- The Redis stall cell now reads the burst key's live counter and requires at least the full failure spend
- Unit tests drop the charging writer double, bare dicts, list mutation and wall-clock timestamps
- Partial-stream test models are frozen
OAuthScopeResponse holds a tools/call response's http.response.start so a managed OAuth scope challenge can replace it with a 403. Once the call was allowed, the held start still waited for the next body message, which for a slow tool is the 15s SSE keep-alive ping. Send it as soon as the call is allowed instead.
Fixes#46659
* fix(router): stop concurrent deployment deletes from crashing deployment lookups
delete_deployment and upsert_deployment shrink model_list before they repair
the index maps, so a lookup on another thread in that window read a stale
index: IndexError, or the neighbouring deployment and its credentials. An add
racing a delete could corrupt the index for good.
One RLock now covers model_list and the three index maps. Delete, upsert, add
and the set_model_list reset change them under it, and every lookup that turns
an index into a deployment reads under it.
Fixes#45242
* test(router): release the held delete when the read reaches the index lock
The race tests released the held write after a fixed 0.2 s, so a reader the runner
stalled past it read the repaired list and passed on unfixed code. The read now runs
on its own thread and the write stays held until the read returns or reaches the
router's index lock; the 10 s bound only fails a broken synchronization.
The integration test gains the audit cells: chat, streaming, Responses and
Anthropic messages calls (sync and async, by model name and team public name)
during a held delete, the same for upsert, add and set_model_list, a request for
the deployment being deleted, a provider error, a double delete, and thread and
async bursts during upsert churn.
* test(router): cover the early return of a delete and the team filter of get_model_ids
delete_deployment now returns None from inside the index lock, and get_model_ids by
name reads its deployments through _deployments_named; pin both: deleting an unknown
id returns None and leaves the list alone, and exclude_team_models drops only the
team deployment.
* fix(router): read deployments by name under the index lock outside the Router
The response polling provider check, the complexity router's adaptive pool and the
savings baseline turned the name index into list positions themselves, so a concurrent
delete could still hand them a stale slot. They now read through Router.deployments_named,
which takes the deployment index lock.
* fix(router): type the locked deployment lookups as DeploymentTypedDict
deployments_named and _team_deployments_named returned tuple[Any, ...]. They now return
DeploymentTypedDict rows, which is what model_list holds. The adaptive pool setup in the
Router and the complexity router drop their branches for pydantic Deployment rows, which
these lookups never return, and should_include_deployment accepts the typed row.
---------
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* fix(guardrails): exclude litellm_metadata from pass-through guardrail scan text
The pass-through guardrail translation json-dumps the request body as the
scan text when no request_fields are configured. The unified guardrail hook
injects litellm_metadata into that body first, so the dump carried the
caller's key metadata. Exclude it alongside metadata and litellm_logging_obj;
vendors still receive it through request_data.
* test(guardrails): type the pass-through scan-text tests per AGENTS.md
Preserve oversized JSON integers in proxy requests and model rewrites
Parse large bodies in a worker thread to avoid blocking request handling
Fixes#47947
Co-authored-by: Jeevan Babu Gotru <114808955+jeevan1098@users.noreply.github.com>
Co-authored-by: moe-berri <moe@berri.ai>
* fix(proxy): reconcile team member total_spend with current cycle spend
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): read /team/list as a list and drain the scripted provider
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(repositories): compose the membership reset writer and drop SQL text asserts
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: type the cascade repair test and flatten memberships without a stacked comprehension
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: keep the reset job test file's existing typing untouched
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(teams): show caller member spend and budget on Your Teams
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(teams): use member-linked reset dates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(teams): keep type-discipline suppressions on cast lines
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(teams): preserve empty page list response
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(teams): keep the member reset date inside the spend column
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(teams): match email-only roster members for caller membership
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): show team member budget reset date in UTC
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(teams): address review on caller membership enrichment
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): label the caller's team spend line My Spend
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>
* fix(opencode): bill OpenCode Go requests from the reported list_cost
OpenCode returns usage.opencode.list_cost on every response. Read it into the provider-reported cost the cost calculator checks before the price map, for chat and Responses, streamed and not. Keep the static rows as the fallback, and stop the generic usage.cost path from billing Go requests at 0 (usage.cost is what hit the prepaid balance, 0 inside the plan).
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(core): resolve reported cost breakdowns without recursion
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(opencode): cover reported list_cost spend through the proxy
Replaces the recursive _reported_cost_value with a flat _cost_number helper
so the code-quality gate passes, and adds an integration test that runs the
proxy against a scripted OpenCode upstream for a non-stream and a stream
chat completion, asserting the response cost header and the spend log row
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(opencode): bill native /v1/messages from the reported list_cost
The native Anthropic Messages route priced OpenCode Go bodies from the price
rows twice over: the non-stream body is a TypedDict the response-cost header
path priced as-is, and the stream assembled its ModelResponse with the rows
cost already stamped. Both now read usage.opencode.list_cost, the non-stream
body through billable_result and the stream from the final message_delta.
The integration test now covers chat, responses and messages, stream and
non-stream, through the proxy against a scripted OpenCode upstream
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(opencode): keep the stream cost stamp inside the lint gate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(opencode): read list_cost off dict chunks and trust it only from OpenCode on /v1/messages
Stream builders receive chunks both as mappings and as ModelResponseStream
objects, so the list_cost scan now reads usage through chunk_usage. The
native Messages route only trusts a reported cost from opencode_go, every
other upstream keeps the price map, which also keeps a zero usage.cost from
being billed as free. Served bodies without stop_sequence still price, and
the new code stays inside the basedpyright gate
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>
* feat(proxy): add disable_pre_routing_error_logs to skip spend rows for pre-routing rejections
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): decide pre-routing rejections by pipeline stage, not exception type
Guardrails such as AIM raise ProxyException(400), the same shape as an unparsable
body, so the status code list skipped their spend rows. The pipeline stamps
litellm_call_id only after auth, body parsing and model resolution, so a failure
reaching the hook without one died before any provider was considered.
_handle_logging_proxy_only_error flags those requests when it mints the call id,
and is_pre_routing_rejection keys off that flag plus ProxyModelNotFoundError.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): mark pre-routing rejections with a server-owned sentinel
request_data is the client body, so a boolean marker or a litellm_call_id in it
can be sent by the client to hide a guardrail block or force a spend row. The
failure handler now stores an object() sentinel whenever it finds no logging
object, and is_pre_routing_rejection checks identity, which JSON cannot forge.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): skip declared text-only deployments for image requests without enable_pre_call_checks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): run the vision filter after the cooldown filter so a cooled vision leg falls back to the text leg
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): apply the vision filter after pre-call checks and tidy the new tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): mark the remaining locals in the vision filter tests Final
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(guardrails): add native Reco guardrail provider (pre_call)
Registers guardrail: reco as a first-class vendor integration, built on
the existing generic guardrail API wire contract rather than reimplementing
the HTTP client and payload mapping. Maps reco_tenant_id to the
X-Reco-Tenant-Id header and hardcodes fail_open/fail_on_error since those
should not be customer-configurable. v1 only supports mode: pre_call;
post_call and streaming redaction already work against the existing
generic pilot and are deferred.
Also overrides apply_guardrail to re-raise blocked-request errors with the
guardrail's own configured name: the base class hardcodes a module-level
name in that exception, which would otherwise mislabel every blocked Reco
request in logs.
* feat(guardrails): configurable Reco fail modes
Expose unreachable_fallback and fail_on_error on the Reco guardrail
and keep fail-open as the default. Values under optional_params win.
Top-level litellm_params values apply only when set explicitly, since
their defaults are fail-closed and would otherwise flip the default
Also type RecoGuardrail's forwarded kwargs with an Unpack'd TypedDict
instead of silencing ANN003
Signed-off-by: MickeyShnaiderman-RecoLabs <mickeys@reco.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
* chore(guardrails): align Reco with main's CI gates
Upstream moved unit tests from tests/test_litellm to tests/unit, so
test_reco.py was invoked by no CI job. Move it next to the other
guardrail tests
Replace RecoGuardrail's forwarded kwargs with explicit keyword
params, read optional_params through a pydantic adapter instead of
untyped dict/getattr access, freeze RecoOptionalParams, and drop
mutable-ok markers that suppress nothing, to stay within main's
type-discipline and basedpyright budgets
Signed-off-by: MickeyShnaiderman-RecoLabs <mickeys@reco.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(guardrails): fail closed by default in the Reco guardrail
Matches GenericGuardrailAPI and every other guardrail here: a Reco error or outage now blocks the request unless the admin sets fail_on_error: false. Tests cover the default, explicit fail-open, and top-level vs optional_params precedence
Co-authored-by: RecoLabs-YaronBratspiess <208601538+RecoLabs-YaronBratspiess@users.noreply.github.com>
Co-authored-by: MickeyShnaiderman-RecoLabs <77006830+MickeyShnaiderman-RecoLabs@users.noreply.github.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): honor explicit fail-open on Reco when optional_params is a model
model_dump(exclude_unset=True) so pydantic defaults in optional_params no longer override an explicit top-level fail_on_error. Also drop the duplicate log_guardrail_information decorator, call the parent by keyword, freeze RecoConfigModel, and type the tests
Co-authored-by: RecoLabs-YaronBratspiess <208601538+RecoLabs-YaronBratspiess@users.noreply.github.com>
Co-authored-by: MickeyShnaiderman-RecoLabs <77006830+MickeyShnaiderman-RecoLabs@users.noreply.github.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): keep Reco config model assignable and the hook decorator the gate requires
frozen=True on RecoConfigModel froze the shared LitellmParams mixin, which the guardrail registry assigns resolved secrets on, so every guardrail failed to load. Dropped it and added a test that LitellmParams stays assignable. Restored log_guardrail_information on the Reco override since tests/code_coverage_tests/check_guardrail_apply_decorator.py requires it on every hook. Test params typed as Mapping for LIT001
Co-authored-by: RecoLabs-YaronBratspiess <208601538+RecoLabs-YaronBratspiess@users.noreply.github.com>
Co-authored-by: MickeyShnaiderman-RecoLabs <77006830+MickeyShnaiderman-RecoLabs@users.noreply.github.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(guardrails): format the Reco test file
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Signed-off-by: MickeyShnaiderman-RecoLabs <mickeys@reco.ai>
Co-authored-by: Yaron Bratspiess <yaronb@reco.ai>
Co-authored-by: MickeyShnaiderman-RecoLabs <mickeys@reco.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: MickeyShnaiderman-RecoLabs <77006830+MickeyShnaiderman-RecoLabs@users.noreply.github.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): buffer tool discoveries in redis and let the leader write LiteLLM_ToolTable in one statement
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): declare the redis family on the tool discovery buffer and drop the blind except and cast
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): satisfy LIT010 and LIT014 in the tool discovery buffer
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): mark the aggregation fold Final
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): requeue drained tool rows to redis when the write provably did not apply
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): drain tool discoveries on their own lock and scheduler job, not the spend commit
* chore(proxy): suppress the untyped apscheduler add_job on the tool discovery job
* refactor(proxy): move the LiteLLM_ToolTable bulk upsert into its own module next to the other bulk upserts
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): name the LiteLLM_ToolTable bulk write span so the prisma span check resolves it
* refactor(proxy): move the tool discovery drain out of DBSpendUpdateWriter into tool_registry_writer
* refactor(proxy): share db_write_failure_is_requeue_safe from exception_handler so the spend writer stays untouched
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(ui): configure the default Usage time range
* fix(ui): retain the selected calendar preset during input sync
* fix(ui): preserve fallback dates when applying across DST
* refactor(typing): narrow Any sources across providers, proxy and guardrails (wave 1)
* refactor(typing): narrow Any sources across hubs, providers and proxy (wave 2)
* refactor(typing): validate RunwayML task JSON and let dotprompt loaders accept exported prompts
* fix: restore pass-through behavior on paths the typing pass tightened
MCP client IP extraction trusts X-Forwarded-For only when use_x_forwarded_for is True, dotprompt skips a malformed JSON prompt entry instead of raising, RunwayML task payloads pass through unvalidated, and a malformed provider body raises the same AttributeError as before at the CompactifAI, Gemini, and mock transport parse sites
* fix(runwayml): keep a malformed 2xx task body on the 500 path
* fix(edenai,cli): keep a non-object body in the error and fail on a malformed migration report
EdenAI's embedding and image generation parse dropped a non-object body from the error
they raised, so the message no longer named what the provider sent. A helper now raises
with the body in the message, and both paths have a regression test.
`lite encryption migrate` exited 0 with no message when the proxy's report was not an
object or its residual_legacy was not a number, where base crashed. It now fails with a
message naming the value.
The CompactifAI and Gemini image-edit non-object body tests accept TypeError or
AttributeError, which both base and this branch raise, so they guard against a
ValidationError instead of pinning one class. RunwayML's async parse gets the same
non-object body test as the sync one.
* fix: keep base's error classes, duck-typed checks and fail-closed guardrails the typing pass changed
* test: annotate the new regression tests' locals with Final
* test: annotate the remaining new test locals with Final
* fix(spend): await the per-request rollup enqueues and report their failures
The daily and entity spend rollups ran in an unreferenced asyncio task that
nothing awaited or drained, so a shutdown after the spend log was enqueued
could drop every rollup for that request, and a malformed metadata payload
dropped the request from all daily tables at debug level. The rollups now run
inline in update_database, each helper failure is logged through
spend_log_error with the request id, and unreadable metadata only costs the
row its metadata-derived fields
Resolves LIT-6027
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): type the rollup failure helpers for the lint gates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): track the rollup enqueue task so shutdown drains it
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): shutdown drain waits for an in-flight rollup enqueue
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): register the rollup task without blocking the cost callback
Awaiting the rollups inline made a blocked queue put stall increment_spend_counters, so budget checks could run on stale counters. The task is now only registered via spawn_logging_task; drain_logging_tasks still waits for it on shutdown
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(proxy): add LITELLM_OFFLINE_MODE to stop every request the proxy makes on its own
* fix(ui): name LITELLM_OFFLINE_MODE where the cost map panel says local mode is forced
* test: isolate the offline-mode tokenizer tests from the local Hugging Face cache
* test: cover the offline policy templates and the cached Kimi K3 tokenizer
* test(integration): count Kimi K3 tokens in the offline-mode egress test
* refactor(token_counter): skip non-bundled tokenizers in offline mode instead of listing downloaded ones
---------
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* feat(chat): port Moyai UI with Model Hub and images
* feat(chat): add Models sidebar with embedded Model Hub
* feat(chat): polish Model Hub with provider cards and logos
* refactor(chat): use a provider dropdown in Model Hub
* feat(chat): keep workspace switching visible with a Chat identity
* Add minimal opt-in Chat usage metrics and prioritize Chat in workspace selector
* fix(chat): enable usage metrics by default only when chat is used
* fix(chat): count requesting users with frontend-only metrics
* feat(chat): send default-on request metrics to litellm-tel
The router plants its deployment fields in litellm_metadata for Interactions
calls, while the proxy put the request's metadata (spend_logs_metadata, tags,
key fields) under metadata. The spend log resolves litellm_metadata and only
carries user_api_key* fields over, so spend_logs_metadata never reached
LiteLLM_SpendLogs. Route /interactions like /responses so both land in
litellm_metadata.
Fixes#47841
Co-authored-by: Igor Tavares <2163472+igorborgest@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* feat(ui): sort every teams table data column
* fix(ui): order unlimited team limits as infinity and verify org scope
* fix(ui): validate team sort filters without recursion
* feat(ui): sort every users table data column
* fix(ui): order unlimited user budgets as infinity and verify org scope
* fix(ui): cover user sort queries and document pagination bound
* fix(ui): preserve Aria usage token breakdown and viewer model access
* fix(ui): make Aria conversations easier to read and reply to
* fix(ui): wrap long headings in assistant tables
* feat(ui): simplify Aria and add usage charts with PDF answer export
* fix(ui): retain full chart values in Aria PDF exports
* feat(ui): consolidate gateway and usage assistants as Aria Agent
* refactor(ui): give Aria an original blue sprite mascot
* feat(ui): prompt shared Aria from usage and retire duplicate usage agent
* fix(ui): keep Aria naming consistent and reachable across dashboard
* feat(ui): open Aria in a floating popup with suggested questions
* fix(ui): simplify the shared Aria Agent title
* feat(proxy): add LITELLM_DISABLE_LATEST_RELEASE_CHECK to stop the release check
The dashboard asks the proxy for the latest LiteLLM release, and the proxy fetches it from api.github.com on every cache miss. Deployments that block or audit outbound traffic had no way to turn that off. With LITELLM_DISABLE_LATEST_RELEASE_CHECK=true the endpoint returns null without making a request, which the dashboard already treats as no upgrade banner.
* fix(proxy): regenerate dashboard types for the release check flag
The endpoint docstring feeds the OpenAPI description, so the ui-api-types
check needs schema.d.ts regenerated. The docstring now says the flag skips
every outbound request, which stays true once the changelog feed is read
too
---------
Co-authored-by: Sujit Nirmal <nirmalsujit891@gmail.com>
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
The Admin UI upgrade notice read GitHub's latest release, which the release
pipeline sets on its own, so admins were offered releases the changelog had
not announced yet and sent to the auto-generated GitHub release page. The
notice now reads the newest stable release from the docs changelog feed and
links to its changelog page. GitHub release notes are still used for the
feature and fix counts of that version's minor line.
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* fix(responses): round-trip Anthropic compaction blocks as compaction items
/v1/responses on Anthropic routes now returns Claude's compaction block as a
compaction output item (and streams it as output_item.added/done), and a
compaction input item is replayed to Claude as its native compaction block,
so the next turn reuses the summary instead of compacting again. Other routes
receive the summary as assistant text. The Anthropic stream handler now keeps
the summary text that arrives in compaction_delta.
Fixes#41456
* fix(responses): replay compaction blocks natively only when the request compacts
* fix(responses): carry compaction through dict-form edits, SDK replay, affinity, and guardrails
Read Anthropic's dict-form context_management, accept SDK ResponseCompactionItem
objects on replay, strip the encrypted_content affinity wrap before decoding,
scan and rewrite compaction summaries in Responses guardrails, drop the history
a summary replay replaces, send the summary as a user message so thinking
ordering holds, and send the streamed compaction .done with the newest block.
* fix(responses): count, route, guard, and redact compaction items consistently
A compaction item now reads as its summary everywhere the proxy counts or routes
a Responses request: pre-call context checks, the TPM limiter, the input token
endpoint, the stream usage estimate, and the previous_response_id session rebuild
all drop the history the item replaces. A Claude compaction item sent to a
non-Anthropic model (including a fallback) becomes a user summary message instead
of an encrypted blob the provider rejects, and Claude on Bedrock Claude Platform
takes the summary path. Output guardrails see the summary of a returned
compaction item, and logging redaction hides it.
* fix(responses): start previous_response_id replay at a stored compaction and count reservations from it
* fix(responses): keep a stored compaction summary whole in spend logs
* fix(responses): keep stored compaction items summary-only, redact compaction_delta, and finish compaction before reasoning
A spend-log row now stores a top-level compaction input item as its summary alone, so extra keys in a
client-built item no longer reach the database whole. Message redaction also nulls the streamed
compaction_delta, and the streaming bridge sends the compaction item's done event before the reasoning
item that follows it. Adds the audit's integration tests for compaction items on the wire.
* test(responses): cover stored compaction items, compaction_delta redaction, and compaction done order
Adds integration cells for the summary-only spend row of a caller-sent compaction item and its previous_response_id replay, a redacted chat stream row that holds no streamed compaction_delta, and a compaction then thinking stream whose done events follow output order.
* fix(spend_logs): honor the redaction header on failure rows for litellm_metadata routes
A failed /v1/responses or /v1/messages call keeps its proxy request headers in
litellm_metadata, but the failure row read redaction headers from metadata only,
so x-litellm-enable-message-redaction never redacted those rows.
* fix(spend_logs): lift only the redaction opt-in header into failure rows
The failure hook on litellm_metadata routes copied every real request header into the caller's own metadata dict, so the stored request body gained the headers, a caller's metadata.headers was replaced, and a disable header loosened global redaction on failed calls. It now copies only the enable headers into a new litellm_params metadata dict, and only when the caller sent no metadata.headers, so no failure row is less redacted than on main
* test(responses): cover failure-row redaction headers and caller metadata on litellm_metadata routes
* fix(responses): keep earlier-turn instructions after compaction and count compaction items by their summary
A previous_response_id rebuild that starts at a compaction now keeps the system and developer
messages of every earlier turn. Token estimates for raw Responses input count a compaction item
as its summary text instead of the serialized item.
* fix(responses): drop the stored history a caller-sent compaction item replaces on previous_response_id
* fix(responses): count only message items with a string role as compaction instructions
* test(responses): flatten the last two-for comprehension in the compaction wire test
* fix(responses): replay from a compaction in stored Responses output and SDK compaction items
A previous_response_id whose stored row is a Responses output holding a compaction item now starts its replay at that compaction, and the handler dumps SDK compaction objects before checking for a summary. Adds tests for the uncovered compaction paths.
* fix(responses): keep the stored tool call a function_call_output answers when a compaction item replaces history
* fix(responses): keep a stored tool call on every turn after a compaction item and bound the stored summary
A previous_response_id rebuild that starts at a turn holding a compaction item now sends again each stored call a
replayed tool output answers, so a retry or a later turn no longer loses the turn-1 call. The start is picked only from
rows up to the referenced response. A spend row keeps a compaction summary up to the larger of 64K chars and
MAX_STRING_LENGTH_PROMPT_IN_DB instead of with no bound.
* fix(responses): replay a compacted session only through the referenced response
A later sibling turn that sent a compaction item put its summary between a stored tool call and its tool output, so Claude answered 400 on a turn that continued the first of two retried turns, and on a retry sent without the item
* fix(spend-logs): keep main's stored value for a prompt length limit under 2
At a MAX_STRING_LENGTH_PROMPT_IN_DB of 0 or 1 the shared truncation helper stored only the truncation marker, where
main stores the marker followed by the whole value
* fix(spend-logs): keep main's stored tail for a negative prompt length limit
At a negative MAX_STRING_LENGTH_PROMPT_IN_DB the shared truncation helper stored one more character of each value than main, since it dropped main's clamp of the end slice to the limit minus the start
* fix(responses): keep a compaction item when a guardrail rewrites its summary through structured_messages
* test(responses): run the compaction wire tests on the worker database under isolated workers
* fix(router): keep the encrypted content affinity pin out of provider requests
* fix(proxy): inspect compaction summaries in guardrails, strip a client-sent affinity pin, and price failures from the newest compaction
* fix(proxy): count a failed chat or /v1/messages call on its whole history, not from a compaction-typed message
* fix(proxy): trim a failed call's input at the newest compaction only when the client called /v1/responses
* fix(proxy): trim a failed call's input at the newest compaction when the proxy dispatched it as a Responses call
* test(proxy): run the dispatched-call-type failure test through the real request setup
* fix(proxy): count a failed Cursor stream's input from the newest compaction item
The Cursor route maps to no call type, so the stream generator's failure hook fell
back to the route and counted the whole history. Pass the processor's route_type.
* fix(proxy): count a broken Cursor stream's prompt from the newest compaction item
* fix(responses): keep a tool call a later output answers when trimming before a compaction item
* fix(responses): move a compaction-split tool call's turn to right before its output on both compaction routes
* perf(responses): look up moved turn items in a set so a long compaction-split turn trims in linear time
* test(responses): measure the compaction-split turn move as a CodSpeed benchmark instead of a clock read in unit tests
* fix(responses): move only calls still open at the compaction, and bill a disconnected stream from the newest compaction item
* fix(responses): restore only the newest stored call when a reused call_id is answered after a compaction item
* fix(spend logs): bound a Responses compaction item's summary like a chat block instead of cutting its encrypted_content
* test(proxy): price a failed dispatched call through a real ProxyLogging instead of mocked hooks
* fix(responses): finish a stream whose Claude compaction failed and group answered call ids by turn once
* fix(responses): count input_tokens after a compaction item the way inference sends it
* fix(proxy): keep a retried /v1/messages stream's spend log by logging the superseded attempt as a failure
A /v1/messages stream the router retries before any content shares one logging object across both attempts. The superseded attempt's end-of-stream logging ran as a success (a usage-only or placeholder result) and claimed the request's one-shot success log, so the recovered stream's spend row was either missing or written under the superseded attempt's message id. The passthrough logging path now logs an Anthropic stream whose frames carry an `event: error` as a failure with whatever usage the provider reported, the way a dropped stream already does, and the router closes the superseded stream before it opens the retry so that logging is queued first.
* fix(proxy): log a provider error frame through an attempt-scoped logging copy
The error-frame failure stashed the superseded attempt's usage on the logging
object the retry shares, so the retry's success log carried the failed
attempt's token counts. The failure now logs through a copy of the logging
object with its own model_call_details, and the helper moves into the
Anthropic passthrough logging handler so the proxy streaming handler only
routes by endpoint type.
* fix(proxy): scope the error-frame failure log to streams closed at the frame
A stream that ran to its end at the provider's error frame kept logging
through the success route before this PR, and the attempt-scoped failure
log is now taken only for a stream the router closed at that frame, with
the copy made at the close so the retry's deployment never reaches it
* fix(router): log each dropped /v1/messages attempt through its own logging copy and open the retry without its usage
A /v1/messages stream dropped after message_start and retried in its model group shares one Logging object
across attempts, so the retry's success log inherited the dropped attempt's stashed usage and exception,
and a second drop never reached the failure handlers because the first had already marked the object as
logged. The dropped attempt now dispatches its failure handlers through an attempt-scoped copy, and the
router discards the stashed usage right before it opens the next attempt, on same-group retries and on
every fallback hop, so a request that runs out of attempts still bills the last attempt's partial usage.
* fix(router): dispatch chat stream failures through the attempt-scoped logging copy
The router now clears a dropped attempt's stashed usage before every fallback hop, so the chat stream wrapper's queued failure log must read that usage from its own copy of the logging object, like the /v1/messages path already does. The stash test asserts through a real success log, the cooldown test reads a real Router's cooldown list, and the integration helpers carry full types.
* test(vertex): give the stream wrapper's logging stub an attempt_scoped_copy
* test: route the pass-through logging mock's attempt copy to itself and read the callback sink through a reader
The pass-through failure test stubbed dispatch_failure_handlers on a spec'd MagicMock, which the attempt-scoped copy no longer reached, so the logging worker never finished. The integration tests kept earlier sink batches in a caller-owned list the helper mutated; a small reader keeps them instead.
* test(router): use real Logging in fallback cooldown test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): preserve superseded retry usage for billing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): bill retry input after prior stream usage
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): track retry dispatch for terminal billing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): use deterministic retry timestamp
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): avoid real clock in fallback tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(tests): remove duplicate streaming logger import
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): retain error-frame usage for exhausted retries
* test(proxy): fix retry billing expectations and helper annotations
* fix(proxy): preserve failure estimate without carried usage
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(proxy): audit retry helpers and fixtures
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): fix retry fixture timestamps
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): observe retry stash at attempt boundary
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logging): keep terminal failure attribution when dropped attempts log on copies
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logging): publish a dropped attempt's payload only while it is still the current attempt
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): cover spend-log encoding error propagation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic): skip adapter failure dispatch when the wrapped stream already logged it
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): cool down the final fallback attempt when its failure callbacks were blocked
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(anthropic): import Final in adapter regression
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): drop spend-log encoding expectation superseded by main's poison isolation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic): finish the wrapped stream's failure log before surfacing the error
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic): wait for the wrapped stream's failure log to finish like the inline dispatch did
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(anthropic): wait for the executor-run sync failure callback separately from the async caller boundary
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): pin pass-through stream fixture start times
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logging): publish failed attempt payload before awaiting failure callbacks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logging): publish failed attempt payload from the failure handler after baseline invalidation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(logging): drop unused discard_partial_usage_for_failure
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>
* feat(vertex-ai): support gemini 3.1 flash tts
* fix(vertex-ai): keep TTS metadata compatible with the cost map guard
* fix(vertex-ai): preserve existing Gemini TTS models and voice mappings
* fix(vertex-ai): recognize provider-stripped TTS model names
* test(vertex-ai): match current speech HTTP error response
* fix(vertex-ai): preserve nested speech locale and voice
* fix(vertex-ai): use provider speech media type in proxy
* fix(gemini): preserve TTS dispatch and nested speech settings
* test(gemini): run TTS regressions in CI shards
* fix(vertex-ai): account for Gemini Cloud TTS audio cost
* fix(vertex-ai): bill Gemini TTS without optional audio decoder
* test(gemini): cover TTS mapping and billing edge cases
* test(vertex-ai): cover Gemini voice normalization in provider shard
* fix(vertex-ai): keep Gemini TTS routing with generic provider metadata
* chore(vertex-ai): remove obsolete lint suppressions
* fix(gemini): strip audio format from speech configuration
* chore(vertex-ai): remove obsolete mutation suppressions
* fix(vertex-ai): preserve FLAC billing and wrapped audio headers
* fix(vertex-ai): reject unmeasurable FLAC before billing
* fix(vertex-ai): reconcile speech support with current provider mappings
* fix(vertex-ai): validate speech mappings and usage types
* fix(vertex-ai): preserve speech mapper override forwarding
* fix(gemini): map voice aliases across speech request forms
* fix(vertex-ai): send only formats the speech bridge cannot serve to Cloud TTS
Gemini TTS detection now goes by model name, so newer Vertex Gemini TTS
models keep working, and only mp3, opus, alaw, mulaw and other container
formats move to Cloud Text-to-Speech. wav and pcm requests stay on
generateContent as on main.
A Cloud TTS response whose duration cannot be measured now returns the
audio unbilled with a warning instead of raising after a paid call. FLAC
handling is removed because Cloud TTS has no FLAC encoding.
The cost map, the google_genai mappers and the proxy error path go back
to main, since those changes were outside this feature.
* fix(vertex_ai): keep Gemini TTS formats, region and instructions on routes that serve them
Only mp3, opus, alaw and mulaw go to Cloud Text-to-Speech. Every other
format gets a local 400 that lists the supported ones, before Google is
called.
Cloud TTS uses the deployment's us or eu regional host. Other regions
and a custom api_base get a 400 that says to request wav or pcm.
instructions is sent as the Cloud TTS style prompt, and a request with
no voice keeps the Gemini model.
get_usage_object is back to main's code, so dict usages still go
through Usage.__init__, and the proxy no longer labels pcm16 or
linear16 output as WAV.
* fix(vertex_ai): send Gemini TTS to every regional Cloud TTS host and keep speak tags as text
Cloud Text-to-Speech serves Gemini TTS on a host named after each Vertex
location, so a non-global vertex_location now uses
{location}-texttospeech.googleapis.com instead of only the us and eu hosts.
Google answers for regions it does not serve.
Gemini TTS voices reject SSML, so input that contains <speak> is sent as
text for Gemini TTS models. Chirp keeps the SSML auto-detect.
Removes the proxy alaw and mulaw media-type entries. Cloud TTS returns
those encodings with a WAV header, so the response is labeled audio/wav
and the entries never applied.
Adds a regression test that custom per-token pricing bills the usage a
speech response reports.
* fix(vertex_ai): map Gemini TTS regions to Google's Cloud TTS locations and keep a bad voice from cooling down the deployment
US and EU Vertex regions go to the us and eu Cloud TTS hosts, northamerica-northeast1 to its own, global or unset to global, and any other region gets a local 400. A Cloud TTS 404 on the Gemini path, such as a misspelled voice, comes back as a 400 so the router keeps the deployment serving wav. Usage reads the sent request from the response instead of the logging object.
* fix(vertex_ai): default Gemini TTS Cloud formats to a Gemini voice and validate speakers
Parse only usage fields from the sent Cloud TTS request, so a numeric speakingRate no longer fails after Google bills it.
Send the Gemini voice Kore when no voice is named, and reject Cloud TTS voice names unless drop_params is set.
Reject malformed speaker entries unless drop_params is set, and translate Cloud TTS speaker fields on wav and chat audio.
Use the Vertex default region when no location is set, so mp3 and wav share a region.
* test(vertex_ai): cover two-speaker Gemini TTS mp3 through aspeech with fake credentials
Replaces two tests that patched the Vertex TTS config's own token and URL methods.
* fix(vertex_ai): reject malformed Gemini TTS voices and keep beta Chirp and Lyria params unmapped
* fix(vertex_ai): drop unknown Gemini TTS voice keys on wav and pcm instead of rejecting them
* fix(vertex_ai): reject unknown Gemini TTS voice keys on wav, pcm, and chat audio unless drop_params is set
* fix(vertex_ai): honor every drop_params setting in the Gemini TTS voice key check
Global drop_params, batch row and deployment drop_params on Vertex batch
file uploads now drop unknown voice keys. A voice object with both
speechConfig and speech_config gets a 400 for the ignored speech_config.
* fix(gemini): drop unknown nested voice fields under drop_params and detect TTS by served model
* fix(gemini): filter unknown speech config fields with fixed-depth helpers and pass audio params through unchanged
* fix(gemini): camel-case snake replicated voice keys so drop_params keeps them
* fix(vertex-ai): reject voice fields Cloud TTS cannot send unless drop_params is set
* fix(vertex-ai): reject wrong-typed Cloud TTS voice values and check speakers as sent
Gemini TTS on mp3, opus, alaw, or mulaw now answers 400 for a voice field whose value Cloud TTS cannot send, such as a list languageCode or a string voiceConfig, and for nested voice fields under a speaker that also names speakerId. drop_params still drops them.
* fix(vertex-ai): reject wrong-typed speech config wrappers and speakerId overriding a prebuilt voice on Cloud TTS
* fix(vertex-ai): keep speakers and voice_config beside a speech_config wrapper on Cloud TTS
* fix(vertex-ai): pick Cloud TTS voices from the same speech config the WAV path sends to Gemini
* fix(files): carry the deployment's drop_params on model= file uploads so Vertex batch rows drop unknown voice keys
* fix(gemini): keep a structured speech voice when the model is a model_alias_map alias for a Gemini TTS model
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cli): send pi's session id from lite pi so sessions group and stick
* docs(cli): drop the provider_block docstring lines the README already covers
* docs(cli): note the session id format the proxy reads for lite pi
* test(responses): cover billing every round of a streamed MCP auto-execute
* fix(responses): bill every round of a streamed MCP auto-execute on one spend row
* fix(responses): bill every round of a streamed MCP auto-execute on bridged providers
A streamed /v1/responses MCP auto-execute on a provider bridged through chat
completions (for example Anthropic) billed only round 1, because each round's
chat stream dispatched on the shared logging object and the first dispatch won.
Bridged rounds now go through the same one-row billing as native rounds. A
round is billed as soon as its chat stream ends, before its closing events
reach the client. The row carries the final response, usage and cost summed
over every round, and the fixed margin once. A round served from the response
cache is billed at zero. A follow-up chat stream that breaks bills the paid
rounds on its failure row. A single-round stream logs exactly as before.
* fix(responses): charge one fixed margin and keep bridged usage fields on streamed MCP rounds
A follow-up round that fails after earlier rounds were billed now charges the
per-request fixed margin once, and its failure row carries no cost breakdown
that would disagree with the summed cost.
A bridged multi-round stream logs a plain cache_hit flag like a single-round
stream does, and its usage keeps the summed provider usage fields of every
round.
A new test covers a stream dropped after its event loop closed, which must
release its parked log without an unawaited coroutine warning.
* fix(responses): price each streamed MCP round on its own and bill every round when a guardrail blocks
Each round of a streamed MCP auto-execute is now priced from its own
uncached cost, so a provider that states its cost (xAI) charges the stated
cost of every round plus the fixed margin once, and the cost breakdown
always agrees with the billed cost.
Summed usage goes through a JSON-safe dump, so a nested provider field such
as xAI's context_details no longer breaks a failed stream's response.failed
event.
A post-call guardrail that blocks a multi-round bridged stream now drops the
parked success log and bills every round on the failure row, and a failed
follow-up round's failure row carries the summed breakdown of both rounds.
* fix(responses): keep earlier MCP rounds on their success row when a later round fails
When a later round of a streamed MCP auto-execute fails, the rounds before
it are now logged on their success row, and the failure row bills only the
failed round with no second fixed margin. That failure log runs on its own
copy of the request's logging state, so its usage and cost never leak into
the earlier rounds' row.
A post-call guardrail that blocks a native multi-round stream keeps the
summed success row beside the $0 failure row, as at the merge base, while a
bridged stream still bills every round on its failure row.
* fix(responses): keep a failed later MCP round on its own failure row
A streamed MCP auto-execute whose later round failed wrote only the earlier
rounds' success row. The failure was logged on a copy of the logging state,
while the proxy builds its failure row from the request's own state, which by
then held the success payload, so the failure row took the success row's id
and was dropped.
Now the failure is logged on the request's own state as at the merge base,
and once a later round starts, the success row for the rounds before it is
logged from a copy of the state taken at that moment, so the two rows never
mix.
* fix(proxy): let an MCP tool call reuse its request's max_parallel_requests slot
* test(proxy): create the other-request task in a way Python 3.10 supports and mark its bindings Final
* fix(proxy): keep a reused max_parallel slot until the request's last round
An MCP tool call that reuses its request's max_parallel_requests slot no
longer loses it to the first round's late success callback, so the key
stays counted for the rounds still to run. The reused call also stops
replacing the request's rate limit headers.
* fix(responses): keep an unpriced streamed MCP round unpriced instead of billing it as free
* fix(responses): log a bridged MCP stream as a chat completion with every round's usage
* fix(router): unregister strategy selectors from global callbacks on discard
Router.discard only removed its own bound methods from litellm's callback
lists, so the strategy selectors it registered (least-busy, usage-based,
latency-based, cost-based and routing group selectors) stayed behind and
kept receiving events after the router was gone. Reuse the identity based
unregister that update_settings already uses so a discarded router takes
only its own selectors with it
* fix(router): purge discarded selectors from every event callback list
function_setup copies litellm.callbacks into the success and failure
lists on every request, so a router that served traffic still leaked its
selectors there after discard. Route the cleanup through
remove_callback_from_all_lists, which now also covers input_callback, and
fold the selector gathering into discard so the router coverage check
sees no untested helper
* fix(router): keep live routers, in-flight hooks and user_config limits intact on discard
discard() now rebuilds every global callback list without the router's selectors, optional pre-call checks and own usage callbacks instead of removing them in place, so a callback loop already running never skips a hook. It then re-registers what the remaining live routers need, so a same-strategy survivor keeps its deduped handler. The proxy's per-request user_config router is discarded only after its call returns.
* fix(router): bind user_config handlers to the request and tighten discard
When a user_config request carries a logging object, its router is
discarded before the request runs and its handlers ride on that
logging object, so v1 rpm and v2 tpm limits count every request and
concurrent requests count once. Without one, the router is discarded
after the request as before. The router's pre-call loops also read
the request-scoped handlers.
discard() now refills only the handler keys it vacated, guards the
callback lists and the live-router set with a lock, covers routers
built without a model_list, and drops its Slack alerting, adaptive
router hook and budget limiter sync task
* fix(proxy): reuse one user_config router per config and bind its handlers to each request
Every user_config request now goes through a cached router built once per
config. Its strategy handlers leave the global callback lists and are bound
to the request's logging object instead, so limits count each request once
and nothing is left behind after the request.
* fix(router): keep the proxy budget limiter on user_config requests
A user_config router now swaps in only its strategy selectors, so the proxy's
RouterBudgetLimiting stays on the request and keeps counting its spend. Usage
logged after a strategy is retired, such as a request still in flight when its
user_config router is evicted, now schedules one more push to Redis.
* fix(proxy): init the retire fields on the key model budget limiter
The key model budget limiter builds its own state instead of calling the base
init, so with the proxy's Redis attached every spend increment raised on the
missing retire flag and the key's model budget never counted spend.
* fix(router): bind the deployment callbacks to user_config requests
A cached user_config router serves requests through each request's logging
object but bound only its selectors and policies there, so a failing
deployment was never cooled down and its usage counters missed requests.
* fix(router): retry an evicted router's budget writes and keep the adaptive header on user_config requests
A retired budget limiter now keeps retrying its queued Redis increments every
sync interval until Redis accepts them, instead of giving up after one failed
write.
The x-litellm-adaptive-router-model header now comes from one stateless hook in
litellm.callbacks that holds no router, so user_config adaptive routers, whose
per-router hooks are request-scoped, still answer with the header.
* fix(router): lock request callback setup against router cleanup and drain in-flight budget writes on retire
function_setup now edits the global callback lists under the same lock that
router cleanup uses, so a router dropping its callbacks on another thread can
no longer shift the indexes function_setup pops or put a dropped handler back.
A budget limiter retired while a Redis write is still in flight now keeps
retrying that batch if the write fails, instead of leaving the spend queued
with no task left to send it.
* fix(utils): set up loggers after releasing the callback lists lock
function_setup held the callback lists lock while set_callbacks ran its one-time
logger setup, which can block on a Slack package install, so other threads and
Router.discard waited on it. The lock now covers only the list reads and writes.
* test(router): annotate the retire test's locals as Final
* fix(logging): skip replaced global callbacks on the input path too
replace_global_callback already kept a same-key global logger out of
success and failure dispatch. pre_call and post_call still sent it the
input events, so a logger with an input hook could count a request start
it never saw finish. Both now share one filter with the success path
* test(logging): type the input-path regression test
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix: Send the include_usage chunk with an empty choices array
Signed-off-by: Alberto Perdomo <aperdomo@redhat.com>
* test: Skip chunks with no choices when reading streams
Signed-off-by: Alberto Perdomo <aperdomo@redhat.com>
* fix: Strip usage from plain-iterator async stream chunks
Signed-off-by: Alberto Perdomo <aperdomo@redhat.com>
* test: Expect empty choices on the usage chunk in the gemma tracing test
Signed-off-by: Alberto Perdomo <aperdomo@redhat.com>
* fix(streaming): send the empty-choices usage chunk only to callers that asked for include_usage
The usage chunk now has choices=[] only when the caller set
stream_options.include_usage itself. When the OpenAI handler, the proxy's
always_include_stream_usage setting, or the harness added include_usage on the
caller's behalf, the chunk keeps its legacy single empty-delta choice, so
clients that read choices[0] on every chunk keep working.
The proxy and harness mark their injection with the private
_litellm_stream_usage_injected flag, and the proxy scrubs a client-sent copy.
Plain-iterator streams keep usage on their chunk when usage was not requested,
and the LLM Shield trailing flush ignores chunks with no choices.
* fix(proxy): mark the default stream usage injection so hooks keep the legacy usage chunk shape
The proxy's default strip-mode injection adds include_usage for clients that did not ask and drops the usage chunk before it reaches them, but streaming iterator hooks still saw it with choices=[]. Marking that injection with _litellm_stream_usage_injected keeps the old single empty choice for them.
* fix(router): treat deployment and router-default stream_options as injected, and drop the client flag on the queue route
* refactor(router): move the stream usage injection check into router_utils
* fix(router): read stream_options from pydantic deployment params when marking injected usage
Update the mantle, openinference, and text-completion integration tests to expect the include_usage chunk with empty choices.
* fix(proxy): keep the stream usage injection marker out of stored request bodies
* test(streaming): cover who asked for stream usage on chat, queue, deployment and spend log paths
* test: type the queue flag test, pin the logging start time, and build the deployment usage config without mutation
---------
Signed-off-by: Alberto Perdomo <aperdomo@redhat.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
