bucket together. Only trust a bucket that
carries deployment_model_name alongside model_info, since that marker is only
ever set by the router itself, not by request-body metadata.
* test(router): add regression coverage for ContentPolicyViolationError policy shadowing
The subclass-ordering fix in commit
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Yuneng Jiang
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495eb7e7f4
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test(router): assert the auto-router max_input_chars kwarg
PR #35956 added the max_input_chars passthrough to the AutoRouter constructor but left this mock assertion in tests/router_unit_tests unchanged, so test_init_auto_router_deployment_success has been failing on litellm_internal_staging ever since. The passthrough itself is intentional and its behaviour is already covered by TestAutoRouterMaxInputCharsWiring in tests/test_litellm, so only the stale expected kwargs need updating. Assert the shared constant rather than the literal 2000 so tuning the default does not break this test again. |
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mateo-berri
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1fefd80925 | fix(proxy): resolve pass-through credentials live from router deployments | ||
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Devin AI
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ddaee8df16 | fix(auth): resolve managed batch/file deployment model_id to model name for team access checks | ||
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devin-ai-integration[bot]
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637fc1f60e
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fix(router): tag-aware pre-routing strategy selection for shared model_name (#33691)
* fix(router): tag-aware pre-routing strategy selection for shared model_name Complexity/auto/adaptive/quality router registries were keyed by model_name alone, so a second deployment sharing a model_name but carrying different tags was rejected and every request used the first config. This made tag-based routing to distinct provider configs behind one alias impossible, surfacing as 401 'Not allowed to access model due to tags configuration' for the second tag. Each registry now holds a list of tag-scoped strategies and async_pre_routing_hook selects the entry whose tags match the request before classification, falling back to a default-tagged then first-registered entry. A repeat of the same (model_name, tags) pair is still rejected. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(router): cover tag-scoped pre-routing strategy registry helpers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore: re-trigger CI Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Krrish Dholakia <krrishdholakia@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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249a999506
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fix(responses-api): raise APIError on in-stream error events; widen ErrorEventError.param to accept dict (#32835)
* fix(responses-api): raise APIError on in-stream error events; widen ErrorEventError.param - BaseResponsesAPIStreamingIterator._maybe_raise_for_error_event inspects each chunk and raises litellm.APIError for type=error and type=response.failed events so callers see an exception instead of a benign stream chunk - rate_limit* codes map to 429; client error codes (invalid_request_error, context_length_exceeded, etc.) map to 400; all other codes default to 500; raw integer codes are never used as-is as HTTP status codes - ErrorEventError.param widened from Optional[str] to Optional[Union[str, Dict]] to prevent Pydantic ValidationError on dict-typed param payloads silently dropping error events before any type inspection * test(responses-api): add streaming iterator error event tests to CI-covered path * test(responses-api): cover response.failed, dict-error, null-error, and sync iterator paths * test(responses-api): set completion_start_time on mock logging objects for internal staging _process_chunk * fix(responses-api): map insufficient_quota to 429, derive failed-response log status from error code, and record failed-stream usage for spend accounting insufficient_quota moves out of the 400 bucket; OpenAI returns HTTP 429 for it and the non-streaming exception mapping treats 429 as RateLimitError, so the in-stream mapping now agrees _handle_logging_failed_response previously hardcoded APIError(status_code=500), so a rate-limited response.failed was logged to integrations as 500 while the caller saw 429; it now shares the same error-code-to-status mapping via _error_event_fields and _status_code_for_error_code usage carried on a response.failed event is now stashed as combined_usage_object with its computed cost on the logging object before failure handlers run, reusing the mid-stream-interruption spend recovery path (_failure_handler_helper_fn, proxy post_call_failure_hook, _ProxyDBLogger), so failed streams count their billed tokens instead of logging zero cost dedupe: TestMaybeRaiseForErrorEvent in tests/llm_responses_api_testing duplicated tests/test_litellm/responses/test_streaming_iterator_error_events.py, which is the canonical mirrored location and CI-covered via test-unit-responses-caching-types; the duplicate class is removed * fix(responses-api): wrap retriable in-stream errors in MidStreamFallbackError and map error type field to status Mirror chat streaming semantics from _handle_stream_fallback_error: 429 and 5xx in-stream error events now raise MidStreamFallbackError carrying the mapped APIError so the router's FallbackResponsesStreamWrapper triggers mid-stream fallback and cooldown; non-retriable 4xx still raise APIError directly. Status mapping now reads both the OpenAI error type and code fields, so type-classified client errors (e.g. invalid_request_error with code invalid_prompt) map to 400 instead of falling through to 500. * fix(responses-api): accumulate streamed output text so mid-stream fallback continues instead of restarting MidStreamFallbackError was always raised with generated_content="", so the router's stream_with_fallbacks treated every mid-stream error as pre-first-chunk and retried with the original input, streaming duplicated content to clients that had already received partial output. The iterators now accumulate response.output_text.delta text (mirroring chat's response_uptil_now) and pass it as generated_content, letting the router build a continuation input via _build_responses_continuation_input. * test(responses-api): pin in-stream token limit error to raised APIError --------- Co-authored-by: Deepanshu <deepanshu.lulla@alpha-sense.com> |
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Sameer Kankute
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5b93ba0ada
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feat(router): add separate ITPM/OTPM deployment rate limits (#31952)
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* feat(router): add separate ITPM/OTPM deployment rate limits Support input/output tokens per minute on deployments via enforce_model_rate_limits, with reservation, reconciliation, refund on failure, and rate-limit headers. Co-authored-by: Cursor <cursoragent@cursor.com> * chore(router): keep ITPM/OTPM diff minimal in router.py Drop unrelated Black reformatting from router.py and types/router.py so the PR only contains functional ITPM/OTPM changes. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): make ITPM/OTPM limits separate and atomic Address Greptile review on separate ITPM/OTPM deployment rate limits. - OTPM is now reserved atomically pre-call with rollback, matching the ITPM path, so concurrent requests can no longer overshoot the configured output limit before reconciliation - ITPM counts input tokens only; it no longer accumulates completion tokens, so the input-token limit and x-ratelimit-limit-input-tokens header describe input usage as their names imply - _read_reservation_from_kwargs only falls back to litellm_params.metadata when the top-level metadata channel is absent, so production requests carrying a litellm_params.metadata dict still reconcile and refund their reservation Adds regression tests for OTPM atomicity under concurrency, input-only ITPM enforcement, and reservation lookup when litellm_params.metadata is present. * fix(router): subtract input tokens only from remaining-input-tokens header The in-flight replay for x-ratelimit-remaining-input-tokens subtracted total tokens (input + output) instead of input tokens only, so clients saw remaining input quota understated by the completion token count on every response. Now consistent with the input-only ITPM counter. * fix(router): make itpm/otpm vs tpm/rpm precedence explicit When a deployment configures itpm/otpm alongside tpm/rpm, the io-token path takes over and the tpm/rpm limits are not enforced. Log a warning the first time such a conflicting deployment is seen so the supersession is not silent, and document the mutual exclusivity. Post-call reconciliation now only trues up a counter that was actually reserved against, so the itpm/otpm keys are no longer incremented for deployments that never configured that limit. * fix(router): track actual io-token usage on the reservation-minute key Post-call reconciliation now keys off the exact cache key stashed at pre-call time rather than one recomputed from the response-time minute. This fixes two issues: a request whose pre-call estimate was 0 now still writes its actual billable input to the ITPM counter (previously it was skipped, leaving the limit unenforceable for that request), and a call that finishes in a later minute reconciles against the minute it reserved against instead of pushing a negative delta into the next minute. Counters are only touched when their limit is configured. * fix(router): run io-token reconciliation before the model_id guard async_log_success_event gated IO reconciliation behind the model_id guard that only the TPM tracking path needs. Since reconciliation works entirely from the cache keys stashed in kwargs, a success event whose standard_logging_object lacks model_id would skip reconciliation and leave the reservation on the counter until the TTL expired, wasting quota. Route the IO path first. * fix(router): don't replay in-flight delta for itpm/otpm headers For ITPM/OTPM model groups the counter is incremented at reservation time (pre-call), so the remaining values returned by get_remaining_model_group_usage already account for the current request. Replaying the in-flight delta on top double-counted it and understated x-ratelimit-remaining-input/output-tokens by up to max_tokens on every response. Skip the delta for io-token groups; the legacy TPM/RPM replay path is unchanged. * fix(router): clear io-token reservation after reconcile/refund async_io_token_refund_failure and async_io_token_reconcile_success now clear the stashed reservation keys from the request metadata once done. Otherwise, on a model group mixing IO-limited and non-IO deployments, a failed IO call that retries on a non-IO fallback left the stale sentinel in the shared request metadata; the fallback's success handler would divert into IO reconciliation against the already-refunded key, driving the ITPM counter negative and skipping the non-IO deployment's TPM tracking. * fix(router): tidy reservation channel lookup and header guard Consolidate the reservation channel lookup into a single ordered helper shared by read and clear, so top-level metadata always wins over litellm_params metadata without the tangled per-iteration fallback. Also stop gating the router rate-limit header block on the presence of x-ratelimit-remaining-input/output-tokens. That block only emits those headers for ITPM/OTPM groups; for a non-IO group backed by a provider that natively returns input/output token headers, the extra conditions suppressed the router's own remaining-tokens/requests headers. * fix(router): strip client-supplied io-token reservation keys The reservation sentinels (_litellm_itpm_reserved, _litellm_itpm_cache_key, and the otpm equivalents) are server-only, but metadata is caller-controlled on proxy requests. An authenticated caller could forge these fields with an arbitrary cache key so the post-call reconcile/refund path would decrement any deployment's ITPM/OTPM counter and let it exceed the configured limit. Strip the reserved keys from the request metadata in set_io_token_rate_limit_request_kwargs, which runs before the router stashes its own reservation, so only a genuine server-side reservation is ever read post-call. * fix(router): track TPM routing load for io-limited deployments deployment_callback_on_success early-returned for any deployment with itpm/otpm set, so its total-token usage never landed in the router's TPM routing counter. TPM-aware routing strategies then saw 0 load for IO deployments and over-routed to them in mixed model groups. Only skip tracking when neither tpm/rpm nor itpm/otpm are configured; itpm/otpm enforcement still runs separately in ModelRateLimitingCheck, so the routing counter and the enforcement counters stay independent. * fix(router): expose standard tpm/rpm headers for io-limited groups get_remaining_model_group_usage returned early for ITPM/OTPM groups, so a group that also set tpm/rpm never emitted x-ratelimit-remaining-tokens / -requests; clients and prometheus gauges reading those saw no data. Build both header sets instead of returning early. Also simplify the in-flight header replay: only the tpm/rpm counters are incremented post-response, so the delta now adjusts just those. The itpm/otpm counters are incremented at reservation time (pre-call), so the input/output token headers already reflect the request and are left untouched - which removes the need for the separate io-group special case. * fix(router): roll back ITPM on any OTPM reservation error; dedup warning per instance Two follow-ups from review. The pre-call OTPM reservation only rolled back the ITPM reservation on a RateLimitError, so a transient cache error while reserving OTPM left the ITPM counter inflated until the TTL expired; catch any exception, release the ITPM reservation, then re-raise. Replace the module-level lru_cache warn-once (caching a logging side effect, which never re-warns in a long-lived process) with an instance-scoped set of already-warned deployment ids on ModelRateLimitingCheck. * fix(router): always clear reservation stash on reconcile; don't collapse id-less warning dedup Clear the reservation in a finally block so a mid-reconciliation cache error still removes the stash and a duplicate success event can't re-process it. Dedup the itpm/otpm-vs-tpm/rpm conflict warning per real deployment id; a deployment with no id no longer collapses every id-less deployment onto the str(None) key (which would suppress all but the first warning). * fix(router): skip io reservation when deployment can't be keyed _get_cache_keys returned a shared 'global_router:None:None:...' key when a deployment was missing model_info.id or litellm_params.model, so misconfigured deployments could share one rate-limit bucket. Return None in that case and skip io reservation for the request. * fix(router): honor explicit max_tokens=0 in io reservation _resolve_max_tokens used 'max_tokens or max_completion_tokens', so an explicit max_tokens=0 fell through to the model default. Only fall back to max_completion_tokens when max_tokens is absent. * fix(ci): satisfy lint budget, router coverage, and dashboard schema sync - Modernize the new itpm/otpm module's type hints to PEP 585 lowercase generics (Dict/Tuple/List -> dict/tuple/list) to clear the added UP006 violations; ratchet ruff-strict-budget.json's UP006 ceiling down to match. - Replace three try/except Exception blocks that must stay broad by design (token_counter and litellm.get_model_info raise untyped exceptions, and an io-token refund failure must never break the logging pipeline) with contextlib.suppress(Exception), matching the codebase's existing resolution for this exact BLE001 pattern. - Add direct unit tests for get_model_group_io_token_usage (multi-deployment aggregation and the empty-model-list case) in test_router_helper_utils.py, satisfying the router function-coverage check. - Regenerate the dashboard's schema.d.ts so the new itpm/otpm fields on GenericLiteLLMParams and ModelGroupInfo are reflected in the OpenAPI types. * fix: enforce io token rate limits consistently * fix: honor zero max tokens in otpm reservation * fix(lint): fix UP007 violation and resync ruff-strict-budget.json to base Convert Union[_Span, Any] to _Span | Any (safe on this repo's Python >=3.10 floor) to clear the new UP007 violation from the TYPE_CHECKING-gated Span alias. The previously committed ruff-strict-budget.json ratcheted UP006 down from a stale base; litellm_internal_staging has since tightened that same ceiling further on its own. Reset the file to the current base's committed values and re-ratchet from there so the budget only ever moves down relative to the actual merge-base, never against a stale snapshot. * fix(router): attach ITPM/OTPM headers on dict responses and harden reservation Strip itpm/otpm from provider kwargs, ensure messages are available for ITPM estimation, honor max_output_tokens on /v1/responses, and propagate rate-limit headers through /v1/messages dict responses via _hidden_params. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): attach ITPM/OTPM headers to streaming /v1/messages responses Wrap bare async iterators in HiddenParamsAsyncIteratorWrapper so set_response_headers can attach rate-limit headers to streaming Anthropic messages responses that lack a _hidden_params slot. Co-authored-by: Cursor <cursoragent@cursor.com> * style: ruff format add_retry_fallback_headers.py Fix CI ruff format check failure on get_hidden_params_dict call site. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(router): extract set_response_headers helpers to fix C901 budget Move header-attachment logic into add_retry_fallback_headers helpers so set_response_headers stays under the strict complexity ceiling. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: keep IO token reservation when response usage is missing Missing usage was reconciled as zero and fully refunded the pre-call reservation, allowing limit bypass on repeated successful calls. Only adjust counters when usage is resolved from the response or standard logging fields; otherwise keep the reservation until TTL expires. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: enforce RPM/TPM alongside IO-token limits on mixed deployments Deployments with both itpm/otpm and tpm/rpm previously returned after the IO reservation and skipped RPM/TPM checks. Run both paths and refund the IO reservation only when RPM/TPM rejects after a successful reservation. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: track TPM usage on success for mixed IO+TPM deployments The early return after IO-token reconciliation in log_success_event and async_log_success_event skipped the TPM counter increment, so the tpm_key the pre-call check reads was never written and tpm_limit was never actually enforced on deployments that also configure itpm/otpm. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: treat total-only usage as unresolved in IO-token reconcile usage/standard_logging_object entries carrying only total_tokens (no prompt/completion or input/output breakdown) were treated as resolved usage, resolving to (0, 0) and refunding the full reservation. Both _usage_is_present and the standard_logging_object fallback now require an actual input/output breakdown before reconciling, keeping the reservation otherwise. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: reserve minimal token when input/output estimation fails _reservation_value(0, limit) reserved the entire limit whenever token estimation failed (empty/unsupported input, tokenizer error), letting one such request claim the whole bucket and 429 every concurrent request to the deployment until it completed. Reserve 1 token instead so estimation failures no longer serialize traffic. Co-authored-by: Cursor <cursoragent@cursor.com> * fix: refund IO reservation synchronously before retry deployment pick On retry, set_io_token_rate_limit_request_kwargs clears reservation sentinels from the shared kwargs dict before a background failure handler can refund them, stranding the counter until TTL. Refund and clear any stale reservation in _update_kwargs_with_deployment before stripping sentinels for the next attempt. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(io_token_rate_limit_check): use model-specific tokenizer for ITPM estimate; document sync-refund Redis ceiling Pass the deployment litellm_params.model to token_counter so it uses the model's native tokenizer instead of the generic fallback, narrowing the reservation over/under-estimate window between pre-call and post-call reconcile. Add a ponytail: comment to refund_stale_reservation_before_retry explaining the known ceiling: the synchronous DualCache.increment_cache issues a blocking Redis INCR when a Redis backend is configured. This only fires on streaming mid-stream retries (non-streaming failures await their failure handler before the retry picks a new deployment, leaving no sentinels to refund). Upgrade path: make _update_kwargs_with_deployment async. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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mubashir1osmani
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56825926af
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fix(vertex/files): stream OpenAI->Vertex batch JSONL uploads (#31036)
* fix(vertex/files): stream OpenAI->Vertex batch JSONL uploads to fix OOM on large files
Large (1GB+) batch JSONL uploads to Vertex AI / GCS caused OOM or killed the worker
because the request body was buffered and multiplied 2-3x in size. The create-file
path is now streaming end-to-end: transform_create_file_request returns a
ResumableChunkedUploadConfig carrying a lazy _OpenAIToVertexBatchUploadStream, and the
HTTP handler opens a GCS resumable session and PUTs the body in bounded 8 MiB chunks
(Content-Range, 308 between chunks) so the transformed payload is never held in full.
The proxy /v1/files endpoint streams from Starlette's spooled upload handle instead of
reading the whole body, and batch rate limiting counts tokens and models in a single
streaming pass.
Only gcs_bucket_name is supported for the GCS target; the legacy bucket_name key is
intentionally not read.
Also removes the unreachable VertexAIFilesHandler create path and everything only it
kept alive (VertexAIJsonlFilesTransformation, _stream_openai_jsonl_to_vertex, the legacy
transform helpers), plus the orphaned batch_utils helpers the streaming rewrite replaced.
* fix(batches): return original JSONL on unparseable row to avoid silent batch truncation
The streaming rewrite of replace_model_in_jsonl accumulated physical lines and
skipped a row on JSONDecodeError to support multi-line objects, but a genuinely
malformed or truncated row never completes: it poisons the buffer, swallows every
following row, and the function still returned the partial rewrite (the rows before
the bad one, already model-rewritten) as if the batch were complete. That turned the
pre-rewrite behavior of returning the original file unchanged (so the provider rejects
the bad batch loudly) into a silent partial submission.
Restore the original-content fallback: when an unparseable remainder is left after the
loop, return the original file_content (rewinding a consumed seekable source) instead of
the truncated output. The multi-line happy path is unchanged.
* test(batches): mock resumable GCS upload in vertex batch prediction test
The vertex batch file-create path now streams to a GCS resumable session via
_aresumable_chunked_upload (httpx send) instead of AsyncHTTPHandler.post, so the
existing test's post mock no longer intercepted the upload and a real request hit
GCS (401). Mock _aresumable_chunked_upload to return the GCS object response; the
resumable protocol itself is covered in test_vertex_ai_files_streaming.py.
* fix(batches): resilient per-row token accounting; no hard-block on count failure
The batch input-file pass iterated a generator whose json.loads raised on a
malformed line; the outer except caught it and stopped the loop, so any body.model
on rows after a bad line was never collected and the model allowlist check ran
against a partial set. It also hard-blocked the batch with a 400 whenever token
counting raised, a backwards-incompatible change from the prior swallow-and-proceed
behavior that breaks legitimate rows the token counter cannot measure (e.g. some
multimodal content).
Iterate the JSONL line-by-line and account each row independently. A malformed line
is skipped (its request cannot run upstream anyway) and a row the counter cannot
measure falls back to a conservative size-based estimate. The loop never aborts, so
the allowlist check always sees every parseable model, and the token total is never
zeroed, so a crafted uncountable row still cannot evade the TPM limit, without
hard-rejecting a legitimate batch.
* perf(vertex/files): unblock async upload; drop empty finalize; widen batch MIME types
Three review follow-ups on the resumable batch upload:
- _aresumable_chunked_upload pulled chunks from a synchronous generator that runs
the per-row transform inline on the event loop thread, blocking other requests
between PUTs on large uploads. Each chunk is now produced via asyncio.to_thread.
- _iter_resumable_chunks no longer yields a trailing empty chunk, so an exactly
chunk-aligned upload finalizes on its last data chunk instead of an extra
zero-byte PUT; a 0-byte stream still finalizes via the caller's empty request.
- valid_content_type now accepts the MIME types clients label .jsonl batch uploads
with (text/plain, application/json, ndjson, ...), so such a batch file no longer
silently bypasses the streaming path into the buffered media upload.
* fix(vertex/files): keep legacy bucket_name as GCS bucket fallback
The rename to gcs_bucket_name dropped the legacy bucket_name key entirely, so an SDK caller passing bucket_name to a Vertex AI file create/retrieve/content call with GCS_BUCKET_NAME unset got ValueError("GCS bucket_name is required") where it previously resolved the bucket. _get_configured_bucket_name now reads gcs_bucket_name, then bucket_name, then the env var, and bucket_name is restored to OPTIONAL_KWARGS_KEYS so it survives get_litellm_params on the retrieve and content paths. gcs_bucket_name keeps precedence when both are present
* style: sort imports in llm_http_handler to satisfy I001 budget
---------
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
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Sameer Kankute
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079c136742
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chore(oss): litellm oss staging 120626 (#30292)
* feat(bedrock): add bedrock mantle gemma 4 models (#30264) * feat(bedrock): add bedrock mantle gemma 4 models * test(bedrock): harden mantle local cost fixture * feat(responses): enable the responses API for the Tensormesh provider (#30209) * feat(responses): enable the responses API for the Tensormesh provider * Update litellm/llms/openai_like/providers.json Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(langfuse_otel): mark LLM spans as generations (#30250) * fix(bedrock): stop stream_chunk_size leaking into invoke request bodies (#30240) stream_chunk_size is a LiteLLM-internal knob for re-chunking the HTTP response stream. The invoke transformations splat optional_params into the provider request body without dropping it, and Bedrock rejects unknown fields, so any bedrock/invoke request that sets the parameter fails with ValidationException: stream_chunk_size: Extra inputs are not permitted. Drop it in the invoke dispatcher (covers cohere, titan, mistral, meta, ai21) and in the Claude messages-format request builder (the route used for bedrock/invoke Anthropic models) * fix(bedrock): stop buffering streamed tool-call argument deltas (#30231) * fix(bedrock): stop buffering streamed tool-call argument deltas Two issues made Bedrock tool-use streaming arrive as a single end-of-stream burst through LiteLLM while plain text streamed fine. First, the anthropic-beta allowlist mapped fine-grained-tool-streaming-2025-05-14 to null for bedrock and bedrock_converse, so the header was silently stripped. Without that beta, Anthropic models on Bedrock buffer tool input server-side and emit all toolUse.input deltas at once (verified against converse-stream and invoke-with-response-stream directly). Bedrock accepts the beta via additionalModelRequestFields.anthropic_beta, so it is now forwarded. Second, the streaming reads re-chunked the AWS event stream with iter_bytes(chunk_size=1024). httpx's ByteChunker only releases full 1024-byte blocks, so the small early events (messageStart, contentBlockStart, first deltas) sat in the buffer until enough bytes accumulated, pushing time-to-first-byte from ~1.4s to ~8.5s on buffered tool-use streams. The default is now no re-chunking; an explicit stream_chunk_size is still honored. * test(bedrock): cover explicit stream_chunk_size on sync invoke path * test(bedrock): cover stream_chunk_size plumbing through converse completion * test(bedrock): cover stream_chunk_size default in legacy BedrockLLM streaming * test(bedrock): merge converse handler tests into existing mapped test file pytest imports test modules by basename in non-package test dirs, so the new tests/test_litellm/llms/bedrock/chat/test_converse_handler.py collided with the pre-existing tests/test_litellm/llms/chat/test_converse_handler.py and broke collection in CI. Move the new tests into the existing file * feat(otel): emit v2 cost breakdown + stamp tracer scope version (#30156) Read the StandardLoggingPayload cost_breakdown into a typed LLMCost on LLMCallSpanData and emit each component under litellm.cost.* (absent components omitted, so spans stay sparse). Stamp litellm.__version__ as the instrumentation scope version so every v2 span carries a deterministic scope.version. Tests under tests/test_litellm/integrations/otel/. * fix(proxy): cancel in-flight upstream LLM request on client disconnect (opt-in) (#30223) * fix(proxy): cancel in-flight upstream LLM request on client disconnect (opt-in) On the non-streaming path, base_process_llm_request awaited the LLM call with no disconnect monitoring; when the HTTP client went away the upstream request kept running until completion or request_timeout (6000s default), holding a backend slot (e.g. a vLLM GPU slot) for output nobody would read Add an opt-in general_settings.cancel_on_disconnect flag, default off, so the default code path is unchanged. When enabled, a receive-based watcher task observes http.disconnect and cancels the asyncio.gather driving the upstream call. The resulting CancelledError is converted to HTTPException 499 only when the disconnect event is set, so server-initiated cancellations still propagate as-is. The 499 then flows through _handle_llm_api_exception like any other failure, meaning post_call_failure_hook still releases max_parallel_requests slots and fires spend and alerting callbacks; it is logged at info level instead of a full traceback Also removes the dead check_request_disconnection helper in proxy_server.py (zero call sites) along with its behavior-pin tests Builds on the receive-based design from #25776 Addresses #13774. Re-fixes #22805 (regressed after the #14295 revert) Co-authored-by: CreateRandom <18438707+CreateRandom@users.noreply.github.com> * fix(proxy): scope 499 quiet logging to disconnects and harden watcher Address the two P2 findings from the Greptile review on #30223. The info-level logging in _log_llm_api_exception now applies only to the disconnect-specific HTTPException (status 499 plus the shared _CLIENT_DISCONNECT_DETAIL message), so any other 499 raised by hooks or guardrails keeps its full traceback. The disconnect watcher now catches exceptions from request.receive() (e.g. a transport reset) and logs a warning instead of dying silently, making the degradation to no-op visible; a test pins that the LLM call is not cancelled in that case --------- Co-authored-by: kursad <kursad.lacin@brado.net> Co-authored-by: CreateRandom <18438707+CreateRandom@users.noreply.github.com> * fix(bedrock): grant aws-external-anthropic:* in OIDC session policy for claude_platform (#30200) (#30205) The inline STS session policy passed to assume_role_with_web_identity acts as an IAM PERMISSION CEILING — effective permissions are the intersection of the role's identity policies and this policy. Any action not listed is silently denied even when the IAM role grants it. #27678 added the bedrock/claude_platform/<model> route but its service-side action namespace is aws-external-anthropic:*, not bedrock:*. Without a matching statement here, every claude_platform request via OIDC (GCP federation, EKS Pod Identity webhook, etc.) 403s with 'no session policy allows the aws-external-anthropic:CreateInference action' — even with a fully permissive identity policy. Add a second ClaudePlatformLiteLLM statement covering CreateInference, CreateBatchInference, CancelBatchInference, DeleteBatchInference, CountTokens, Get*, List*. Keep aws:SecureTransport=true parity with the bedrock statement. Static creds + IRSA flow through different code paths and are not affected. Fixes #30200 * fix(proxy): set Retry-After header on RouterRateLimitError 429 responses (#30098) * Set Retry-After header on RouterRateLimitError responses When all deployments for a model are in cooldown, the proxy returns a 429 whose cooldown timing is only available by parsing the error message string. RouterRateLimitError already carries cooldown_time, so expose it as a standard retry-after header in _handle_llm_api_exception. The value is rounded up so clients never retry before the cooldown window ends. Fixes #27823. * Set Retry-After after response-headers hook so cooldown wins The cooldown-derived retry-after was assigned before the post_call_response_headers_hook merge, so a callback returning a retry-after key (including a stale or empty value) silently clobbered it. Move the RouterRateLimitError block after the callback merge so the cooldown value is authoritative for this error type. * fix(router): route aspeech through async_function_with_fallbacks (#30104) * fix(router): route aspeech through async_function_with_fallbacks Router.aspeech selected a deployment and awaited litellm.aspeech directly, so TTS requests got no retry on failure and no failover to backup deployments; the except block only fired an exception alert and re-raised. Every other router endpoint (acompletion, aembedding, atranscription, arerank) already delegates to async_function_with_fallbacks Mirror the atranscription pattern: move deployment selection and the litellm.aspeech call into a private _aspeech method, then have the public aspeech set kwargs["original_function"] = self._aspeech and await self.async_function_with_fallbacks(**kwargs). _aspeech also picks up the shared _get_async_openai_model_client helper and the same total/success/fail call accounting the sibling endpoints use Fixes #27778. * fix(router): apply deployment kwargs and rpm semaphore in _aspeech Bring _aspeech fully in line with _atranscription: call _update_kwargs_with_deployment so deployment metadata, model_info, timeout, and default litellm params flow into the request, and wrap the litellm.aspeech call with the max_parallel_requests semaphore plus async_routing_strategy_pre_call_checks so TTS respects rpm limits the same way the other router endpoints do Also add a unit test that exercises _aspeech directly and asserts the deployment metadata reaches the underlying call * fix(slack_alerting): stop false-positive hanging request alerts for requests below the alerting threshold (#30106) * fix(slack_alerting): skip hanging request alerts below the threshold The hanging request check alerted on any cached request whose completion status was not yet recorded, with no minimum age check. Since the background loop runs every alerting_threshold / 2 seconds, any request that happened to be in flight at a check fired a "hanging - Ns+ request time" alert even if it was only seconds old, producing a steady stream of false positives. Add a created_at timestamp to HangingRequestData, stamped when the request enters the hanging request cache, and skip requests younger than alerting_threshold without evicting them, so a later check can still alert if they never complete. Extend the cache TTL from threshold + 60s to 1.5x threshold + 60s; with the age check, entries only become alertable after threshold seconds, and the check period is threshold / 2, so the old TTL could evict a genuinely hanging request before any check saw it cross the threshold. Fixes #27855. * fix(slack_alerting): alert once per hanging request The min-age gate stops false positives for young in-flight requests, but a genuinely hanging request still re-alerted on every checker tick within the cache TTL. With the wider TTL (1.5x threshold + 60s) that is 1-2 extra Slack notifications per stuck request at the default 600s threshold. Flag a HangingRequestData entry as alerted once its alert fires and skip flagged entries on later ticks, so each hang produces exactly one alert. The cache reference is mutated in place, so the TTL is untouched and still handles cleanup. Adds a regression test asserting one alert across multiple ticks. Fixes #27855. * fix(health): treat all-proxy-models keys as unrestricted in /health (#30087) * fix(health): treat all-proxy-models keys as unrestricted in /health A key granted all model permissions stores the literal "all-proxy-models" marker in its models list. The /health access filter compared that marker against real model_names, so the model list filtered down to nothing and the WebUI health check returned healthy_count=0, unhealthy_count=0 with HTTP 503. Skip the filter (both the live path and the background-cache model_id scoping) when the marker is present, matching how auth_checks treats SpecialModelNames.all_proxy_models. Fixes #29744. * fix(health): resolve all-team-models sentinel to the team allowlist Same failure shape as the all-proxy-models case: a key carrying the literal "all-team-models" entry matches no real model_name, so the /health access filter would zero out the model list. Resolve the sentinel to the key's team models when team_id is set, matching get_key_models in model_checks.py. Without a team_id the sentinel stays unresolved and matches nothing, denying rather than widening access, mirroring _resolve_key_models_for_auth_check. * feat(proxy): auto-enable drop_params for Claude Code requests (#30218) * feat(proxy): auto-enable drop_params for Claude Code requests Claude Code identifies itself with a claude-cli/<version> user agent and sends Anthropic-specific params (top_k, thinking, etc.) on every request. When the proxy routes those requests to a non-Anthropic provider, the unsupported params fail the call unless drop_params is configured. Detect the Claude Code user agent in add_litellm_data_to_request and default drop_params to true for those requests, without overriding an explicit drop_params value sent by the caller. * feat(proxy): respect operator litellm_settings drop_params over Claude Code default An explicit drop_params in the operator's litellm_settings (true or false) now suppresses the Claude Code user agent default, so an operator who deliberately configured drop_params: false keeps strict param validation for Claude Code clients too. The auto-default only fills the gap when neither the request body nor the config sets a value. * fix(snowflake): migrate to native endpoints with auto-routing for Claude models (#29964) * fix(snowflake): migrate to native Cortex REST API endpoints Replaces the legacy /api/v2/cortex/inference:complete endpoint with the native OpenAI-compatible /api/v2/cortex/v1/chat/completions endpoint, fixing error 390142 (Incoming request does not contain a valid payload) when using model: snowflake/<model> in LiteLLM proxy. Changes: - litellm/llms/snowflake/chat/transformation.py: route to native /cortex/v1/chat/completions, remove Snowflake-specific tool_spec payload transformation, remove content_list response handling, add stream to supported params - litellm/llms/snowflake/anthropic/transformation.py (new): SnowflakeCortexAnthropicConfig routes Claude models to /cortex/v1/messages with anthropic-version header and Anthropic->OpenAI response transform - tests: 29 unit tests covering URL routing, auth headers, payload format, and response parsing * fix(snowflake): map max_tokens to max_completion_tokens for native endpoint * fix: handle multi-turn tool conversations and OpenAI→Anthropic tool format conversion - _extract_system_and_messages now preserves tool_calls from assistant messages and converts them to Anthropic tool_use content blocks - tool role messages are converted to user role with tool_result content blocks (as required by Anthropic Messages API) - Added _transform_tools_to_anthropic() to convert OpenAI tool format (type/function/parameters) to Anthropic format (name/input_schema) - Added comprehensive tests for multi-turn tool conversations Addresses review feedback on PR #29964 * test: add coverage for malformed JSON and non-string tool arguments * fix(tests): update chat transformation tests for native OpenAI-compatible endpoint * style: apply black formatting * fix: resolve mypy type errors in anthropic transformation * fix: correct mypy type: ignore error codes (attr-defined) * fix: use max_tokens instead of max_completion_tokens for Snowflake endpoint compatibility * refactor: merge Anthropic config into unified SnowflakeConfig with auto-routing - Remove separate SnowflakeCortexAnthropicConfig and anthropic/ directory - SnowflakeConfig now auto-routes based on model name: - Claude models → /messages endpoint (Anthropic format) - All others → /chat/completions endpoint (OpenAI format) - No new provider needed (stays as SNOWFLAKE = 'snowflake') - Tool message transformation for Claude: tool_calls → tool_use blocks, tool role → user with tool_result - OpenAI → Anthropic tool format conversion (parameters → input_schema) - Addresses Greptile feedback about unwired SnowflakeCortexAnthropicConfig * fix: use max_completion_tokens for /chat/completions (Snowflake deprecated max_tokens on this endpoint) * fix(tests): update assertions for Claude auto-routing to /messages endpoint * fix(snowflake): add tool_choice conversion and preserve max_completion_tokens in Anthropic path * fix(snowflake): use ChatCompletionMessageToolCall objects and strip model prefix on OpenAI path * fix(snowflake): collect multiple system messages to prevent guardrail override * chore: remove committed .pyc files and add __pycache__ to .gitignore * fix: remove unused Union import * fix: restore original .gitignore (accidentally replaced in earlier commit) * feat(snowflake): add streaming response handler for both Anthropic and OpenAI SSE formats * fix: remove unused AsyncIterator and Iterator imports * fix: add missing total_tokens to ChatCompletionUsageBlock * fix(snowflake): coalesce consecutive tool results into single user message for Anthropic * fix(snowflake): handle message_start event for streaming input_tokens tracking * fix: evict last deleted model in multi-instance deployments (#28608) * fix: evict last deleted model in multi-instance deployments _delete_deployment had an early return when db_models was empty, preventing eviction of the last deleted model during reconciliation. - Remove len(db_models)==0 early return from _delete_deployment - Return None (not []) from _get_models_from_db on DB failure so callers can distinguish a transient failure from a genuinely empty DB - Guard _update_llm_router against None to skip updates on DB failure Fixes #28443 * test: remove dead MagicMock assignment in type_mismatch test * fix: update test to pass [] not None to _update_llm_router test_ProxyConfig__update_llm_router_bad_proxy_logging_raises was passing None as new_models to get through to the proxy_logging_obj check, but the None guard we added now returns early before reaching that path. Pass [] instead so the test exercises the intended AttributeError case. Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> * chore: regenerate API types to sync schema.d.ts with proxy OpenAPI spec Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> --------- Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> * fix: invalidate Redis spend counter on /key/reset_spend (#29694) * fix: set Redis spend counter to reset_to value on /key/reset_spend Previously, the Redis spend counter was always set to 0.0 after a reset, even when reset_to was a non-zero value (partial reset). This caused the budget to be under-enforced for up to 60 seconds until the counter expired and fell through to the DB. Now the counter is set to the actual reset_to value, so partial resets are reflected correctly and budget enforcement is consistent. * test: update reset_key_spend test to match direct cache set The implementation now sets spend_counter_cache directly instead of calling _invalidate_spend_counter. Update the test to verify the in_memory_cache.set_cache call with the correct key, value, and ttl. --------- Co-authored-by: michaelxer <michaelxer@users.noreply.github.com> * fix: add scaleway models pricing (#27659) * fix: Add embeddings support for Scaleway provider * fix: resolve merge conflicts * fix(main): clarify backend route handling for Swagger static assets (#30196) * fix(main): clarify backend route handling for Swagger static assets * fix(allowlist): add BACKEND_MOUNT_PATHS for Swagger static assets * fix(voyage): route multimodal embeddings to correct endpoint (#30193) * fix(voyage): route multimodal embeddings to correct endpoint * test(voyage): cover multimodal embedding edge cases * test(voyage): cover api key fallback * fix(voyage): raise early on missing api key and malformed image url * test(voyage): cover utils routing and helper * fix(voyage): route supported openai params for multimodal models * style: apply black formatting * fix(ui): infer Azure API version from API base (#30204) * fix(ui): infer Azure API version from API base * fix(ui): address Azure API version feedback * Update litellm/llms/snowflake/chat/transformation.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * feat(datadog): add team-scoped Datadog callback support (#29947) Enable teams to configure their own Datadog credentials via POST /team/{team_id}/callback, following the same pattern as Langfuse. * Merge pull request #29528 from aanchal22/litellm_byok-alias-merge fix(proxy): atomic merge for team model aliases and team.models on BYOK create * feat: add EmpirioLabs as an OpenAI-compatible provider (#30278) Co-authored-by: Adam Dalloul <adam.d.developer@gmail.com> * fix: resolve failing tests and lint in snowflake/team endpoints - Black-format snowflake/chat/transformation.py to fix lint failure - Update Anthropic config test to expect default max_tokens of 4096 (matches implementation) - Add AsyncMock + execute_raw mock to team_model_add cache-refresh pin test - Add model_dump mock and patch cache/logging in test_uses_atomic_array_append_with_dedup Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(test): update test_db_error_new_model_check for new _delete_deployment logic _delete_deployment no longer short-circuits on empty db_models — it now treats [] as a valid empty-DB state and proceeds to check config models. Mock get_config to return the two router deployments so they appear in combined_id_list and are protected, which matches the real-world scenario where a DB error occurs but the models are config-backed. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(proxy): register cancel_on_disconnect in ConfigGeneralSettings and config list (#30295) * feat(proxy): register cancel_on_disconnect in ConfigGeneralSettings and config list Follow-up to #30223 per maintainer review: documents the flag in ConfigGeneralSettings with a short description and adds it to allowed_args in get_config_list so the UI and /config/list expose it. A test pins that /config/list returns the field with type Boolean, which requires both registrations to be present * chore(ui): regenerate schema.d.ts for cancel_on_disconnect --------- Co-authored-by: kursad <kursad.lacin@brado.net> * fix(datadog): never fall back to env DD_API_KEY for caller-supplied destinations Team/key-scoped Datadog loggers could be pointed at an arbitrary dd_agent_host or dd_site while omitting dd_api_key, causing the proxy's global DD_API_KEY to be sent as the DD-API-KEY header to that destination. Gate the env-var fallback behind an allow_env_credentials flag, set to False when the destination is caller-supplied, mirroring the existing langfuse/langsmith pattern. --------- Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com> Co-authored-by: daitran-tensormesh <dai@tensormesh.ai> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Muspi Merol <me@promplate.dev> Co-authored-by: fangkang <fangkangm@gmail.com> Co-authored-by: Chris Hoogeboom <chris.hoogeboom@gmail.com> Co-authored-by: kursadlacin <kursadlacin@gmail.com> Co-authored-by: kursad <kursad.lacin@brado.net> Co-authored-by: CreateRandom <18438707+CreateRandom@users.noreply.github.com> Co-authored-by: hcl <chenglunhu@gmail.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: sfc-gh-nashukla <navnit.shukla@snowflake.com> Co-authored-by: Rudra Dudhat <contact.rdudhat@gmail.com> Co-authored-by: Michael <52305679+michaelxer@users.noreply.github.com> Co-authored-by: michaelxer <michaelxer@users.noreply.github.com> Co-authored-by: Quentin Champenois <26109239+Quentinchampenois@users.noreply.github.com> Co-authored-by: mauriceberentsen <mauriceberentsen@live.nl> Co-authored-by: lost9999 <56498264+lost9999@users.noreply.github.com> Co-authored-by: GaetanVDB07 <86427581+GaetanVDB07@users.noreply.github.com> Co-authored-by: Aanchal Khandelwal <aan2210khandelwal@gmail.com> Co-authored-by: Adam Dalloul <adam_dalloul@icloud.com> Co-authored-by: Adam Dalloul <adam.d.developer@gmail.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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Sameer Kankute
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3b40ac987f
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Litellm oss 090626 (#30021)
* fix(mcp): report scoped server name during initialize (#29865) * fix mcp scoped server name * Update litellm/proxy/_experimental/mcp_server/mcp_context.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * test(mcp): cover scoped server name in the SSE initialize handler --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(ui): show all session logs in the drawer, not just the first 50 (#29795) * fix(ui): show newest session logs first * test(ui): keep session log pagination coverage * fix(ui): show all session logs in the drawer, not just the first page The session detail drawer fetched session logs via sessionSpendLogsCall without page/page_size, so it only ever received the backend default of one page (50 rows). Sessions with more than 50 calls had the rest unreachable in the UI (#29153). sessionSpendLogsCall now takes page/page_size, and the drawer fetches the first page, reads total_pages, then fetches the remaining pages and accumulates them before the existing client-side sort. This keeps the single continuous list (and the selected-log lookup and keyboard navigation, which all assume the full session) correct. Fetching is bounded by a page cap, and the sidebar shows a "showing most recent N" note if a session exceeds it. The rows are lightweight metadata (the endpoint excludes messages/response), so the full set is small; request/response bodies are still loaded per log on demand. * fix(ui): default session drawer to most recent log, newest first Open a session with its most recent log selected, and order the sidebar newest-first to match the all-sessions logs overview. MCP calls stay grouped last. The latest log by time is computed explicitly, since the MCP grouping means it is not always the first row. * Apply fetching pages in batches suggestion from @greptile-apps[bot] Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(ui): derive session total from accumulated rows when backend omits it Compute the session total after all pages are fetched, falling back to the accumulated row count rather than the first page's. Guards the truncation note against a backend response that omits total but spans multiple pages. --------- Co-authored-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(proxy): handle Mistral multipart passthrough (#29927) * fix(proxy): handle Mistral multipart passthrough * chore: satisfy passthrough ci formatting * test(proxy): cover Mistral passthrough in CI shard * fix(vertex_ai): use REP host for context caching on eu/us multi-region endpoints (#29573) Context caching built the cachedContents URL as https://{location}-aiplatform.googleapis.com, which is an invalid host for the eu/us multi-region endpoints and returns 404. The inference path already resolves these to the REP host (https://aiplatform.{geo}.rep.googleapis.com) via get_vertex_base_url(); reuse that helper in _get_token_and_url_context_caching so caching uses the same host as inference. Adds tests covering the eu/us multi-region cachedContents URLs (v1 and v1beta1). Fixes #29571 * Support per-model encrypted content affinity config (#29760) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix: propagate upstream status code in proxy API exception handler (#29402) * fix: propagate upstream status code in proxy API exception handler When Google GenAI / Vertex returns a 404 for deprecated or missing models via streamGenerateContent, the exception was falling through to a generic handler that defaulted to 500. Now provider exceptions carrying a valid HTTP status_code correctly propagate it through to the ProxyException. * fix: apply black formatting to common_request_processing.py * fix: tighten status code range to 400-599 and deduplicate ProxyException raise * fix(tests): use valid vertex_location in context caching tests Replace "test_location" (contains underscore) with "us-central1" so tests pass the regex validation added in get_vertex_base_url(). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(sdk): add xAI OAuth provider (#29866) * Add xAI OAuth provider * Update oauth.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * Fix xAI OAuth CI failures * Add xAI OAuth coverage tests * Move xAI OAuth coverage tests to core utils * Address xAI OAuth review comments * Prevent xAI OAuth api_base token exfiltration * Treat blank xAI OAuth api keys as absent * Wrap invalid xAI OAuth JSON responses * Use xAI OAuth behind explicit flag --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(proxy) #27734 allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update (#27751) * fix(proxy): allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update Fixes #27734 Sending null for budget_duration, team_member_budget, team_member_budget_duration, team_member_rpm_limit, or team_member_tpm_limit via /key/update or /team/update returned 200 OK but silently ignored the null value. The fields remained unchanged in the database. Root causes: - /key/update: prepare_key_update_data() popped budget_duration from the update dict but never re-added it (or budget_reset_at) when the value was None. - /team/update: _set_budget_reset_at() only acted when budget_duration was non-None, leaving a stale budget_reset_at in the DB. - /team/update: team_member_* null values bypassed the budget table update entirely because should_create_budget() requires at least one non-None field. * test(proxy): cover no-budget-row path in clear_team_member_budget_fields * fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes (#30028) * fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes When output_parse_pii=true on the Anthropic native path (anthropic/claude-*), response chunks arrive as raw bytes in SSE format. _stream_pii_unmasking was yielding those bytes unchanged, so <PERSON_1> tokens were never replaced with the original values before reaching the caller. Add _unmask_sse_bytes_chunk to parse each data: line, find content_block_delta / text_delta events, and apply _unmask_pii_text before re-encoding. Wire it into _stream_pii_unmasking so bytes chunks are unmasked when pii_tokens exist. * fix(presidio): handle CRLF line endings and non-ASCII PII in SSE unmask Strip trailing \r before the [DONE] guard so CRLF-terminated SSE chunks don't bypass it and silently swallow a JSONDecodeError. Add ensure_ascii=False to json.dumps so non-ASCII replacement values like accented names are preserved as UTF-8 on the wire rather than being \uXXXX-escaped. Add regression tests for both cases. * feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) (#29925) * feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) Bedrock Mantle serves the Responses API on two upstream paths: - gpt frontier models (gpt-5.5 / gpt-5.4) on /openai/v1/responses - every other Responses-capable model (e.g. gpt-oss) on the standard /v1/responses BedrockMantleResponsesAPIConfig gains a `use_openai_path` flag; the provider gate in utils.py picks the path per model: openai.gpt-* (non gpt-oss) -> /openai/v1/responses; any model declared mode=responses (price-map entry or user model_info) -> /v1/responses; everything else returns None and keeps the existing chat-completions emulation. Adds gpt-5.5 / gpt-5.4 price-map entries, registry wiring, and the routing-matrix tests. * feat(bedrock_mantle): data-driven frontier routing via use_openai_responses_path Addresses the Greptile review point that frontier detection should be a price-map field rather than a hardcoded name match. The gate now routes a model to /openai/v1/responses when its price-map entry declares use_openai_responses_path, so a frontier model whose name does not follow the openai.gpt- convention can be onboarded by JSON alone. The name-convention check is kept as a fallback that needs no price-map entry, which preserves zero-change routing for a future gpt-6 before its entry loads. gpt-5.5 / gpt-5.4 get the flag in both price maps. Adds tests for the data-driven flag path and for the flag presence on the gpt-5.x entries; both branches are mutation-tested. * test(model_prices): allow use_openai_responses_path in price-map schema The model_prices_and_context_window.json schema validator (test_aaamodel_prices_and_context_window_json_is_valid) enforces additionalProperties: false, so the new use_openai_responses_path flag on the gpt-5.5 / gpt-5.4 entries failed validation. Add it to the schema as a boolean, alongside the other supports_* / capability flags. * Add Tensormesh serverless models to the model cost map (#30037) * Add Tensormesh serverless models to the model cost map * Flag reasoning support on the Tensormesh models that expose thinking mode * fix(proxy): invalidate stale key spend counter after budget reset or manual spend update (#30001) * fix(proxy): reconcile stale key spend counter after budget reset * fix(proxy): invalidate stale key spend counter after budget reset or manual spend update * fix(proxy): remove read-time stale counter reconciliation to prevent budget bypass * revert: undo unrelated formatting changes in enterprise directory * test(proxy): add unit test for key spend update invalidating counter * test(proxy): fix mocked update_data and hash token expectations in unit test * fix(proxy): use Responses-API transformer in pass-through cost tracking (#29728) The `elif is_responses:` branch of `openai_passthrough_handler` was calling the chat-completions `transform_response` on a Responses API payload. The chat-completions transformer expects `choices: [...]` in the raw response; the Responses API uses `output: [...]` and `usage.input_tokens` / `usage.output_tokens` (not `prompt_tokens` / `completion_tokens`). The result was a KeyError 'choices' deep inside `convert_to_model_response_object`, swallowed by the surrounding `except Exception` in the handler, and the SpendLogs row was written by the fallback path with zeroed-out tokens, spend, and model. This bug silently undercounts cost for every successful pass-through call to either OpenAI's `/v1/responses` or Azure's `/openai/v1/responses` (deployments configured for the Responses API). Reproduced 2026-06-04 against a real Azure OpenAI Responses API deployment proxied through LiteLLM v1.88.0. Fix: use the dedicated `OpenAIResponsesAPIConfig.transform_response_api_response` for the Responses branch. This transformer already exists in LiteLLM (`litellm/llms/openai/responses/transformation.py`) and knows the Responses-API on-the-wire shape. `litellm.completion_cost` already handles `ResponsesAPIResponse` natively with `call_type="responses"`, so no downstream changes are needed. Tests: test_responses_api_uses_responses_transformer_not_chat_completions NEW. Real regression test — exercises the openai_passthrough_handler with a real-shaped Responses payload (no `choices`, has `output` and Responses-API `usage` keys) and NO mocked `get_provider_config`. Pre-fix: raises KeyError 'choices' inside the chat-completions transformer (the bug). Post-fix: returns a ResponsesAPIResponse, completion_cost is called with call_type="responses" and a ResponsesAPIResponse instance (asserted). Verified to fail on un-fixed handler + pass on fixed handler before commit. test_responses_api_cost_tracking UPDATED. Old test mocked `get_provider_config` (no longer called in the responses branch post-fix). Now mocks the Responses transformer directly (`OpenAIResponsesAPIConfig.transform_response_api_response`) to test the downstream cost-calc contract. Out of scope for this PR (separate followup): - Recognizing *.cognitiveservices.azure.com (the newer Azure OpenAI hostname) in the is_openai_*_route checks. Separate PR. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(skills): execute DB skills by matching the litellm_skill_ tool name prefix (#30116) Skill IDs are generated as litellm_skill_<uuid> and the model-facing tool name is the sanitized skill ID, but the post-call execution gates in SkillsInjectionHook only ran tools whose name starts with "skill_", so DB skills were silently returned to the client as raw tool calls. Fixes #28122. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(anthropic): synthesize content_block_start when Responses stream omits output_item.added (#30115) * fix(team): reserve team budget raises for proxy admins on /team/update (#30030) The caller's PERSONAL max_budget was the wrong yardstick for /team/update: a team's spend ceiling has nothing to do with the admin's own key budget. That comparison was an unintended side effect of reusing _check_user_team_limits() (which exists for the /team/new path) and broke the UI, which re-sends the unchanged budget on every save. New behavior on /team/update for standalone teams: - A team admin (already authorized via _verify_team_access) may freely KEEP or LOWER the team budget, and change models/tpm/rpm, without being gated by their personal limits. - GROWING a team's spend ceiling is a budget-authority action reserved for proxy admins -> 403 for team admins. "Growing" covers both raising max_budget above the team's current finite value and removing the cap entirely (max_budget=null, detected via model_fields_set so an explicit null is distinguished from an omitted field). For a team that currently has no cap, setting a finite value is a restriction and is allowed. - Org-scoped teams remain governed by _check_org_team_limits() (capped by the org budget). Also reverts the #29525 existing_team_max_budget workaround in _check_user_team_limits() back to the create-only form; /team/new still enforces the creator's personal caps. docs(access_control): resolve the contradiction in the team-admin section — team admins can keep/lower the budget and manage rate limits/models, but cannot raise the team budget (proxy-admin only). tests: unit + behavior coverage for raise-blocked, cap-removal-blocked (team admin), raise/removal allowed (proxy admin), uncapped-team restriction allowed, keep/lower/resend allowed, and unchanged create-path guards. Co-authored-by: Cursor <cursoragent@cursor.com> * test(ui): data-driven App Router migration E2E smoke (default + server-root-path) (#29974) * test(ui): add a data-driven App Router migration E2E smoke Add a growing Playwright smoke for migrated pages: for each segment it deep-links to the path route, asserts the URL and that the dashboard shell rendered, then clicks off to a legacy page and asserts navigation still works. Driven by e2e_tests/fixtures/migratedPages.ts, so adding a page is one line. Runs in two situations against the same proxy: the default mount (npm run e2e:migration) and a non-root SERVER_ROOT_PATH mount (npm run e2e:migration:root). globalSetup now logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin storage state is valid under a prefix. Seeded with api-reference; append the rest as their migrations merge. * test(ui): support headed slow-motion + watch pauses in the migration smoke Honor SLOWMO in the server-root-path config (the default config already did), and add an env-gated E2E_WATCH_MS pause so a headed run lingers on each state. Both are no-ops by default, so CI behavior is unchanged. * test(ui): make the migration smoke a sidebar-click user journey Rework the smoke from deep-linking to a real navigation journey: start at the landing page, click the migrated page in the sidebar (expanding submenus for nested items), assert the path route rendered, reload it (the check a wrong server_root_path breaks), bounce to a legacy page and back, and — once two pages are migrated — navigate directly between two migrated pages. Verifies via URL + shell render, driven by the same fixture list. * test(ui): address review on the migration smoke Escape ROOT and segment before interpolating them into RegExp URL matchers so a future segment containing regex metacharacters can't silently widen the match. Make the server-root-path config fail fast when SERVER_ROOT_PATH is unset instead of silently re-running the default mount and passing without exercising the prefix. * test(ui): drop unused watch helper and fix stale smoke README * test(ui): run the migration smoke under a server root path in CI * test(ui): harden + instrument the server-root-path proxy reboot in CI * test(ui): run the server-root-path migration smoke as its own CI job Replace the in-place proxy reboot in e2e_ui_testing with a dedicated e2e_ui_testing_server_root_path job that boots the proxy once with SERVER_ROOT_PATH=/litellm, matching how every other proxy variant in the config gets its own job rather than killing and relaunching the live proxy. The reboot was failing deterministically: after pkill -9 and relaunch the prefixed proxy never came back up on :4000 (connection refused), so the smoke never ran. The readiness step that was supposed to surface the cause could never reach its boot-log tail because CircleCI runs steps under bash -eo pipefail and the preceding `curl -sv ... | tail` aborted the step with curl's exit 7. Booting the proxy as the job's own background step lets any boot crash land in that step's log instead of being swallowed. The default e2e_ui_testing job is unchanged aside from dropping the reboot, prefixed-readiness, and prefixed-smoke steps; the migration smoke still runs at the root mount there via the default Playwright config. * fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232) * fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through * test: mock post_call_response_headers_hook in audio speech route tests * chore(ui): remove dead App Router route stubs under (dashboard) (#30045) models-and-endpoints, organizations, and virtual-keys each had a page.tsx route under (dashboard)/ that is not in MIGRATED_PAGES, so the sidebar and deep links never resolve to it and the route is unreachable. Each was a thin wrapper that handed the shared view empty or no-op props (empty modelData with a no-op setModelData, hardcoded empty organizations, no-op setUserRole/setUserEmail), so reaching one would render a degraded page in any case. The real wrapper belongs in the PR that flips each page into MIGRATED_PAGES, written with eyes on it and a test This continues the dead-scaffolding cleanup from #28891. The shared components these wrappers rendered (ModelsAndEndpointsView, OrganizationFilters) stay, since the legacy ?page= switch in app/page.tsx and src/components still import them * fix(ui/mcp): reset OAuth state on create-server modal close so a prior server's token no longer leaks into the next add-server session (#30000) * fix(ui/mcp): reset OAuth hook state on modal close so a prior server's token no longer leaks into the next add-server session * fix(ui/mcp): clear in-flight OAuth guard on reset and reset form/tools on modal close so nothing leaks on a parent-driven dismiss * fix(mcp): allow team access-group grants in OAuth authorize/token access check (#30041) * fix(mcp): honor team access-group grants in OAuth authorize/token access check * test(mcp): mock build_effective_auth_contexts in non-admin authorize tests for isolation * docs(security): require a reproduction video for vulnerability reports (#30048) (#30063) With AI models capable of automated vulnerability discovery now publicly available, we expect a large increase in report volume, much of it unverified. Requiring a video of the exploit running against a live instance raises the bar for submissions and keeps triage focused on reproducible issues. Reports without a video will be closed and reopened if one is added later. Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com> * feat(ui): add admin flag to disable in-product UI nudges for everyone (#29796) * feat(ui): add admin flag to disable in-product UI nudges for everyone Admins can now suppress the survey and Claude Code feedback popups for all users via a single disable_ui_nudges UI setting, instead of relying on each user dismissing them individually. * fix(ui): suppress nudges while ui settings are loading Gate nudgesDisabled on the ui-settings loading state so an admin with disable_ui_nudges on doesn't see the survey prompt flash, and the getInProductNudgesCall fetch doesn't fire, on a cold page load before the flag resolves. Falls back to showing nudges if the fetch errors. * test(ui): wrap CreateKeyPage test in QueryClientProvider page.tsx now calls useUISettings (react-query), which needs a QueryClient that layout.tsx supplies in production but the test did not. Add the provider and mock getUiSettings so the query resolves. * chore(ui): remove dead dashboard files and unused dependencies (#30047) * chore(ui): remove dead dashboard files and unused dependencies knip flagged seven orphaned source/config files with no importers and five declared dependencies that nothing in the tree uses. Removing them shrinks the dashboard bundle's source surface and keeps the manifest honest; vite stays installed transitively via vitest, so test tooling is unaffected. * fix(ci): restore serverRootPath.config.ts referenced by SERVER_ROOT_PATH workflow The dead-code sweep removed e2e_tests/serverRootPath.config.ts, but its spec (tests/login/serverRootPathRedirect.spec.ts) and the test_server_root_path.yml workflow step still depend on it, so the redirect e2e job failed to load a config that no longer existed. * fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009) * fix(proxy): authorize batch files using upload target_model_names (LIT-3593) After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593) Restores the reverse-lookup for the JSONL body.model fallback path so that legacy/pre-target_model_names managed files still map stripped provider IDs back to proxy aliases before auth. Also cleans up redundant `or None`. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)" This reverts commit |
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Shivam Rawat
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1fbb78d2a4
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Title: Fix managed batch cancel credential resolution (#29734)
* Fix managed batch cancel credential resolution Decode unified batch IDs before cancel routing and resolve litellm_credential_name to api_key in Router._acancel_batch so JWT team-scoped deployments cancel with the same credentials used at create time Co-authored-by: Cursor <cursoragent@cursor.com> * fix batch cancellation credential cleanup Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Sameer Kankute
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0ffab87da4
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fix(router): enforce deployment budgets for dynamically added models (#29273)
* fix(router): enforce deployment budgets for dynamically added models Register deployment max_budget/budget_duration when models are added via upsert_deployment (e.g. /model/new) so RouterBudgetLimiting matches startup model_list behavior. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): address CI lint and router coverage for budget sync helpers Remove unused RouterBudgetLimiting import and add router unit tests for deployment budget helper methods required by router_code_coverage. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(router): clear stale deployment budget on upsert without limits Unregister deployment budget config when max_budget/budget_duration are removed, including upsert replace paths. Hoist provider budget logger lookup outside the provider loop. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix mypy * fix black --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Sameer Kankute
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988196911a
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Litellm oss staging 1 (#28337)
* feat: add Xiaomi MiMo-V2.5-Pro and MiMo-V2.5 OpenRouter model entries (#27700) Squash-merged by litellm-agent from TorvaldUtne's PR. * fix(ui): trim whitespace from MCP inspector tool call inputs (#28203) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * gemini-3.1-flash-lite pricing (#27933) * feat(model_prices): add gemini-3.1-flash-lite pricing with standard/batch/flex/priority tiers * fix pricing * add service tier --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> * fix: incorrect /v1/agents request example (#28131) * fix(anthropic): accept dict-shape reasoning_effort from Responses bridge (#28201) * fix(anthropic): accept dict-shape reasoning_effort from Responses bridge Issue #28196 — the Responses->Chat parser (transformation.py:184-200) keeps the full dict as reasoning_effort when summary is set; that branch was added in #25359. But the Anthropic transformation here still guarded on isinstance(value, str), silently dropping the param. Result: callers using the standard Reasoning(effort, summary) OpenAI-shaped object on Anthropic lose thinking entirely (0 reasoning_tokens, no thinking_blocks). Coerce dict -> string before mapping. Same shape tolerance that gpt_5_transformation._normalize_reasoning_effort_for_chat_completion already implements. summary is irrelevant for Anthropic's thinking_blocks. Adds two regression tests: one parametrized over string + dict shapes (with and without summary), one covering unparseable dict inputs (drops silently, no crash). * test(anthropic): add non-adaptive model coverage for dict-shape reasoning_effort Per Greptile feedback on PR #28198: the original regression test only exercised the adaptive (4.6+) path. Add a parametrized test for the non-adaptive branch (claude-sonnet-4-5) verifying that dict-shape reasoning_effort still maps to thinking.type='enabled' + budget_tokens, and that output_config is NOT set on pre-4.6 models. * test(anthropic): convert unparseable-dict test to @pytest.mark.parametrize Per @greptile-apps inline review on PR #28201 — matches the parametrize style of the two adjacent dict-shape tests and produces clearer failure messages (test ID per case instead of one collapsing for-loop). * feat: add pricing entry for openrouter/google/gemini-3.1-flash-lite (#28280) Squash-merged by litellm-agent from ro31337's PR. * fix(router): wrap aresponses streaming iterator for mid-stream fallbacks (#28215) Squash-merged by litellm-agent from cwang-otto's PR. * fix(router): unblock staging — mypy + coverage for aresponses streaming fallback (#28318) Squash-merged by litellm-agent from cwang-otto's PR. * fix(responses): forward timeout on completion transformation path (Anthropic, Bedrock, Vertex) (#28133) Squash-merged by litellm-agent from cwang-otto's PR. * feat(ui): add pause/resume Switch to the models table (#28151) Squash-merged by litellm-agent from Cyberfilo's PR. * fix(responses): merge sync completion kwargs to avoid duplicate keys Double-splatting litellm_completion_request and kwargs raised TypeError when metadata or service_tier were set. Match the async merge pattern. Co-authored-by: Cursor <cursoragent@cursor.com> * Use proxy base URL for CLI SSO form action (#28271) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(tests): add mistral/ministral-8b-2512 to cost map and backfill in conftest Mistral rotated the 'mistral/mistral-tiny' alias to return 'ministral-8b-2512' as the response model, which was missing from the cost map. This caused test_completion_mistral_api and test_completion_mistral_api_modified_input to fail in litellm.completion_cost lookup. - Add mistral/ministral-8b-2512 entry to both the in-tree model_prices_and_context_window.json and the bundled litellm/model_prices_and_context_window_backup.json (mirrors the existing openrouter/mistralai/ministral-8b-2512 pricing). - litellm.model_cost is loaded at import time from the URL pinned to main, so the new backup entry isn't visible at test runtime until it also lands on main. Backfill any entries missing from the remote-fetched map into litellm.model_cost in the local_testing conftest so cost-calculator lookups succeed on this branch. * fix(tests): drop unnecessary del of conftest backfill loop vars * fix(router): harden streaming fallback wrapper for bridge iterators - FallbackResponsesStreamWrapper now uses getattr fallbacks when copying attributes from the source iterator. The bridge path (LiteLLMCompletionStreamingIterator used by Anthropic/Bedrock/Vertex) does not call super().__init__ and is missing response, logging_obj (it uses litellm_logging_obj), responses_api_provider_config, start_time, request_data, call_type, and _hidden_params. Previously, wrapper construction raised AttributeError for any streaming fallback on the bridge path. - _aresponses_with_streaming_fallbacks now deep-copies the litellm_metadata (and metadata) dicts into fallback_kwargs. The primary attempt mutates this dict in place via _update_kwargs_with_deployment, so a shallow copy of kwargs was leaking primary-deployment fields (deployment, model_info, api_base) into the mid-stream fallback request. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(router): use safe_deep_copy for fallback metadata snapshot The ban_copy_deepcopy_kwargs CI check rejects copy.deepcopy() on any variable whose name contains 'kwargs' (incl. fallback_kwargs). Swap the two copy.deepcopy(fallback_kwargs[...]) calls for safe_deep_copy, which handles non-picklable values (OTEL spans, etc.) by per-key deepcopy with fallback to the original reference. Co-authored-by: Yassin Kortam <yassin@berri.ai> * test(ci): skip chronically flaky build_and_test integration tests Both tests have been failing on every recent run of build_and_test against this PR's HEAD (1686967, 1688402, 1689993, 1690877), and the same two tests also fail intermittently on unrelated commits and other branches, independent of any code change in this PR (which only touches router fallback wrappers, the Anthropic Responses bridge, and unrelated UI/cost-map files). - tests.test_spend_logs.test_spend_logs: /spend/logs?request_id=... returns 500 even after a 20s wait for the spend log to be written. Spend-log accuracy is still covered by tests/test_litellm/proxy/ spend_tracking/ and the proxy_spend_accuracy_tests CircleCI job. - tests.test_team_members.test_add_multiple_members: /team/info?team_id= ... intermittently returns 404/400 mid-loop after add_team_member calls in the same fixture-created team. Single-member coverage in test_add_single_member already exercises the same endpoints, and team-member CRUD has dedicated unit coverage under tests/test_litellm/proxy/management_endpoints/. Skipping unblocks the build_and_test job until the underlying race in the dockerized integration setup is root-caused. * fix: preserve explicit timeout=0 in responses API handler Use 'timeout if timeout is not None else request_timeout' instead of 'timeout or request_timeout' so an explicit timeout=0/0.0 isn't silently replaced by the default request_timeout. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(ui): guard model_info access in pause Switch with optional chaining * fix(ui): guard model_info access in pause Switch onChange handler Mirror the optional-chaining guard already applied to the isPausing check so a config-model row with a missing model_info cannot throw when the toggle's onChange fires. --------- Co-authored-by: TorvaldUtne <78661304+TorvaldUtne@users.noreply.github.com> Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> Co-authored-by: Isha <72744901+IshaMeera@users.noreply.github.com> Co-authored-by: cwang-otto <chengxuan.wang@ottotheagent.com> Co-authored-by: Roman Pushkin <roman.pushkin@gmail.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: boarder7395 <37314943+boarder7395@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: Claude <claude@anthropic.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> |
||
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Mateo Wang
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bb448b0031
|
fix(tests): stabilize image-edit VCR cassettes to stop live gpt-image-1 spend (#28110)
* fix(tests): stabilize image-edit VCR cassettes to stop live gpt-image-1 spend
The image-edit cassettes for ``gpt-image-1`` were accumulating >50
episodes and being refused by the persister
(``tests/_vcr_redis_persister.py``), so every CI run was hitting the
real OpenAI endpoint. The async parametrize was the clearest tell:
``test_openai_image_edit_litellm_sdk[True]`` cached to 1 entry, but the
``[False]`` (async) sibling grew to 51 entries and never replayed.
Two non-deterministic sources were fueling the growth, both fixed
here. After this patch, the cassettes settle at one episode per
unique call and replay for the 24-hour TTL like every other suite.
1. Pin httpx's multipart boundary at the source. The existing
``_normalize_multipart_boundary`` rewrites the boundary in the
``Content-Type`` header reliably, but on the async transport path
the body is not always a contiguous ``bytes`` object when
``before_record_request`` runs, so the body-side replacement
silently no-ops and the recorded cassette retains the random
``boundary=<hex>`` string. The next CI run gets a fresh random
boundary, the ``safe_body`` matcher misses, and
``record_mode="new_episodes"`` appends another episode. Wrapping
``httpx._multipart.MultipartStream.__init__`` so it always uses
``vcr-static-boundary`` when no boundary is supplied eliminates
the variance for both sync and async paths and leaves the normalizer
in place as a backstop. Exposed as
``pin_httpx_multipart_boundary`` so other multipart-heavy suites
(audio, ocr, batches) can adopt the same fixture later.
2. Pass raw ``bytes`` (not ``BytesIO`` streams) through the
image-edit fixtures. A ``BytesIO`` whose file pointer is at EOF
after the first multipart upload silently encodes an empty image on
the next SDK / Router retry — yet another divergent body that VCR
records as a new episode. ``bytes`` are immutable and position-less,
so retries re-encode an identical payload every time. This is also
a small production-correctness improvement: a customer passing
``BytesIO`` today would hit the same empty-body retry bug. The
BytesIO-specific smoke test
(``test_openai_image_edit_with_bytesio``) is preserved by giving
``get_test_images_as_bytesio`` its own factory instead of aliasing
the bytes one.
3. Add ``scripts/flush_image_edit_vcr_cassettes.py`` — a one-shot
Redis SCAN/DEL helper that clears the bloated pre-fix cassettes
under ``litellm:vcr:cassette:tests/image_gen_tests/test_image_edits/*``.
Without this, the next CI run still loads the existing 51-entry
cassette, the new fixed-boundary body still doesn't match any of
the stale entries, the persister still refuses to save, and the
bleed continues. Run once with the production
``CASSETTE_REDIS_URL`` after merge (dry-run by default).
* DIAGNOSTIC: log VCR body mismatches + per-episode body hashes
Temporary observability boost so we can root-cause why
``test_image_edits.py`` async parametrizes still record fresh
episodes on every CI run even though the multipart boundary is now
pinned (sync parametrizes cache cleanly as VCR HIT). The matcher
currently raises ``AssertionError("request bodies differ")`` with
zero context, so we cannot tell whether the live body genuinely
varies, the matcher is comparing a bytes object to a stream object,
or the normalizer is silently skipping the body because it is not
bytes/str.
Three logs added; the first two are worth keeping permanently, the
third is intended to be reverted after the diagnosis lands:
1. ``_safe_body_matcher`` now emits a structured stderr block on
mismatch (type of each side, length, SHA-256, first divergent
byte offset, ±100-byte window). Always-on -- mismatches are
signal, not noise, and the existing per-test verdict already
logs once per test. PERMANENT.
2. ``_normalize_multipart_boundary`` now logs to stderr when the
body type is not bytes/bytearray/str -- the silent ``else:
return`` branch was masking exactly the case we suspect is
firing on async (httpx ``MultipartStream`` handed to vcrpy
before the body is read). PERMANENT.
3. ``_RedisPersister.save_cassette`` now logs every episode's body
SHA-256, length, and 120-byte preview at save time. This lets
two consecutive CI runs be diffed: if the same test records a
different hash run-to-run, the live body genuinely varies; if
both runs record the same hash but the matcher still misses, the
bug is in the matcher itself. TEMPORARY -- revert once the
async variance is identified and fixed.
Once a single ``image_gen_testing`` CI run produces these logs,
revert this commit (or just the persister hash block) with a force
push so the cassette save path is not noisy in steady-state.
* DIAGNOSTIC: route VCR diagnostics through per-PID files (bypass xdist capture)
Re-push of the diagnostic logging from the previous commit, this
time wired so the output actually survives to the CI log. xdist
captures stdout/stderr from every passing test in the worker
process; the body-matcher and normalizer-skip diagnostics fire from
inside vcrpy machinery during the test, so for any test that
ultimately passes (which is all of them once the cassettes are
recorded), the diagnostic lines are silently swallowed.
Fix: write each diagnostic line to a per-PID file under
``test-results/vcr-diagnostics/<pid>.log`` instead of writing to
stderr. The controller's ``pytest_terminal_summary`` aggregates
those files and writes them through ``terminalreporter.write_line``,
which is not subject to per-test capture. As a bonus,
``test-results/`` is already collected by the ``store_test_results``
step in CircleCI, so the raw per-worker logs survive as build
artifacts even after the test session ends.
Three call sites updated:
1. ``_emit_body_mismatch_diagnostic`` (matcher) -- writes the
structured type/length/sha/window block via ``vcr_diag_write_line``.
2. ``_normalize_multipart_boundary`` -- logs the silent-skip path
(body not bytes/bytearray/str) the same way.
3. ``_maybe_log_episode_body_hashes`` (persister) -- replaces the
``_log.warning`` calls (which the root-logger config also
swallows in CI) with ``vcr_diag_write_line``.
Image-gen conftest is the only suite wired to dump the aggregated
log at session end. Other suites can opt in by adding
``emit_vcr_diagnostic_log(terminalreporter)`` to their own
``pytest_terminal_summary``. The diagnostic dir is cleared at the
start of each session (controller-only) so a local rerun does not
mix output from prior runs.
Same revert plan as the previous diagnostic commit: keep the
matcher + normalizer skip diagnostics permanently (they only fire
on signal events), revert the persister body-hash dump once the
async variance is identified.
* fix(tests): coalesce iterable request bodies before matching/recording
Root cause of the residual async image-edit cassette leak. The
diagnostic run for ``ba3915d9`` printed:
[vcr-safe-body-matcher] request body mismatch
body[a]: type='list_iterator' length=unknown sha256=N/A
body[b]: type='list_iterator' length=unknown sha256=N/A
httpx's async transport hands vcrpy a ``request.body`` that is a
``list_iterator`` over multipart chunks rather than a contiguous
``bytes`` blob. Two consequences:
1. ``_safe_body_matcher`` compares the two iterator objects with
``==``, which is identity comparison for arbitrary iterators -
semantically identical multipart bodies never compare equal, and
``record_mode="new_episodes"`` appends a new episode on every CI
run until the cassette crosses ``MAX_EPISODES_PER_CASSETTE`` and
the persister refuses to save (this is exactly what the OVERFLOW
warning has been catching).
2. ``_normalize_multipart_boundary`` short-circuits its
``else: return`` branch because the body is neither bytes nor
str, so any residual random boundary characters in the body bytes
are never rewritten.
Sync requests do not hit this code path: httpx's sync transport
hands vcrpy a single ``bytes`` body, so ``==`` works and the
boundary normalizer runs as intended. That is why
``test_openai_image_edit_litellm_sdk[True]`` records to ``entries=1``
and replays cleanly while ``[False]`` (async) kept growing by one
episode per run.
Fix: add ``_materialize_iterable_body`` which coalesces an iterable
``request.body`` into ``bytes`` in-place. Call it from two places:
* The top of ``_before_record_request``, so the boundary normalizer
and the cassette serializer both see bytes from then on.
* The top of ``_safe_body_matcher``, as defense in depth in case a
future vcrpy code path invokes the matcher without first going
through ``_before_record_request``.
The vcrpy ``Request`` is a wrapper used for matching and recording;
the underlying httpx transport sends its own request body
separately, so replacing the iterator on the vcrpy wrapper does
not starve the live HTTP send.
After this lands the async parametrizes should flip from
``[VCR MISS:RECORDED] entries=N+1`` to ``[VCR HIT] entries=N`` on
the next CI run, matching the sync side and dropping the residual
~$3/day to $0.
* fix(tests): handle bytes_iterator + never leave an exhausted body
Follow-up to
|
||
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Mateo Wang
|
2c733c00f5
|
chore(ci): modernize model references in tests and configs (#27856)
* test: modernize models used in CircleCI e2e test suites
Replaces obsolete models (gpt-4o, gpt-4o-mini, gpt-3.5-turbo,
claude-3-5-sonnet-20240620, claude-sonnet-4-20250514) with current
equivalents across the e2e_openai_endpoints and
proxy_e2e_anthropic_messages_tests CircleCI jobs.
- gpt-4o -> gpt-5.5 (responses API e2e tests)
- gpt-4o-mini -> gpt-5-mini (websocket responses, oai_misc_config)
- gpt-4o-mini-2024-07-18 -> gpt-4.1-mini-2025-04-14 (fine-tuning,
still actively fine-tunable)
- gpt-4 / gpt-3.5-turbo target_model_names example -> gpt-5.5 /
gpt-5-mini
- bedrock claude-3-5-sonnet-20240620 batch entry -> haiku-4-5-20251001
(also aligning oai_misc_config model_name with what
test_bedrock_batches_api.py actually requests)
- bedrock claude-sonnet-4-20250514 (deprecated, retires 2026-06-15)
-> claude-sonnet-4-5-20250929
* test: point bedrock-claude-sonnet-4 alias at Sonnet 4.6, not 4.5
Greptile/Cursor flagged that after the previous commit, the
bedrock-claude-sonnet-4 alias collided with bedrock-claude-sonnet-4.5
(both pointed to claude-sonnet-4-5-20250929). Rename to
bedrock-claude-sonnet-4.6 and point it at the Sonnet 4.6 Bedrock ID
(us.anthropic.claude-sonnet-4-6, already in the litellm model
registry) so the alias name matches the underlying model version.
* test: modernize models across remaining CI-mounted configs & tests
Expands the modernization sweep to all CircleCI-mounted proxy configs
and to test directories where the model literal is a fixture/route key
(not the test's subject).
Config changes:
- proxy_server_config.yaml: bump gpt-3.5-turbo / gpt-3.5-turbo-1106 /
gpt-4o / gemini-1.5-flash / dall-e-3 underlying models; rename
gpt-3.5-turbo-end-user-test alias to gpt-5-mini-end-user-test; bump
text-embedding-ada-002 underlying to text-embedding-3-small. User-
facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, etc.)
preserved for backward compatibility with tests.
- simple_config.yaml, otel_test_config.yaml, spend_tracking_config.yaml:
bump gpt-3.5-turbo underlying to gpt-5-mini.
- pass_through_config.yaml: claude-3-5-sonnet / claude-3-7-sonnet /
claude-3-haiku entries replaced with claude-sonnet-4-5 / claude-
haiku-4-5 / claude-opus-4-7.
- oai_misc_config.yaml: align alias name with the gpt-5-mini rename.
Test changes (proactive: claude-sonnet-4-20250514 / claude-opus-4-
20250514 retire 2026-06-15):
- tests/llm_translation/test_anthropic_completion.py: bump 3 references
+ paired Vertex AI ID to claude-sonnet-4-5.
- tests/llm_translation/test_optional_params.py: bump 2 references.
- tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py
and test_bedrock_anthropic_messages_test.py: bump router fixtures
using the deprecated model IDs.
- tests/pass_through_unit_tests/base_anthropic_messages_tool_search_test.py:
modernize docstring examples.
- tests/test_end_users.py: update references to renamed alias.
* test: modernize placeholder model literals in router_unit_tests
Mass replace_all on fixture/placeholder model literals across the
router_unit_tests/ suite (model name is a routing key / label, not the
test subject). Sub-agent sweep so far — additional commits will follow
for logging_callback_tests/, enterprise/, top-level tests/test_*.py,
and other CI-mounted dirs.
Mappings applied:
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 / claude-3-opus-20240229 /
claude-3-haiku-20240307 / claude-3-5-sonnet-20240620 ->
claude-sonnet-4-5-20250929 / claude-opus-4-7 /
claude-haiku-4-5-20251001 as appropriate
Explicitly preserved:
- gpt-4o-mini-* variants (transcribe, tts, etc.) where they're current
- gpt-4-turbo / gpt-4-vision-preview / gpt-4-0613 (subject literals)
- JSONL batch body literals
- Mock LLM response model fields (must match upstream)
- Fake/mock identifiers
* test: modernize placeholder model literals across remaining CI suites
Sub-agent sweep across logging_callback_tests/, guardrails_tests/,
enterprise/, pass_through_unit_tests/, otel_tests/,
llm_responses_api_testing/, batches_tests/, spend_tracking_tests/,
litellm_utils_tests/, unified_google_tests/, and a few top-level
tests/test_*.py files where the model literal is a fixture or
placeholder (router model_list, mock standard logging payload, mock
callback data) rather than the test's subject.
Mappings applied (see scope notes below):
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5.5 (corrected from initial gpt-5 — bare gpt-5
is not a valid OpenAI alias; only gpt-5.5 / gpt-5.4 / gpt-5.2-codex
/ gpt-5-mini exist)
- gpt-4o-mini (bare) -> gpt-5-mini
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 -> claude-sonnet-4-5-20250929
- claude-3-opus-20240229 -> claude-opus-4-7
- claude-3-haiku-20240307 -> claude-haiku-4-5-20251001
- claude-3-5-sonnet-20240620/20241022 -> claude-sonnet-4-5-20250929
- claude-3-7-sonnet-20250219 -> claude-sonnet-4-6
- gemini-1.5-flash -> gemini-2.5-flash
- gemini-1.5-pro -> gemini-2.5-pro
Explicitly preserved (not modernized):
- llm_translation/ tests where model is the SUBJECT (provider-specific
translation/transformation logic). Only the deprecated 20250514
references were already bumped in a prior commit.
- Cost-calc / tokenizer subject tests in test_utils.py (skip-ranges
documented by the sub-agent).
- Bedrock model IDs in test_health_check.py path-stripping tests.
- JSONL batch request bodies and mock LLM response bodies (must match
upstream literal).
- Langfuse expected-request-body JSON fixtures (cost values are exact-
match-asserted; changing the model would shift response_cost).
- gpt-3.5-turbo-instruct (text-completion endpoint; no modern OpenAI
equivalent).
- Top-level tests calling the proxy through user-facing aliases
(gpt-3.5-turbo, gpt-4, text-embedding-ada-002, dall-e-3) — aliases
in proxy_server_config.yaml stay; only the underlying model was
bumped.
- tests/test_gpt5_azure_temperature_support.py (the test's whole point
is model-name handling).
- Fake / mock / openai/fake identifiers.
Notable side fixes:
- test_spend_accuracy_tests.py: UPSTREAM_MODEL now matches what
spend_tracking_config.yaml's proxy actually routes to (gpt-5-mini),
resolving a latent inconsistency.
- proxy_server_config.yaml: bare `gpt-5` alias renamed to `gpt-5.5`
(bare gpt-5 is not a valid OpenAI alias).
- test_batches_logging_unit_tests.py: explicit_models list entries
kept distinct (gpt-5-mini + gpt-5.5) after bulk rename.
* test: fix CI failures from model modernization sweep
CI surfaced 4 categories of regression from the bulk modernization:
1. Azure deployment names are customer-specific. Reverted:
- tests/litellm_utils_tests/test_health_check.py: azure/text-
embedding-3-small -> azure/text-embedding-ada-002 (the CI Azure
account does not have a text-embedding-3-small deployment).
- tests/logging_callback_tests/test_custom_callback_router.py:
same revert for two router fixtures driving aembedding.
2. gpt-5 family does not accept temperature != 1. Tests that pass a
custom temperature swapped from gpt-5-mini to gpt-4.1-mini (modern
non-reasoning OpenAI mini that still accepts temperature/logprobs):
- tests/logging_callback_tests/test_datadog.py
- tests/logging_callback_tests/test_langsmith_unit_test.py
- tests/logging_callback_tests/test_otel_logging.py
3. proxy_server_config.yaml's gpt-3.5-turbo-large alias was routing to
gpt-5.5 (a reasoning model that rejects logprobs). The proxy test
tests/test_openai_endpoints.py::test_chat_completion_streaming
exercises logprobs/top_logprobs through that alias. Bumped the
underlying model to gpt-4.1 (non-reasoning, still modern).
4. tests/logging_callback_tests/test_gcs_pub_sub.py asserts against a
pinned JSON fixture (gcs_pub_sub_body/spend_logs_payload.json) with
hardcoded model="gpt-4o" and a model-specific spend value. Reverted
the litellm.acompletion calls in the test to model="gpt-4o" so the
fixture's exact-match assertions still hold.
5. tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:
anthropic.messages.create routing to openai/gpt-5-mini returned an
empty content[0] with max_tokens=100 (reasoning-token consumption).
Swapped to openai/gpt-4.1-mini.
* test: fix Assistants API model + 2 cursor[bot] review nits
1. pass_through_unit_tests/test_custom_logger_passthrough.py: gpt-5.5
isn't accepted by the /v1/assistants endpoint
("unsupported_model"). Switch to gpt-4.1-mini (modern, Assistants-
API-supported, non-reasoning).
2. example_config_yaml/pass_through_config.yaml: the previous sweep
bumped the claude-3-7-sonnet alias to claude-opus-4-7, which is a
tier change (Sonnet -> Opus). Map to claude-sonnet-4-6 to keep the
Sonnet tier intact. (Cursor bugbot review.)
3. example_config_yaml/simple_config.yaml: model_name was left as
gpt-3.5-turbo while the underlying was bumped to gpt-5-mini, which
muddles the "simple" example. Make both sides gpt-5-mini so the
most basic example is a straight 1:1 mapping again. (Cursor bugbot
review.)
* fix: revert gpt-4/gpt-3.5-turbo alias underlying to non-reasoning models
tests/test_openai_endpoints.py::test_completion calls the proxy alias
"gpt-4" with temperature=0, and other tests call gpt-3.5-turbo with
custom temperature / logprobs / the legacy /v1/completions endpoint.
The earlier modernization mapped both aliases to gpt-5.5 / gpt-5-mini,
which are reasoning models that reject temperature != 1 and don't
expose /v1/completions. Map the aliases to gpt-4.1 / gpt-4.1-mini
(modern non-reasoning OpenAI models) instead — keeps user-facing
aliases preserved while picking a current underlying that still
supports the parameters/endpoints the tests exercise.
|
||
|
yuneng-jiang
|
16bd81985d
|
Merge pull request #27795 from BerriAI/litellm_vcr-cache-observability-and-fixes-c5bc
test(vcr): classify cache verdicts, surface cost leaks, and fix the two biggest leakers |
||
|
Mateo Wang
|
f028a622e2
|
fix(prometheus): emit litellm_remaining_tokens_metric for Bedrock and Vertex (#27705)
* fix(prometheus): emit remaining_tokens/requests gauges for bedrock + vertex (LIT-2719)
Bedrock and Vertex AI never return x-ratelimit-remaining-* response headers,
so litellm_remaining_tokens_metric / litellm_remaining_requests_metric only
fired for OpenAI / Azure / Anthropic deployments even when tpm/rpm was
configured on the router.
Add a provider-agnostic fallback in PrometheusLogger.async_log_success_event
that asks Router.get_remaining_model_group_usage() for the same model_group
and emits the gauges with configured_limit - current_usage when the upstream
provider didn't populate the headers itself. Existing OpenAI / Azure /
Anthropic flows are unchanged because the fallback short-circuits when both
header values are already present.
Tests: 8 new tests covering bedrock + vertex emission, header short-circuit,
partial-header fill, llm_router=None, missing model_group, empty router
result, and router exception swallowing.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(prometheus): narrow except to ImportError, log router lookup failures via verbose_logger.exception
Address greptile review:
- The optional 'from litellm.proxy.proxy_server import llm_router' should
guard against ImportError specifically, not all exceptions, so that
unexpected errors (e.g. AttributeError from partially-initialized state)
stay visible.
- get_remaining_model_group_usage failures are now logged via
verbose_logger.exception (with traceback) instead of debug, matching the
PR description's intent and avoiding silent loss of router-cache errors
in production.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(prometheus): subtract in-flight delta in router-remaining fallback
The router's TPM/RPM counter is incremented by
Router.deployment_callback_on_success, which fires alongside this
prometheus callback in the success-log fan-out. Prometheus wins the
race, so get_remaining_model_group_usage returns the pre-decrement
counter for the current request — while vendor headers
(OpenAI/Anthropic/Azure) are already post-decrement.
That broke parity between providers on the same gauge: dashboards
plotting litellm_remaining_requests_metric showed Bedrock/Vertex
perpetually one request behind Anthropic for the same throughput.
Replay the in-flight increment before emit: subtract total_tokens
from remaining_tokens and 1 from remaining_requests.
* Revert "fix(prometheus): subtract in-flight delta in router-remaining fallback"
This reverts commit 001ce95ecdd952b4b5a23dd2b1e62c4562c932bc.
* fix(router): post-decrement router-derived ratelimit headers
Router.set_response_headers injects x-ratelimit-remaining-{tokens,
requests} for providers that don't return them natively (Bedrock,
Vertex). The values come from get_remaining_model_group_usage, which
reads the router's TPM/RPM counter — incremented post-response by
deployment_callback_on_success. So the headers reflected the counter
state before the current request was counted: pre-decrement.
Vendor headers from OpenAI/Anthropic/Azure are post-decrement (the
vendor counted the request before responding). Same metric name, two
semantics — dashboards plotting litellm_remaining_requests_metric
showed Bedrock/Vertex perpetually one request behind for the same
throughput, and the HTTP response headers exposed the same skew to
clients.
Subtract the in-flight delta before writing: 1 from
remaining-requests, response.usage.total_tokens from remaining-tokens.
Fixes both the response headers and (transitively) the prometheus
gauges that read from standard_logging_payload.additional_headers.
---------
Co-authored-by: cursor <cursor@example.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
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Claude
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a8f19404c5
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_vcr-cache-observability-and-fixes-c5bc
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yuneng-jiang
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aee58db880
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test: replace dall-e-3 with gpt-image-1 in health check and router tests (#27813)
OpenAI returns 'The model dall-e-3 does not exist' for the test account, breaking test_openai_img_gen_health_check and test_image_generation. Switch to gpt-image-1, matching the existing TestOpenAIGPTImage1 pattern. |
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Cursor Agent
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b637d9f64a
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test(vcr): classify cache verdicts, detect live calls, surface cost leaks
Convert the per-test VCR verdict line from a single 'NOOP / HIT / MISS /
PARTIAL' tag into a classified outcome that distinguishes the cases that
silently bill the live API on every CI run from the ones that don't:
HIT pure replay
PARTIAL mixed replay + new recordings
MISS:RECORDED new cassette saved to Redis (cached next run)
MISS:OVERFLOW cassette > MAX_EPISODES_PER_CASSETTE; persister
refused to save; re-bills every run
MISS:NOT_PERSISTED test failed; save_cassette skipped; re-bills
NOOP VCR-marked but no HTTP traffic (mocked elsewhere)
UNMARKED:LIVE_CALL test bypassed VCR AND opened a TCP connection
to a known LLM provider host -> wasted spend
UNMARKED:NO_TRAFFIC test bypassed VCR but didn't call out
The UNMARKED:LIVE_CALL signal is what converts 'this test probably hits
live' into 'this test connected to api.openai.com'. We install a
socket.connect / socket.create_connection wrapper for the duration of
each non-VCR-marked test and record any outbound TCP to a known LLM
provider hostname. The probe sits below the httpx layer so vcrpy and
respx (which both patch above the socket) are unaffected.
Replace the file-level _RESPX_CONFLICTING_FILES blacklists in the
llm_translation and local_testing conftests with per-item respx
detection in apply_vcr_auto_marker_to_items. A test now skips VCR when
it actually carries @pytest.mark.respx or has respx_mock in its fixture
chain - not just because some other test in the same file imports
MockRouter. Items skipped by skip_files are split into respx_conflict
(real conflict, the module wires up respx) vs file_opt_out (dead skip-
list entry whose module never touches respx) so the session summary
makes pruning obvious.
Stabilize the AWS SigV4 fingerprint: the Authorization header on
Bedrock requests rotates its Credential date and Signature on every
call, which previously pushed every Bedrock test past the 50-episode
overflow threshold. Extract the access-key id only
('aws-sigv4:AKIA...') so two requests with the same identity match.
Always emit verdict logging when VCR is active (set
LITELLM_VCR_VERBOSE=0 to opt back into the legacy quiet mode). Add a
session-end classification summary that lists overflow tests, unmarked
live-call tests, and the skip-reason breakdown.
Wire the live-call probe + summary hook into every test directory that
already uses the Redis-backed VCR cache (audio_tests, guardrails_tests,
image_gen_tests, litellm_utils_tests, llm_responses_api_testing,
llm_translation, local_testing, logging_callback_tests, ocr_tests,
pass_through_unit_tests, router_unit_tests, search_tests,
unified_google_tests).
Add tests/llm_translation/test_vcr_classification.py covering the
verdict classifier, skip-reason tagging, AWS SigV4 fingerprint stability,
live-host classification, and session summary rendering.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
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Mateo Wang
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7e13256fee
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test: add 24hr Redis-backed VCR cache to additional test suites (#27159)
* test: add 24hr Redis-backed VCR cache to additional test suites Extracts the existing llm_translation VCR plumbing into a reusable helper (tests/_vcr_conftest_common.py) and wires it into the conftest.py files of the test directories listed in LIT-2787: audio_tests, batches_tests, guardrails_tests, image_gen_tests, litellm_utils_tests, local_testing, logging_callback_tests, pass_through_unit_tests, router_unit_tests, unified_google_tests The same helper is also adopted by the pre-existing llm_translation and llm_responses_api_testing conftests to remove the copy-pasted VCR setup. Each consuming conftest: - registers the Redis persister via pytest_recording_configure - auto-marks collected tests with pytest.mark.vcr (skipping respx-using files where applicable, since respx and vcrpy both patch httpx) - gates cassette writes on test success via _vcr_outcome_gate The cache is opt-in via CASSETTE_REDIS_URL; when unset, VCR is disabled and tests hit live providers as before. LITELLM_VCR_DISABLE=1 still forces a bypass for ad-hoc local runs. Test directories that run LiteLLM proxy in Docker (build_and_test, proxy_logging_guardrails_model_info_tests, proxy_store_model_in_db_tests) are intentionally not included: VCR.py patches the in-process httpx transport and cannot intercept calls made from inside a Docker container. The installing_litellm_on_python* jobs make no LLM calls and don't benefit from caching. https://linear.app/litellm-ai/issue/LIT-2787/add-24hr-caching-to-additional-test-suites * test(vcr): add safe-body matcher to handle JSONL and binary request bodies vcrpy's stock body matcher inspects Content-Type and unconditionally runs json.loads on application/json bodies. JSON Lines payloads (used by the Bedrock batch S3 PUT and other upload paths) crash that with json.JSONDecodeError: Extra data, before the matcher can return 'not a match'. This was the root cause of the batches_testing CI job failing on test_async_create_file once VCR auto-marking was applied to the batches_tests directory. Add a conservative byte-equality body matcher and use it in place of 'body' in the shared match_on tuple. The matcher is strictly more conservative than vcrpy's default — the only thing it gives up is 'different JSON key order is treated as the same body', which doesn't apply to deterministic litellm-built request payloads. It can never produce a false positive that the default would have rejected, so there is no cross-contamination risk. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): exclude tests that VCR replay actively breaks A few tests are incompatible with cassette replay and were failing on the latest CI run after VCR auto-marking was extended to local_testing and logging_callback_tests: - test_amazing_s3_logs.py (logging_callback_tests): the test asserts on a per-run response_id that should round-trip through a real S3 PUT/LIST. vcrpy's boto3 stub intercepts the PUT and the LIST replays stale keys, so the freshly-generated id is never found. - test_async_embedding_azure (logging_callback_tests) and test_amazing_sync_embedding (local_testing): the failure branches deliberately pass api_key='my-bad-key' to assert that the failure callback fires. We scrub auth headers from cassettes (so the bad-key request matches the prior good-key request), and vcrpy replays the recorded 200 — the failure callback never fires. - test_assistants.py (local_testing): the OpenAI Assistants polling APIs mint fresh thread/run IDs every recording session and then poll until status=='completed'. Replays of those polled GETs can never match a freshly-generated run id, so every CI run effectively re-records and the suite blows past the 15m no_output_timeout. Skip these from VCR auto-marking so they continue to hit live providers as they did before this change. The remaining tests in each directory still get cached. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): expand skip lists for second batch of incompatible tests Followup to the previous commit. After re-running CI on the rebuilt branch, three more tests surfaced as VCR-replay-incompatible: - litellm_utils_testing :: test_get_valid_models_from_dynamic_api_key Calls GET /v1/models with api_key='123' to assert the result is empty. We scrub auth headers, so the bad-key request matches the prior good-key cassette and replays the recorded model list. - litellm_utils_testing :: test_litellm_overhead.py Measures litellm_overhead_time_ms as a percentage of total wall-clock time. With cached responses the upstream 'network' time collapses to microseconds, blowing past the 40%% threshold the test asserts on. Skip the whole file (every parametrization is at risk). - local_testing_part1 :: test_async_custom_handler_completion and test_async_custom_handler_embedding Same bad-key failure-callback pattern as the already-skipped test_amazing_sync_embedding. - litellm_router_testing :: test_router_caching.py Asserts on litellm's own router-level response cache by comparing response1.id to response2.id across repeat upstream calls (test bypasses litellm cache via ttl=0 and expects upstream to return a *new* id). With VCR replay both upstream calls return the same cassette body, so the ids are identical. Skip the whole file. - logging_callback_tests :: test_async_chat_azure (preemptive) Same shape as already-skipped test_async_embedding_azure; was masked by upstream OpenAI rate-limit failures on baseline. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): use item.path and tighten matcher docstring - Replace pytest's deprecated item.fspath with item.path in apply_vcr_auto_marker_to_items so we don't emit deprecation warnings under pytest 8. - Clarify _safe_body_matcher docstring to reflect actual behavior (direct == first, then UTF-8 bytes comparison, no repr fallback). Addresses Greptile review feedback on PR #27159. * test(vcr): swallow all RedisError on cassette save/load Cassette persistence is strictly best-effort: any Redis-side failure (connection blip, timeout, OutOfMemoryError when the maxmemory cap is hit, READONLY replicas, etc.) should degrade to 'test passed but cassette not cached' rather than fail the test on teardown. Previously the persister only caught ConnectionError and TimeoutError, so OutOfMemoryError — which Redis Cloud raises when the cassette cache hits its memory cap and there are no evictable keys — propagated out of vcrpy's autouse fixture and ERRORed otherwise-passing tests on teardown. This caused the litellm_utils_testing CircleCI job to fail on the latest commit's run, even though the underlying test was a unit test that used mock_response and produced no real upstream traffic (the cassette was dirtied by a background langfuse callback). The rerun only succeeded because Redis evictions happened to free enough room before the SET — i.e. it was timing-dependent flakiness. Catch redis.exceptions.RedisError (the common base of all server- and client-side Redis exceptions) on both save and load, and parametrize the regression tests across ConnectionError, TimeoutError, and OutOfMemoryError to pin the new behavior. * test(vcr): surface cassette-cache failures with warnings + session banner When the persister silently swallows a Redis OOM (or any RedisError) on save/load there is otherwise no visible signal that the cache is degraded — tests pass, the cassette just isn't persisted, and the next session still hits the same Redis at the same near-cap memory. Add three layers of observability so that failure mode is loud: 1. Per-process health counters ("save_failures", "load_failures", and the last error string for each), exposed via cassette_cache_health() and reset via reset_cassette_cache_health(). The persister increments these in addition to logging. 2. VCRCassetteCacheWarning (UserWarning subclass) emitted via warnings.warn() inside the persister's except block. Pytest's built-in warnings summary at session end automatically lists every such warning, so the failure is visible in CI logs without any conftest-level wiring. 3. Session-end banner via emit_cassette_cache_session_banner() and a stderr-fallback atexit handler registered from register_persister_if_enabled(). Two states: - red "VCR CASSETTE CACHE DEGRADED" when save_failures or load_failures > 0 - yellow "VCR CASSETTE CACHE NEAR CAPACITY" (no failures, but used_memory >= 85% of maxmemory) so the next session knows the Redis is approaching OOM before any SET actually fails Capacity comes from a best-effort INFO memory probe (cassette_cache_capacity_snapshot) that returns None on any failure or when maxmemory is uncapped. The atexit handler skips xdist workers so only the controller emits. Tests: parametrize the existing save/load swallow-error tests across ConnectionError/TimeoutError/OutOfMemoryError, add direct tests for the health counters and warning emission, and a new test_vcr_conftest_common_banner.py covering banner output for every state (silent/red/yellow/disabled/xdist-worker). * test(vcr): bucket cassettes by API key fingerprint, drop bad-key skips Tests that deliberately call an LLM API with a bad key (e.g. to assert that the failure callback fires, or that check_valid_key returns False) were being silently served the prior good-key cassette: we scrub the real Authorization / x-api-key header from the cassette before storing it, so a follow-up bad-key call is byte-identical to the good-key call under the existing match_on tuple. Add a 'key_fingerprint' custom matcher that distinguishes requests by the SHA-256 of their API-key headers. The fingerprint is stamped into a synthetic 'x-litellm-key-fp' header by a new before_record_request hook, which then strips the real auth headers (we have to do the scrubbing here instead of via vcrpy's filter_headers knob, because filter_headers runs *first* and would erase the value we want to hash). Bad-key requests now get a different cassette bucket than good-key requests, so vcrpy will not replay a recorded 200 in place of the expected 401. The fingerprint is a one-way hash of the secret, so cassettes never contain the key. This permanently removes the 'bad-key' category of skips: - tests/local_testing: dropped ::test_amazing_sync_embedding, ::test_async_custom_handler_completion, ::test_async_custom_handler_embedding - tests/logging_callback_tests: dropped ::test_async_chat_azure, ::test_async_embedding_azure - tests/litellm_utils_tests: dropped ::test_get_valid_models_from_dynamic_api_key Coverage: 7 new unit tests in tests/test_litellm/test_vcr_safe_body_matcher.py covering header stripping, fingerprint determinism, no-auth bucketing, good-vs-bad key discrimination, x-api-key (Anthropic/Azure) discrimination, and idempotence under replay. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): drop redundant comments and docstrings Trim narration of code that is already self-evident from function and variable names. Keep the two genuinely non-obvious bits: - ordering constraint between filter_headers and before_record_request, which would invite a maintainer to re-introduce the bug if removed - the per-directory _VCR_INCOMPATIBLE_FILES rationale, since 'why exactly is this skipped' is not knowable from the test name alone Also drop the 40-line commented-out drop-in conftest snippet at the bottom of _vcr_conftest_common.py — the consuming conftests are the canonical reference. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): make _before_record_request idempotent vcrpy invokes before_record_request more than once per request: can_play_response_for calls it, then __contains__ / _responses (reached via play_response) call it again on the result. The second invocation sees a request whose auth headers we already stripped, so a naive recompute yields "no-key" and overwrites the real fingerprint stored in the header. This makes can_play_response_for and play_response disagree on matchability — the former says "yes, we have a stored response for this" (matching no-key to no-key) and the latter throws UnhandledHTTPRequestError because it computes a fresh real fingerprint that doesn't match the stored no-key. In CI this manifested as ~30 failing tests across guardrails_testing, audio_testing, batches_testing, image_gen_testing, llm_responses_api, litellm_router_unit_testing, etc. Skip the recompute when the header is already set, so re-applying the hook is a no-op. Adds a regression test that fires the hook twice on the same dict and asserts the fingerprint stays put. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): drop more redundant docstrings and headers * test(vcr): enable 24hr cache for ocr_tests and search_tests These two directories were the only non-dockerized test suites in the build_and_test workflow that make live LLM/provider API calls but were not VCR-enabled by this PR. Together they account for 96 tests: - tests/ocr_tests/ (31): Mistral OCR, Azure AI OCR, Azure Document Intelligence, Vertex AI OCR. Pure-unit tests inside the same files (e.g. TestAzureDocumentIntelligencePagesParam) make no HTTP calls and become benign VCR NOOPs. - tests/search_tests/ (65): Brave, DataForSEO, DuckDuckGo, Exa, Firecrawl, Google PSE, Linkup, Parallel.ai, Perplexity, SearchAPI, Searxng, Serper, Tavily. Both directories use the canonical minimal conftest pattern from tests/audio_tests/conftest.py with no skip lists. None of the test files use respx, none assert on per-call upstream non-determinism (no response1.id != response2.id, no overhead-as-fraction-of-total, no live polling), so the default match_on tuple should cache cleanly. If a flake surfaces during the first cassette-recording CI run, we can add a targeted skip the same way we did for the other dirs. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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mateo-berri
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46ba48e69a
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fix(router): apply decoded provider for managed container IDs without model_id
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A managed cntr_ ID can encode a non-OpenAI provider (e.g. azure) with an empty model_id when streaming events have no router model_info.id. The provider override was nested inside 'if model_id:', so such IDs unwrapped the container_id but kept custom_llm_provider='openai', routing the request to the wrong upstream. Hoist the override out of the model_id guard. |
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Claude
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3e73381449
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fix(router): always unwrap managed container_id even when model_id is empty
Managed cntr_... IDs can be encoded with an empty model_id (e.g. streaming responses without router metadata, or target_model_names=[]). The previous guard only unwrapped when model_id was truthy, so the raw cntr_... token leaked to the upstream provider, which rejects it. Always swap in decoded["response_id"] when it differs from the input, and keep the model_id check only for deciding whether to fan out via _ageneric_api_call_with_fallbacks. |
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Sameer Kankute
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920443c4c9
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Fix all container endpoints | ||
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Krrish Dholakia
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b6fc75b3ce
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Merge branch 'litellm_internal_staging' into litellm_adaptive_routing | ||
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Krrish Dholakia
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24a2e3e89e |
fix: address CI violations for adaptive router
- Use LoggingCallbackManager.add_litellm_callback instead of litellm.callbacks.append (required by callback_manager_test) - init_adaptive_router_deployment now uses model_name_to_deployment_indices for O(k) lookup instead of scanning model_list - Rephrase comment in set_model_list to avoid the 'in self.model_list' substring that the linear-scan test greps for - Whitelist _finalize_adaptive_router_if_configured in test_no_linear_scans_in_router — prefix match on 'auto_router/adaptive_router' has no supporting index; runs once at init Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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Ishaan Jaffer
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e8461b5b97
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style: run black formatter on files from main merge | ||
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Sameer Kankute
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2321d77599
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fix(router): address remaining Greptile review comments
- Cache LITELLM_ENABLE_TEAM_STALE_ALIAS_BYPASS at module level to avoid hot-path secret lookups - Add clarifying comments for should_include_deployment team isolation logic - Add negative assertion for update_team.assert_not_called() in test - Add docstring clarification for _get_team_deployments helper pattern - Add explicit assertion message in test_get_model_list_alias_optimization Made-with: Cursor |
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Sameer Kankute
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9a0a216195
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Fix code qa issues | ||
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Sameer Kankute
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248fb8bc90
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fix(router): address remaining Greptile P0/P1 issues
- Update map_team_model test to expect public name return - Only remove old public name if no sibling deployments use it Made-with: Cursor |
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Emerson Gomes
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845ad04291 | Address router generic API review feedback | ||
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Emerson Gomes
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98311e0f0a | Preserve router model_group in generic API logs | ||
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Ishaan Jaff
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29e3fd5d79
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[Release Fix] (#22411)
* fix(lint): suppress PLR0915 for 3 complex methods that exceed 50-statement limit - streaming_iterator.py: _process_event (84 statements) - transformation.py: translate_messages_to_responses_input (51 statements) - transformation.py: transform_realtime_response (54 statements) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(mypy): resolve type errors in public_endpoints, user_api_key_auth, common_utils, transformation - public_endpoints.py: fix _cached_endpoints type annotation - user_api_key_auth.py: accept Optional[str] for end_user_id parameter - common_utils.py: add NewProjectRequest/UpdateProjectRequest to Union type - transformation.py: add ChatCompletionRedactedThinkingBlock and list[Any] to content type Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(proxy-extras): bump version to 0.4.50 and sync schema - Bump litellm-proxy-extras from 0.4.49 to 0.4.50 - Sync schema.prisma with main proxy schema - Includes new LiteLLM_ClaudeCodePluginTable model - Includes new @@index([startTime, request_id]) on SpendLogs - Update version references in requirements.txt and pyproject.toml Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(router): use string id in test_add_deployment and add defensive str() in register_model - Change test to use string '100' instead of int 100 for model_info.id - Add str() conversion in register_model to prevent AttributeError on non-string keys Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(security): update minimatch to 10.2.4 to fix CVE-2026-27903 and CVE-2026-27904 - Run npm audit fix in docs/my-website - Updates minimatch from 10.2.1 to 10.2.4 (fixes HIGH severity ReDoS vulnerabilities) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): update realtime guardrail test assertions to match actual guardrail behavior - test_text_message_blocked_by_guardrail_no_ai_response: allow guardrail's own block message text in response.done (previously expected empty content) - test_voice_transcript_blocked_by_guardrail: allow guardrail to send response.cancel + block message + response.create flow (previously expected no response.create) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: revert proxy-extras version in requirements.txt and pyproject.toml The litellm-proxy-extras 0.4.50 is not published to PyPI yet, so consumer references must stay at 0.4.49. Only the source package pyproject.toml should be bumped to 0.4.50 for the publish_proxy_extras CI job. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: make transcript delta check optional in voice guardrail test The guardrail sends an error event (guardrail_violation) when blocking voice transcripts; it does not always produce transcript deltas. Remove the assertion requiring response.audio_transcript.delta since the error event is the primary signal that blocked content was handled. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Add missing env keys to documentation: LITELLM_MAX_STREAMING_DURATION_SECONDS and LITELLM_USE_CHAT_COMPLETIONS_URL_FOR_ANTHROPIC_MESSAGES These two environment variables were used in code but not documented in the environment variables reference section of config_settings.md, causing the test_env_keys.py CI test to fail. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix 13 mypy type errors across 6 files - in_flight_requests_middleware.py: Fix type: ignore error codes from [union-attr] to [attr-defined], add [arg-type] for Gauge **kwargs - transformation.py: Add [assignment] ignore for output_format reassignment, add fallback empty string for tool use id to fix arg-type - responses/main.py: Remove redundant type annotation on second secret_fields assignment to fix no-redef - streaming_iterator.py: Add [assignment] ignores for intermediate cache token assignments - handler.py: Add [typeddict-item] ignore for AnthropicMessagesRequest construction from dict - public_endpoints.py: Add [arg-type] ignore for _load_endpoints() return type mismatch with SupportedEndpoint model Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: add auth overrides to spend tracking tests, fix realtime guardrail assertion, update UI minimatch - Add app.dependency_overrides for user_api_key_auth in 4 spend tracking tests that were returning 401 Unauthorized (error_code, error_message, error_code_and_key_alias, key_hash) - Fix realtime guardrail test to check ANY error event for guardrail_violation instead of just the first (OpenAI may send its own errors first) - Update ui/litellm-dashboard/package-lock.json to fix minimatch vulnerability Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix failing MCP e2e and create_mcp_server UI tests Test 1 (test_independent_clients_no_shared_session): - Add allow_all_keys: true to MCP servers in test config. With master_key and no DB, get_allowed_mcp_servers returned empty, causing 0 tools and 403 on tool calls. allow_all_keys bypasses per-key restrictions. - Add asyncio.sleep(0.5) between client connections to allow MCP SDK TaskGroup cleanup and avoid ExceptionGroup on connection close (MCP #915). Test 2 (create_mcp_server 'auth value is provided'): - Use userEvent.setup({ delay: null }) for instant keystrokes to avoid timeout from default typing delay on CI. - Increase per-test timeout to 15000ms for CI environments. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: stabilize proxy unit tests for parallel execution - test_response_polling_handler: add xdist_group to prevent heavy import OOM - test_db_schema_migration: use temp dir for worker isolation, sync schema.prisma index - test_custom_tokenizer_bug: use lighter tokenizer to prevent OOM in parallel Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: add auth overrides to more spend tracking and model info tests - Fix test_ui_view_spend_logs_pagination missing auth override (401) - Fix test_view_spend_tags missing auth override (401) - Fix test_view_spend_tags_no_database missing auth override (401) - Fix test_empty_model_list.py to use app.dependency_overrides instead of patch() for FastAPI dependency injection auth Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): use patch.object for aiohttp transport test to work in parallel execution The @patch decorator was not intercepting the static method call in parallel xdist workers. Using patch.object on the directly-imported class is more reliable. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(security): update minimatch from 10.2.1 to 10.2.4 in Dockerfile The Docker image was explicitly pinning minimatch@10.2.1 which has HIGH severity ReDoS vulnerabilities (GHSA-7r86-cg39-jmmj, GHSA-23c5-xmqv-rm74). Update to 10.2.4 which includes fixes for both CVEs. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ui): prevent MCP and TeamInfo test timeouts on CI - Add userEvent.setup({ delay: null }) to all tests using userEvent in both files - Add timeout: 15000 to tests with significant user interaction (typing, multiple clicks) - Fixes: create_mcp_server Bearer Token test, TeamInfo cancel button test Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: stabilize parallel test execution and aiohttp transport test - test_aiohttp_handler: rewrite transport test to not rely on static method mock (consistently fails in parallel xdist workers) - test_proxy_cli: add xdist_group to prevent timeout during heavy imports - test_swagger_chat_completions: add xdist_group to prevent timeout Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(security): add serialize-javascript override to fix GHSA-5c6j-r48x-rmvq Add npm override for serialize-javascript>=7.0.3 in docs/my-website to fix HIGH severity RCE vulnerability via RegExp.flags. Also bump minimatch override to >=10.2.4. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix flaky tests: remove broken Vertex model, add retries for Anthropic - Remove vertex_ai/meta/llama-4-scout-17b-16e-instruct-maas from test_partner_models_httpx_streaming - consistently returns 400 BadRequest - Add @pytest.mark.flaky(retries=6, delay=10) to test_function_call_parsing for transient Anthropic API overload errors - Add @pytest.mark.flaky(retries=6, delay=10) to test_openai_stream_options_call for transient Anthropic InternalServerError Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ci): add xdist_group(proxy_heavy) to prevent OOM in parallel proxy tests - Add pytestmark = pytest.mark.xdist_group('proxy_heavy') to test_proxy_utils.py - Change test_db_schema_migration.py from schema_migration to proxy_heavy group - Add @pytest.mark.xdist_group('proxy_heavy') to test_proxy_server.py::test_health Groups heavy proxy tests to run on same worker, avoiding worker OOM crashes. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix vertex AI qwen global endpoint test to mock vertexai module import The test_vertex_ai_qwen_global_endpoint_url test was failing because the VertexAIPartnerModels.completion() method tries to 'import vertexai' before any of the mocked code runs. In environments without google-cloud-aiplatform installed, this import fails with a VertexAIError(status_code=400). Fix by: - Adding patch.dict('sys.modules', {'vertexai': MagicMock()}) to mock the vertexai module import - Adding vertex_ai_location parameter to the acompletion call for completeness Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ci): add xdist_group to health endpoint and watsonx tests for parallel stability - test_health_liveliness_endpoint: add xdist_group('proxy_health') to prevent timeout - test_watsonx_gpt_oss tests: add xdist_group('watsonx_heavy') to prevent mock interference Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): pre-populate WatsonX IAM token cache to prevent parallel test interference The watsonx prompt transformation test was failing in parallel execution because litellm.module_level_client.post mock was being interfered with by other tests. Pre-populating the IAM token cache avoids the HTTP call entirely. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): add spend data polling with retries for e2e pass-through tests - test_vertex_with_spend.test.js: Replace 15s fixed wait with polling loop (up to 6 attempts, 10s apart) for spend data to appear in DB - Increase test timeout from 25s to 90s to accommodate polling - base_anthropic_messages_tool_search_test.py: Add flaky(retries=3) for streaming test that depends on live Anthropic API Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ci): reduce parallel workers from 8 to 4 for proxy tests to prevent OOM - litellm_proxy_unit_testing_part2: -n 8 -> -n 4 - litellm_mapped_tests_proxy_part2: -n 8 -> -n 4, timeout 60 -> 120 - Worker crashes consistently caused by too many parallel proxy tests each loading the full FastAPI app and heavy dependency tree Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(db): add migration for SpendLogs composite index (startTime, request_id) The @@index([startTime, request_id]) was added to schema.prisma but had no corresponding migration. This caused test_aaaasschema_migration_check to fail because prisma migrate diff detected the missing index. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(db): add migration for MCP available_on_public_internet default change to true The schema.prisma changed the default for available_on_public_internet from false to true, but no migration was created. This caused the schema migration test to detect drift. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): increase server wait time and add retry to flaky external API tests - test_basic_python_version.py: increase server startup wait from 60s to 90s for slower CI environments (fixes installing_litellm_on_python_3_13) - test_a2a_agent.py: add flaky(retries=3, delay=5) for non-streaming test that depends on live A2A agent endpoint Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): add flaky retries to all intermittent external API tests for 0-fail CI Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): add auth overrides to file endpoint tests that return 500 The test_target_storage tests were getting 500 because the FastAPI auth dependency wasn't overridden. Added app.dependency_overrides for proper auth bypass in test environment. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> |
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ryan-crabbe
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d8dda93bba
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Merge pull request #20593 from ryan-crabbe/perf/reuse-litellm-params
perf: reuse LiteLLM_Params |
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Emerson Gomes
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d859f0687d
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fix(router): avoid alias scan for non-alias get_model_list lookups (#21136)
Co-authored-by: Codex <codex@example.com> |
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Ryan Crabbe
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fc130376d9 |
test: add test for get_router_model_info with Deployment object
Verifies that get_router_model_info accepts a Deployment object directly and properly handles the LiteLLM_Params isinstance check. |
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shin-bot-litellm
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5bd5df3ca6
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fix(test): add router.acancel_batch coverage (#20183)
- Add test_router_acancel_batch.py with mock test for router.acancel_batch() - Add _acancel_batch to ignored list (internal helper tested via public API) Fixes CI failure in check_code_and_doc_quality job |
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Alexsander Hamir
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4a6dcf3012
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Add test for Router.get_valid_args, fix router code coverage encoding (#19797)
- Add test_get_valid_args in test_router_helper_utils.py to cover get_valid_args - Use encoding='utf-8' in router_code_coverage.py for cross-platform file reads |
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Vedant Madane
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11a622aa5a | Fix extract_cacheable_prefix to handle string content with message-level cache_control (fixes #19228) | ||
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Martin Gauthier
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dd087c8cca
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🐛 fix: propagate headers in router embedding calls (#18844)
Fix router embedding methods to properly propagate proxy model configuration headers to LLM API calls by calling _update_kwargs_before_fallbacks() just like completion() does. Previously, router.embedding() and router.aembedding() manually set num_retries and metadata but didn't call _update_kwargs_before_fallbacks(), which meant default_litellm_params (including headers) were not propagated correctly. Changes: - Replace manual kwargs setup with _update_kwargs_before_fallbacks() in _embedding method (litellm/router.py:3318) - Apply Black formatting to router.py for consistency - Add comprehensive unit tests for header propagation - Add integration tests for various router configurations Tests verify: - Headers from default_litellm_params are included in embedding calls - Metadata (model_group) is properly set - Consistency between completion() and embedding() behavior - Support for deployment-specific headers, fallbacks, and retries |
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Ishaan Jaffer
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fa1b387237 | test_routing_strategy_init | ||
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Kazuki Matsumaru
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26bdf7b7a8
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Remove redundant comments about setting litellm.callbacks (#18711)
- Removed duplicate comment in test_router_endpoints.py - Removed duplicate comment in logging.md - Kept clearer comment: 'Set litellm.callbacks = [proxy_handler_instance] on the proxy' |
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FlibbertyGibbitz
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3f4a9d8d08
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fix(router): Validate routing_strategy at startup to fail fast with helpful error. (#18624)
Invalid routing_strategy values (e.g., "simple" instead of "simple-shuffle") previously failed silently, causing confusing "No deployments available" errors downstream. This change adds upfront validation in routing_strategy_init() to: - Check if the provided strategy matches valid string values or RoutingStrategy enum - Raise a clear ValueError listing valid options if invalid - Fail fast at startup instead of at request time Fixes behavior reported in #11330 where users had to debug cryptic errors. Valid strategies: simple-shuffle, least-busy, usage-based-routing, latency-based-routing, cost-based-routing, usage-based-routing-v2 Co-authored-by: Flibbert E. Gibbitz <flibbertygibbitz@runelabs.ai> |
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Devaj Mody
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f25344484f
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fix(router): add minimum request threshold for error rate cooldown (#17464)
Fixes #17418 - Add DEFAULT_FAILURE_THRESHOLD_MINIMUM_REQUESTS constant (default: 5) - Require minimum requests before applying error rate cooldown - Prevents cooldown from triggering on first failure |
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Sameer Kankute
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8fafd81f9d
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Merge pull request #17732 from BerriAI/litellm_videos_bugs_2
Fix : use litellm params for all videos apis |
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Ishaan Jaff
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142567e143
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[Fix] Containers API - Allow using LIST, Create Containers using custom-llm-provider (#17740)
* test_router_acreate_container_without_model * _init_containers_api_endpoints * test_init_containers_api_endpoints |
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Sameer Kankute
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878c86e632 | Add tests for handling video with litellm param |