Commit graph

412 commits

Author SHA1 Message Date
Mateo Wang
d25b58f744
fix(count_tokens): count Anthropic-format requests for OpenAI the way /v1/messages inference converts them (#46759)
* fix(count_tokens): convert Anthropic-format messages for the OpenAI counter the way inference does

* test(count_tokens): check /v1/messages/count_tokens sends OpenAI the input /v1/messages inference sends

* fix(count_tokens): build the Anthropic count request without a cast and sync dashboard API types

* test(count_tokens): compare tools by value in the public api test

* fix(count_tokens): count Anthropic bodies the way /v1/messages inference sends them to OpenAI

Unwrap affinity-encoded reasoning, count the structured-output schema, flatten replayed web search results, join a list system prompt, and answer a message without a role with a 400 before calling OpenAI. messages_format is now internal to the Anthropic count route instead of a public /utils/token_counter field.

* test(count_tokens): expect the image detail the adapter now sends after merging main

* fix(count_tokens): type normalize_native_messages without the unimported Any

On Python 3.10 to 3.13 the annotation is evaluated at import, so the proxy failed to start with NameError

* test(count_tokens): expect the converted Responses input in the budgeted-key count integration test

---------

Co-authored-by: Mrinal Chanshetty <mrinal@berri.ai>
2026-10-16 01:58:46 +00:00
yucheng-berri
627bcab42b
fix(guardrails): honor streaming settings on the Noma v2 guardrail (#46606)
* fix(guardrails): honor streaming settings on the Noma v2 guardrail

The Noma v2 initializer now passes streaming_buffer_until_moderated,
streaming_end_of_stream_only, streaming_sampling_rate and
streaming_buffer_release_on_scan from the guardrail config to
NomaV2Guardrail, so the unified streaming hook applies them. The
constructor validates them, so a custom guardrail class built on
NomaV2Guardrail gets the same checks. Unset keys keep the hook defaults,
and an invalid value is ignored with a warning naming the guardrail, so
the guardrail still loads.

Resolves LIT-9633

* test(guardrails): cover Noma v2 streaming settings across clients, failures and workers

Adds integration cells for the custom-subclass loader, string and invalid
values, unset and false keys, a Noma outage with and without block_failures,
an upstream rejection, n=2 choices, pre_call and non-streaming guardrails,
the OpenAI and Anthropic SDKs (sync and async), stored-guardrail info, a
PATCH while traffic flows, a burst while Noma is down, a slow Noma, and
replaced workers.

Resolves LIT-9633

* test(guardrails): pin the PATCH probes to one worker at a time

Each probe suspends the other worker and opens a fresh connection, so the
test checks that every worker applies the patched setting.

Resolves LIT-9633

* test(guardrails): check sampled scans by count, not window position

/v1/messages hands the streaming hook raw network reads, so where the
default sampling windows fall depends on timing; the base leg caught one
shifted window. Check the scan count and the final full-text scan instead.

Resolves LIT-9633

---------

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
2026-10-15 18:29:05 -07:00
ryan-crabbe-berri
38f3f8a1a9
fix(proxy): cooldown errors carry 429, Sentry starts at boot without request bodies, tracing failures log at ERROR, exporter counters exported (#46344)
* fix(router): carry a 429 status on cooldown and no-deployment errors

RouterRateLimitError and RouterRateLimitErrorBasic had no status_code, so the
proxy answered an all-deployments-cooled-down request as a generic 500 class
error and logged the bug report notice for every cooldown. Both now carry
status_code 429, which the proxy maps to a rate_limit_error and which the
retry policy already treats as retryable

* fix(proxy): start Sentry at config load and never attach request bodies

Sentry only came up inside set_callbacks on the first LLM call, so boot and
background errors were never reported, and general_settings.alerting: [sentry]
always raised Missing SENTRY_DSN because the alerting path read a dead
litellm.utils pin instead of the live SDK. The proxy now initializes Sentry
once while loading the config whenever sentry is a configured callback or
alerting target, the alerting and failure handlers read the live instance, and
max_request_body_size is pinned to never so prompts and completions stay out
of Sentry events

* fix(tracing): log Lens failures at ERROR and export row counters to Prometheus

A tracing store that fails to start, or a Lens service that rejects a batch,
was only logged at WARNING, so operators running at the default ERROR level
never saw tracing silently go dark. Both now log at ERROR and name the lens
store. The exporter's rows_written and rows_dropped tallies were never
exported, so the two counts are now Prometheus counters
litellm_lens_export_rows_written_total and
litellm_lens_export_rows_dropped_total, registered lazily on the default
registry like the other proxy-level counters and charted on the all-metrics
Grafana dashboard

* test(proxy): drop the litellm import the alerting tests no longer use

* fix(proxy): start Sentry once a DSN is set, from any config source

Boot-time init used to lock Sentry in even with no SENTRY_DSN, so a DSN loaded later from DB environment_variables was never picked up. initialize_sentry now skips when no DSN is set and re-inits when the DSN changes. alerting_handler calls it too, so alerting: [sentry] set through the DB works. Drops the litellm_settings.callbacks check since that config fails to load with sentry in it

* fix(sentry): keep stack frame locals out of events unless PII is opted in

Frame locals carried prompts (messages, request bodies, provider options) into every error event. include_local_variables now follows SENTRY_SEND_DEFAULT_PII

* test(router): drop the test that only pinned the 429 class attribute

* fix(proxy): start Sentry at boot when it is only an input callback

* fix(proxy): keep Sentry init and alerting within the strict ruff and basedpyright ceilings

---------

Co-authored-by: yuneng-jiang <yuneng@berri.ai>
2026-10-16 00:53:52 +00:00
tin-berri
9c62573005
fix(proxy): limit gzip to dashboard analytics and offload compression (#46712)
* fix(proxy): limit gzip to dashboard analytics and offload compression

* fix(proxy): preserve gzip for customer analytics aliases
2026-10-15 17:27:03 -07:00
devin-ai-integration[bot]
77c22a4c01
feat(proxy): add agent_access_default_deny for least-privilege agent access (#43979)
* feat(proxy): add require_key_agent_access_defined for least-privilege agent access

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): align A2A model visibility assertions with supported routes

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): keep A2A model entries on their existing routes

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): point the listing model at the harness upstream

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): coerce require_key_agent_access_defined like the settings validator

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): inject agent access lookups instead of patching the handler

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(proxy): rename require_key_agent_access_defined to agent_access_default_deny

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: ryan <ryan@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 16:49:26 -07:00
joshua-berri
440744f967
feat(mcp): enable verified stateless protocol capabilities (#46264)
* feat(mcp): advertise verified stateless capabilities

* fix(mcp): honor rate limits during capability discovery

* test(mcp): cover protocol interactions and scoped enablement rollback

* fix(mcp): preserve legacy capabilities and bound discovery probes

* fix(mcp): keep discovery results single-assignment

* ci(mcp): distribute acceptance cases across existing workers

* ci: balance MCP integration cases across idle workers

* ci: isolate MCP interaction acceptance workload

* test(mcp): acknowledge fixture notifications after dispatch

* test(mcp): drain session dispatch before fixture deletion

* test(mcp): preserve deletion of streaming fixture requests

---------

Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>
2026-10-15 23:18:18 +00:00
devin-ai-integration[bot]
8007773ec5
fix(mcp): request offline access from Google upstream OAuth providers (#41197)
* fix(mcp): request offline access from Google upstream OAuth providers

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style(mcp): format authorize_with_server redirect

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(mcp): type empty OAuth authorization defaults

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>
2026-10-15 16:08:36 -07:00
devin-ai-integration[bot]
1ddaa54793
fix(mcp): scope gateway OAuth consent to x-mcp-servers and add explicit scope setting (#44957)
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:58:34 -07:00
Yassin Kortam
a02f1b4939
fix(proxy): preserve AWS session tokens for RDS IAM auth (#46559)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 22:51:39 +00:00
Yassin Kortam
e4df98272e
fix(mcp): resolve /mcp/proxy tool_id from the owning server instead of relisting every server (#46545)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 22:46:50 +00:00
Yassin Kortam
ba3fce2bda
feat(ui): scope the MCP server selector to the team, user and access groups it edits (#46565)
GET /v1/mcp/server takes an optional user_id (admin, or the user themselves) and returns the union of the servers each of that user's teams reaches plus allow_all_keys servers. A user in no team gets the unscoped list, a deleted team still listed on the user is skipped, an unknown user is a 404 and a restricted virtual key is refused like for team_id. team_id keeps precedence when both are passed.

The dashboard MCPServerSelector passes the team and user it edits (key edit sends keyData.team_id and user_id, key create sends the picked team and owner, user edit sends the user) and narrows the server options to members of the access groups selected in the same control, keeping allow_all_keys servers and servers already granted so they can still be removed.

Resolves LIT-7784

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:16:05 -07:00
Yassin Kortam
92fb55522a
feat(mcp): add mcp_disabled_capabilities to stop advertising prompts and resources (#46563)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:15:40 -07:00
Yassin Kortam
82977e2465
fix(mcp): accept validated JWT subjects after virtual-key mapping (#46549)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:15:20 -07:00
Yassin Kortam
04645d0a07
fix(mcp): persist the first DCR client for config-declared servers regardless of who registers (#46544)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:14:43 -07:00
Yassin Kortam
40e27812a7
fix(proxy): route SSO token exchange and userinfo calls through litellm's httpx client (#46547)
fastapi_sso opens a bare httpx.AsyncClient for the non-PKCE token exchange and
userinfo call, so litellm_settings.ssl_verify and SSL_VERIFY never applied and
an IdP on an internal CA failed with an opaque 503. A LiteLLMHttpClientSSO mixin
replays that exchange on litellm's shared SSO client for the generic, Google and
Microsoft providers and surfaces IdP connection and TLS failures as a 401
ProxyException naming the endpoint.

Resolves LIT-9445

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:14:25 -07:00
Yassin Kortam
40187731b7
fix(proxy): chain RDS IAM DB auth through the IRSA role when the DB role trusts only the pod role (#46540)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 15:13:40 -07:00
rameswaran-mohan
e65e5abc4e
feat(proxy): name the successor model for deprecating deployments (#41670)
* feat(proxy): name the successor model for deprecating deployments

* chore(ui): add successor_model to the generated deprecation api types

* fix(proxy): keep the cost map successor when a deployment overrides only the date

* fix(proxy): read the cost map successor from metadata.successor

The cost map schema rejects a top-level successor_model key, and curated
entries already carry the successor under metadata.successor. Read that key,
and look it up even when the cost map entry has no deprecation date, so a
deployment that sets only its own date still names the successor.

* fix(proxy): keep the first deployment when deduping, let a blank successor hide the cost map one, and name a served successor by its model group

* fix(proxy): name only the deployment's own successor_model, since cost map successors are LiteLLM ids rather than served model names

* fix(proxy): leave out a successor_model the deployment's callers cannot call, with a warning

* fix(proxy): report successor_model as the admin set it and only warn when no model matches it

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 14:50:14 -07:00
Dushyant Acharya
06efa5de85
fix(proxy): honor disable_end_user_cost_tracking in spend logs and end-user tables (#40945)
* fix(proxy): strictly honor disable_end_user_cost_tracking in SpendLogs

* fix(proxy): drop end-user id on failed requests and ClickHouse rows when end-user cost tracking is off

* fix(clickhouse): drop the end-user id from spend log metadata when end-user cost tracking is off

* test(spend): cover disable_end_user_cost_tracking across endpoints, failures, cache hits and chaos

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 21:48:20 +00:00
joshua-berri
4a4a0e8d3c
feat(mcp): relay authorized modern upstream subscriptions (#46153)
* feat(mcp): relay authorized modern upstream subscriptions

* fix(mcp): close subscriptions when caller identity changes

* fix(mcp): preserve subscription scope and setup changes

* fix(mcp): preserve subscriptions across managed token renewal

* fix(mcp): forward legacy notifications with subscription-owned authorization

* test(mcp): verify modern method boundaries and unsupported legacy resources

* test(mcp): model SDK context fields in cleanup regressions

---------

Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>
2026-10-15 16:16:49 -04:00
devin-ai-integration[bot]
da2f5a498f
feat(agents): support Databricks Agent Platform agents in the agent gateway (#45681)
* feat(agents): support Databricks Agent Platform agents in the agent gateway

Add a databricks_agent provider that speaks the MLflow ResponsesAgent wire
(Responses-shaped input, output_text items, output_text.delta SSE) to Model
Serving endpoints (/invocations or the unified /serving-endpoints/responses)
and Databricks Apps (/responses), with a PAT or OAuth M2M client credentials

Register it through the agents config block or the Admin UI agent catalog and
call it through /a2a/<agent> (message/send, message/stream) or model:
a2a/<agent> chat completions. The chat route now runs every completion-bridge
agent through its own provider, and attaches the minted Databricks OAuth token
for both bridge and URL agents. Consumed OAuth settings never reach the
provider call

* fix(agents): harden databricks_agent input, output, and OAuth handling

Non-text content parts answer 400 unless drop_params is set, a reply without
an output list answers 502, flat OAuth fields resolve an os.environ api_base,
the bridge debug log no longer echoes the request model, routing tests stub
only the HTTP boundary, and the catalog description fits the dropdown

* fix(agents): merge agent and client extra_headers on the a2a chat route, and reject an empty databricks_oauth block

* fix(agents): bridge only databricks_agent agents on the a2a chat route, keep the card url over a client api_base, and require workspace_url for a Databricks App

* refactor(agents): read the a2a chat bridge providers from a constants set instead of branching on a provider name

* fix(databricks_agent): let the configured credential win, reject malformed client extra_headers, and keep a missing endpoint name empty

* test(agents): drive the flat OAuth a2a send through the real bridge

* fix(agents): keep an empty databricks_oauth block ignored on url agents, as before this change

* fix(agents): accept bare App hosts, env service principals, and os.environ refs on Databricks agents

* fix(databricks_agent): address review caveats on chat bridging, params, and auth

Map max_tokens and max_completion_tokens to max_output_tokens and pass
temperature, top_p, and user, so /v1/messages works without drop_params.
Send A2A message metadata only with string values, answering 400 or
dropping the rest under drop_params. Join message items with a blank line
in both stream and non-stream replies. Cache the env service principal
token until shortly before it expires. Keep databricks_agent replies out
of the response cache.

On the chat bridge, let request fields win over the agent's stored params
while pinning the agent's api_base and api_key, and apply the agent's
static_headers between client and agent extra_headers, as /a2a does.
Resolve os.environ/ only for databricks_agent api_base and api_key instead
of every bridge provider. Ignore an unusable databricks_oauth block on URL
agents on chat, as at the merge base, instead of answering 400.

* test(internal_context): list the databricks agent token cache as process-local

* fix(databricks_agent): keep the agent's endpoint, input, and target out of client control

extra_body model and input answer 400, or are dropped under drop_params.
A client api_base or base_url never replaces the agent's card URL on the
bridge. Chat to a URL agent keeps its merge-base call, and an incomplete
databricks_oauth block on a URL agent keeps its merge-base ValueError.

* test(databricks): expect the merge-base 400 for a client api_base on agent chat

* fix(databricks): keep agent-owned inputs and identity headers out of a chat caller's reach

* fix(databricks): bound the agent-over-caller merge to two levels so it needs no recursion

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 12:42:06 -07:00
yucheng-berri
d9b5d9e19f
Revert "feat(proxy): add LITELLM_FIPS_MODE startup gate with provider assertion and loud password migration failure (#42700)" (#46740)
This reverts commit 1238cfe90f.

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
2026-10-15 12:39:14 -07:00
Mateo Wang
1938f537bf
fix(decisions): read a deployment's own supports_box_questions flag before the cost map (#46696)
* fix(decisions): read a deployment's own supports_box_questions flag before the cost map

The box-question check only read the shared cost-map row and required a decisions mode there, so an OpenAI-format deployment whose model_info sets supports_box_questions was refused with a 400, which kept the wire test from #46633 red on main

* fix(decisions): keep the box flag on its deployment and out of request bodies

A model_info that is not a plain dict no longer fails the call, the proxy
decisions endpoint drops a caller-sent model_info, and the router stops
copying supports_box_questions onto the shared cost-map key.

* fix(decisions): keep the box flag shared with same-model deployments like main

Scoping supports_box_questions to one deployment turned box questions on an unflagged sibling of the same backend model from reaching the provider into a 400. Siblings inherit the flag through the shared cost-map row again, as they do on main. Also formats two new tests.

* test(decisions): pin box flag inheritance by an unflagged same-model deployment

* test(decisions): audit box-question deployment flag across providers, routes, and chaos cases
2026-10-15 12:34:36 -07:00
Kerry Lu
11e9fcc033
fix(cost): price bridged /v1/messages reasoning tokens from the chat completion, not the served Anthropic body (#46726)
* fix(cost): price bridged /v1/messages reasoning tokens from the chat completion, not the served Anthropic body

* fix(cost): keep the type gate flat for the bridged /v1/messages billing path

---------

Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 19:10:33 +00:00
Mateo Wang
67d75522ed
fix(test): wait for the wedged Redis to be reached instead of a fixed 0.1s sleep in team roster sync tests (#46727)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 18:54:26 +00:00
joshua-berri
1fc456917f
fix(mcp): preserve progress and cancel upstream work promptly (#46134)
* fix(mcp): preserve progress and cancel upstream work promptly

* fix(mcp): apply output guardrails to progress messages

---------

Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com>
2026-10-15 14:53:36 -04:00
devin-ai-integration[bot]
e344dbd8db
feat(proxy): split Azure PTU deployments across teams with per-team PTU ceilings and PTU-hour reporting (#43043)
* feat(proxy): split Azure PTU deployments across teams by share

A PTU deployment's model_info takes ptu_shares (team_id -> whole PTUs adding up to
ptu_count) in place of a single team_id. With LITELLM_ENABLE_PTU_COST_ATTRIBUTION on,
routing hides the deployment from teams holding no share, the v3 limiter enforces each
share as a per-team TPM ceiling from Azure's per-model TPM-per-PTU sizing, the daily
flat-cost rollup splits the hourly cost by share, and /team/daily/activity plus the Team
Usage page report PTU-hours next to tokens.

* fix(proxy): weight cached input in PTU ceilings and size team-scoped deployments by public name

The PTU flag is read from the process environment on every check instead of
through the secret-manager path, so a proxy with a hosted secret manager does
not pay a round trip per request. A team's ceiling now carries the model's
cached-input ratio and settlement charges cache reads at that ratio, matching
how Azure sizes a PTU. A deployment registered for one team is found by its
team_public_model_name for PTU-hours and the ceiling, since its model_name is
rewritten to a unique internal name. ptu_shares are StrictInt on ModelInfo and
parsed_ptu_shares refuses booleans, strings, and non-string team ids, a
fractional ptu_count reserves nothing, and models_processed counts distinct
deployments rather than holdings.

* fix(proxy): reserve PTU ceilings in normalized tokens, keep share routing flag-independent, and warn only shared or Azure reservations

* fix(proxy): size the uncapped output floor against the PTU share in raw output tokens and escape the exported team id

* fix(ptu): refuse ptu_shares naming a team that does not exist

* refactor(ptu): keep Azure detection under llms/azure and check share teams with one query

* fix(proxy): drop the reverted TeamIdSearchFilter import after merging main

Main reverted the team key search change that added TeamIdSearchFilter, so the PTU share team check types its where clause locally

* fix(proxy): chunk the ptu_shares team lookup under the IN-list bound

* fix(proxy): count a request naming a shared PTU deployment directly against its group's ceiling

* fix(proxy): resolve every name a shared PTU deployment is served under to its group's ceiling

* fix(ptu): refuse ptu_shares declared without ptu_count and cost_per_ptu_per_hour

* fix(ui): seed total_ptu_hours in the empty daily activity metadata

* fix(ptu): size usage rows by the name the request used

* fix(ptu): size a team's usage rows by the deployment it is served from

* fix(ptu): never size a team's usage row by another team's reservation

* fix(ptu): reserve an uncapped request against the cap the proxy writes, not its prompt length

* fix(ptu): read a share map only through the terms registration requires

A ptu_shares map stored without ptu_count, cost_per_ptu_per_hour and
ptu_effective_from, or one that does not add up to ptu_count, is refused at
registration but was enforced once loaded: every other team got the 400 and
the share holder a ceiling while no flat cost accrued. _deployment_shares now
reads the shares through ptu_terms, so such a row reserves nothing, the same
as before the map was read.

* fix(ptu): keep a declared split as the access rule and check a config split at boot with the flag off

6fb24d1d read ptu_shares through the pricing terms so a termless map reserved
nothing, but with the flag off the router skips ptu_config_error for config.yaml
entries, so such an entry loaded and served every team, against the rule that a
declared split restricts access whether or not cost attribution is on.
_deployment_shares reads the declared map again, and the router now raises
ptu_config_error for a config-sourced entry declaring ptu_shares regardless of
the flag, so a malformed split is refused at boot instead of being honoured or
ignored silently.

* fix(ptu): charge wildcard-served names, pass-through usage, and team-less settlements against the team's PTU ceiling

A name served by a wildcard route now resolves to the shared deployment behind it, so the
limiter's ceiling and the team daily activity sizing both find it. Pass-through responses
settle the PTU counter from combined_usage_object in Azure-normalized tokens, and a
reservation taken at admission is settled even when the success metadata lost the team.

* fix(ptu): resolve a wildcard-served name to the one pattern the router picks, and a deployment id before any wildcard

A team's wildcard reservation behind an open proxy-wide * route was charged and sized for traffic the * route served, and naming a shared deployment by id next to a catch-all wildcard escaped its per-team ceiling. Router.wildcard_route_deployments now owns the most-specific-proxy-wide-else-team precedence, and both the limiter and the consumption page resolve through it after listed rows and deployment ids.

* test(router): pin the wildcard route precedence that PTU sizing and the router share

* fix(proxy): accept whole-number PTU shares written as floats, as ptu_count already does

A share of 2.0 now reads as 2 on POST /model/new and in config.yaml, where it was
refused with a 422 and dropped at load. Fractional, infinite, boolean and string
shares stay refused. Adds unit tests for the malformed-rate, provider-over-prefix,
zero-token Responses usage, fractional-count and sizing-warning paths.

* fix(proxy): settle team PTU reservations in their own minute and keep billed PTU days when shares move

* fix(proxy): write each PTU deployment day's team charges in one transaction

The backfill counts a deployment day as priced once any team's row exists for it,
so a rollup that wrote team A's share and lost team C's left team C unbilled for
good. Each deployment day's team rows now go through one Prisma batch with the
retry around the whole batch, so a day is fully written or not written at all and
the next backfill prices it for every team.

* fix(proxy): read the PTU flag from a secret manager, serve share holders from their share, and refuse unfittable calls and share-holding team deletes

* test(router): list the cached PTU ceiling helpers in the router coverage check

* fix(proxy): read the PTU flag only for share holders, guard org and SCIM team deletes, keep share holders on their shared deployment through retries and the scheduler, and date PTU-hours by the terms in force

* fix(proxy): bill a rerun PTU day to the current share holders alone

* fix(proxy): replace a PTU day's rows by day and deployment, not a negated team list

* fix(proxy): read the PTU flag from the secret manager first, like get_secret

* fix(router): scope retry health lookups to the caller only for PTU share holders

* fix(router): move the share-holder retry check into ptu_shares

Adds ptu_hours and total_ptu_hours to the daily activity integration goldens and fixtures, since every route now reports them

* test(integration): cover PTU shares across routing, delete guards, cost attribution and config regex timing

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 18:44:30 +00:00
moyai-devin-berriai[bot]
3151c47960
fix(guardrails): resolve decision models in caller team scope (#46085)
* fix(guardrails): resolve decision and judge models in caller team scope

* fix(guardrails): scope guardrail model calls to the caller's team only where it owns the deployment

Read the team only from the auth object the proxy attached to the request, never from caller JSON,
and use it only when the router's route to the guardrail model for that team reaches a deployment a
teamless caller cannot. Shared names, aliases, legacy team tags and wildcards keep resolving and
billing as before. Decision calls pass the team in litellm_metadata only when it is used, so the
logged model group stays intact.

Adds integration cells for chat, responses and messages, forged team ids, a team deployment that
shares a name with a shared model or wildcard, and billing, plus unit cases for legacy team tags
and aliases.

* fix(guardrails): route team guardrail calls to the team deployment without charging the team

Guardrail calls on a team's own model now go to the deployment the router picks for that
team, by its id, with no team on the call. Like every other guardrail call, they write no
spend row and add nothing to the team's or the key's spend

* fix(guardrails): pin the team deployment only for the judge guardrail, not shadow eval judge calls

* fix(guardrails): keep the teamless route when only a team wildcard covers the guardrail model

* refactor(guardrails): scope the team model fix to the decision model guardrail only

* fix(guardrails): send decision calls on a team's own model with the team, and keep team wildcards out

The decision call on a team's own model now carries the caller's team instead of being pinned to a
deployment id, so it is charged to that team and goes through the team's normal routing: an access
window that reserves the deployment for the team lets the call through, and pre-call checks see the
input and skip a deployment too small for it.

A team deployment listed under a wildcard public name, such as team_public_model_name openai/*, no
longer captures a guardrail model the team never named, whatever model it points at.

Adds unit and integration cells for the reserved deployment, mixed context windows under
enable_pre_call_checks, a team wildcard name over a fixed model, and the owner team's spend.

* fix(guardrails): log the owner team's name on decision calls charged to it

The decision call on a team's own model now carries the team alias beside the team id, so the
spend row and the Logs page name the team the call was charged to.

* fix(decision_model): use the caller's team only for names nothing else serves

A team model named like a shared deployment, a shared wildcard or an SDK
public name took over the guardrail's decision calls for that team, so a
team admin could point a proxy-wide guardrail at their own endpoint. The
team is now used only when a caller without a team reaches no model under
the name.

* refactor(decision_model): drop the team route subset check the served check covers

Once nothing serves the name without a team, every deployment a caller
without a team can reach is a wildcard, so the subset check only ever
rejected an empty team route. Pin team wildcards over a name nothing else
serves.

* fix(decision_model): use the caller's team only when judge_target finds nothing without a team

The served check rebuilt the router's rules and missed a shared wildcard whose
provider comes from custom_llm_provider, so a team model under the guardrail's
name took over that team's decision calls. Ask judge_target, the same lookup the
teamless dispatch makes, instead

---------

Co-authored-by: moyai-devin-berriai[bot] <336287033+moyai-devin-berriai[bot]@users.noreply.github.com>
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
2026-10-15 11:43:36 -07:00
devin-ai-integration[bot]
30ada9d26a
feat(batches): store each batch line's request and response in S3 and GCS (#41691)
* feat(batches): emit per-line JSONL batch records to callbacks

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): only emit line items for final batches

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* chore(deps): bump soupsieve to 2.9.2 for GHSA-gjv8-xp57-g29c and GHSA-j934-xhv5-fg8f

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style(batches): satisfy ruff format for line item logging

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* chore(ui): regenerate schema.d.ts for store_batch_line_items_in_callbacks

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): cover line-item edge shapes and general settings propagation

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): keep deployment credentials out of callback-visible params

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(batches): declare credential transport attribute on Logging

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): integration contract for per-line batch callback events

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): resolve store_batch_line_items_in_callbacks through the settings store

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): assert per-line events beside the aggregate and create events

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): drop resurrected use_legacy_interactions_schema shim from merge

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): assert line item events carry no credentials

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): reset batch line-item flag when the setting is absent

Removing store_batch_line_items_in_callbacks from the DB general settings left the module flag at its previous value because the effect early-returned when the key was neither in the DB nor owned by YAML. The proxy owns the global, so an absent resolved value now writes False.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): map anthropic batch lines through the anthropic message transformer

Anthropic result lines carry a message-shaped body, so ModelResponse(**body) produced empty choices and a usage key that blocked the batch-rate usage attach. Extract the existing AnthropicResponse -> ModelResponse conversion used for /v1/messages logging into anthropic_message_to_model_response and reuse it for anthropic line items.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style: tag the anthropic result cast with a cast-ok reason

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style: shorten cast-ok reason so ruff format passes

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): skip line-item callbacks for providers without a line reconstruction

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): reconstruct bedrock and mistral batch lines through their provider transformations

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style: wrap widened provider literals so ruff format passes

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): pair bedrock lines by recordId and type them from the reconstructed response

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): keep line item events out of proxy limiters and strip credentials from child params

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): keep cast-ok tags on the flagged cast lines for the discipline gate

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): skip failed line item events in parallel request limiter failure hooks

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): tolerate lifecycle spend rows when asserting no line item rows

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): place mutable-ok tags on the lines the discipline gate flags

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): skip router budget accounting for batch line item events

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): keep anthropic line errors and skip native vertex batch rows

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): restore test-quality tags on line item tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test: move batch line-item unit test to tests/unit after merging main

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): emit batch line-item callbacks once per batch

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): release line-item claim when fan-out emitted nothing

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): make the line-item claim release ownership-safe

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): keep bodyless failed batch lines reaching callbacks

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(logging): seed batch line hidden params in get_hidden_params defaults

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* perf(batches): reuse fetched batch result files for line-item logging

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): release line-item claim when nothing was emitted

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): type batch line-item callback sites to satisfy basedpyright budget

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style: wrap batch hidden-params cast for ruff format

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): reason suppressions for batch line-item lint deltas

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* chore: drop stale mutable-ok suppressions after LIT002 removal

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(batches): skip batch line-item events in ClickHouse spend sink and router quota counters (#44486)

* fix(batches): skip batch line-item events in ClickHouse spend sink and router quota counters

Batch line-item callbacks (call_type=acompletion + litellm_params.batch_parent_id)
bypassed the call-type-only batch guards:

- ClickHouseSpendLogger wrote one spend row per line on top of the aggregate
  aretrieve_batch row, billing every batch twice with the flag on.
- Router deployment callbacks and the routing-strategy usage handlers charged the
  historical batch's tokens/rpm to the live TPM/RPM counters, so after
  Router.aretrieve_batch the next chat raised RouterRateLimitError.

Skip these events wherever the aggregate batch retrieve is already skipped.

* fix(logging): keep internal litellm_params authoritative in model_call_details

A request body key named litellm_params lands in optional_params, and
update_environment_variables merged **optional_params after the internal
entry, so a caller could overwrite the logging kwargs' litellm_params and
forge markers like batch_parent_id. Live-reproduced: a Gemini chat whose
body carried {"litellm_params": {"batch_parent_id": ...}} returned 200
with no ClickHouse spend row. Re-assert the internal litellm_params after
the merge so every sink (ClickHouse, Postgres, router quota counters)
reads the same trusted value, and assert the aggregate aretrieve_batch
row still writes in the ClickHouse line-item test (review finding).

* fix(clickhouse): skip failed batch line items in the spend sink too

A failed JSONL line is part of the aggregate aretrieve_batch row's
request counts; writing it its own spend_logs row inflated request
counts with the line-item flag on. Extend the batch line-item guard to
the failure handler (review finding) and pin both directions: a failed
line item writes no row, a genuine live failure still does.

* fix(batches): declare batch_line_items service family on claim calls

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(integrations): keep batch line items out of the built-in metering sinks

With store_batch_line_items_in_callbacks on, per-line batch events carry a
real response_cost and reached six metering sinks that lacked the
is_batch_line_item_event guard, so a completed batch metered aggregate +
per-line (roughly 2x true spend): prometheus (litellm_spend_metric and
request counters), openmeter, lago, datadog cost management (FOCUS
BilledCost), newrelic metrics, and the OTel v1/v2 gen_ai.usage.cost
metrics. Skip line-item events in each sink's success/failure metering
entry points, matching the guards already on the Postgres and ClickHouse
spend sinks. OTel spans for line items are still emitted; only their
cost/token metrics are skipped. Tests drive real sink instances on the
real dispatch lists through a completed 2-line batch and assert each
sink meters exactly the aggregate.

* style: format metering-sinks test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(otel): skip synthetic line-item durations in v2 metrics; isolate prometheus test

Follow-ups from review on the sink guards: record_failure() now skips
batch line items too (a failed line's interval measures retrieval and
emission, not its model call), and the prometheus guard test snapshots
and restores the process-wide registry collectors instead of leaving
them unregistered. The OTel v2 test is now a flag on/off A/B over the
whole metric snapshot: cost and usage values must match exactly and no
metric may gain datapoints with the flag on.

* chore: finish main merge conflict resolution for batch line items

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style: sort imports in litellm_logging after main merge

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(batches): use the public hook class names main now exports

* fix(batches): only the batch writer can mark a callback event as a line item

amoderation, transcription and speech build litellm_params from every request kwarg,
so a body field named batch_parent_id reached Logging.litellm_params and every
spend, budget and rate-limit hook skipped the request. update_environment_variables
now drops an incoming batch_parent_id; the line-item writer sets it through
Logging.mark_batch_line_item. Batch line hidden params are emitted only when set.

* chore(batches): keep the lint gates within main's ceilings after the merge

Typed the helpers main now types (Mapping litellm_params, Any Span), replaced the
banned cast with a literal match, dropped isinstance checks main made redundant,
and moved test-quality reasons onto the lines the gate reads.

* fix(anthropic): read the message id off the validated message

The anthropic_messages logging path can hand over an already parsed message object,
which has no .get; main read its id through getattr, so take it from the validated
AnthropicResponse instead.

* fix(batches): an unreadable error file no longer drops the output line events

Costing counts an error file it could not fetch as no failed lines; line logging
refetched it and the raise aborted the whole fan-out, so the successful lines were
never emitted. The error file now reads as empty with a warning.

* test(batches): pin billing for batch_parent_id on every endpoint and value shape

Chat completions, embeddings, responses and messages join moderations, speech and
transcriptions, and speech is driven with an empty, int, list, object and 5 KB value.

* test(batches): bill every request of a concurrent burst mixing forged and plain bodies

* revert: keep the line-item fan-out all-or-nothing on an unreadable error file

85fc4498cc emitted the output lines and kept the batch claim when the error file
could not be read, so its failed lines were never retried. Raising releases the
claim and the next retrieve retries the whole fan-out.

* test(batches): pin the all-or-nothing retry and warm the burst model first

An unreadable error file emits no lines and the next retrieve emits all of them.
The burst cell drives one speech model after a warm-up request so a cold worker
cannot fail it, and waits for the batched key spend.

* fix(batches): run the line fan-out outside the aggregate event's deadline

The logging worker cancels a callback coroutine after its per-callback
deadline, and the line fan-out ran inside the aggregate aretrieve_batch event
before its callbacks, so a large batch or a slow sink could cancel the
aggregate billing event. The fan-out now runs in its own task, built from a
copy of the parent's litellm_params taken before the aggregate callbacks
write their request-local markers.

Anthropic keeps no input file and reports input_file_id "None", which the
fan-out fetched and failed on, so no Anthropic line ever arrived. That id is
now treated as no input file.

* fix(batches): let running line fan-outs finish before proxy shutdown closes their clients

A started fan-out keeps its batch claim, so a shutdown that cut it short
skipped the unsent lines until the claim expired. proxy_shutdown_event now
waits up to MAX_TIME_TO_CLEAR_QUEUE for them first. Also replace a test's
type: ignore with an isinstance check.

* fix(batches): keep batch line fields off callback kwargs and skip fan-outs at shutdown

Line bodies were spread into the callback kwargs, so a line's metadata could settle router rate limit reservations; they now stay in optional_params, and the router rate limit and prompt caching hooks skip line events.
A retrieve logged after the shutdown drain, or by the logging worker's exit flush, no longer starts a fan-out its loop would destroy while it holds the batch claim.
The output file is fetched before the error file again.

* fix(batches): log batch lines under the retrieve's callback settings and keep them out of alerting and shadow eval

Line events inherit the retrieve request's key and team callback settings, so turn_off_message_logging and per-team logging credentials apply to them, and they keep the system prompt in the logged messages.
Shadow eval, Datadog metrics, Slack daily reports and PagerDuty skip line events, since the batch API served them and the aggregate event already counts the batch.

* test(batches): line events follow the key's message logging opt-out

* test(batches): line events follow team logging settings, keep the line system prompt and survive a restart once

* fix(batches): keep in-memory line claims for 10,000 batches and pin managed batch emission across poller and retrieves

* Keep batch line unit tests in-process and drop repeated per-sink comments

* Share one batch provider alias across batch_utils and line item logging

* Report Bedrock line status codes, skip unknown Bedrock lines without raising, fetch the input file after the native Vertex check

* Read a swallowed Redis claim failure as unavailable, price unpriceable lines at zero, keep the OTel failure docstring

* Call handle_completed_batch when line items are off, keep a cache test from leaking Redis into the line claim cache, pin an unpriceable line's zero cost on the callback kwargs

* Hand the cost poller's credential snapshot to line item file reads, so a managed Bedrock batch's lines read its input from the deployment bucket

* Log batch lines through the sync callbacks a direct async call runs, keep failed lines out of router cooldown counts, and emit an error line whose body is text

* fix(batches): log failed Bedrock embedding lines as embeddings with their input

A Bedrock batch input record carries no url, so a failed Titan v2 line fell back to acompletion and its
inputText never reached the event messages. The failed line now takes aembedding from the deployment
model and the record's inputText is the line input

* fix(batches): keep a Bedrock line's system prompt in its logged messages

Bedrock batch input records hold the system prompt as content blocks, which logging only reads off the kwargs as text, so Claude and Nova lines dropped it

* feat(batches): store per-line batch requests and responses in S3/GCS via batch_line_item_callbacks

Replace the per-line logging path with a dedicated hook. When the hourly batch cost
poller finishes a managed batch, it pairs every output and error line with its input
line, prices each line, and hands one payload to every logger listed in
litellm_settings.batch_line_item_callbacks. s3_v2 and gcs_bucket write it as one
NDJSON object per batch under batch_line_items/<day>/<batch id>.jsonl.

Bodies are dropped and the header kept when the creator key or team, the global
setting, or the logger itself turns off message logging, and when the creator can
no longer be found. A failed upload is logged and never blocks spend tracking.

* fix(batches): store batch line items after the batch is billed and retired

Send a billed batch's lines only after its row is marked complete, so a slow or
failing sink never holds a claimed batch open. Skip reading the input file when
the bodies are dropped anyway, still send the error lines of a batch whose output
file is gone, and end every NDJSON record with a newline.

* test(batches): cover team-level and deleted-key redaction of batch line items

* fix(batches): store batch line items in the background so a hung bucket never holds up billing

The poller now retires a batch first and hands its line items to a per-worker background store that runs one batch at a time. A slow, hung or failing bucket no longer delays billing or retiring the other batches in the poll cycle. While a poll cycle's worth of batches is still waiting to store, the next batch's lines are dropped with an error.

* fix(batches): store an unbilled batch's line items only once it is retired

When retiring an expired, cancelled or all-failed batch fails, the batch stays on the poll page, so its lines are no longer read and stored again on every poll cycle until it is retired. The poller also releases a billed batch's output bytes before reading the next batch's output, as it did before line items existed.

* fix(batches): price and write batch line items off the event loop

Pricing every line of a large batch and serializing its object ran on the
proxy's event loop, so a 50k-line batch stalled the worker for seconds.
Both now run in a worker thread. An object the bucket refuses for good is
no longer kept in s3_v2's drop marks, which only a log-queue flush clears.
Vertex AI input rows carry the custom_id in their key or request labels, so
their lines now get the request too.

* fix(batches): pair no request for a shared custom_id and wait for an unclaimed batch's retry

A Vertex AI embeddings entry whose input is a list is split into one row per
item, all with the same custom_id, so its line now gets no request instead of
the last row. On a database without batch_processed nothing claims a billed
batch, so when marking it complete fails it stays in the poll page and its
lines now wait for the next poll instead of being written on every cycle.

* fix(batches): store batch line items only once the poll has billed every batch

Pricing a large batch's lines on a worker thread still competes with the poll for the GIL, so the next batches
in the same poll were billed and retired seconds later. The background stores now wait until the poll cycle that
queued them has finished.

* fix(batches): hash line-item objects off the event loop and keep lines with a lone surrogate

A batch's whole line-items object was hashed for its S3 PUT on the event loop, and a line
holding a lone surrogate from a provider's JSON escapes made the object impossible to
encode as UTF-8, so the batch's object was never written. The object is now prepared in a
worker thread, and only the line that cannot be encoded is written with escaped characters.

* fix(batches): keep request and response for batches created without a virtual key

A batch created with a JWT has no API key on its row, and its line items were stored without
request and response as if its creator had been deleted. Such a batch now follows its team's
and the proxy's message logging settings, the same as a master key batch. A deleted key or team
or a failed lookup still drops the bodies.

* fix(batches): pair line items with the right request on every deployment and skip empty objects

A batch retired with nothing billable now reads its input file by the id the provider reported, so a batch that
ran on the second deployment of a model group keeps each line's request. A Vertex AI line read as custom_id
"unknown" pairs with no input row, and a batch whose files hold no readable line writes no object

* fix(batches): let OAuth2 batches follow team and proxy message logging settings

The line-item redaction check looked up every saved creator credential other than the master key or a CLI session as a virtual key. An OAuth2 batch saves the raw token, so it read like a deleted key and lost its request and response

It now looks up only a saved value shaped like a virtual key's hash, reusing is_valid_sha256_hash, so OAuth2 batches follow their team's logging settings and the proxy-wide setting while deleted keys still fail closed

* fix(batches): hash the creator credential and write batch line items in parts

The creator credential reaches line metadata only as a sha256 hash, so an
OAuth2 token or the master key alias is never written to the bucket. A queued
store keeps only whether the batch was billed and downloads the output file
again at its turn, logging an error naming the batch if that fails. Lines are
built and uploaded one part at a time, each closing once its raw request and
result bytes reach BATCH_LINE_ITEMS_MAX_PART_BYTES (16 MiB by default), with
the input file indexed by byte span instead of parsed up front.

* docs(batches): say async_log_batch_line_items is called once per part

* fix(batches): log an error when a batch's deployment is gone before its line items are stored

---------

Co-authored-by: shivam <shivam@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: yucheng <yucheng@berri.ai>
2026-10-15 11:32:56 -07:00
devin-ai-integration[bot]
fbc2e358bc
fix(responses): bill a background response once, on the first read or poll that sees it finished (#45703)
* fix(responses): bill a background response once, from the poll job

Reading a completed background response with GET /v1/responses/{id} wrote a
full-cost spend row on every read, on top of the row the background cost poll
writes. Reads of a Responses object (GET, DELETE, cancel) now never bill, and
the poll job is the single biller.

The poll job now bills with the creating request's attribution (key hash, team,
org, user, aliases, tags) read off the managed object row, through a helper it
shares with the batch cost poll. The background create persists the creating
key and request tags so that attribution survives until the poll runs.

* test(proxy): a background response read reports zero cost

* fix(responses): bill a background response once, on the first read or poll that sees it finished

A conditional update moves the stored row out of queued or in_progress so only one worker or pod bills it, through one re-read stamped with the creator's attribution. A failed billing read puts the row back for the next poll

* fix(responses): keep the caller's response id out of the billing failure warning

* fix(responses): keep the creating client's User-Agent tags on the one background charge

* fix(responses): keep managed background reads free and bill each response once

The managed files hook marks reads and cancels of proxy-issued response ids, so only those stay free. SDK and database-less reads of a background response still bill, extra_body background creates are tracked, and the poll's status read no longer cools down a deployment on a 404.

* fix(responses): bill finished background responses from the fetched body and store rows Postgres accepts

* fix(responses): give the background billing event its own spend log row and bill responses the create left untracked

* fix(responses): narrow the managed files hook with a protocol instead of an enterprise import

* fix(responses): leave a read the caller retargets with client-side credentials to the cost poll

* fix(responses): bill background responses on the creator's end user and report the charge on the settling read

The read that settles the bill returns the charge in x-litellm-response-cost, the billed event
carries the creator's end user and the key, team, and user budget fields, and its spend row is
named after the id the client got. Override reads, cancels, and deletes settle from the
configured deployment, a streamed create marks its row billed, stored rows keep no model
output, and model insights counts the billed row's spend without a request.

* test(responses): cover background response billing across proxies, reads and chaos

* fix(responses): settle background billing only for callers allowed to address the response

A delete now settles the bill only after the response id access check passes, a streamed
create is marked billed when it sets background inside extra_body or its completed event
arrives after the last chunk, the billing event keeps the deployment's litellm_params
base_model, a key with no user and no team bills no user instead of its owner scope, and the
enterprise cost check import is optional

* fix(responses): record the bound on the pending status IN filters

* fix(responses): send the billed cost split on the settling read and keep the batch cost event as it was

The read that settles a background response now sends the whole cost header
family from the billed event, so the breakdown headers add up to the charge.
Batch cost events go back to main's attribution (creator id as the user, no
budget fields); only background responses get the end user and budgets.

Integration tests expect the charge on the settling read (or none when the
poll billed first), one charge for a streamed create, and SDK flows that poll
with the id each read returns.

* fix(responses): bill each background response once across upgrades, streams, and failed settles

Rows stored before this billing model are found by the issued id and rekeyed by the
provider id, and the cost poll retires one a read already billed. A streamed background
create is free on its own and bills the finished response through the same managed row
before the client sees response.completed, so a racing read cannot bill it again. A
settle that fails retries in the background, a retargeted read with no row tracks and
bills from the configured deployment, and a delete keeps its billed cost header.
Reverts the unrelated json.dumps narrowing in the completion transformation.

* fix(responses): bill cache-polled background streams and match poll rows by the issued id

* test(responses): cover deletes, failed settles, budgets, base models, and cache-polled background billing

Adds integration cells for the background response billing paths the audit
inventory lists: a DELETE that settles the bill and refuses a stranger, a
settle the database refuses that retries once it recovers, the Prometheus
remaining budget, base_model pricing from model_info and litellm_params, the
daily model usage rollup, the end user, the settling read's cost split, stored
rows without model output, a forged managed marker on the create, streamed
creates with background in extra_body, and the cache-polled create

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 11:00:14 -07:00
Yusuf Efe
c9ce9a733d
fix(proxy): allow model instances in LiteLLM_EndUserTable validation (#41677)
* fix(proxy): allow model instances in LiteLLM_EndUserTable validation

* fix(proxy): preserve property-backed attributes when coercing spend

* refactor(proxy): default null end-user spend with a field validator

* fix(proxy): drop model-wide from_attributes from the end-user table

* test(proxy): unskip the /customer/block integration contracts

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 10:57:26 -07:00
Mateo Wang
622daf3cdf
fix(scim): write a group's roster in one locked transaction instead of one member at a time (#45197)
* fix(scim): write a group's roster in one locked transaction instead of one member at a time

POST, PUT and PATCH /scim/v2/Groups resolve every member in one query and write the roster, the
membership rows and the users' team tags in one transaction under the team's advisory lock, so a
500-member push runs a fixed number of statements instead of thousands. PUT now answers with the
roster it just wrote

* test(scim): assert the roster the IdP gets back and boot the bulk roster cell with two workers

* fix(scim): skip the team lock for a rename-only PATCH and lock member rows in id order before the roster write

A PATCH naming no members opened the roster transaction and took the team advisory lock for nothing. A SIGKILLed worker then left its orphaned query engine holding that lock until the 60 s transaction timeout, and /team/delete, which takes the same lock, timed out behind it. An empty delta is now answered from a plain team read, with no transaction and no lock

Two groups trading members in parallel locked user rows in opposite orders, and one request died with a Postgres deadlock. Every user row a push touches is now locked with SELECT ... ORDER BY user_id FOR UPDATE before the first write, so the two requests serialize

The bulk roster cell gets a 120 s client through a new owned_proxy_process client_timeout, so an unfixed push fails on the statement count instead of the harness clock, requires positive counts on both pushes, and gains a parallel roster-trade test that answered 500 before the lock

* fix(scim): evict the cached team on a group rename and read a no-op roster from the writer

A rename-only PUT or PATCH wrote the new alias and left the team cached under
its id and old alias on every worker, so keys kept logging spend against the
old team alias until the TTL expired. The group write now evicts the cached
team (and broadcasts the eviction) right after the alias or metadata update.

sync_team_roster reads the team from the writer when the plan names nobody,
so a replica cannot hand back the pre-rename row; a plan already matching the
roster returns inside the lock without writing, evicting, or emitting the
members metric; the response is built from the written row, so lastModified
reflects the roster write; and detaching a removed member bumps the user's
updated_at like every other user write.

* fix(scim): bump detached members' updated_at in UTC

The detach UPDATE wrote updated_at = CURRENT_TIMESTAMP, which Postgres casts
into Prisma's naive timestamp column in the session timezone, so on a database
whose session is not UTC the removed member's row landed hours away from the
UTC instants Prisma itself writes. Write NOW() AT TIME ZONE 'UTC' instead, and
have the bulk roster cell assert the bumped row sits between two reads of the
database's own UTC clock taken around the replace.

* fix(scim): chunk the group write's member lookups under the bind cap

Every Prisma "in" filter the group write issues bound one parameter per
member with nothing bounding the list, which check_unbounded_in_lists
reports as 11 new findings. The single-field lookups now go through
litellm.repositories.chunked_in (caller_transaction inside the roster
transaction, per_chunk_ok for the role recompute), and the one
cross-field OR read slices its values at IN_LIST_CHUNK_SIZE and records
the bound. A push of IN_LIST_CHUNK_SIZE + 1 members now reads in two
slices, and a member named only in the last slice still resolves.

* fix(proxy): send bulk cache evictions in slices so the broadcaster drops none

Veria pointed out that the invalidation publisher caps its pending tasks at
1,024 and drops the excess with a warning, and that a group push now detaches
every removed member's keys in one call instead of one member at a time, so a
removal of more than roughly 340 members (three cache keys each) silently left
stale key objects on the other replicas. The merge base never hit the cap
because each member was a separate request.

Bulk evictions (team, user, organization, and session key deletes, plus the
roster settle) now publish in slices of 256 and wait, bounded at two seconds,
for the backlog already handed to the event loop before each slice. A Redis
that never answers costs a bulk caller at most that wait per slice instead of
wedging the request, and single-key callers are untouched. Regression tests
push 1,500 keys and a 500-member removal through a slow publisher and assert
every eviction reaches Redis; both fail against the previous tip.

* fix(proxy): clear this worker's cache before pacing bulk eviction broadcasts

Greptile pointed out that pacing the broadcasts in slices also paced the
local eviction: a bulk delete waited for the publish backlog before dropping
the next slice from this worker's own memory, so on a Redis that accepts
connections but never answers a key deleted from the database kept
authenticating on the handling worker for up to two seconds per slice. The
merge base cleared every key locally at once.

Bulk evictions now drop every affected entry from this worker's memory first,
through the cache's own partition lookup since key objects live apart from
the other auth objects, and only then publish in paced slices. The roster
settle does the same for the deleted tokens, the JWT mapping keys and every
changed member's user and membership entries before any step that can wait.
Regression tests run both paths against a publisher that never answers and
check that nothing is still cached on this worker before the first bound
elapses; both fail with the local eviction removed.

* fix(proxy): drop the Redis copies of bulk-evicted auth objects before pacing the broadcasts

* docs(proxy): drop the module docstring that repeated the PR description

* fix(scim): bound bulk cache evictions to one Redis round trip and close lock-order gaps

Bulk key evictions now drop entries from memory, delete them from Redis in one
chunked DEL, and broadcast every key in one pipelined publish, so a large roster
removal no longer overflows the publisher's pending cap or costs a Redis round
trip per member. A push waits for in-flight membership loads before evicting.

User rows are locked in byte order to match the spend writer, a bulk user delete
takes every team lock before its first user write, and a POST whose roster write
fails deletes the empty team so the IdP retry creates it again.

* test(team): observe delete broadcasts at the Redis layer

* fix(scim): lock user rows in id order on every multi-row writer and create unprovisioned members concurrently

* fix(team): chunk the email lookup behind the member row lock

* fix(scim): create a member deleted mid-push again instead of failing the group write

* fix(scim): refuse strict-mode mid-push deletes with 400 and check license seats once per batch

A member deleted mid-push is created again only when scim_upsert_user allows it,
under the verb's own created_via. New group members are checked against the
license seat limit as one batch before any is created. Auth cache publish drops
log the key count instead of the key.

* fix(scim): lock member rows while recomputing admin roles after a group push

* fix(users): re-read teams under the row locks in bulk user delete so a racing group push keeps no deleted member

* fix(users): take /user/delete and SCIM DELETE /Users users off their current teams under the row locks so a racing group push keeps no deleted member

* fix(scim): keep retrying a push while deletes race it, lock rows in member bulk delete, evict removed keys from Redis first

A group push gave up after one retry when SCIM user deletes kept landing between attempts, answering 500 in 9 of 10 race rounds. It now retries while each attempt finds newly deleted members, and gives up only when a member it created again goes missing a second time.

The team member bulk delete now locks the removed members' user rows in the shared order and takes the team off their teams arrays in one array_remove statement, so it no longer writes back a teams array read before a concurrent push added another team.

A push that removes members now drops their deleted team keys from memory and Redis together with the members' other cache entries before the team eviction, so a removed key cannot refill from Redis mid-cleanup.

* fix(user-delete): keep the team alias label on the team members gauge after removals

* test(integration): count relay statements over plaintext so an SSL-enabled Postgres does not hide them

* fix(user-delete): skip a team deleted while the user delete waited on its lock instead of answering 404

* fix(scim): answer 404 and roll back when the team is deleted during a roster write

* test(integration): audit cells for SCIM bulk roster writes, user delete locking and the eviction broadcast
2026-10-15 10:57:00 -07:00
Thijmen Stavenuiter
a76e723b26
feat(proxy): report when each per-model budget window resets (#45797)
* feat(proxy): report when each per-model budget window resets

model_max_budget_usage on /key/info, /user/info and /team/info now carries budget_reset_at per model, the open window's start plus its period, or null when no window is open. The window start is read in the same batched lookup as the spend counter

* fix(proxy): count a monthly budget window from its own start when reporting its reset

duration_in_seconds measures Nmo from now, so a window opened on January 15 and read on February 10 reported February 12, then null while the counter still refused requests until February 15. duration_in_seconds_from measures the month from the window start, and duration_in_seconds now shares that month arithmetic

* fix(proxy): measure months from timezone-aware datetimes and assert whole usage values

datetime.fromtimestamp without a tz tripped DTZ006. The month arithmetic now runs on an aware local datetime, which keeps the same wall-clock result. The duration tests move to parametrized functions, since subTest payloads carrying datetimes cannot cross the xdist worker boundary, and the new usage tests compare the whole entry

* fix(budgets): end a monthly budget window a calendar month after it opens

Each charge recounted the month from the charge date, so a monthly window
opened in a month of another length expired days before or after the reset
/key/info reports. The window is now measured from its start, by the same
helper the usage report uses. A period ending after year 9999 reports no
reset instead of failing the read.

* fix(budgets): count monthly budget windows in UTC for every router budget

Months were counted on the host's local calendar, so replicas with different TZ
settings disagreed on when a monthly window ends. Provider, deployment, tag and
per-model budgets now all measure a window from its start in UTC, and a test
covers the router budgets. A reset past year 9999 is documented as null.

* test(budgets): cover monthly tag budgets in the router window test

* test(budgets): add integration cells for budget_reset_at and monthly budget windows

* test(budgets): find a monthly window in another span on every calendar day

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 10:56:45 -07:00
L
bdd80781f2
fix(proxy): list team access group models in /v1/model/info and keep key model lists narrow (#32599)
* fix(proxy): list models from team access groups

* 修复 PR #32599 的类型检查并补齐模型列表回退测试

* fix(proxy): keep a key's own model list narrow when adding team access group models

A key with its own model list was shown every model from its team's access
groups on /v1/models, /v1/model/info and /model_group/info, though auth
denies those calls. Team access group models now widen a key's list only when
the key inherits the team's models. /v1/model/info reuses the shared listing
helper without a catch-all, and route-level tests replace the mock-only ones

* fix(proxy): skip the list build in the unrestricted model info check and test every listing route

The unrestricted check for /v1/model/info only needs to know whether the key
and team lists are empty, so it no longer builds and expands the model list a
second time. The route test now covers /v1/models and /model_group/info next
to both model info routes

* fix(proxy): scope model info for personal and agent keys with no model list

* fix(proxy): keep config keys' team access groups and own-team team_id scope in model listing

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 10:23:03 -07:00
devin-ai-integration[bot]
3740d48844
test(cost): add tier 1 claude messages stream twins and recapture drifted usage shapes (#46690)
* test(cost): add tier 1 claude messages stream twins and recapture drifted usage shapes

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): freeze the login throttle clock so the retry-after assertion is deterministic

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 17:11:13 +00:00
yuneng-jiang
694582aeb3
fix(jwt): honor end_user_id_jwt_field on the JWT-to-virtual-key mapped path (#46637)
* fix(jwt): honor end_user_id_jwt_field on the JWT-to-virtual-key mapped path

A JWT mapped to a virtual key dropped the end-user claim, so spend rows had
no end user and customer budgets, limits and region never applied. The mapped
token now carries the claim, and it takes precedence over the body user and
the x-litellm-end-user-id header, which remain the fallback when the claim is
missing or empty.

* test(jwt): budget-check the body or header end user when a mapped JWT has no end-user claim

* fix(jwt): replace the annotation offsets with a targeted pyright suppression to keep LIT001 flat
2026-10-15 16:57:23 +00:00
devin-ai-integration[bot]
17f621e116
fix(vertex_ai): route Model Garden models through the generateContent adapter (#41836)
* fix(vertex_ai): route Model Garden models through the generateContent adapter

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(vertex_ai): annotate generateContent route test parameters

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(vertex_ai): type litellm_params in get_vertex_ai_model_route

* fix(vertex_ai): bill and log Model Garden generateContent calls like chat completions

Streamed Model Garden calls through the generateContent adapter now request
stream usage where the deployment supports it, keep cached-token details, and
look up the provider-relative cost key, so they bill like the non-stream call.
The adapter forwards router metadata, passes upstream errors through with their
status, countTokens falls back to local counting for non-Gemini routes, and the
native Gemini config is limited to the Gemini routes.

* fix(google_genai): keep adapter stream usage, admin opt-out, single failure count, and base_model routing

Streamed generateContent through the chat adapter now ends with the upstream usage, honors
always_include_stream_usage false and the caller's stream_options, counts one failure per
failed call, and routes Vertex deployments by their base_model like chat does

* fix(google_genai): ask for stream usage on every adapter stream so Claude streams end with usage

* test(google_genai): expect the trailing usage chunk on bridged OpenAI streams

The OpenAI bridge test now sends the usage chunk OpenAI returns for include_usage and expects it translated into usageMetadata. The response_format support helper goes back to its single-purpose form since its only other caller is gone.

* fix(google_genai): end adapter streams with one STOP event carrying usage, and keep upstream usage after the finish chunk

* fix(google_genai): send the held STOP event when no usage arrives, keep a caller's stream_options, and route countTokens like generateContent

* test(integration): cover the moved Vertex routes, adapter stream usage, the shared iterator and usage settings over the wire

* test(integration): add cache-hit twins for the stream usage setting and non-stream cells for every iterator member

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 08:06:49 -07:00
mrinal-berri
08a24d391a
fix(count_tokens): count system and tools on Vertex Gemini, fall back to Mantle on Bedrock 404 (#46430)
* fix: align token counting with inference context

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix: preserve Vertex Gemini count message shapes

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix: forward Google countTokens tools in shapes every provider counter accepts

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test: add package marker for Vertex count-token unit tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(vertex_ai): ignore deployment system_instruction when counting tokens

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(count_tokens): forward system and tools on Google AI Studio, keep strict on Anthropic tools

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style(count_tokens): ruff format gemini count handler

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(count_tokens): return Mapping from count request body builders

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(count_tokens): truncate long Anthropic tool names on Vertex count, update stale strict test expectations

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(count_tokens): simplify Gemini count context and tests

Put the Vertex Gemini count branch back in the same shape as main and the partner model branch, keeping only the system and tools context, the provider error mapping and the gemini tokenizer default

Share one error response helper between the Vertex and AI Studio callers, drop the unread kind fields and the extra validation of map_function output, and say Gemini instead of Vertex AI in the error that AI Studio users also see

Tighten the tests by removing a stray parametrize on a helper, sharing the SDK count args, asserting the exact forwarded system and tools, and folding the Anthropic tool shape tests into one table

* fix(count_tokens): reuse inference tool translation for Vertex Gemini count

Vertex and AI Studio count now convert tools with the same functions inference uses, translate_anthropic_tools_to_openai and the Responses tool converter, before VertexGeminiConfig.map_function. Unnamed and Anthropic hosted tools now count the same declarations inference sends instead of being dropped

Tools that cannot be converted, such as a non list tools value, a non object tool or a schema that is not a JSON object, now return a 400 before any request instead of being counted without them

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 10:36:10 -04:00
Mateo Wang
18831b818c
fix: keep model capability flags out of provider requests (#46647)
* fix: keep model capability flags out of provider requests

A supports_* flag or another model map field set on a deployment's litellm_params was forwarded
to the provider as a request field, so Bedrock answered 400 Extra inputs are not permitted on
chat traffic and on the background health check alike. The shared owned-kwarg predicate now
treats every ProviderSpecificModelInfo field as litellm-owned.

Builds on the health-check-only approach in #40952 by leilei3167.

* fix: treat every supports_ model map flag as a capability field and warn when one sits in litellm_params

* fix(router): skip declared litellm params in the capability flag warning and warn for runtime-added deployments

* fix(router): strip model capability flags from the router's deployments instead of every request

* fix(router): keep capability flags out of health probes and read them from the loaded catalog

* perf(router): read the catalog's supports_ field set once per cost map load

Cache the loaded catalog's field names when the cost map snapshot is taken so the capability-flag check stops walking every catalog entry per deployment, and add integration cells that drive the flagged and control deployments through chat, streaming, messages, responses, embeddings, health and model management against a vendor that rejects the flags
2026-10-15 14:30:10 +00:00
devin-ai-integration[bot]
c00706218b
fix(vertex_ai): return 400 with file line number for malformed batch JSONL row (#40097)
* fix(vertex_ai): return 400 with file line number for malformed batch JSONL row

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(vertex_ai): keep yield outside the JSON decode guard

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(http_handler): surface BaseLLMException raised while streaming a request body

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(http_handler): only follow __cause__ when unwrapping streamed body errors

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(http_handler): avoid recursive streamed error unwrapping

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(vertex_ai): return a 400 naming the line for wrong-shape and non-UTF-8 batch rows

Keep main's error path for a directly raised provider error and only unwrap
one found behind a transport error. Add the parser column to invalid JSON
errors, and cover the real aiohttp chain in the _handle_error test

* fix(vertex_ai): report every row conversion error as a 400 naming its line

A message with no role, a non-string role, a bad temperature, or a litellm
BadRequestError raised while converting a row still returned a 500, and the
async upload lost the 400 for litellm's own exceptions. The stream now turns
any error from one row's conversion into a 400 naming that line.

_handle_error only unwraps an httpx.TransportError, which is what the aiohttp
transport raises around a failing request body, so other callers keep their
own status. A file that starts with a UTF-8 byte order mark now uploads, and
provider messages start with 'Batch input file line N' like the proxy check.

* fix(vertex_ai): reject null or missing batch bodies and unparseable rows with a 400 naming the line

A chat row whose body is missing or not an object now raises a 400 naming
its line instead of uploading a blank prompt, and a non-object body on
line 1 no longer crashes the GCS object name lookup. Rows too deeply nested
or too long to parse return a 400 from both the SDK and the proxy's own
batch file check. JSON error columns now count leading whitespace.

* fix(vertex_ai): keep batch rows on their file line through router and guardrail rewrites

The Router model rewrite and batch guardrails now keep blank lines and blank out dropped records, so a provider error naming a line still points into the caller's file. The rewrite strips a leading BOM per line, and a non-string body.model on line 1 is reported as a 400 naming the line

* test(integration): cover Vertex batch row line errors across routes, rewrites, SDK and worker chaos

* fix(router): keep blank lines only for Vertex batch uploads and leave guardrail rewrites compact

* test(integration): score the whole OpenAI upload after a guardrail drop and cover a mixed OpenAI and Vertex batch upload

---------

Co-authored-by: jesus <jesus@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 03:21:48 -07:00
Oliver Jensen
84e8204d7f
fix(proxy): scope /spend/tags aggregates to the caller's own and permitted-team logs (#46194)
* fix(proxy): scope /spend/tags aggregates to the caller's own and permitted-team logs

Non-admin callers previously received the proxy-wide per-tag spend
aggregation. The endpoint now resolves the same read scope as
/spend/logs/ui and /spend/logs/session/ui, and the query honors the
start_date/end_date parameters it previously accepted but ignored.

* fix(proxy): use Annotated auth dependency on /spend/tags and sync dashboard API types

* fix(proxy): bind /spend/tags dates as UTC datetimes, not session-timezone strings

Raw YYYY-MM-DD strings cast to timestamptz are read in the database
session timezone, shifting the day window by that offset. Parse them
to UTC-aware datetimes first, like every sibling spend query in this
file, and reject malformed dates with a 400 before they reach the
database.
2026-10-15 10:09:21 +02:00
Kolade Fajimi
ea777eb21b
fix(auth): return a generic 401 for an unknown key (#39787)
* fix(auth): return a generic 401 for an unknown key

The wrong-key 401 shipped the internal verification table name and the
submitted key's full SHA-256 hash to any unauthenticated caller. Both now
go to the proxy's own log and the response carries only "Invalid API key
provided."

The Admin UI detected a dead session by string-matching that message, so it
now reads the structured error type instead.

* Update ui/litellm-dashboard/src/lib/http/client.ts

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* fix(auth): log the missing key hash where every resolve path passes

Review catch: JWT key-mapping misses resolve through IdentityStore without
touching the main key path, so logging the hash there left those callers with
nothing but the generic 401. Log it at the store's raise site instead, which
every resolve path shares, and drop the now-duplicate log.

* test(auth): inject a key-less client instead of patching the DB fetch

The store test tripped TQ008 by patching _fetch_key_object_from_db_with_reconnect.
Hand IdentityStore a client whose get_data returns no row instead, so the miss is
driven through the real lookup rather than around it.

* fix(auth): log the unknown key's hash once on the auth failure line

The per-lookup warnings in get_key_object and IdentityStore logged whatever value
they were handed, which on the failure-logging path is the raw key a caller sent
(a provider key included), let a newline in ?key= forge log lines, and fired on
lookups that expect a miss. The hash now rides KeyNotFoundError onto the single
existing auth failure log line next to the requester IP, with control characters
escaped. Also drops the new comments and updates skipped tests that quoted the
old message.

* test(auth): add the blank lines ruff format expects before _InFlightCountingPrisma

* test(integration): expect the generic wrong-key 401 in the management lifecycle tests

* fix(auth): keep the operator wording on the unknown-key log line and drop the redundant 401 rewrite

* test(auth): cover the generic unknown-key 401 across routes, proxies, and a worker kill

* test(auth): cover the realtime upgrade refusing an unknown key without echoing it

---------

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 01:05:25 -07:00
devin-ai-integration[bot]
bf56719f09
fix: cap cold MCP schema workers at usable CPUs and deflake wall-clock unit tests (#45791)
* test: inject clocks and wait on conditions in three wall-clock-flaky unit tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test: keep generic API logger tests on 3.10 and cover automatic sending

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test: pin router usage minute in shared rate-limit header test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test: stabilize three wall-clock-sensitive unit tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(mcp): cap cold schema validation workers at the CPUs the proxy can use

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test: inject the cache clock and wait on lock contention instead of 1s deadlines

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(mcp): wait on listing events instead of 1s deadlines in the discovery drain test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo <mateo@berri.ai>
2026-10-15 00:47:59 -07:00
Hayden Moulds
de0ed1557e
fix(proxy): resolve model aliases to their target deployment for listing metadata (#41041)
* fix(proxy): resolve model aliases to their target deployment for listing metadata

A model alias (a key's `aliases`, a team's `model_aliases`, or the router's
`model_group_alias`) is rewritten at request time and owns no deployment row,
so `get_model_listing_info` returns None for it and the alias name is not a
cost-map key either. Both metadata candidate sources come up empty and the
listing entry carries no `mode`, `max_input_tokens`, or `max_output_tokens`,
while the deployment it routes to reports them on the same response.

Resolve a listed alias to the deployment it routes to for the metadata lookup,
keeping the alias as the response id. Maps are applied in order, each against
the result of the last, mirroring how `litellm_pre_call_utils` applies the team
map and then the key map, so a chained alias reports the deployment the caller
actually reaches rather than an intermediate one. An alias shadowing a
same-named deployment follows the alias, because the request rewrite does too.

Fixes the model_aliases half of #40553.

* fix(proxy): look listed aliases up through the shared alias chain

Drop the separate alias resolver and retarget a listed alias in
alias_listing_entries and alias_target instead, so /v1/models and
/v1/models/{id} report the model /chat/completions rewrites it to, and
only when the caller can list that model

* fix(proxy): keep deployed listed models' own rows and resolve team alias targets at list and retrieval

* fix(proxy): resolve router_settings aliases, keep alias labels, and skip paused targets in model listing

* fix(proxy): leave an alias to an undiscoverable model bare in model listing

A team alias whose target has discoverable: false showed the hidden model's mode and limits on GET /v1/models and retrieved it by alias. Undiscoverable groups now count as hidden for alias resolution, as on main, while admins still see them.

* fix(proxy): leave an alias to a model a listing callback hides bare in model listing

* fix(proxy): keep aliases bare for models a listing callback never judged or another team owns

---------

Co-authored-by: haydster7 <haydster7@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-15 00:38:50 -07:00
Mateo Wang
3cc9e7ef8e
perf(proxy): cache the public provider and agent field endpoints (#46617)
/public/providers/fields re-read and re-parsed the bundled 85K
provider_create_fields.json on every request, and /public/agents/fields did the
same for that file plus agent_create_fields.json. Both are unauthenticated
public endpoints, and both did the work inside an `async def`, so the read and
the parse ran on the event loop and serialized against every other in-flight
request. Measured against the bundled files, that is roughly 0.40 ms of blocking
work per request for the provider endpoint and 0.45 ms for the agent endpoint

Both now memoize with `lru_cache`, which is what `/public/endpoints` in the same
module already does through its `_cached_endpoints` global, so each file is read
once per process rather than once per request

The agent endpoint mutated the dicts it had just loaded, appending inherited
provider credential fields and popping `inherit_credentials_from_provider`. That
is only safe while the data is re-read every time, so caching it meant making the
merge pure: `_agent_with_inherited_credentials` builds a new mapping per agent,
and the cached value is the merged result rather than the raw file contents.
Responses are byte identical before and after, checked on both endpoints against
a live proxy

The bundled records are typed as Mapping[str, object] and narrowed with
isinstance at the point of use, rather than typing.Any, which ruff-strict bans

Side effects: 3 of the repo's ASYNC230 violations go away, and basedpyright
errors in the file drop from 63 to 52

Rebased onto main after /public/providers/fields started validating the bundled
JSON through a pydantic adapter on every request. That validation now runs once
and the validated records are cached; the agent endpoint keeps merging the raw
provider records, so both responses stay byte identical to main.

Co-authored-by: Alok Sharma <alok44170@gmail.com>
2026-10-15 00:13:07 -07:00
TheMentalCoding
ca04c4909e
feat(ui): filter active and paused model deployments (#43710)
* feat(ui): status filter + sort and provider-aware search on Models & Endpoints

The models table mixes active and paused deployments with no way to tell
them apart beyond the pause toggle, and the drawer only filters by public
model name and access group.

Backend (/v2/model/info):
- new optional `blocked` query param to filter by routing status
- new `blocked` sort field (asc = active first); the existing `status`
  field keeps sorting by config-vs-DB source
- `search` now also matches litellm_params.model, so typing a provider
  or upstream model id (e.g. "nvidia_nim", "openai/gpt-4") finds
  deployments whose public name doesn't mention them

Frontend (Models & Endpoints):
- visible Status column with Active/Paused badges, sortable
  (active first on asc)
- Status filter (All/Active/Paused) in the Filters drawer, wired to the
  new server param through URL state

The routing-status filter ignores non-bool sentinels the same way
exclude_auto_routers does, so direct calls bypassing FastAPI keep their
no-filter behavior.

* fix(ui): inverted routing-status filter mapping and compact Status column

Selecting "Active" in the Filters drawer sent blocked=true to the server,
showing the paused deployments instead of the active ones (and vice
versa). The mapping now lives in routingStatusToBlocked() with unit
tests, and the Status column is narrower so the row actions stay in
view.

* fix(ui): pin the Actions column to the right on the models table

With the new Status column the table overflows on narrower screens and
the pause/resume switches (last column) scroll out of view. Pinning the
Actions column keeps them visible; uses the existing DataTable
meta.pinned support (same pattern as MemberTable).

* refactor: readable db search where-condition and ruff-format clean

* fix: apply routing-status filter inside the search flow and regen API types

Greptile flagged (P1): with search + a status filter combined, the
bounded DB fetch ran before status filtering, so matches of the other
status could consume the page budget and leave short pages / stale
totals.

- extract _matches_routing_status() (sentinel-safe) and apply it to the
  router-side matches inside _apply_search_filter_to_models
- push the status condition into the DB where clause of
  _fetch_db_models_for_search, so rows of the other status never count
  against the bounded fetch
- endpoint passes blocked through to the search flow; tests cover the
  combined search+status case and the generated where clause
- regenerate ui/litellm-dashboard/src/lib/http/schema.d.ts for the new
  query param
- update useModels.test.ts expectations for the new trailing argument

* fix(proxy): keep the flat DB where shape for single-condition searches

The upstream CI test
test_apply_search_filter_honours_exact_model_name_in_db_query pins the
Prisma where shape: exact model_name stays a top-level key, and plain
substring search keeps {model_name: {contains, mode}} at the top level.
Only genuinely multi-condition queries (status filter and/or router-id
exclusion) now wrap in AND.

* fix(proxy): avoid reassigning a Final variable in the db where builder

basedpyright's reportGeneralTypeIssues budget counts the reassignment of
the Final-annotated db_where_condition; express it as a single
conditional expression instead.

* chore(deps): bump pypdf to 6.19.0 to clear osv-scan

pypdf 6.16.2 has 8 High CVEs (GHSA-5jq2-8x83-x246 and aliases) fixed in
6.17.0-6.19.0; bump past all of them

* Revert "chore(deps): bump pypdf to 6.19.0 to clear osv-scan"

This reverts commit 0e2528123db7ab23304ae20f6a4c0961d0e2d073.

* fix(proxy): keep LIT002 budget flat in the model search where-builder

Extract the dynamic Prisma where-condition fragments into module-level
helpers so every dict starts on a short line, split the litellm_params
fallback lookup into a Final local, and annotate suppressions on the
construct start lines the checker attributes

* chore(tests): repoint unbounded-IN baseline at the extracted where-builder helper

The bounded-router-id filter moved from _fetch_db_models_for_search into
_not_in_router_ids, so the old baseline key is stale and the new helper
site is the finding to record

* fix(proxy): avoid searching encrypted deployment model names

* refactor(ui): keep model routing status as a filter only

* docs(api): regenerate model info sorting description

* fix(api): remove remaining paused status sort references

---------

Co-authored-by: thementalcoding <312162298+thementalcoding@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-14 23:19:59 -07:00
yuneng-jiang
aa694f316d
fix(proxy): keep JSON nulls as null in audit log values (#46577)
LiteLLM_AuditLogs masked before_value and updated_values with
SensitiveDataMasker.mask_dict, which stringifies every non-native leaf, so a
null in the change was stored as the string "None" (or "" under a key-named
field). Walk audit values with mask_credentials_in_payload instead, injecting
the existing {"key"} masker so the masked format and scope stay the same.
2026-10-15 05:50:09 +00:00
Mihidum
b025681bef
fix(proxy): gzip responses over 16 KiB off the event loop (#46362)
* fix(proxy): gzip responses over 16 KiB off the event loop

GZipBufferedResponseMiddleware compressed every body under 1 MiB inline.
gzip.compress holds the event loop for its whole run, and its cost follows
how well the body compresses: an 824 KB base64 embeddings response (100
inputs, the OpenAI SDK default encoding) takes about 165 ms, so every other
request on the worker waits that long, and with several in flight the
compressions run back to back.

Lower OFF_LOOP_SIZE_BYTES to 16 KiB so only bodies that compress in well
under a millisecond stay on the loop. zlib releases the GIL, so the loop
keeps serving while a worker thread compresses.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* test(proxy): pin the gzip off-loop boundary at exactly OFF_LOOP_SIZE_BYTES

A body of exactly OFF_LOOP_SIZE_BYTES compresses in a worker thread, as the
`<` in _compress implies. Suggested in review.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* test(proxy): pin an embeddings-sized gzip body off the event loop and drop the source comment

The off-loop test was relative to OFF_LOOP_SIZE_BYTES, so it still passed with the old
1 MiB line. An 824 KB body, the size of the 100-input base64 embeddings response in the
issue, now has to compress in a worker thread. The recorder no longer mutates a list, and
the threshold rationale stays in the commit history instead of a source comment.

---------

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-14 22:36:59 -07:00
Mateo Wang
3fec5075fa
feat(typesafe): support Jev 1.14 images, box questions, and long-context headers (#46596)
* feat(typesafe): support Jev 1.14 images, box questions, and long-context headers

* fix(cost): drop the typesafe/jev-1.14.0 entry main already prices

* fix(typesafe): send images only with the images header and box questions only to models that answer them

TypeSafe takes assets and input_image parts only when the request carries
TypeSafe-Danger-Zone-Images: true, so without it they follow drop_params like
any other provider that cannot take images. Box support now comes from a
supports_box_questions cost-map flag set on jev-1.14.0 and jev-preview, so
jev-1.13.0 and jev-latest refuse or drop a box question before the call. A
malformed provider_specific_header answers 400 instead of 500.

* fix(typesafe): allow null box confidence and validate asset references and base64

* fix(typesafe): gate box questions on the images header, drop unreadable assets under drop_params, forward opt-in headers on the pass-through

---------

Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-14 22:29:48 -07:00
yuneng-jiang
9444f53300
fix(proxy): store list-valued audit log changes as JSON text (#46555)
LiteLLM_AuditLogs parses before_value and updated_values as JSON but only re-serialized dicts, so a list change reached Prisma as a Python list and the row write failed. Every deployment warning ignore, snooze and restore hit this. Mask and re-serialize any JSON value instead
2026-10-14 22:16:47 -07:00
Mateo Wang
52fc37888b
fix(responses bridge): round-trip tool_search_call and tool_search_output items between turns (#46444)
* fix(responses bridge): keep defer_loading on function tools sent to the Responses API

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): give the defer_loading casts a cast-ok reason

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(responses bridge): build defer_loading outside the tool loop so Final stays valid

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): round-trip tool_search_call and tool_search_output items between turns

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(responses bridge): read replayed tool-search and namespace fields through typed helpers

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): keep tool_search items on a turn with no message or tool call

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): keep every reasoning item on a search-only turn

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): leave content unset on a search-only turn so replay adds no empty message

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): replay tool search items only with tool_search, count replayed tools in the allowlist, keep namespace off guardrails

* fix(responses bridge): honor drop_params for defer_loading and route tool_search to Responses

Under drop_params, defer_loading is dropped when no tool_search tool is sent,
so the 400 it would cause upstream goes away as before. A non-bool value answers
400 without drop_params and is dropped with it. A null tool-level value falls
back to the nested function value. A request carrying a tool_search tool now
bridges to Responses on OpenAI and Azure endpoints even with reasoning_effort
none, since chat completions rejects the tool_search type.

* fix(responses bridge): replay tool search items in output order and count replayed tools in tool policy

Store the ordered output prefix through the last tool search item, reasoning included, so a
second reasoning item no longer makes OpenAI reject the replay. The shared chat-to-Responses
converter now replays tool search items and namespace only when the bridge opts in, so Noma,
the complexity router and guardrail payloads keep their shape. The tool policy guardrail and
the allowlist count replayed tools only when the request can send them.

* fix(responses bridge): forward defer_loading only beside a tool_search tool

defer_loading only means something with tool_search, and backends without it
reject the key (xAI answers 403). A true value with no tool_search tool now
answers 400 naming drop_params and is dropped under drop_params; a false value
there is a no-op and is dropped.

* fix(tool_loop): keep tool search items and namespace between rounds

* fix(responses bridge): check replayed tool search loads when a deployment adds tool_search

* fix(chat): drop litellm response fields before strict OpenAI-compatible providers

A chat reply from the Responses bridge carries provider_specific_fields on the
message and on each tool call, plus reasoning_items. Groq, Fireworks, Mistral
and Together reject unknown fields, so sending that reply back to them as
history failed with a 400 or 422. Strip them in the shared helper and use it
in those providers.

* fix(caching): keep reasoning_items and tool search items on response cache hits

A cached bridge response lost reasoning_items on a non-streaming hit and lost
both reasoning_items and provider_specific_fields (tool_search_items) on a
streamed hit, so the next turn could not replay the search or the reasoning
around it

* test(integration): cover tool search item replay on the chat to Responses bridge

Proxy, SDK, authorization and chaos cells for returning and replaying
tool_search_call and tool_search_output items and the tool call namespace

* test(integration): add response cache twins for the tool search guardrail cells

Each guardrail cell now has a twin where the answer is already in the Redis response cache: a key opted out of global guardrails caches a replay that loads a policy-blocked tool, the same replay without guardrails is cached before block mode sees it, rewrite mode is not served the unrewritten conversation's cached answer, and an allowed replay is served from the cache.

* fix(responses bridge): forward defer_loading beside a client-executed tool_search

The bridge now replays a client tool_search_call and the client's tool_search_output through provider_specific_fields.tool_search_items, so a deferred function beside a client tool_search keeps defer_loading like it does beside a hosted one

* test(responses bridge): pin the client tool_search turn and its replay, streamed and not

* fix(responses bridge): strip nested namespace for strict providers and keep streamed reasoning_items on text replies

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses bridge): keep dropping defer_loading beside a client-executed tool_search

Forwarding defer_loading beside a client tool_search made GPT stop with a
search call the chat client has to answer by hand, so a plain question that
used to get tool calls got none. Keep main's behavior of dropping it there.

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-14 21:40:14 -07:00