The new cold-counter reseed test drove its redis client untyped, so the strict
tests/pyrightconfig.json (reportUnknown*, reportAny) flagged ten errors once the
file landed: scan_iter/get came back unknown and the pool.map lambda had an
untyped parameter. Annotate the client as redis.Redis[str] via a TYPE_CHECKING
import (the runtime import stays lazy so the suite still skips, not errors, when
redis is absent), which resolves scan_iter to Iterator[str] and get to str | None,
and replace the lambda with a typed inner function mirroring _burst. basedpyright
--project tests is back to zero errors.
The deprecated OldTeams component takes only accessToken, userID, userRole
and premiumUser; it ignores the teams prop these tests passed and instead
populates its table from the mocked teamListCall. The delete-warning block
never set teamListCall, and vi.clearAllMocks clears call history but not
implementations, so the table rendered the "Legacy Team" (keys.length 2)
left behind by the previous block's last test. Both delete tests therefore
ran against that leaked team: the keys-present case passed only because the
leaked count happened to be 2, and the no-keys case rendered the same warning
it asserted should be absent, so it failed.
Seed the team through the channel the component actually reads (teamListCall)
and drop the props it never consumes, so each test renders exactly the team
it declares. The keys-present case now uses a distinctive count so it can no
longer pass on a coincidental leak
Fix the typo on the header comment and drop the orphaned namespace/ttl
comment remnants left indented under cache_params; the active values are
already set above. Flagged by greptile review.
The autouse session fixture skipped the whole tests/e2e session when no proxy
answered, which also skipped test_lifecycle.py, a pure unit test of run_case that
never touches the proxy. A regression test that silently skips gives no signal,
so the skip now lives in pytest_runtest_setup gated on the same e2e marker the
spend-log truncate guard already uses: live tests skip when no proxy is up while
harness unit coverage always runs. The liveness probe is cached with lru_cache so
it still runs once per session
The suite ships tests/pyrightconfig.json (strict, no Any), but basedpyright
--project tests reported four errors in it: three reportAny on the parametrize
ids=lambda c: c.__name__, and one reportUnusedFunction on the underscore-prefixed
autouse fixture _require_live_proxy. Replace the untyped lambda with a typed
_case_id(case_cls: Type[_BudgetCase]) -> str so the ids are no longer Any, and
rename the fixture to require_live_proxy so basedpyright no longer treats it as an
unused private function (it is referenced only by pytest's autouse machinery).
basedpyright --project tests now reports zero errors.
test_custom_pricing_is_isolated_from_sibling_deployment documents a real proxy
gap (a deployment's custom per-token pricing leaks into the shared cost map for
sibling deployments of the same underlying model) and was left unconditionally
failing, which pollutes the suite's pass/fail signal. Mark it xfail(strict=True)
so the suite stays green while the leak persists and turns into a failure the
moment isolation is fixed, prompting the marker's removal.
run_case called case.init() outside the try/finally that runs teardown(), so a
case that registers cleanups progressively (create team, then user, then key)
and then fails partway through init() would leak the already-created entities on
the long-lived shared proxy. Move init() inside the try so teardown always runs.
Add a regression test that registers a cleanup then raises mid-init and asserts
the resource is still released.
On the should-still-succeed path of the per-model and tag isolation
tests, check is_budget_block before require_successful_call. If the
isolation bug fires the unaffected model/tag is blocked, so asserting
the specific 'blocked by X' invariant first yields the diagnostic
message instead of a generic upstream-failure. Matches the ordering in
test_soft_budget_e2e.py.
require_successful_call fails hard, it does not skip; the trailing
comment was factually wrong. The function name already states intent,
so the comment is removed in both per-model and tag budget helpers.
Remove the duplicate cache/cache_params block in the gateway config so the two
can't silently diverge under future edits. Reorder the soft-budget test to assert
the call isn't a budget block before require_successful_call, since that helper
hard-fails any non-2xx and left the budget-block check unreachable; the misleading
"skip" comment is corrected. Add a deferred delete in test_budget_delete_removes_it
so a failed delete doesn't leak a budget on the shared proxy. Scope the
spend_tracking sys.path insertion in pytest_sessionfinish to just the cleanup
import so a broader "pytest tests/" run isn't left with a mutated path.
Adds a "valkey-semantic" cache type so semantic prompt caching can run
against Valkey clusters (for example AWS ElastiCache for Valkey) using the
valkey-search module.
The existing "redis-semantic" backend cannot drive valkey-search. RedisVL
gates the connection on a RediSearch module version that valkey-search does
not report, and its SemanticCache index declares the prompt as a TEXT field,
which valkey-search does not implement. ValkeySemanticCache therefore talks to
valkey-search directly over redis-py: it builds a vector index from the field
types valkey-search supports (TAG for caller scope, VECTOR for the prompt
embedding) and runs KNN queries for retrieval. Prompt extraction, embedding
generation, and cached-response parsing are reused from RedisSemanticCache
since those are backend agnostic. The redis dependency is imported lazily in
the cache dispatch so importing litellm without redis installed still works.
It also fixes semantic-cache scope keys so similarity matching works across
reworded prompts. get_cache_key() hashed messages / prompt / input into the
litellm_cache_key that every semantic backend filters its KNN search on, so a
paraphrase landed in a different bucket and never matched, even far above the
similarity threshold. For semantic cache types the prompt-bearing params are
now excluded from the scope key and the server-set tenant identity
(user_api_key, team, org) is appended instead, restoring embedding matching
within a tenant while keeping cache entries scoped to the authenticated
key / team / org. The three semantic backends share this key, so the same
change fixes redis-semantic and qdrant-semantic.
Connections resolve from VALKEY_HOST / VALKEY_PORT / VALKEY_PASSWORD, falling
back to REDIS_* for drop-in compatibility, and passwordless clusters (IAM or
no-auth) are supported.
Resolves#29121Fixes#29086
The delete-team confirmation modal warned that a team's keys would be
deleted but said nothing about models. #29977 made team deletion also
delete the team's BYOK models, so the modal copy was understating what
gets removed.
The warning banner now mentions models alongside keys, and the
always-shown confirmation message does too so a team that has models but
no keys (the banner only renders when keys exist) still gets warned.
The "View Usage Guide" button on the legacy Usage page (shown when
DISABLE_EXPENSIVE_DB_QUERIES is set, i.e. SpendLogs has 1M+ rows) linked
to docs/proxy/spending_monitoring, which was removed from the docs and
now returns 404. Point it at docs/proxy/cost_tracking, which is live.
Fixes LIT-2724
A streaming request that breaks mid-flight, for example on a mid-stream read
timeout, still bills the provider for the chunks already delivered, yet the proxy
recorded that interrupted request as a zero-spend failure. An earlier revision
logged the recovered partial usage through the success path, which mislabeled a
failed request as a success and produced a misleading spend row
This recovers the partial usage where the failure is actually logged. The
streaming handler assembles the usage from the chunks seen so far and stashes it,
with its cost, on the logging object before firing the failure handlers. The
proxy failure hook lifts that usage and cost onto request_data before the
non-serialisable logging object is popped, and the spend-log writer records the
real partial spend on the failure row instead of a hardcoded zero;
get_logging_payload honors the recovered usage for the token columns and
_failure_handler_helper_fn preserves the recovered cost so the non-DB failure
loggers stay consistent
A request that recovers via a successful fallback is unaffected: the failure hook
only fires when the whole request fails, so the fallback's combined-usage success
row stays the single source of truth and there is no double counting
Resolves LIT-3825
Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
* fix(otel): one v2 logger owns the global provider; scope tenant creds per exporter
The proxy published the OTel global TracerProvider before callbacks were
initialized, so no preset logger existed yet and a second generic logger was
built that won the global provider. Server spans then exported through a
different provider than the preset's gen-ai spans, orphaning the LLM span on
the preset backend. Publish after callback init and reuse the already-built
logger instead.
Separately, per-request tenant OTLP credentials were stamped onto every OTLP
exporter, leaking one backend's key onto a co-configured backend. Tag each
exporter with the preset that contributed it and apply dynamic credentials
only to the matching owner.
* fix(otel): satisfy Any-discipline on changed lines
Type the logger-selection parameter as Sequence[object] (isinstance narrows
it), cast the list[Any] global at the single call site, and pass model_copy a
typed dict[str, str] update so no changed line carries an Any value.
* fix(otel): annotate the untyped-global boundary with any-ok
select_global_otel_v2_logger consumes litellm._in_memory_loggers, a shared
List[Any] global this change does not own. A cast doesn't satisfy the
Any-discipline checker (it inspects the inner expression), and re-annotating the
global is out of scope, so mark the single boundary line any-ok.
* test(otel): cover the startup global-provider publish via injectable helper
The publish step lived inline in proxy_startup_event (a FastAPI lifespan unit
tests do not execute), so its lines were uncovered though the selection logic
was tested. Extract publish_global_otel_v2_provider, which selects the single v2
logger and publishes its provider through an injected setter, and unit-test that
the published provider is the selected logger's. proxy_server delegates to it.
* refactor(otel): select global provider from the registered owner, not a list scan
The startup publish picked the global TracerProvider by scanning
_in_memory_loggers for the first OpenTelemetryV2, re-deriving an answer the
factory already settled: the first logger built registers itself as
proxy_server.open_telemetry_logger, and every other v2 path (guardrail, identity
seeding, phase spans) routes through that owner via _registered_v2_logger. Pass
that owner into select_global_otel_v2_logger so the global provider reuses the
same logger instead of an independent, order-dependent guess; the list scan
remains the SDK-path fallback. The owner is injected at the proxy call site to
keep the helper free of hidden global reads.
* refactor(otel): type ExporterSpec.owner as an ExporterOwner enum
The owner field carried free-form strings that had to match preset callback
names. Introduce a str-based ExporterOwner enum (values equal to the callback
names, so per-request credential routing's owner==callback_name comparison still
holds) and have each preset tag its exporter with the enum member.
* refactor(otel): rename ExporterOwner.ARIZE to ARIZE_AX
Distinguish the hosted Arize AX backend from Arize Phoenix at the member level
while keeping the value 'arize' (the public callback name routing compares
against). Add a comment noting AX and Phoenix are separate backends.
* fix(proxy): use e.request_data for logging_obj in ModifyResponseException streaming passthrough
When a guardrail blocks a streaming request pre-call by raising
ModifyResponseException (or RejectedRequestError), chat_completion streams the
violation message back as a 200 by building a CustomStreamWrapper. It read the
logging object from the outer request body (`data.get("litellm_logging_obj")`),
but that dict never carries litellm_logging_obj -- it diverges from the
processor's data at function_setup, and only the processor copy (exposed as
e.request_data, already bound to `_data` here) gets the logging object
attached. CustomStreamWrapper.__init__ then dereferences
`logging_obj.model_call_details` on None and 500s the request with
"AttributeError: 'NoneType' object has no attribute 'model_call_details'".
Read logging_obj from `_data` (= e.request_data) in both streaming
passthrough handlers so the refusal streams correctly. The non-streaming and
the anthropic/responses passthrough paths were unaffected.
Adds a regression test asserting the wrapper receives the logging object from
e.request_data rather than None.
* test(proxy): cover RejectedRequestError streaming passthrough
The streaming logging_obj fix was applied to both the ModifyResponseException
and RejectedRequestError handlers, but only the former had a regression test.
Extract a shared helper and add a parallel test for the RejectedRequestError
streaming path so both handlers stay guarded against the None-logging_obj crash.
---------
Co-authored-by: Joseph Barker <joseph.barker@rubrik.com>
Switch the zizmor check to fail on any finding at medium severity or
above (advanced-security off, min-severity medium, annotations on) so it
can be promoted to a required check, and pin the engine to zizmor 1.24.1
through zizmor-action v0.5.6 for deterministic runs.
Clear the findings that were outstanding so the check passes: correct
mismatched action pin version comments, scope the proxy endpoint
workflow's id-token and pull-requests permissions to the jobs that use
them, and mark the server-root-path docker build as non-publishing while
dropping its shared gha build cache.
* feat(proxy): add configurable response headers middleware
Adds a small ASGI middleware that sets standard response headers
(X-Frame-Options, Content-Security-Policy frame-ancestors, X-Content-Type-Options)
on proxy and UI responses. Strict-Transport-Security is optional and gated
behind LITELLM_ENABLE_HSTS for HTTPS deployments. Values use setdefault so a
route that sets its own header is preserved.
* feat(proxy/ui): make login page credentials hint configurable
build_ui_login_form accepts a hide_default_credentials_hint parameter and
google_login reads LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT (or general_settings)
so the legacy login page behaves consistently with the new UI. Also collapses
a duplicated branch and removes an unused variable and module-level constant.
* fix(proxy/ui): apply credentials hint flag on /fallback/login
The /fallback/login handler still rendered the default-credentials hint
regardless of LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT. Collapse its duplicate
branch and forward the flag, matching google_login, so all login surfaces
behave consistently. Adds regression tests for /fallback/login and makes the
ui_sso test helper restore os.environ so env vars do not leak across tests.
Cut the default "Virtual Keys" landing (?page=api-keys) over to a path route at
(dashboard)/api-keys. The dashboard is extracted into a shared ApiKeysDashboard
component used by both the new route and the index's inline render, so there's
no duplication. Adding the MIGRATED_PAGES entry repoints the sidebar item and
redirects ?page=api-keys to /ui/api-keys.
The index is the post-login landing and still hosts the legacy switch for the
not-yet-migrated pages (models, pass-through, usage) plus the invitation flow,
so it stays. The auto-redirect now fires only for an explicit ?page= param,
leaving the bare /ui/ landing to render inline; this keeps the return-URL
handling and the invitation_id flow (both of which run at the bare landing)
intact, where a blanket redirect would have dropped them. The new route uses
useAuthorized for the login gate, matching every other migrated route.
Delete the in-product survey and Claude Code feedback prompts end to end.
Frontend: remove the src/components/survey/ module, the index page's nudge
state/effects/handlers, the getInProductNudgesCall helper, and the orphaned
"Disable UI nudges" toggle in the admin UI Settings page; prune the stale
eslint-suppressions entries.
Backend: remove the now-dead /in_product_nudges route, the InProductNudgeResponse
type, and the disable_ui_nudges UI setting (Field + allowlist). Nothing read it
for logic and the UISettings model is extra="allow", so existing stored configs
are unaffected (the value is just no longer surfaced). schema.d.ts is regenerated
and the two tests covering the removed route/setting are dropped.
PR #30784 deleted .github/workflows/review_gate.yml and
triage_pr_with_llm.yml, but test_github_triage_workflows.py still
listed both in its parametrize tables, so _load_workflow raised
FileNotFoundError for every case naming them.
Remove the two stale entries from DESTRUCTIVE_GATE_ENV and
LLM_CLIENT_INSTALLER_WORKFLOWS; the remaining four workflows that still
exist keep their guardrail coverage.
* chore(ci): remove Agent Shin pull_request_target workflows
Drop the two Agent Shin workflows that ran on the pull_request_target
trigger: the PR triage workflow and the review gate. Both were dry-run
and gated behind AGENT_SHIN_ENABLED, so no live automation changes.
The shared scripts under .github/scripts stay in place; four other
Agent Shin workflows still depend on them and run on schedule, dispatch,
and issue events rather than pull_request_target
* ci(zizmor): also run on litellm_internal_staging
* fix(proxy): bump health-check max_tokens default to 16 for GPT-5 compatibility (#30708)
OpenAI GPT-5 models require max_completion_tokens >= 16.
Health checks were using 5 (proxy/health_check.py) and 10
(health_check_helpers.py), causing failures on GPT-5 models.
Fixes#23836
* fix: increase health check max_tokens from 5 to 16 (#23836) (#26610)
GPT-5 models enforce a minimum of 16 for max_output_tokens. The current
default of 5 still causes health checks to fail for these models. Bump
the non-wildcard default to 16 — the smallest value that satisfies all
known provider minimums while keeping health checks lightweight.
Also tightens the wildcard test assertion from a weak disjunctive check
to strict key-absence.
Co-authored-by: Sameer Kankute <sameer@berri.ai>
* fix: ensure checks show gemini-3-flash-preview supports responseJsonS… (#30696)
* fix: ensure checks show gemini-3-flash-preview supports responseJsonSchema.
* fix: remove async keyword from test.
* fix: make Bedrock Mantle Responses routing data-driven per model (#30700)
* Make Bedrock Mantle Responses routing data-driven per model
Route Bedrock Mantle models to the native Responses API based on each
model's price-map capability signal instead of a hardcoded model-name
heuristic, and derive the OpenAI-compatible base path segment per model.
Responses dispatch now selects the native config when the model advertises
responses support (/v1/responses in supported_endpoints, or mode=responses),
both overridable via register_model and proxy model_info. This enables
native Responses for gpt-oss-120b/20b and the gemma-4 family while keeping
chat-only models (gpt-oss safeguard, nvidia, mistral, ...) on the existing
chat-completions emulation. Capability is per-model, so gpt-oss-120b routes
natively while gpt-oss-safeguard-120b does not despite sharing the gpt-oss
substring.
The wire path is a separate concern, driven by the existing
use_openai_responses_path flag rather than a model-name match: gpt-5.x and
gemma-4-* on /openai/v1, everything else (incl. gpt-oss) on /v1. The chat
config now derives its base from the same flag, fixing gemma-4
chat-completions requests that previously went to /v1 instead of /openai/v1.
Cost maps: add supported_endpoints to the gpt-oss entries (responses for the
non-safeguard variants, chat-only for safeguard) and supported_endpoints +
use_openai_responses_path to all three gemma-4 entries.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Address review: move capability helper into bedrock_mantle package
Move the Responses capability check out of utils.py into
litellm/llms/bedrock_mantle/common_utils.py as mantle_supports_responses,
alongside its companion wire-path helper mantle_base_segment. Both are now
pure functions of (model, model_cost): the price-map mode/supported_endpoints
read replaces the get_model_info call, so the rules are unit-testable without
patching global state and the Bedrock Mantle package is self-contained.
Use str | None instead of Optional[str] on the new signatures to satisfy the
ruff UP045 strict-rule gate. Add direct unit tests for both helpers.
Fix test_register_model_restore_undoes_existing_key_overwrite: gpt-oss-120b
now legitimately supports Responses, so it can no longer be the
"None after restore" vehicle; use the chat-only safeguard variant, which
isolates the register/restore effect from the model's own capability.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
* fix(proxy): fail fast on non-PostgreSQL DATABASE_URL instead of hanging on startup (#30366)
* fix(proxy): fail fast on non-PostgreSQL DATABASE_URL instead of hanging on startup
LiteLLM's Prisma datasource is pinned to provider = 'postgresql', so a sqlite:// or mysql:// DATABASE_URL can never connect.
Today that surfaces as an opaque startup stall where the port never binds, and a separate 'DB not connected' 500 on /key/generate when no DATABASE_URL is set at all leaves operators guessing what to configure.
Validate the DATABASE_URL / DIRECT_URL scheme in run_server before any Prisma call and exit with an actionable message naming the unsupported scheme.
Also reword CommonProxyErrors.db_not_connected_error to tell the operator to set DATABASE_URL to a postgresql:// connection string.
Add regression tests covering postgres acceptance and sqlite/mysql/mssql rejection.
* fix: resolve CI failures and proxy DB URL typing issue
* fix(dashscope): treat an explicit 0.0 tier cost as a real price, not missing (#30653)
The tiered cost calculator resolved a tier's per-token cost with
`tier.get(cost_key) or tier.get(fallback_cost_key, 0)`. Because `or`
short-circuits on any falsy value, a tier that legitimately prices a
component at 0.0 (e.g. a free-cache-read tier with
cache_read_input_token_cost: 0.0, or a free-reasoning tier) is treated
as missing and silently billed at the full fallback rate
(input_cost_per_token / output_cost_per_token).
The flat-pricing path in the same module already handles this correctly
with an `is None` guard. Resolve tier costs through a small helper that
mirrors it, so 0.0 is honored at both the in-range and overflow sites.
No shipped model currently has a 0.0 tier cost, so this is a latent
defect; the fix makes the tiered path consistent with the flat path and
prevents over-charging the first time such a tier appears. Adds unit
tests covering the in-range and overflow paths, and drops an unused
import flagged by ruff in the touched test file.
* feat(proxy): show session-aggregate cost and duration in request logs (#25708) (#30507)
* fix(anthropic): don't leak tool 'type' into OpenAI function parameters schema (#30618)
In the messages->chat/completions bridge, translate_anthropic_tools_to_openai
merged every non-mapped tool key into the function parameters dict. The
Anthropic tool 'type' (e.g. 'custom') thus overwrote parameters.type ('object'
-> 'custom'), and providers reject it ('custom' is not a valid JSON-Schema type).
Exclude 'type' from the passthrough. Fixes#30557.
* fix(proxy): stop IAM-refresh engine restart from cascading reconnects (#29176) (#30183)
An RDS IAM token refresh recreates the Prisma client, which SIGKILLs the
running query-engine and spawns a new one. That planned kill was
indistinguishable from a crash, and three reconnect paths used two
uncoordinated locks, so a single refresh triggered a cascade of engine
kill/respawn cycles:
1. `_safe_refresh_token` (holds `_reconnection_lock`) -> recreate -> kill old
engine, spawn new one.
2. The engine-death watcher sees that kill, assumes a crash, and calls
`attempt_db_reconnect(force=True)` (a different lock,
`_db_reconnect_lock`) -> recreate again -> kills the fresh engine.
3. In-flight queries failing during the swap are classified as transport
errors and trigger their own `attempt_db_reconnect` -> recreate again.
Fix coordinates planned restarts across the wrapper and the watcher:
- PrismaWrapper records the old engine PID in `_expected_engine_deaths`
before killing it; all four watcher death-detectors (waitpid thread,
pidfd, already-dead probe, os.kill poll) consume that PID and skip the
reconnect instead of treating it as a crash.
- `recreate_prisma_client` now serializes through `_reconnection_lock` and
bumps a monotonic `_engine_generation`. Callers pass `expected_generation`
as an optimistic-lock token, so racing/cascading recreates collapse into a
single restart (losers no-op). This closes the two-lock gap.
- The direct reconnect path probes the writer with SELECT 1 before
recreating; a healthy connection (e.g. engine already replaced by a
refresh) skips the recreate entirely.
- `_safe_refresh_token` coalesces: it skips when the current token still has
more than the refresh buffer of runway, so stacked triggers (proactive
loop + __getattr__ fallback) don't each restart the engine. An
`on_engine_replaced` hook re-arms the watcher on the new PID.
RoutingPrismaWrapper forwards `expected_generation` and skips recreating the
reader when the writer recreate was skipped.
* feat(bedrock): support file content retrieval for batch output files (#30595)
Implements transform_file_content_request and transform_file_content_response
in BedrockFilesConfig so GET /v1/files/{id}/content works for Bedrock batch
files. The request transform resolves the file id (direct s3:// URI or base64
unified id) to its S3 object, validates bucket and key prefix against the
server-configured bucket, and SigV4-signs an S3 GetObject using the same
credential and region resolution as the existing upload path. The credential
and region params are validated into a typed model at the boundary, so the only
untyped values left are the botocore signing primitives.
Also fixes the proxy managed-files path: CredentialLiteLLMParams now carries
s3_bucket_name (previously dropped when building deployment credentials) and
the managed-files hook passes the deployment credential snapshot when routing
afile_content, so unified-id content retrieval works with per-model bucket
config instead of only the AWS_S3_BUCKET_NAME env var.
Preserves managed-file access control: the proxy file-content endpoint now
rejects raw cloud-storage ids (s3://, gs://), which would otherwise skip the
owner/team check that only runs for unified ids and let a caller read another
tenant's batch output by its object key. Managed outputs are reachable only
through their unified file id. The afile_content "not found" error now reports
the caller's unified id rather than the resolved internal S3 URI.
Fixes#16186, #15563
* fix(oci): make Cohere {{trace}} judges work (tool param types + agentic tool-calling continuation) (#30646)
* fix(oci): map Cohere tool array/object params to lowercase builtins
OCI's Cohere backend returns HTTP 500 on a tool parameter typed as a bare
"List", which is what OCI_JSON_TO_PYTHON_TYPES produced for JSON-schema
arrays. MLflow {{trace}} judges trip this: their tools (get_root_span,
get_span) take an attributes_to_fetch array. The lowercase builtins list/dict
are accepted; only the bare "List" 500s ("Dict" happens to be tolerated, but
both are lowercased for consistency).
Verified live against us-chicago-1 (cohere.command-a-03-2025 and
command-latest). Adds a unit regression on the transformed parameterDefinitions
plus a gated integration test exercising an array-param tool end to end.
* fix(oci): make Cohere agentic tool-calling continuation work
Two bugs broke the OCI Cohere tool-calling loop that MLflow {{trace}} judges
drive once a tool has been executed and its result is fed back.
Request side: litellm pulled the last user message into the top-level `message`
and emitted the tool result as a TOOL entry in chatHistory. OCI rejects that
("cannot specify message if the last entry in chat history contains tool
results"), and an empty message alone is rejected too ("message must be at least
1 token long or tool results must be specified"). OCI carries the current turn's
results in a dedicated top-level `toolResults` field. The Cohere transform now
sends an empty message, keeps the user turn in chatHistory, and puts the results
in `toolResults`, matching the langchain-oracle reference. Tool results are no
longer represented as chatHistory entries.
Response side: tool-grounded answers come back with citations carrying
`documentIds` (camelCase) and no `document_ids`, which made the required
`CohereCitation.document_ids` field fail validation and sink the whole response
parse. Those citations are never surfaced, so the field (and CohereSearchQuery's
generation_id) is now optional.
Verified live against us-chicago-1 (cohere.command-a-03-2025 and command-latest),
single and multi-round tool loops. Adds unit regressions on the transformed
request shape and on citation parsing, plus gated integration tests for the
continuation.
* feat: integrate Repelloai Argus guardrail (#30673)
* feat(guardrails): add RepelloAI Argus guardrail integration (#1)
* feat(guardrails): add RepelloAI Argus guardrail integration
Add a new guardrail hook backed by RepelloAI Argus, with dashboard-managed
asset policies enforced via an asset_id and X-API-Key auth.
* fix(guardrails): harden RepelloAI Argus guardrail
- scan streaming responses on output (was bypassing the guardrail)
- log blocked verdicts as guardrail_intervened instead of success
- treat auth/config errors (401/403/404/422) as misconfiguration that
always blocks, not a fail-open-able unreachable error
- default unreachable_fallback to fail_closed and read it directly;
block on unknown/malformed verdicts so an API change can't silently
disable enforcement
- type unreachable_fallback as a Literal, drop the duplicate config model,
expose unreachable_fallback in the config schema, and stop leaking the
raw provider response / exception strings to the client
* fix(guardrails): address RepelloAI Argus review feedback
- support ARGUS_API_KEY (with REPELLOAI_API_KEY fallback)
- make asset_id required in the config model
- normalize unreachable_fallback so only fail_open opens; block on 400 misconfig
- correct the shared unreachable_fallback field description
* docs(guardrails): add RepelloAI Argus docs page and dashboard listing
- add docs page covering config, env vars, modes, verdicts, failure semantics
- list RepelloAI Argus in the Guardrail Garden with provider/logo mappings
- add a regression test for the provider logo and display-name resolution
* fix(guardrails): keep RepelloAI asset_id optional in config model
A required asset_id leaked onto the shared LitellmParams (which inherits
RepelloAIGuardrailConfigModel), breaking validation for every other
guardrail. Keep it optional like sibling models; the guardrail __init__
still raises when asset_id is missing, which is the real enforcement.
* Add comment for last user turn scanning
* feat(guardrails): harden repelloai scanning
* feat(guardrails): expand repelloai scanning to include tool definitions
Add extraction of tool definitions and tool call arguments to the RepelloAI
guardrail scanning. Improves detection coverage by including function schemas
and parameters in the prompt sent to the guardrail service. Also captures
detailed error responses in logs and adds guardrail header to streaming responses.
* refactor(guardrails): fix and harden repelloai schema text extraction
- Fix duplicate text in _iter_schema_text: previously all dict values were
re-queued onto the stack even after scalar/list keys were already extracted
explicitly, causing names/descriptions to appear twice in the scanned prompt
- Extract schema key frozensets to module-level constants so they are not
reconstructed on every call
- Change _iter_schema_text from @classmethod to @staticmethod (cls unused)
- Narrow _call_analyze stage param from str to Literal["prompt", "response"]
- Add HttpxResponse type annotation to _raise_for_config_error
- Add LLMResponseTypes annotation to async_post_call_success_hook response param
* fix(guardrails): resolve pyright type errors in repelloai guardrail
- Narrow async_handler.post return from Response|None to Response with
explicit None guard before calling raise_for_status/json
- Fix list comprehension returning str|None by switching to explicit loop
with isinstance guard so pyright tracks the narrowing
- Cast model_dump() result to Dict since hasattr does not narrow object
type in pyright
* fix(guardrails/repello): include Responses API instructions field in prompt scan
The /v1/responses top-level `instructions` field was not included in
_extract_prompt_text, allowing a caller to bypass guardrail policy checks
by putting blocked content in `instructions` while keeping `input` benign.
* feat: add api_key to config model and read prompt from data dict
* fix(guardrails/repello): plug input_text and tool-call response bypass gaps
Responses API input content parts with type 'input_text' were silently
dropped by build_inspection_messages (which only handles type='text'),
allowing callers to send blocked content via that path without triggering
the pre-call scan. Fix: add _extract_input_text_parts to RepelloAIGuardrail
and call it when walking the Responses API input messages.
Post-call scanning skipped responses whose choices contained only tool_calls
or function_call (message.content=None), letting models put blocked output in
function arguments undetected. Fix: _extract_chat_completion_text now calls
_extract_tool_call_args_from_message on each choice message.
Also replace typing.Dict/List with builtin dict/list to clear TID251 strict
ruff violations introduced by this file.
* fix(guardrails/repello): scan Responses API function_call output arguments
Output items with type 'function_call' in a /v1/responses response were
skipped by _extract_responses_api_text; only 'message' items were walked.
A model could return blocked content in function_call.arguments undetected.
Now extract arguments from function_call output items before scanning.
* refactor(guardrails/repello): clean up typing and remove lint-any workarounds
- Replace Optional[X]/Union[X,Y] with X|None/X|Y union syntax throughout
- Use dict[str, object] instead of bare dict in all signatures
- Remove **kwargs from __init__; declare guardrail_name, event_hook, default_on explicitly
- Replace getattr(litellm_params, ...) with direct attribute access now that LitellmParams inherits RepelloAIGuardrailConfigModel
- Add _event_hook_from_mode() to convert str|list[str]|Mode to typed GuardrailEventHooks
- Use TypeAdapter.validate_json() instead of response.json() + manual dict construction
- Add _is_object_dict/_is_object_list TypeGuard helpers to narrow object types without Any
- Remove cast() workarounds and typed intermediate variables that existed only for the now-removed lint-any CI check
- Drop _AddLiteLLMCallback Protocol; budget has sufficient slack for the one reportUnknownMemberType
- Fix GuardrailConfigModel missing type arg: GuardrailConfigModel[BaseModel]
* fix(guardrails/repello): suppress LIT007 on TypeGuard helpers and add streaming scan-skip warning
- Add guard-ok suppressions to _is_object_dict and _is_object_list to satisfy the LIT007 hard-zero budget gate
- Emit verbose_proxy_logger.warning when the streaming hook finds no inspectable text after assembly, matching observability of pre/post hooks
* refactor: modifications for lint check
* feat: add Pinstripes as an OpenAI-compatible provider (#30567)
* feat: add Pinstripes as an OpenAI-compatible provider
Pinstripes (https://pinstripes.io) is an OpenAI-compatible inference
provider serving open-source models (GLM-4.5-Air, Qwen3, DeepSeek, etc.)
with per-token pricing and no subscriptions.
Changes:
- `litellm/llms/openai_like/providers.json`: register pinstripes with
base_url, api_key_env, and max_completion_tokens→max_tokens mapping
- `litellm/types/utils.py`: add `PINSTRIPES = "pinstripes"` to LlmProviders
- `litellm/constants.py`: add to openai_compatible_providers and
openai_compatible_endpoints lists
- `litellm/litellm_core_utils/get_llm_provider_logic.py`: auto-detect
provider when api_base is "https://pinstripes.io/v1"
- `provider_endpoints_support.json`: document supported endpoints
- `tests/`: 7 unit tests covering provider registration, resolution,
URL auto-detection, api_base override, and Router config
Usage:
import litellm
response = litellm.completion(
model="pinstripes/ps/glm-4.5-air",
messages=[{"role": "user", "content": "Hello"}],
api_key=os.environ["PINSTRIPES_API_KEY"],
)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pinstripes): resolve Greptile P1 review comments
- Add api_base_env: PINSTRIPES_API_BASE to providers.json so env var override works
- Set responses: false in provider_endpoints_support.json — not actually wired up
- Remove docs/my-website/docs/providers/pinstripes.md — belongs in litellm-docs repo
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pinstripes): add api_base_env and correct responses capability
- Add api_base_env: PINSTRIPES_API_BASE to providers.json
- Set responses: false in provider_endpoints_support.json
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pinstripes): wire up Responses API — add supported_endpoints
Adds supported_endpoints: ["/v1/chat/completions", "/v1/responses"] so
JSONProviderRegistry.supports_responses_api returns true correctly,
matching what provider_endpoints_support.json advertises.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(pinstripes): enable embeddings endpoint
Pinstripes serves nomic-embed-text-v1.5 and bge-m3 via /v1/embeddings.
Add /v1/embeddings to supported_endpoints and set embeddings: true.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pinstripes): use 4-space indentation in model_prices_and_context_window.json
Matches the file's existing convention. Flagged by Greptile review.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pinstripes): set a2a: false — A2A protocol not implemented
All comparable JSON-configured providers (tensormesh, parasail, empiriolabs,
libertai, neosantara) have a2a: false. Pinstripes does not implement the
Google A2A protocol, so this should be false to match.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: inference_provider <max@redactedlab.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(rag): attach existing OpenAI file ids (#30628)
* fix(rag): attach existing OpenAI file ids
* chore: use modern typing in rag ingest fix
* chore: retrigger ci
* fix(anthropic-messages): apply cache_control_injection_points on /v1/messages path (#30341)
cache_control_injection_points was only consumed by the chat/completions
prompt-management hook; on the native Anthropic /v1/messages path it was
forwarded unused, so deployment-level cache injection was silently dropped
(cache_creation_input_tokens stayed 0 for Anthropic-native clients).
Add AnthropicCacheControlHook.apply_to_anthropic_messages_request to inject
cache_control at block level for system / tools / message locations (the only
forms /v1/messages accepts), wire it into the native anthropic_messages
handler, and pop the param so it does not leak upstream as an unknown field.
A {location: message, role: system} config is redirected to the top-level
system prompt so the same YAML works on both endpoints.
Injection respects Anthropic's 4-block cache_control limit shared across
system, tools, and messages: client-supplied markers count toward the cap and
are never overwritten, a slot is reserved per Bedrock tool_config point, and
injection stops once the budget is exhausted. Locations this path cannot
represent (tool_config) are forwarded downstream instead of being silently
consumed, mirroring get_chat_completion_prompt's remaining_points pass-through.
Built on litellm_internal_staging. Refs BerriAI/litellm#30293
* fix(proxy): release budget reservation when a request is cancelled mid-flight (#30522)
* fix(proxy): release budget reservation on cancel when no chunk was delivered
The pre-call budget reservation increments the cross-pod spend counter by a
request's worst-case cost, then reconciles it on success (cost callback) or
error (failure hook). A client disconnect or timeout cancels the request and
surfaces as CancelledError / GeneratorExit, which neither path catches, so the
reservation leaks. Under a retry storm the leaked holds accumulate, pin the
counter above real spend, and return spurious 429 "Budget has been exceeded" to
keys whose spend is far below budget; the counter only recovers when its TTL
lapses, so the failure is intermittent and self-healing.
Release the reservation in async_streaming_data_generator (which the Anthropic
and Google SSE generators delegate to) on the (CancelledError, GeneratorExit)
path, alongside the existing max_parallel_requests release. release_budget_
reservation_on_cancel runs under asyncio.shield so it completes despite the
in-progress cancellation, is guarded by the reservation's finalized flag, and
swallows a failing release so it cannot replace the in-flight cancellation.
The refund is gated on whether a chunk reached the client. The flag is set
immediately before the yield, after the slow-path hook await: an async generator
suspends at the yield, so a GeneratorExit on disconnect after a delivered chunk
sees it True (keep the hold), while a cancellation during the slow-path await
leaves it False (refund, nothing sent). A non-streaming cancellation delivers
nothing and a completed non-streaming response is reconciled by the success
callback, so neither needs a release here.
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* fix(proxy): reconcile a cancelled reservation to input cost, not zero
A streaming request cancelled before the first chunk previously reconciled its
reservation to zero and finalized it. But by the time the generator is
consuming the response the provider call was already dispatched, so the input
tokens were billed even though no chunk reached the client, and the
success/failure cost callbacks are skipped on cancellation. Refunding to zero
let a caller send an expensive request and abort pre-token to dodge the input
charge.
Compute the request's input-token cost at reservation time and reconcile the
cancelled reservation to it instead of zero. The worst-case output portion of
the reservation is still released (so a legitimate mid-flight cancellation no
longer pins the counter and 429s the key), while the input the provider already
processed is charged.
---------
Co-authored-by: Bytechoreographer <Bytechoreographer@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* fix(caching): encode object name in GCS cache GET path (#30378)
GCS cache reads always missed when gcs_path was set. The GET methods
interpolated the object name directly into the URL path, while the GCS
JSON API requires it to be URL-encoded (a "/" must be sent as %2F).
With gcs_path configured the object name is "<prefix>/<sha256>", so the
raw slash produced a malformed object path and GCS returned 404. httpx
does not raise on 4xx, so the status_code == 200 check fell through and
get/async_get returned None, silently missing on every read. Without
gcs_path the key has no slash, which is why this went unnoticed.
Wrap the object name with urllib.parse.quote(..., safe="") in get_cache
and async_get_cache. Apply the same encoding to the name= query
parameter in set_cache and async_set_cache so the key written matches
the key read back.
Adds regression tests asserting the GET path and SET query are encoded
(%2F) when gcs_path is set, for both sync and async paths; these fail on
the unpatched code.
Fixes#30377
* chore: add soniox stt-async-v5 model (#30672)
* fix(proxy): include model group aliases in v1 model info (#30626)
* Include model group aliases in v1 model info
* Fix model info alias implementation
* removed extra blank line
* chore: rerun CI
* fix(lint): remove redundant noqa directive in proxy_cli.py
* fix: address greptile review - restore bedrock_mantle auth symbols, guard OCI empty message list, validate DIRECT_URL scheme
* Revert "fix: address greptile review - restore bedrock_mantle auth symbols, guard OCI empty message list, validate DIRECT_URL scheme"
This reverts commit 52c7a07777.
* Revert "fix(anthropic-messages): apply cache_control_injection_points on /v1/messages path (#30341)"
This reverts commit c9e8a177bd.
* Revert "fix(proxy): stop IAM-refresh engine restart from cascading reconnects (#29176) (#30183)"
This reverts commit 85828da695.
* fix(proxy): stop IAM-refresh engine restart from cascading reconnects (#29176) (#30183)
An RDS IAM token refresh recreates the Prisma client, which SIGKILLs the
running query-engine and spawns a new one. That planned kill was
indistinguishable from a crash, and three reconnect paths used two
uncoordinated locks, so a single refresh triggered a cascade of engine
kill/respawn cycles:
1. `_safe_refresh_token` (holds `_reconnection_lock`) -> recreate -> kill old
engine, spawn new one.
2. The engine-death watcher sees that kill, assumes a crash, and calls
`attempt_db_reconnect(force=True)` (a different lock,
`_db_reconnect_lock`) -> recreate again -> kills the fresh engine.
3. In-flight queries failing during the swap are classified as transport
errors and trigger their own `attempt_db_reconnect` -> recreate again.
Fix coordinates planned restarts across the wrapper and the watcher:
- PrismaWrapper records the old engine PID in `_expected_engine_deaths`
before killing it; all four watcher death-detectors (waitpid thread,
pidfd, already-dead probe, os.kill poll) consume that PID and skip the
reconnect instead of treating it as a crash.
- `recreate_prisma_client` now serializes through `_reconnection_lock` and
bumps a monotonic `_engine_generation`. Callers pass `expected_generation`
as an optimistic-lock token, so racing/cascading recreates collapse into a
single restart (losers no-op). This closes the two-lock gap.
- The direct reconnect path probes the writer with SELECT 1 before
recreating; a healthy connection (e.g. engine already replaced by a
refresh) skips the recreate entirely.
- `_safe_refresh_token` coalesces: it skips when the current token still has
more than the refresh buffer of runway, so stacked triggers (proactive
loop + __getattr__ fallback) don't each restart the engine. An
`on_engine_replaced` hook re-arms the watcher on the new PID.
RoutingPrismaWrapper forwards `expected_generation` and skips recreating the
reader when the writer recreate was skipped.
* fix(lint): modernize type annotations in IAM-refresh prisma client files (UP006/UP045)
* Revert "feat(proxy): show session-aggregate cost and duration in request logs (#25708) (#30507)"
This reverts commit f530b2237c.
* Revert "fix(dashscope): treat an explicit 0.0 tier cost as a real price, not missing (#30653)"
This reverts commit 4f58bd0df5.
* Revert "fix(oci): make Cohere {{trace}} judges work (tool param types + agentic tool-calling continuation) (#30646)"
This reverts commit 50f34e0b15.
* Revert "fix(proxy): fail fast on non-PostgreSQL DATABASE_URL instead of hanging on startup (#30366)"
This reverts commit 0544eed6ea.
* fix(bedrock_mantle): restore BedrockMantleAuthMixin and constants removed by routing rewrite
* fix(key management): restore exact /key/list user_id & key_alias matching by default (#30593)
Before substring search was added (commit 33bd570d5e), /key/list matched user_id
and key_alias exactly. That change made admin-authenticated calls substring-match
by default, breaking the prior contract: a caller passing an exact user_id as an
access filter (e.g. an integration scoping to one user with an admin key) then
received other users' keys -- user_id="alice" also returned "alice2",
"alice-test", etc. This is a cross-user key disclosure.
Make substring matching opt-in via a new admin-only substring_matching=true query
param; default to exact, restoring the prior behavior. The dashboard search box
(keyListCall) passes the flag so partial search still works. Non-admins remain
exact and scoped to their own keys.
Updates the proxy-behavior key_alias test to opt in and adds an exact-by-default
guard; adds list_keys unit coverage for the opt-in gate.
---------
Co-authored-by: perseus <51974392+tcconnally@users.noreply.github.com>
Co-authored-by: Hannah Smith <64043506+hannahmadison@users.noreply.github.com>
Co-authored-by: Charlie Patterson <Pattersoncharlesl@gmail.com>
Co-authored-by: Matthew Lapointe <mlapointe@alpha-sense.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: KRISH SONI <67964054+krishvsoni@users.noreply.github.com>
Co-authored-by: Yash Raj Pandey <55940078+devYRPauli@users.noreply.github.com>
Co-authored-by: Nitish Agarwal <1592163+nitishagar@users.noreply.github.com>
Co-authored-by: hcl <chenglunhu@gmail.com>
Co-authored-by: tushar8408 <32977767+tushar8408@users.noreply.github.com>
Co-authored-by: AD Mohanraj <admohanraj@gmail.com>
Co-authored-by: Fede Kamelhar <federico.kamelhar@oracle.com>
Co-authored-by: Lavish Bansal <lavish.bansal619@gmail.com>
Co-authored-by: max-amos <gruffulom@gmail.com>
Co-authored-by: inference_provider <max@redactedlab.com>
Co-authored-by: NK <93352237+Nithish-Yenaganti@users.noreply.github.com>
Co-authored-by: 安妮的心动录 <74543653+anneheartrecord@users.noreply.github.com>
Co-authored-by: Rick <26716961+Bytechoreographer@users.noreply.github.com>
Co-authored-by: Bytechoreographer <Bytechoreographer@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: Burak Ömür <burak.omur.1998@gmail.com>
Co-authored-by: Dan Lemon <daniel.lemon@amazee.io>
Co-authored-by: Vanika Dangi <166420943+vanika02@users.noreply.github.com>
Co-authored-by: Jay Gowdy <130084966+jgowdy-godaddy@users.noreply.github.com>
Drop the two Agent Shin workflows that ran on the pull_request_target
trigger: the PR triage workflow and the review gate. Both were dry-run
and gated behind AGENT_SHIN_ENABLED, so no live automation changes.
The shared scripts under .github/scripts stay in place; four other
Agent Shin workflows still depend on them and run on schedule, dispatch,
and issue events rather than pull_request_target
Budget enforcement reads spend from the cross-pod Redis counter via get_current_spend, which trusted the counter whenever Redis returned a value. A Redis instance that restarts and reloads an older RDB snapshot (the customer's logs repeat "Redis is loading the dataset in memory") comes back with a stale-low counter; that read is a hit, not a clean miss, so the existing DB reseed never ran and a key kept getting admitted even though its recorded spend was already over max_budget. The symptom was recorded spend sitting above the limit while requests kept succeeding.
Read-time enforcement: get_current_spend takes an optional max_budget and, when the counter would admit the request but reads below this caller's last-known recorded spend, re-reads the authoritative spend and enforces against the higher value. The authoritative source depends on the counter: key/team/user/org/team-member read the DB row, per-window budgets aggregate spend logs, and end-user/tag have no DB row so the caller's freshly-loaded recorded spend is used. Healthy primary counters and freshly reset keys stay off the DB path, and the value is cached in-process for a few seconds, so a persistently stale counter drives at most one read per counter per window. When the DB value is higher, the counter is repaired with a monotonic, atomic set-max (RedisCache.async_set_max) so every worker reads the corrected total and a concurrent increment is never clobbered.
Reconcile no longer fails open: when the post-call reservation reconcile found the counter missing or an adjustment that would drive it negative, it deleted the counter and continued (the deletion is what left counters nil/unenforced after a Redis reload). It now reseeds from the DB's lagging authoritative floor instead of deleting; the monotonic set-max can only raise a stale-low counter, and the read-time floor converges to the true total as the spend buffer flushes. The pre-call admission resize path keeps its original fail-closed behavior.
Opt-in strict enforcement: general_settings.fail_closed_budget_enforcement (default False) makes the authoritative re-check run for every budgeted entity (closing the gap where a stale-low counter and a stale-low cached fallback would otherwise both pass the cheap guard), and rejects a request with 503 when the spend backing an admit decision can be verified against neither Redis nor the database. Default behavior is unchanged; the re-check stays bounded by the in-process cache.
Resolves LIT-3772
Cut the legacy "Old Usage" report (?page=usage) over from the switch in
(dashboard)/page.tsx to a path route at (dashboard)/old-usage. The segment is
old-usage rather than usage because the modern usage dashboard (new_usage)
already owns /usage. Adding the MIGRATED_PAGES entry repoints the sidebar item
and redirects existing ?page=usage links to /ui/old-usage.
The report was the switch's catch-all else, so removing it means choosing a new
fallback: collapse the now-redundant explicit api-keys arm into the else so the
main dashboard (UserDashboard) is the default. Unknown ?page= values now land on
the dashboard instead of the Old Usage report, which is the sensible default.
The new route sources identity from useAuthorized() and passes keys={null}: the
key-filter dropdown read the parent's keys state, which was already empty on
direct navigation to ?page=usage, so this preserves that rather than wiring a
paginated key fetch into a deprecated report.
* feat(search): add TinyFish as search provider
Adds TinyFish web search (GET https://api.search.tinyfish.ai) as the
16th search provider in LiteLLM. Follows the BaseSearchConfig pattern
used by other GET-based providers like Brave.
Includes unit tests in tests/test_litellm/ for full patch coverage.
* fix(search/tinyfish): use concrete types to pass any-discipline and ruff UP006/UP045
Replace typing.Dict/List/Optional/Union with modern syntax (dict, list,
X | None) and use concrete type parameters (dict[str, str] for headers,
dict[str, object] for params) to eliminate LIT009 Any-discipline
violations. Move _append_domain_filters to module level to avoid leaking
Any through self.
* fix(search/tinyfish): eliminate Any-typed values for any-discipline gate
Use Pydantic BaseModel and TypeAdapter at httpx/base-class boundaries
to validate untyped inputs (json(), params.get(), bare set). Three
genuine external boundaries annotated with any-ok.
* style: fix black formatting for long line
* fix(search/tinyfish): move any-ok comment to violation line for any-discipline gate
The any-discipline checker matches `# any-ok` comments by line number.
The comment was on the closing-paren line (127) but the violation was
on the call-expression line (126), so the suppression did not apply.
* fix(search/tinyfish): align with approved PR #30158
Drop explicit AND from domain filter query to match the approved
implementation. Set pricing to zero. Rename test to match behavior.
