* fix(search): forward search-tool params through the router, complete Parallel AI v1 param mapping
SearchAPIRouter dropped every parameter configured on a search tool, forwarding
only per-request kwargs. Any tool-level setting (mode, max_results, ...) was
silently lost on the way to the adapter, for every search provider.
Also completes the Parallel AI v1 search surface: after_date, fetch_policy,
location and include_domains now nest under advanced_settings instead of being
sent as unknown top-level fields, responses preserve search_id / session_id /
warnings / raw excerpts, and search cost is derived from the request mode and
the provider's reported usage rather than a single flat rate.
* fix(parallel_ai): stop a caller from pricing its own search request
`_parallel_ai_usage` carries the provider's reported usage into cost
calculation. It was only written when the response contained a usage block, so
a caller could pass `_parallel_ai_usage=[{"name": "sku_search", "count": 0}]`
and, whenever the provider omitted usage, bill $0.00 instead of $0.005 — the
value also reached the upstream request body as an unknown field.
The key is now stripped from inbound params and written unconditionally from
the parsed response, so only the provider can populate it.
* fix(parallel_ai): price fast search mode correctly
* test(parallel_ai): fake search at HTTP boundary
* fix(parallel_ai): tolerate null search result fields
---------
Co-authored-by: khushishelat <shelatkhushi@gmail.com>
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
A test that asserts on the error inside its own except block passes when the
call stops raising, because nothing runs the handler. That is the exact case
the test exists to catch, so the regression lands green.
Rewrites all 111 such blocks into pytest.raises, which fails when the call
succeeds, and selects PT017 in ruff-tests.toml so no new one lands.
`pytest.raises(Exception)` with no `match=` passes on any error that broad. A
TypeError from a refactor, a botched fixture, an import that moved: all of them
read as the rejection the test claims to police, so the test goes green for the
wrong reason and stays green after the behaviour it guards is gone.
PT011 closes that gap for the 317 sites B017 could not reach, because B017 only
fires on a single-statement body with no `as e` binding. Each pattern here is the
message the code actually raised, recorded by running the sites under a plugin
that logged the concrete type and text per call site, so the assertions describe
observed behaviour rather than a guess. Where a site raises more than one message
across its parametrize cases, the pattern is an alternation of what was seen;
where the exception carries an empty `str()` and puts the text on `.message`, the
site keeps a narrow `noqa` with the reason.
PT014 removes four parametrize cases that were listed twice. The duplicate re-runs
an assertion that already passed, and it usually marks a case someone meant to
vary and forgot to edit.
* test: enforce PT012 so a pytest.raises block cannot hide dead assertions
`with pytest.raises(...)` stops at the first statement that raises. Anything
sequenced after it inside the block never runs, so an assertion written there is
never checked and the test still reports green.
Two sites were doing exactly that, and both assertions turned out to be wrong
once they started running. tests/llm_translation/test_prompt_factory.py asserted
the bedrock rejection names "requires at least one non-system message", which
holds. tests/proxy_unit_tests/test_proxy_server.py asserted the prisma startup
failure mentions "httpx.ConnectError", which never appears: the failure is an
httpx.ConnectError whose message is "All connection attempts failed", so that
test now asserts the type. Its DATABASE_URL override moves to monkeypatch, since
the old restore sat below the assertion and leaked the invalid URL into every
later DB test the moment the assertion started being able to fail.
The remaining 72 sites are rewritten without changing what they exercise: setup
that cannot raise moves above the block, a nested `patch` moves outside it, and
bodies with real control flow (a stream drain, an if/else on sync_mode, a
retry loop) move into a local closure the block calls.
Fixing PT012 unmasked two B017s, since ruff only reports a blind
pytest.raises(Exception) once the block holds a single statement.
tests/proxy_unit_tests/test_auth_checks.py narrows to the ProxyException
can_key_call_model actually raises. tests/local_testing/test_completion_cost.py
was asserting vertex_ai/medlm-medium has no cost entry, which stopped being true
at some point; that dead first half is gone and the rest of the test, which
checks medlm pricing resolves above zero, now runs instead of being skipped.
* chore(ci): ratchet TQ004 to 768 after the prisma test moved to monkeypatch
* 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
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.
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.
* 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>
* 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>
* 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.
* 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>
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.
* 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>
- 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
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>
Update test_generate_model_id_with_deployment_model_name to accept the new
error message format that results from the list+join optimization.
The function still correctly rejects None values with a TypeError, but the
error message changed from 'unsupported operand type(s) for +=' to
'expected str instance, NoneType found' due to the implementation change
from string concatenation to list joining.
* fix intent params
* Add responses
* fix unrelated test
* test fix - fireworks API endpoint is down
* test fix fireworks ai is having an active outage
* test_completion_cost_databricks
* dbrx fix test API currently not responding
* Update OpenAI Realtime handler to use the correct endpoint and include all query parameters. Adjusted error messages for missing API base and key. Updated health check URL construction to pass model as a query parameter.
* Enhance OpenAI Realtime handler tests to ensure model parameter inclusion in WebSocket URL. Added new tests to verify correct URL construction with model and additional parameters, preventing 'missing_model' errors. Updated existing tests for consistency.
* Remove debug print statements for API base and key in OpenAIRealtime handler to clean up the code.
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Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* fix unsupported operand type(s) for +=: 'NoneType' and 'str' on clientside auth creds for responses
* fix the client side auth to use correct metadata
* add more tests
* fix tests
* EditAutoRouterTabProps
* Revert "EditAutoRouterTabProps"
This reverts commit 2835d3a374.
* add EditAutoRouterTab
* delete edit
* fixes for edit auto-router
* fix accessing model edit
* working edit auto router
* fix - edit remove custom model name
* fixes for edit auto router settings
* qa for adding a model router
* test fix
* fix(user_api_key_auth.py): add 'headers' to constructed request for websocket
Fix issue on some datastructure versions which require a headers field in scope
* test(test_user_api_key_auth.py): add unit testing for headers in scope change
* fix(router.py): migrate `_arealtime` to generic router endpoint
Fix infinite loop on model name missing for realtime api calls
* test(test_router_helper_utils.py): cleanup test post refactor
* add GET responses endpoints on router
* add GET responses endpoints on router
* add GET responses endpoints on router
* add DELETE responses endpoints on proxy
* fixes for testing GET, DELETE endpoints
* test_basic_responses api e2e
* Fixed issue #8246 (#8250)
* Fixed issue #8246
* Added unit tests for discard() and for remove_callback_from_list_by_object()
* fix(openai.py): support dynamic passing of organization param to openai
handles scenario where client-side org id is passed to openai
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Co-authored-by: Erez Hadad <erezh@il.ibm.com>
* feat(router.py): support request prioritization for text completion calls
* fix(internal_user_endpoints.py): fix sql query to return all keys, including null team id keys on `/user/info`
Fixes https://github.com/BerriAI/litellm/issues/7485
* fix: fix linting errors
* fix: fix linting error
* test(test_router_helper_utils.py): add direct test for '_schedule_factory'
Fixes code qa test
* fix(router.py): fix reading + using deployment-specific num retries on router
Fixes https://github.com/BerriAI/litellm/issues/7001
* fix(router.py): ensure 'timeout' in litellm_params overrides any value in router settings
Refactors all routes to use common '_update_kwargs_with_deployment' which has the timeout handling
* fix(router.py): fix timeout check
