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9 commits

Author SHA1 Message Date
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
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
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
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
Tobias Mayr
d03923e6a9
fix(responses): propagate cache_control through responses->chat completion bridge (#32511)
* fix(responses): propagate cache_control through responses->chat completion bridge

User/assistant messages, tool call outputs, and function calls built from
Responses API input items were dropping cache_control, breaking prompt
caching for Bedrock/Anthropic when routed through the litellm_completion
transform. Also propagate cache_control onto the last content element of
user/assistant messages, since Anthropic/Bedrock read it from the content
block rather than (or in addition to) the message level.

Adds the missing cache_control field to ChatCompletionToolMessage and
ChatCompletionResponseMessage TypedDicts to keep the assignments type-safe.

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

Adding cache_control to the ChatCompletionToolMessage TypedDict changed
the proxy's OpenAPI spec; regenerated via `npm run gen:api`.

* fix(responses): don't overwrite existing content-block cache_control; add list-content test

Per Greptile review on the PR:
- The message-level cache_control was unconditionally overwriting the
  last content block's cache_control when that block already carried
  its own (preserved by _transform_responses_api_content_to_chat_completion_content).
  Now only propagates onto the last block when it doesn't already have one.
- Added the missing test coverage for the content-block propagation path
  with list content, which no existing test exercised (all used plain
  string content, so the isinstance(content, list) branch was never hit).

* style(responses): extract cache_control into a named variable, trim comment

Per style review: the message-building branch read cache_control 3
different ways in 5 lines (.get() twice, then [] indexing once), unlike
the sibling tool-call-output/function-call functions this PR touches,
which each extract it into a named variable up front
(output_cache_control, function_call_cache_control). Matched that
convention here too. Also trimmed the 3-line inline comment to one
line, matching the file's usual comment length for similarly subtle
behavior.

* chore: refresh lazy OpenAPI snapshot

* fix: type cache control propagation

* fix: place cache control type suppressions

* style: format cache control type conversion

* refactor(responses): build bridged cache_control messages in one shot

* fix(responses): keep cache_control marks on bridged tool calls and within the provider cap

A function_call item's mark now rides on the tool call the bridge builds, an assistant text
item merged behind a function_call keeps its own mark, a developer item keeps its mark when
it is mapped to a system message, and a previous_response_id replay yields its stale marks
to the newest ones so the provider cap holds. The Responses layer counts the marks on
function_call and function_call_output items before it places an ordinal injection point,
and the chat pass replaces that count with its own instead of adding to it.

* fix(responses): count each cache_control mark once and keep the bridge within the provider's limits

List content carries an item-level cache_control on its last block only, so the
provider sees one cache point and the breakpoint census counts one. Marked function
tools and SDK-typed input items are handled by the Responses-layer reserve, assistant
text merged into a function call turn keeps its mark on its own block, and the
previous_response_id replay budget drops marks per turn, newest kept, instead of
stripping every older turn once one overshoots.

The request's own marks now fall under the same budget, newest kept, so five marked
items no longer answer the provider's 400. A cache_control value that is not an
ephemeral mark with an optional ttl is left off the bridged message instead of
reaching the provider as sent, and a developer message maps to the system role with
its content, name, and cache_control only, so unknown keys never reach a strict
provider.

* fix(responses): send item cache_control only to cache-point targets and follow drop_params

Item marks reach the provider only when the target turns them into cache
points, and every other target keeps main's behavior of stripping them.
Without drop_params a mark the provider would refuse reaches it as sent,
so the client gets the same 400 as on /v1/chat/completions. With
drop_params a malformed mark is dropped and only the newest 4 are kept.

The shared input-to-messages helper and the developer mapping in
base_utils go back to main, and a marked developer item reaches a
cache-point target as a system message in the bridge.

* fix(responses): budget top-level marks, follow drop_params on Nova tool marks, and match chat-keeping providers

* fix(responses): validate replayed marks and count input tokens without item marks

* fix(responses): leave unknown Bedrock ARNs unmarked under drop_params, match OpenRouter's list, and reserve only forwarded marks

* test(responses): cover item cache_control parity per chat route, drop_params trimming, and replay budgets

* fix(responses): keep item marks off inspection paths and match each chat route's keep rule

Only the request the bridge sends gets item marks now. Guardrails, token
counting, rate limiting, and input_tokens read the input with no item marks,
as on main, so an off-spec mark cannot fail a guardrail call. Tool message
and tool call marks are typed inside the bridge, leaving the shared chat
types and guardrail schemas as on main.

Databricks keeps marks only for Claude, Snowflake uses its chat route's
Claude check, and every Anthropic deployment keeps them whatever its model
name. The injection census skips SDK-typed tools, and the owned-proxy test
expects the marked messages on /v1/responses.

* test(responses): cover guardrail reads without item marks, Snowflake name parity, and SDK-typed tools in the census

* fix(responses): leave a non-list input untouched when stripping item marks

* test(responses): cover string, list, object and tuple input with and without item marks kept

Each input shape now answers the same whether the unmapped Bedrock ARN keeps item marks or strips them under drop_params, through the proxy and the SDK. Object input also runs through the OpenAI-compatible chat bridge, /v1/responses/input_tokens and the project input-token limiter

* test(cache): derive owned-proxy cell timeouts from the harness boot budget

The capped-burst cells and the uncapped response-cache cells boot their own two-worker proxy, and a fixed 240 or 360 second timeout cut them during boot on a slow runner before the harness readiness budget could decide. They now carry the same derived budget as the sibling chaos and guardrail files, with four boot and stop budgets for the restart cell that boots twice

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-14 15:44:34 -07:00
devin-ai-integration[bot]
4f49f88172
fix(proxy): keep idle responses websockets open until a configurable session limit (#44433)
* add config-driven bound to /responses websocket connection

* test(proxy): cover responses websocket session limit and idle first frame

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

* chore(ci): sync API schema and Ruff formatting

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

* fix(proxy): close responses websocket client before upstream cleanup at session limit

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

* test(proxy): assert recorded websocket outcomes and simplify session reaping

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

* test(proxy): move responses websocket session limit timing coverage to integration

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

* test(proxy): run provider-close checks off the event loop

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

* test(integration): cover handshake auth, subprotocol, DB override and worker kill for the responses websocket session limit

Adds the audit cells for the configurable session limit: a rejected bearer fails the handshake with 403, a requested Sec-WebSocket-Protocol is echoed back, a DB override through /config/field/update caps new sessions on every worker without a restart while sessions accepted before it keep their limit, deleting the override restores the default, out-of-range and wrong-type updates answer 400 and leave the stored row alone, and SIGKILLing the worker holding idle sockets drops only its sockets while the proxy keeps serving

* test(integration): open override sockets until both proxy workers hold one

uvicorn workers share one listening socket and a worker that wakes first accepts a whole simultaneous burst, so eight sockets opened at once can all land on one worker. The DB override cell now opens its sockets one at a time, alternating the two paths, until at least eight are open and every worker holds one, bounded at forty

---------

Co-authored-by: Mrinal Chanshetty <mrinal@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-10-07 19:26:30 -07:00
Mateo Wang
58258409c9
refactor(proxy): expose public names for private proxy helpers (#45170)
* refactor(proxy): expose public names for private proxy helpers

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

* fix(proxy): keep original class names behind public aliases

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

* fix(proxy): preserve internal callback filtering

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

* fix(proxy): keep _PROXY_ class names for managed files hooks

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

* fix(proxy): keep old private names in package exports

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

* fix(proxy): preserve recursive auth helper name

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

* test(proxy): align MCP limiter tests with server enforcement

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

* test(proxy): match main's MCP limiter tests

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

* fix(proxy): keep old private names bound in importing modules

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

* fix(proxy): preserve compatibility imports through strict lint

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

* test(proxy): use exact pyright suppression in password helper test

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

* style(proxy): add reasons to compatibility import noqa comments

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

* test(proxy): update IN-list baseline for renamed helpers

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>
2026-10-07 18:59:27 -07:00
devin-ai-integration[bot]
837c6a7481
fix(security): remove the publicly known master key from the repo (#44718)
* fix(security): hash the publicly known master key

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

* docs: replace weak master key examples and regenerate artifacts

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

* test: replace weak key fixtures with generated test keys

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

* ci: generate master keys for proxy startup

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

* fix: preserve lens dev key entropy

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

* fix: restore proxy key compatibility in scrub examples

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

* fix: scrub merged SSO fixture and refresh dashboard bundle

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

* fix(ci): stabilize test keys and metadata collection

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

* chore: drop the rebuilt dashboard bundle

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

---------

Co-authored-by: mateo <mateo@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-06 10:55:24 -07:00
devin-ai-integration[bot]
25109a523b
test(proxy): move utils, agent_endpoints and endpoint tests into tests/unit/proxy (#44006)
* test(proxy): move utils, agent_endpoints and endpoint tests into tests/unit/proxy

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

* test(proxy): package moved unit test directories

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

* test(proxy): exclude proxy-db-owned files from the misc target

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

* test(proxy): drop the redundant fixture docstrings in the proxy conftest

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

---------

Co-authored-by: yuneng <yuneng@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-01 11:06:42 -07:00
Renamed from tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py (Browse further)