Commit graph

430 commits

Author SHA1 Message Date
yuneng-jiang
062f4111ad
fix(ui): take the dashboard's user role and identity from the server (#47025) (#47224)
* fix(ui): take the dashboard's user role and identity from the server

Adds an internal GET /management/v1/users/me that returns the user id, role
and email the proxy resolved for the calling key. The dashboard now reads
identity from it instead of the session cookie's claims, so its navigation and
role gating always match what the backend authorizes. The layout waits on it
behind the existing loading screen, and a failed lookup clears the session and
returns to login. Sessions that must change their password can also read it

* fix(ui): sign out when the current user lookup fails and wait for it on chat

The dashboard layout now holds the loading screen and signs out when
/management/v1/users/me fails, instead of mounting the shell and looping back
to loading as each consumer refetched the failed query. The chat layout also
waits for the identity so its panels never query without a user id. The
lookup goes through the typed client with the regenerated schema.d.ts

* fix(ui): send the session's auth header on the first user lookup and keep chat closed until authorized

The first lookup runs before AuthProvider registers the custom header name, so it now reads auth_header_name from the session cookie. Chat also waits for isAuthorized, so a failed lookup no longer mounts the shell with an empty user id

* fix(ui): type the dashboard callers of the now typed user id

useAuthorized used to hand back the cookie's user id untyped, which hid six strict type errors in its callers. The id is now string | null, so the production build failed. Callers handle the null case, and query key filters accept the boolean blocked filter

* fix(ui): look up the current user only after the proxy URL is discovered

Pages outside the dashboard shell, like chat and connect, could start the lookup before UI config discovery set the proxy base URL. On a split-origin deployment both attempts then hit the UI origin and a valid session was signed out

* fix(ui): keep a loaded identity while UI config discovery reruns

Pausing the lookup by passing a null token switched the query key, so on the dashboard the identity the layout had already loaded vanished until the shell's own UI config request finished. The key now stays the same and only the fetch waits for discovery

(cherry picked from commit 4bafebbcdc)
2026-10-17 20:15:56 -07:00
yuneng-jiang
6a0603e00f
feat(count_tokens)!: backport the count_tokens stack to rc/1.107.0 (#46839, #46843, #46583, #47057, #47064, #47163, #46777) (#47209)
* fix(proxy)!: count prompt-only token_counter requests with the provider when call_endpoint is set (#46839)

* fix(proxy): count prompt-only token_counter requests with the provider when call_endpoint is set

* fix(proxy): keep the local count for a prompt-only token_counter request when the provider count fails

* fix(proxy): log a prompt-only token count fallback as a one-line warning

* fix(proxy): send a prompt-only token_counter request to the provider only on Gemini and Vertex AI

* fix(proxy): count a token_counter prompt sent next to an empty messages or contents list

* fix(proxy): count a prompt next to messages on the local token count instead of answering 500

* fix(proxy): answer 400 for a token count prompt next to a conversation unless drop_params is set

With drop_params the conversation is counted without the prompt. On the local count, a prompt sent with system or tools is counted as a user message with them, like the messages form.

* test(proxy): count tools with a prompt in the token counter fallback test

* test(proxy): cover prompt counting on /utils/token_counter in the Gemini count wire tests

* test(proxy): name the token counter fallback test by what it checks

(cherry picked from commit 2dc6aafa6b)

* fix(count_tokens): apply context_management edits in the Gemini /v1/messages/count_tokens count (#46843)

* fix(count_tokens): apply context_management edits in the Gemini /v1/messages/count_tokens count

/v1/messages runs clear_tool_uses context edits before it sends an Anthropic
body to a Gemini or Vertex AI deployment, but /v1/messages/count_tokens counted
the body unedited, so a request with older tool results cleared counted about
2.8x what inference bills.

The count now runs the same history and context-edit step inference runs,
honors additional_drop_params on the deployment, and skips compact edits so a
count never makes a paid summary call.

* fix(count_tokens): match the Gemini count to inference for compact edits and drop opt-outs

Run compact edits in the count without the summary call so trigger checks and
history slicing match /v1/messages, honor a request-level additional_drop_params,
keep the full body when any deployment in the model group drops context_management,
and answer 400 naming a block Gemini cannot count when an edit trigger fails on it

* fix(count_tokens): count the unedited body when an edit fails and honor deployment ids in the drop check

* fix(count_tokens): log a failed edit in the count at debug, since the send already logs it

* fix(count_tokens): resolve a deployment id before wildcard routes in the drop check, as the router does

* fix(count_tokens): honor the router-wide additional_drop_params opt-out in the drop check

The router merges default_litellm_params between the deployment and the request, so a router-wide context_management opt-out makes /v1/messages send the full history. The count now reads it in the same order. Adds the audit's wire tests for the count's context edits.

* fix(count_tokens): read the opt-out of a deployment the router serves by its litellm model name

* fix(count_tokens): read the opt-out and drop_params from the deployments the router and completion_model send to

* fix(messages): drop an invalid context_management spec under drop_params so the send matches the count

* fix(count_tokens): give Claude Code and Codex counts the drop_params default /v1/messages gives them

The proxy turns on drop_params for Claude Code and Codex user agents on /v1/messages. The count now applies the same default, so an invalid context_management spec drops on both endpoints instead of the count answering 400 while the send answers 200. The wire test also covers default_fallbacks, model_group_alias, and completion_model routes.

* test(count_tokens): cover a coding agent that turns drop_params off and stop two count tests running as Claude Code

(cherry picked from commit f8217d2a03)

* fix(proxy)!: answer 400 for malformed tools on count_tokens instead of crashing (#46583)

* fix(proxy): answer 400 for malformed tools on count_tokens instead of crashing

A non-list tools value crashed the vector store lookup during auth and the
built-in tool cost lookup in the failure logging path, so the proxy answered
an unhandled 500 and closed the keep-alive connection. count_tokens now
answers a 400 invalid_request_error for a malformed body, drops malformed
tools when drop_params is on, and both lookups skip values of the wrong shape.

* fix(proxy): skip non-list tools in the tool allowlist check

Also validate the count_tokens body without recursion, which the recursion detector rejects.

* test(integration): restore the int tools case on count_tokens

The proxy now answers a non-list tools value with a 400, so the case is deterministic again.

* fix(proxy): reject malformed tools at the LLM route entry and keep vector store checks on malformed ids

* fix(proxy): apply drop_params like core when dropping malformed tools, and reject malformed tool vector store ids

Check tools after request setup so the Claude Code default and the logged call type apply, read the request,
global, and model group drop_params the way core does, drop tool_choice and friends with tools, cover Gemini
generateContent, and answer 400 for a malformed tools[].vector_store_ids with the strict flag off

* fix(proxy): keep the request's call type when logging a gate rejection after request setup

The body-shape fallback relabeled a /v1/messages rejection as acompletion and a list-input /v1/responses
rejection as aembedding, so it now only applies when the logging object carries no known call type

* fix(proxy): share the malformed tools check across tool routes and honor drop_params per entry

* fix(proxy): accept null vector_store_ids, read every named store id in auth, check the responses websocket

* refactor(proxy): leave the responses websocket out of the request-level tool check

* fix(proxy): let a request's additional_drop_params replace the deployment list and keep compact's call type on rejections

* fix(proxy): read router default drop lists and deployment ids in the malformed tools check

* fix(proxy): leave malformed tools to the router when it can pick another deployment

Fallbacks, auto-routers, model strings, comma batches and team model names
let the router pick a deployment after the proxy checks the request, so the
proxy now forwards a malformed tools field there as main does, and only
rejects it when the deployment it checks is the one that serves. Token
counting never reroutes, so count_tokens and input_tokens keep reading the
group they count with. additional_drop_params names are read the way core
reads them, so a list with a non-string entry still names its strings.

* test(integration): cover malformed tools on reroutable models, router defaults and deployment ids

* fix(proxy): resolve malformed tools at the deployment the router picks

* fix(proxy): keep provider-repaired tool schemas, honor fallback_on_unsupported_params, skip cooldown on malformed tools

Empty schemas and JSON-string schemas pass the tools check the way litellm's provider paths already read them. The rejection is a BadRequestError subclass carrying the deployment's provider, so fallback_on_unsupported_params: false keeps the 400, and the router never cools a deployment down for a request litellm rejected before calling it. Adds the audit's pre_call guardrail and cross-provider bridge cells.

* test(integration): expect a 400 for an empty-string tools field on /v1/messages

Real Anthropic rejects tools "" with a 400 on main too, so the case joins the malformed tools test

* fix(router): keep web search routing for tools passed as a tuple

* fix(router): keep a deployment's own tools when drop_params drops a malformed request tools

* test(router): list _merged_tools as covered through the deployment tools merge tests

* fix(router): drop the request's tool settings with its malformed tools when deployment tools replace them

* fix(router): skip a tool whose type is not a string in the web search filter instead of raising TypeError

* fix(prometheus): keep deployment health metrics clean on a malformed tools rejection

* test: type the new malformed tools tests

* test: mark new test locals Final and type kwargs dicts

(cherry picked from commit d76ec3a47e)

* ci(cost map): classify token_count_model as an object key in the schema generator (#47057)

* ci(cost map): classify token_count_model as an object key in the schema generator

* ci(cost map): require non-blank token_count_model strings and test the region rules

(cherry picked from commit 6e191a58f1)

* ci(cost map): remove the generated model prices JSON schema (#47064)

* ci(cost map): remove the generated model prices JSON schema

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

* test(cost map): keep schema-independent cost map tests after dropping the schema

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

* ci(cost map): keep the schema file until main's guard stops requiring it

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

* ci(cost map): let bot sync PRs keep touching the schema file until it is deleted

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>
(cherry picked from commit ae6f7f6613)

* fix(count_tokens)!: answer 400 for Vertex partner models without a count API and OpenAI-shaped provider errors on /v1/responses/input_tokens (#47163)

* fix(count_tokens): answer 400 for Vertex partner models without a count API and OpenAI-shaped provider errors on /v1/responses/input_tokens

* fix(count_tokens): answer 400 for Vertex Mistral counts and type the input_tokens error tests

Vertex has no count-tokens route for Mistral or codestral models, so they now
get the same 400 as other partner models without a count API instead of a 404
that points operators at IAM.

* fix(count_tokens): unwrap prefixed provider errors on /v1/responses/input_tokens

* fix(count_tokens): say LiteLLM, not Vertex, cannot count a Vertex partner model

* fix(count_tokens): count a Vertex partner model with its configured custom_tokenizer and unwrap prefixed flat provider errors

* fix(count_tokens): keep the 400 for contents-only Vertex partner counts with a custom_tokenizer

* fix(count_tokens): pass through an OpenAI provider error that omits param or code

* fix(count_tokens): keep the status-based type for Anthropic count errors on the Responses route

* test(count_tokens): cover the Vertex partner count gate and Responses count error shapes on a real proxy

* test(count_tokens): add regression tests for the Vertex partner count gate and Responses count error shapes

(cherry picked from commit ef1d3959a0)

* feat(count_tokens)!: configurable token_count_framing and token_count_model, count source in the response (#46777)

* feat(count_tokens): configurable token_count_framing and token_count_fallback_model, count source in the response

Count endpoints now say where each number came from in litellm_count_source
(provider, fallback_model, local_estimate) and name the fallback model in
litellm_count_fallback_model. When the provider answers 400 or 404 for a model
it cannot count, the proxy counts the same request with token_count_fallback_model.
token_count_framing adds a per-model constant to local estimates. Both settings
ship in the cost map for Bedrock Claude Sonnet/Haiku 5.5, Bedrock Kimi K3, and
Databricks Kimi K3 and DeepSeek V4 Flash, and can be overridden in model_info.

* test(count_tokens): classify the new cost map keys in the schema generator and expect count_source in exact-shape tests

* test(count_tokens): e2e matrix against real inference and integration wire tests for count source, fallback and framing

* fix(count_tokens): keep the provider error when local counting is disabled, name the fallback error, keep settings in cooldown

Moves the cost map lookup off the event loop

* ci(cost map): bound token_count_framing to non-negative and token_count_fallback_model to non-empty

* fix(count_tokens): keep a failed fallback's own status, ship fallbacks only where they count, add system.ai framing

A fallback model that answers 404 returns the requested model's error unchanged, and any other fallback
failure answers with its own status and message. The eu, apac, au and jp Sonnet and Haiku 5.5 entries
no longer ship the Opus 5.5 fallback, which AWS serves only in us-east-1. A configured empty
token_count_fallback_model turns the shipped fallback off. Config framing accepts whole-number floats and
rejects negatives. The Databricks system.ai Kimi K3 and DeepSeek V4 Flash names carry the same framing as
their serving endpoint names, and the e2e matrix runs on Bedrock Haiku 5.5 too.

* test(databricks): list the system.ai Kimi K3 and DeepSeek V4 Flash names with their published DBU rates

* fix(count_tokens): skip a token count fallback model for an hour after it answers 404 on that deployment

A us. or global. Sonnet 5.5 deployment outside us-east-1 paid two extra Bedrock
calls and about 200 ms on every count, since Opus 5.5 cannot count there either.
The Kimi K3 e2e also runs the large system prompt shape now.

* test(count_tokens): use the shared integration port allocator in the fallback wire test

* fix(cost map): keep the Databricks system.ai entries to framing only, so their spend stays as today

* test(count_tokens): cover the fallback 404 skip, inference profile base_model, shipped framing, and deployment-scoped token count settings

Adds integration cells for a fallback model that answers 404, an application inference profile ARN deployment whose base_model carries the shipped fallback, and the shipped Kimi K3 framing with token_count_framing 0 turning it off. Adds unit tests that keep token count settings off the shared backend cost map key and that store a token count setting on PATCH only when the operator changed it

* fix(count_tokens): keep the counter's own 400 and the provider's error when a framed estimate cannot read the body

A 400 the OpenAI or Gemini counter returns before calling the provider is the caller's answer, so it no longer tries the fallback model or a framed estimate. When the framed local estimate cannot read a content block, the client gets the provider's error instead of a 500. Adds /audit round 2's integration tests for the fallback leg's converted body, the Anthropic envelope on fallback failures, and both framing cases.

* fix(count_tokens): answer the provider's error whenever a framed estimate raises

A tool schema the local estimate cannot format, such as a boolean subschema or an array with no items, raised AttributeError or KeyError and answered a 500 on a framed deployment whose provider had already answered 400. Any estimate failure now answers the provider's own error.

* fix(count_tokens): load the custom tokenizer inside the guarded framed estimate

A framed deployment whose custom_tokenizer could not load answered a 500 or 503 where the provider had already answered 400, because the tokenizer was selected outside the estimate's error handling. Selecting it inside answers the provider's error, logs a warning with the estimate's error, and still raises the Rust extension's fork-guard errors.

* fix(count_tokens): look up framing under the deployment's custom_llm_provider

* fix(count_tokens): share one tokenizer download per worker and bound the wait after a provider error

A framed deployment whose custom_tokenizer is not cached locally made every
count wait out the Hugging Face hub's whole retry cycle when the hub could not
be reached, and a burst of those loads held the default thread limiter that
every count's cost map lookup also needs. Counts on a worker now share one
download per minute, a failed download is reused for the rest of that minute,
and after a provider error a count waits at most 5 s before answering the
provider's error. The swallowed-estimate warning logs only the error type.

* fix(count_tokens): keep one tokenizer download per key running and load the local route per request

* test(count_tokens): type the scripted counter and wait on events instead of wall time where possible

* fix(count_tokens): run framed tokenizer loads on their own capped threads and answer a tokenizer panic with the provider error

Framed loads used anyio's default 40 threads, so a hub that drops packets let about 40 hanging loads stall every count on the worker. Loads now run on a per-worker pool of 4, and a count that finds 4 loads running answers the provider's error at once. Any finished load is reused for a minute after it finishes, so a load that fell back to tiktoken is not retried on every count. A pyo3 PanicException from the tokenizer, while loading or counting, now answers the provider's error instead of a plain 500

* feat(proxy): count tokens with token_count_model in its pinned region

token_count_model {model, region} replaces token_count_fallback_model. Bedrock Sonnet and Haiku 5.5 count with Opus 5.5 in us-east-1, or Melbourne for au. profiles, and a failure names the region to enable

* fix(count_tokens): use the renamed count model constant in the e2e test and list token_count_model with the object keys

* fix(proxy): keep the upstream error envelope when adding the region hint

* test(proxy): annotate the token count setting echo test

* ci(cost map): require non-blank token_count_model strings and test the region rules

* fix(count_tokens): answer the token_count_model's error even when framing is set

* fix(count_tokens): keep the provider error for Google contents instead of a framed estimate

* fix(count_tokens): estimate Google contents the route translated to messages

* fix(count_tokens): keep the provider error for Google contents with non-text parts

* test(proxy): drive tokenizer wait and cost map tests by events and a skippable loop clock

* fix(count_tokens): check Google text-only parts without a KeysView comparison basedpyright flags

* feat(proxy): count Bedrock Kimi K3 tokens exactly with its pinned tokenizer

* test(bedrock): keep the Kimi K3 image check in-process

* fix(count_tokens): join the region hint to an upstream message that already ends with a period

Also pins that a blank token_count_model in config falls through to the cost map default

* fix(count_tokens): count Gemini tool-call turns and Responses tools, and stop tokenizer retries from stalling counts

The Google countTokens route estimates contents with functionCall, functionResponse and thoughtSignature parts again, and still answers the provider error for media, thought and unknown parts

The Kimi K3 exact count renders Responses API and Anthropic tools through the chat tool translation the Vertex count already used, now shared from the prompt factory, and falls back to the estimate when the Converse body cannot carry a tool

A failed Kimi K3 tokenizer load is retried in the background without making counts wait, and a load still running after the wait logs a warning

* fix(count_tokens): count Kimi K3 tools the way Bedrock inference sends them

A flat Responses API function or custom tool becomes the chat tool the
Responses route sends to inference, and every other tool goes to the
Converse body as is, so hosted tools Bedrock drops are left out of the
count instead of being counted or turning it into an estimate.

* test(count_tokens): annotate new token counter test locals with Final

* fix(count_tokens): keep shipped count regions inside the deployment's geography

A plain Bedrock Sonnet or Haiku 5.5 deployment in a non-US region no longer sends its count prompt to us-east-1. Global count models and configured token_count_model keep their pinned region. Also expect litellm_count_source in the Vertex Llama count test main added

* fix(count_tokens): resolve count settings off the event loop

(cherry picked from commit 75faaeab64)

---------

Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-17 18:20:22 -07:00
yucheng-berri
9445634193
fix(bedrock): backport #46307 and #46524 to rc/1.107.0 (#47157)
* fix(bedrock)!: stream Converse passthrough frames through post_call guardrails instead of buffering (#46307)

* test(integration): Converse stream post_call guardrail relays frames as they arrive (LIT-9515)

* fix(bedrock): stream Converse passthrough frames through post_call guardrails instead of buffering (LIT-9515)

A post_call guardrail that scans through apply_guardrail now runs on
/bedrock/.../converse-stream the way it runs on /v1/messages: frames reach the
caller as the upstream sends them, every fifth frame and the end of the stream
are scanned, and a block after the first frame ends the stream with an AWS
exception frame. streaming_buffer_until_moderated still holds the stream and
applies masks per content block. Guardrails that need the whole response
(own async_post_call_success_hook, mask_response_content, native hooks, policy
pipelines) keep the buffered path.

* fix(bedrock): apply held Converse stream masks when the upstream ends with an exception frame (LIT-9515)

* fix(proxy): log a relayed passthrough stream's spend before its mid-stream failure hook (LIT-9515)

* fix(bedrock): close and report every way a relayed Converse stream ends (LIT-9515)

- The framer ends the stream with an empty item once the upstream closes, so held masks are applied whether the
  upstream ends with messageStop, an exception or error frame, or a dropped connection
- A guardrail HTTPException after the first frame reaches the relay, which logs the stream's spend, runs the
  failure hook and ends the stream with the exception frame, instead of ending inside the guardrail with no
  failure row
- A failure before the first frame waits for the stream's spend to be logged, as a mid-stream failure does
- Closing the response before its body starts closes the guardrail layers and the upstream
- Each stacked guardrail layer gets its own copy of every frame, so an earlier layer's end-of-stream rewrite never
  reaches frames a later layer still holds
- Deltas whose text ends in half a surrogate pair are decoded with the standard JSON parser

* fix(bedrock): relay a Converse frame whose payload is not UTF-8 instead of ending the stream (LIT-9515)

* test(integration): cover Converse stream relay failure, end-of-stream-only, stacked, disconnect and burst cells (LIT-9515)

* fix(bedrock): estimate prompt tokens for a passthrough stream cut before Bedrock reports usage (LIT-9515)

Bedrock sends usage only in the last frame of a stream, so a stream ended by a guardrail block or a client
disconnect logged 0 prompt tokens while AWS still charges for the prompt. The stream collector now estimates them
from the request the way chat completions streams do

* fix(bedrock): read tool result blocks without recursion in the passthrough prompt estimate (LIT-9515)

* fix(passthrough): keep the spend flush running when the wait for it is cancelled (LIT-9515)

* fix(bedrock): keep a converse-stream buffered when its guardrail releases a held stream on scan (LIT-9515)

A held post_call guardrail with streaming_buffer_release_on_scan releases each
window as received once its scan passes, so the relay delivered the original
text instead of the guardrail's masks. Such a stream keeps the buffered path,
which applies masks per content block as on main.

* fix(bedrock): keep a converse-stream buffered when a post_call guardrail runs in parallel (LIT-9515)

The relay ran every guardrail in config order, so a run_in_parallel guardrail
listed before a masking guardrail scanned the unmasked text. Main's buffered
path runs parallel guardrails after the sequential ones and discards their
rewrites, which the relay cannot reproduce, so these streams stay buffered

* fix(bedrock): mark Noma v2 relay scans like chat and stop reading Bedrock when a held stream's client leaves

- Noma v2 scans on the converse-stream relay carry stream, and the last one
  carries the finished Converse response with its stopReason, as chat sends
  them, so Noma keeps one record per reply. Other guardrails get the request
  unchanged. When the last sampled scan already covered the whole answer, the
  end-of-stream scan still runs for Noma so it gets the finished answer
- A held relay stream whose client leaves before the first frame stops
  reading Bedrock and returns 499, like chat. When Bedrock sent nothing yet,
  the budget reservation and the parallel-request slot are released
- A cancelled wait for the first streamed chunk now stops the upstream read
  instead of leaving it running
- A Noma v2 scan cancelled before Noma answers records not_run instead of
  success with an empty response

* fix(bedrock): send Noma the finished Converse reply's tool calls and reasoning as Converse blocks

* fix(bedrock): give Noma the ended scan of a Converse reply that only calls a tool without input

* test(bedrock): expect the ValidationException main now returns for a held block before the first frame

Main's AWS-shaped passthrough errors (#46522) answer a guardrail block before the first frame with x-amzn-errortype ValidationException, so boto3 reads the code and the guardrail message instead of a bare 400.

* fix(bedrock): keep held masks when an earlier sampled guardrail ends the Converse stream with its message

A sampled guardrail that blocks with disable_exception_on_block ends the stream with its message as raw
event-stream bytes. A held guardrail after it on the same key only read frame objects, so it never saw the
messageStop, skipped its write-back and released the held text without its masks. The Converse handler now
reads those bytes back into frames, so the held guardrail sees the end of the message and masks the text

* fix(proxy): free the parallel slot when a caller leaves a Converse relay holding part of the first frame

The relay skipped releasing the slot and budget reservation whenever a spend
flush was scheduled, but a flush of a partial first frame builds no response
and logs nothing, so the slot stayed held until it expired. The flush now says
whether it logged the stream.

---------

Backport of #46307 to rc/1.107.0
Cherry-picked from ef1cb19351 (main)

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>

* fix(bedrock)!: scan Claude invoke-with-response-stream passthrough output with post_call guardrails (#46524)

* fix(bedrock): scan Claude invoke-with-response-stream passthrough frames with post_call guardrails (LIT-9618)

Invoke streams of Claude models now go through the same frame-by-frame relay as
converse-stream. Each chunk frame's Anthropic event is scanned by the /v1/messages
stream translation, a block ends the stream with an AWS exception frame, and a held
stream gets its masks written back into re-encoded chunk frames. Claude is told by
its model id or, behind an application inference profile, by the anthropic_version
its request body carries. Streams of other model families stay as they were

* test(bedrock): cover invoke stream vendor outage, upstream exception and release on scan (LIT-9618)

* fix(bedrock): hold Claude invoke streams for guardrails the relay cannot run and mark each scan as streaming (LIT-9618)

A guardrail released on scan or run in parallel left a Claude invoke-with-response-stream unscanned, while
converse-stream holds the whole stream and scans it once. Claude invoke streams now take the same buffered
path, with the rewrites written back into the chunk frames that carried each text.

Each invoke scan also sends stream true and the events relayed so far as responses, as /v1/messages does,
so a vendor can tie the scans of one streamed reply together.

* refactor(bedrock): mark the request dicts the buffered stream paths hand to post_call hooks (LIT-9618)

* fix(bedrock): scan a Claude invoke stream the upstream breaks off as a finished stream (LIT-9618)

An invoke stream that ended on an upstream exception, without a message_delta stop_reason, was scanned
as still in flight, so its tool input never reached the guardrail and a held stream released it unscanned.
The scan and its scan key now close such a stream the way converse-stream treats the end of its upstream.

* test(bedrock): pass the converse-stream endpoint where the tool call without input test frames its stream (LIT-9618)

* test(bedrock): expect the ValidationException main now returns when a guardrail blocks a Claude invoke stream before its first frame (LIT-9618)

* test(bedrock): type the Claude invoke event helpers in the passthrough guardrail tests

* test(bedrock): type the remaining parameters of the Claude invoke stream tests

* refactor(bedrock): bind the buffered invoke rewrite in its condition

---------

Backport of #46524 to rc/1.107.0
Cherry-picked from 9f115be88d (main)

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>

---------

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
2026-10-17 14:45:38 -07:00
yuneng-jiang
1738b8a169
fix(vector-stores): keep proxy context out of provider vector store metadata (#47021) (#47159)
* fix(vector-stores): keep proxy context out of provider vector store metadata

The proxy merged its request context (user_api_key_* fields, endpoint,
user_agent, requester_ip_address, litellm_api_version) and the router's
deployment info into the vector store request's metadata. For vector
stores that field is also OpenAI's own metadata, which is capped at 16
keys, so a store created with a team key was full on creation and every
later metadata update returned 400.

Vector store routes now keep that context in litellm_metadata, like
batches, files and responses, and the router does the same for
avector_store_create. Provider-side metadata holds only what the caller
sent.

Adds db_scripts/strip_vector_store_internal_metadata.py, an opt-in
script that removes the proxy-written keys from stores created before
this change. It is a dry run unless --apply is passed.

* fix(vector-stores): page the metadata cleanup script without recursion and tolerate non-string values

Listing every store recursed once per page, which overflows the interpreter stack on large projects. Pages are now walked iteratively. Metadata values are no longer required to be strings, and a malformed response exits 2 with a fixed message instead of a traceback that could echo metadata values.

* fix(vector-stores): read proxy agent id, tags and spend_logs_metadata from litellm_metadata

Vector store routes now keep proxy context in litellm_metadata, but the v3
limiter only read agent_id from metadata, and logging let provider metadata
tags or spend_logs_metadata replace the proxy's values. A string tags value
also crashed get_request_tags.

The limiter now prefers the proxy-resolved agent_id in litellm_metadata.
Logging combines list tags from both buckets (metadata first, deduplicated)
and merges dict spend_logs_metadata with litellm_metadata winning, ignoring
values of the wrong type.

* fix(vector-stores): narrow the logging fallback to mistyped caller values

The tag union and spend_logs_metadata merge changed logged tags and
spend_logs_metadata on every route that has both metadata buckets, deduped
tags quadratically, and stopped background interaction polling from keeping
string tags as sent. Caller values now win exactly as before, and the
proxy's litellm_metadata tags or spend_logs_metadata only replace a caller
value of the wrong type.

The limiter reads agent ids through a pydantic model instead of a cast and
ignores non-string ids.

* fix(vector-stores): log the proxy's full tag list on litellm_metadata routes

On routes that keep proxy context in litellm_metadata, the proxy builds
litellm_metadata.tags from the caller's tags plus key, team and header
tags, but get_request_tags preferred the caller's metadata.tags. A caller
sending metadata.tags on a vector store call dropped the key's tags from
request_tags, which tag spend tracking reads. get_request_tags now prefers
a non-empty litellm_metadata tag list, and falls back to metadata.tags as
before.

* fix(vector-stores): strip LiteLLM-written keys at the provider boundary instead of moving metadata buckets

Moving vector store proxy context into litellm_metadata broke shared readers
(agent limits, request tags, merged logging metadata), and fixing them
widened the change to every litellm_metadata route. This reverts the bucket
move, the router change and the reader fixes, so proxy context stays in
metadata exactly as on main.

Vector store create and update now drop the keys LiteLLM itself writes
(user_api_key*, requester and deployment keys, agent ids) from the metadata
sent to the provider, in the shared optional-param helper both paths use.
The cleanup script reuses the same key list.

* fix(vector-stores): pass non-string metadata keys through the provider metadata filter

* fix(vector-stores): strip LiteLLM-written metadata keys only on proxy and router calls

* fix(vector-stores): send the provider exactly the metadata the caller sent through the proxy

* fix(vector-stores): snapshot caller metadata from the raw request body and keep it out of logged request bodies

* fix(vector-stores): copy the parsed-body metadata when the raw request body cannot be reparsed

(cherry picked from commit 4846cfabc7)
2026-10-17 13:53:28 -07:00
Yassin Kortam
cda17c8e81
fix(mcp)!: backport the OAuth Delegate fields and gateway-owned DCR bridge client to rc/1.107.0 (#46941, #46940) (#47153)
* feat(ui): backport the OAuth Delegate endpoint and scope fields to rc/1.107.0 (#46941)

Backport of #46941 to rc/1.107.0. Cherry-picked from 3637dd711f

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

* fix(mcp)!: backport the gateway-owned DCR client for bridge servers to rc/1.107.0 (#46940)

Backport of #46940 to rc/1.107.0. Cherry-picked from 7049a5ff4d

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>
2026-10-17 12:26:56 -07:00
Yassin Kortam
bfd9594d8e
fix(mcp)!: cap the ID-JAG credential by its signed resource claim and refuse a resource the gateway does not serve (#47094) (#47138)
Backport of #47094 to rc/1.107.0.

Cherry-picked from 8b1859c50d (main).

(cherry picked from commit 8b1859c50d)

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-17 10:31:30 -07:00
Yassin Kortam
1f8bdaa657
feat(mcp): backport the ID-JAG stack to rc/1.107.0 (#46748, #46747, #46745, #47004) (#47058)
* feat(mcp): accept an ID-JAG as an RFC 7523 jwt-bearer grant on the gateway token endpoint (#46748)

Backport of #46748 to rc/1.107.0.
Cherry-picked from bca7650e8f (main).

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

* feat(sso): capture the IdP id_token on Microsoft and Google logins for oauth2_id_jag (#46747)

Backport of #46747 to rc/1.107.0.
Cherry-picked from 3501e36fa9 (main).

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

* feat(sso): retain the SAML assertion at login as the saml2 subject token for oauth2_id_jag (#46745)

Backport of #46745 to rc/1.107.0.
Cherry-picked from f02449ad38 (main).

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

* fix(proxy): keep the OIDC login refresh token as the ID-JAG subject when the SSO client is the ID-JAG client (#47004)

Backport of #47004 to rc/1.107.0.
Cherry-picked from fc484be77a (main).

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>
2026-10-17 09:21:26 -07:00
yuneng-jiang
a00d8a6ee1
fix(proxy): backport the 1.107.0 rc triage fixes to rc/1.107.0 (#47043)
* fix(proxy): give /team/delete transactions a 30s timeout (#46979)

Both interactive transactions in /team/delete used Prisma's 5s default.
A lock wait or a short database stall past 5s expired the transaction
after the keys were already deleted, so the call returned 503 and left
the team row, memberships and team models behind

(cherry picked from commit 6530b329f4)

* fix(sso): concurrent first sign-ins land on the winner's account, worker-kill test stops waiting on the reap (#46855)

* fix(sso): concurrent first sign-ins land on the account the winner created, worker-kill test pins half its streams to each worker

* test(integration): a worker kill returns once the worker is dead, the reap waits at block exit

uvicorn can take a full worker healthcheck to reap a worker that died mid-ping, so kill() held
the caller that long and peers held on the surviving worker hit their client timeout

* fix(sso): a sign-in that loses the first-insert race joins the default teams

The losing sign-in could read the winner's row before new_user added the default teams, so its
CLI key was minted with no team. The race tests now run the real new_user against a fake user table

(cherry picked from commit 29cd11bec6)

* test(e2e): fix MCP tool search hit matching and the retired Bedrock image model (#46998)

* test(e2e): compare parsed MCP tool search hit names instead of raw text

* test(e2e): move Bedrock image generation off the retired Nova Canvas model

(cherry picked from commit e9a8581a02)

* test(integration): fix seven CircleCI integration tests that race or assume a worker spread (#47001)

* test(integration): expect the tool search call replayed beside the function call for Anthropic targets

* test(integration): wait for the team spend flush before killing a worker

* test(integration): poll for the S3 attempt the batch sinks write concurrently

* test(integration): queue the terminal object and its sibling into the same s3_v2 flush

* test(integration): time the long Bedrock version against an equally long unversioned name

* test(integration): pin each half of a burst to one worker instead of hoping the kernel spreads it

* test(integration): assert parsed SSE events for live pings instead of transport chunk boundaries

(cherry picked from commit 910c30381b)

* test(ui): wait for the logout navigation before checking the session is gone (#47008)

(cherry picked from commit 53ef63145b)

* fix(ui): preserve key settings drafts during background refreshes (#41350)

* fix(ui): preserve key settings drafts during background refreshes

* fix(ui): refresh untouched key settings while preserving edits

* fix(ui): keep team-change MCP clears across key refreshes

clearMcpGrants now marks the MCP fields dirty, so a background refresh with
keepDirtyValues no longer restores the grants a team change just cleared.
Also adapts the draft tests to the onSubmit(values, dirtyFields) signature
on main and asserts a refresh does not mark untouched fields dirty, since the
team admin member-key path rejects saves with non-budget dirty fields.
KeyEditView becomes a one-line arrow to stay under the max-lines limit.

* fix(ui): keep MCP tool defaults out of a key's edited fields

MCPToolPermissions writes non-delete tool defaults for unrestricted servers
on mount. Marking that write dirty made a team admin's budget-only save on a
member key get rejected for editing mcp_tool_permissions. onChange now says
whether a write is a default or a user edit, and the key editor dirties only
edits.

The edit session is now keyed by token or token_id, matching the form's own
fallback, so switching between keys that only carry token_id starts fresh.

* fix(ui): keep a new MCP server's default tool limits across refreshes

Default tool writes for a server the user just added in this edit session
are part of that edit, so they are marked dirty and survive a background
refresh. Defaults written for an already saved server stay clean, so a team
admin's budget-only save on a member key is still accepted.

(cherry picked from commit 37b3a697c7)

* fix(logging): stop the spend metadata merge from walking a dict the logging thread writes to (#46044)

(cherry picked from commit aa32e4cc88)

* test(integration): expect a pre-token invalid prompt on a bridged stream to fall back (#47020)

#46493 reads the first stream chunk inside the router's retry and fallback
chain, so an invalid prompt rejected before any token now falls back to the
configured fallback deployment instead of answering 400. The author
confirmed this is intended

The fallback test now asserts the spare serves the stream. The old 400
without a fallback attempt still holds when fallback_on_unsupported_params
is false, so that contract moves to a second proxy with that setting

(cherry picked from commit 856a3f62f3)

* test(e2e): repair fallback management test for config-owned fallbacks (#47023)

* test(e2e): repair fallback round trip for config-owned fallbacks

The e2e stack config sets router_settings.fallbacks, and since #45860 a
/fallback write to a key the config file owns is refused with a 400. The
round trip now runs on context_window fallbacks, which the stack config
leaves to the database, and also deletes the rule and checks it is gone.

A second test locks the new contract: a /fallback write to the
config-owned fallbacks key returns 400 naming router_settings.fallbacks,
and the config rule keeps being served unchanged.

* test(e2e): assert the refused fallback rule is never served

(cherry picked from commit 59fa785de0)

* test(e2e): assert the Vertex cache-creation billing contract in the prompt caching test (#47027)

The cache-creating call now reports cache_creation_input_tokens on top of
Vertex's own prompt count and bills the write at the input rate, as Google
does. The old assertions assumed neither, so the test went red on every run.
Check the cache write, the discounted read, and that a second identical call
reuses the cache instead.

(cherry picked from commit 81a3802a92)

---------

Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-16 19:03:48 -07:00
yuneng-jiang
c61bb56f7a
fix(mcp): stop proxy-started legacy listeners from consuming server rpm (#46968) (#46982)
* fix(mcp): stop proxy-started legacy listeners from consuming server rpm

The listener the proxy opens on notifications/initialized for legacy MCP
sessions ran the server rate-limit admission once per target, so every
session spent an rpm slot before the client sent anything. Admission is
now injected into the listener and applied only to client-initiated
subscriptions (subscriptions/listen and resources/subscribe). Authorization
and its periodic recheck still run on every path.

* test(mcp): key the fake admission window by caller and server

* fix(mcp): stop subscription catalog refreshes from consuming server rpm

A subscription listener lists the caller's catalog to diff list_changed
events, at setup and on every upstream event. Those listings went through
the normal per-server admission, so against an upstream that declares
listChanged each legacy session spent several rpm slots before the client
asked for anything. The listener now marks its targets as already admitted
for its own lifetime, so its refreshes reuse the subscription's admission.
Client requests on the session are still metered.

* test(mcp): exercise subscription admission through the proxy rate limiter

(cherry picked from commit ac6300f380)
2026-10-16 15:22:16 -07:00
Tufail Akram
84eeebd509
fix(proxy): track and drain management audit log writes on shutdown (#43594)
* fix(proxy): track and drain management audit log writes on shutdown

* fix(proxy): track hook spawns and defer registration in audit log drain

* fix: satisfy LIT006 on audit log task registry by documenting the required cast

* fix(proxy): satisfy LIT006 and LIT010 in audit task registry

* test(proxy): drive the audit drain tests with events instead of wall-clock waits

* fix(proxy): drain audit writes beside the shutdown flushes and track only premium writes

Run the audit drain concurrently with the gateway and request-error flushes so
the two waits overlap inside the teardown budget, register the running audit
task only after the premium check, drop the four duplicate task-failure
loggers, and cover the shutdown order and a real hook spawn with tests

* fix(proxy): start hook audit writes before their email and secret manager calls

Key and user hooks now spawn their tracked audit write first, so a slow
invite email or secret manager call no longer spends the drain budget
before the write starts. The endpoints stop tracking the hook tasks, so
shutdown never waits on hook I/O when audit logging is off.

Adds regression tests for the hook order, the failed block or unblock
update, and the shutdown drain without a database.

* fix(proxy): track only the audit insert, not the code that awaits it

The shutdown drain now waits on each audit row insert itself, so it never waits on a caller's later work and covers every caller without per-endpoint wrappers. The user/new hook still tracks its own task because it reads the user row before the insert

* test(proxy): drain the audit registry in the config audit tests

The audit insert now runs in its own tracked task, one hop after the caller's task, so a single yield no longer reaches it

* fix(proxy): name dropped audit rows in the drain timeout warning

Each tracked audit task is named after its action, table, object id and destination, so a shutdown that drops a row says which one. Adds tests that the drain waits for slow audit callbacks and that the warning names the dropped row

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-16 08:41:34 +00:00
yucheng-berri
f281f77bc0
fix(guardrails): record every content filter match in logging_only and offer the mode in the UI (#46673)
* test(guardrails): pin content filter logging_only matches and UI modes in an integration test

* fix(guardrails): record every content filter match in logging_only and offer the mode in the UI

* style(tests): format the content filter logging_only integration test

* refactor(guardrails): keep the logging_only predicate and scan override within the type gates

* fix(guardrails): flag tool arguments a content filter would reject in logging_only and keep scanning

* test(integration): expect guardrail_flagged for an observe-only content filter block in the scope config test

* test(integration): pin logging_only flags for tool arguments an enforcing content filter rejects

* refactor(guardrails): drop the content filter flagged branch no logging_only scan can reach

* test(integration): pin OTel spans, Guardrails Monitor and a provider outage burst for a logging_only content filter

* test(integration): pin MCP tool call verdicts and fail the Monitor cell when usage never rolls up

* test(integration): pin category and competitor intent verdicts and the provider failure row in logging_only

---------

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
2026-10-16 00:37:03 -07:00
Mateo Wang
b21e659c24
fix(proxy)!: count endpoints return errors in their source API shape instead of silent local counts (#46815)
* 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

* fix(count_tokens): count Anthropic-format requests for Gemini the way /v1/messages inference converts them

* fix(count_tokens): return a 400 naming Anthropic blocks the OpenAI and Gemini count can't convert

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

* fix(count_tokens): reject unconvertible blocks nested inside a tool_result

* 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): fetch Gemini remote media without blocking the event loop

* 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

* chore(count_tokens): give the Gemini count helpers' list returns a reason

* fix(count_tokens): normalize Anthropic messages for Gemini counts the way /v1/messages does

* fix(count_tokens): count Gemini bodies after inference's history rewrites and answer converter errors with 400

* test(count_tokens): cover the Gemini count error paths and compaction with a text-block system

* fix(proxy): count endpoints return missing-key and request errors in their source API shape

* fix(proxy): drop imports the count error change left unused

* fix(proxy): let Entra-authenticated Azure AI Claude count tokens and keep Google count errors in the Google envelope

* fix(proxy): send Azure environment keys as x-api-key on Azure AI Claude counts and log unexpected Google count failures

* fix(proxy): count with the global OpenAI and Anthropic keys chat already uses

* fix(proxy): resolve the OpenAI count base with the key so a global key stays on its gateway

* fix(proxy): keep unexpected Google count failures generic so internal details stay out of the response

* fix(proxy): resolve the Azure AI Claude count base from the same settings chat reads

* fix(proxy): count OpenAI tokens with the workload identity bearer chat already uses

* fix(proxy): mint the OpenAI workload identity bearer inside the count error handling

* fix(proxy): report a failed OpenAI workload identity exchange on the count endpoints as a 401

---------

Co-authored-by: Mrinal Chanshetty <mrinal@berri.ai>
2026-10-16 00:11:39 -07:00
yucheng-berri
b5870df967
fix(bedrock-passthrough)!: return AWS-shaped errors so AWS SDKs read the code and message (#46522)
* fix(bedrock-passthrough): return AWS-shaped errors so AWS SDKs read the code and message

A guardrail block on a /bedrock route now answers with x-amzn-errortype ValidationException and a top-level message, and an error Bedrock returned (such as a 429 ThrottlingException) is passed through with its status, x-amzn-errortype and body

* fix(bedrock-passthrough): keep 5xx guardrail failures and failure-hook replacements unchanged

* test(bedrock-passthrough): guardrail vendor failures and unknown models keep the litellm error

* fix(bedrock-passthrough): only answer guardrail exceptions that blocked content as ValidationException

* fix(bedrock-passthrough): pass Bedrock's content-type through with its error body

* refactor(bedrock-passthrough): wrap the guardrail ProxyException instead of copying its fields

Unit tests drive the error response with the real request processor and ProxyLogging

* test(bedrock-passthrough): cover the direct model route, invoke, and auth, budget and rate-limit errors

* fix(bedrock-passthrough): pass through only errors a Bedrock model operation returned

A guardrail service's HTTP error that carries x-amzn-errortype keeps the litellm error

* refactor(bedrock-passthrough): mark Bedrock's errors where the passthrough raises them instead of matching the URL

A guardrail service's HTTP error never goes through the passthrough call, so it keeps the litellm error whatever its URL

---------

Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
2026-10-15 22:05:46 -07:00
devin-ai-integration[bot]
5570d4268c
fix(proxy): only release the legacy limiter's slot from an admitted Responses WebSocket (#46822)
The shared disconnect release dispatched to the legacy limiter, which decrements unconditionally, so a rejected realtime attempt freed a slot it never took. The generic release is v3-only again and the Responses WebSocket close releases through its own method

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 20:34:48 -07:00
Mateo Wang
79ca820933
fix(count_tokens): return a 400 naming Anthropic blocks the OpenAI and Gemini count can't convert (#46772)
* 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

* fix(count_tokens): count Anthropic-format requests for Gemini the way /v1/messages inference converts them

* fix(count_tokens): return a 400 naming Anthropic blocks the OpenAI and Gemini count can't convert

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

* fix(count_tokens): reject unconvertible blocks nested inside a tool_result

* 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): fetch Gemini remote media without blocking the event loop

* 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

* chore(count_tokens): give the Gemini count helpers' list returns a reason

* fix(count_tokens): normalize Anthropic messages for Gemini counts the way /v1/messages does

* fix(count_tokens): count Gemini bodies after inference's history rewrites and answer converter errors with 400

* test(count_tokens): cover the Gemini count error paths and compaction with a text-block system

---------

Co-authored-by: Mrinal Chanshetty <mrinal@berri.ai>
2026-10-16 03:19:55 +00:00
Kerry Lu
081cfa2a62
fix(proxy): reset end-user spend in committed pages so the budget cascade survives a large LiteLLM_EndUserTable (#46502)
* fix(proxy): reset end-user spend in committed pages so the budget cascade survives large LiteLLM_EndUserTable

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

* style(proxy): collapse _enduser_ids_by_tier return to one line for ruff format

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

* fix(proxy): mark the end-user page IN list as bounded for the unbounded-IN check

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

---------

Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 19:47:12 -07:00
Kerry Lu
5ed3629242
fix(responses): write one spend-log row per native WebSocket turn (#46768)
* fix(responses): write one spend-log row per native WebSocket turn

Each response.create turn on a native Responses WebSocket connection logs and bills as its own call when its terminal event arrives, keyed by the resp_ id the client saw, instead of one row at socket close that sums every turn

* test(responses): mock the websocket slot release and mark the per-turn start time naive

* style(responses): keep the per-turn start time line within ruff format

* refactor(responses): type websocket turn events as read-only mappings

* fix(responses): settle the websocket budget reservation on the first turn only

Every per-turn logging copy carried the connection's admission reservation, so two turns whose cost callbacks overlapped could both reconcile it. The first turn keeps the reservation and later turns charge their cost directly

* fix(proxy): keep the legacy limiter's websocket slot until disconnect

A websocket turn callback no longer decrements current_requests in the legacy limiter. The socket's slot is released once from arelease_max_parallel_requests_on_disconnect, which now dispatches to the legacy handler as well

---------

Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-15 19:05:22 -07:00
yuneng-jiang
cf1e6b19ab
fix(sso): share SAML sign-in state over Redis without enable_redis_auth_cache (#46807)
* fix(sso): share SAML sign-in state over Redis without enable_redis_auth_cache

SAML login tickets, the single-use assertion mark and cached IdP metadata
lived in user_api_key_cache, which only gets Redis when
enable_redis_auth_cache is on. With several replicas or workers the IdP
callback often landed on a process that never saw the ticket and got a
401, and IdP-initiated sign-in was refused even with Redis configured.

SAML state now has its own DualCache that _attach_redis_usage_cache
always wires to Redis, like the CLI SSO session cache, and the SAML cache
calls are async.

* test(sso): drop docstring from the SAML proxy pair fixture

* test(sso): cover the SAML login and metadata endpoints
2026-10-16 02:01:04 +00:00
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