* fix(batches): cost an unmanaged gs:// batch through the deployment that created it
The create now stores the router deployment id as model_id inside the
managed object row's file_object JSON and CheckBatchCost reads it before
falling back to the first deployment matching the base model in the
gs:// path. Rows without the field keep the old lookup
* fix(batches): tolerate a non-string or malformed file_object when reading the stored deployment
* fix(batches): read the stored creating deployment from the writer, not a lagging read replica
* fix(batches): resolve the writer database once so the type gate count does not grow
* fix(batches): decode a dict-shaped file_object when reading the stored deployment, accumulate wire samples, annotate test locals
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Code outside the router now reaches it only through the entry points
(registry, settings, health, select, apply, observe, register_plugin, retire)
or the endpoint methods; the outside-member allowlist shrinks from 139 to 45.
litellm/router.py no longer imports litellm.proxy: it asks the installed
RouterHost (litellm/router_host.py) for vertex pass-through credentials,
member auto-router authorization and auto-router prompt compression, and the
proxy installs its host on import. Call sites where a model name can be
missing keep the old answer instead of reaching an entry point with None.
* fix(responses): resume background response streams with stream and starting_after
Retrieving a response with stream=true and starting_after=N now returns the
replayed event stream from OpenAI and Azure instead of one JSON object, on the
SDK (get_responses / aget_responses) and on the proxy's GET /v1/responses/{id}
Providers that cannot replay a stored stream drop the params under drop_params
and raise UnsupportedParamsError without it. Malformed values answer 400 with
the param named. A replay that reaches its terminal event settles the
background response's bill once and passes the provider's usage through
without estimating one. An empty replay (cursor at the end) ends normally
* fix(responses): encrypt replayed stream ids and resume Azure AI Foundry streams
A replayed background stream now gets the same response id encryption as a
created one, so the key that made the response can reuse the id. Azure AI
Foundry deployments resume streams like Azure ones, and the chat-bridged
Responses iterator closes its wrapped stream instead of raising.
* fix(responses): drop malformed resume params under drop_params and keep JSON answers to a streamed retrieve
A bad stream flag drops to a plain retrieve and a bad cursor to a full replay when drop_params is on, and a cursor without stream is ignored even when malformed. A streamed retrieve that the upstream answers with JSON returns the response object instead of an empty stream. get_responses forwards only the include keys from extra_query.
* fix(responses): give proxy stream resumes the deployment stream_timeout and document retrieve query params
* fix(responses): keep deployment stream off retrieves and reject oversized cursors
* fix(responses): keep router default stream off plain retrieves
* test(responses): black box coverage for resume refusals, drop_params, stream timeout and billing
* test(responses): replay a real stream in the billing test and type the fake wrapper chunks
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>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): cover the batch cost poller gaps left after #47190
* fix(batches): keep unbillable batches from blocking file deletes and new-batch polling
The file delete check now ignores batches past MANAGED_OBJECT_STALENESS_CUTOFF_DAYS, a provider 404 for the output object retires the batch, each poll page takes the arrival lane first, a batch expires only after the poller visits it past the cutoff, and the compare-and-swap matches batch_processed instead of updated_at
* test(batches): cover the full arrival page and a failed expiry write in the batch cost poller
Old batches still get polled every other cycle while new batches fill the page, old batches that fill a page never push a new batch out after boot, and a failed stale_expired write no longer stops the rest of the page from being polled
* fix(batches): share the poll page between old and new batches and hold output files until billed
Each lane now gets at least half of the poll page, a lane with nothing left gives its half to the other, and a lane read that resumed mid-lane wraps to the start, so neither old nor new batches can starve the other.
The delete guard applies the 7 day cutoff to input files only. Output and error files stay locked until the batch is billed or retired, and stale_expired rows no longer lock anything.
Only a lasting provider failure expires a batch past the cutoff, so a timeout or a 5xx no longer gives up on a batch that may still bill. Past the cutoff a lasting failure, a lasting cost-tracking failure, or an output file id that never appeared retires a finished row instead of polling it forever.
* fix(batches): retry refused finished batches past 7 days, expire unfinished ones on a failed retrieve
A finished batch the provider refuses after 7 days (rotated key, bucket 403, a 404 that does not name the batch) now keeps retrying so its spend is written once the config is fixed, instead of retiring unbilled. A batch the provider still reports running keeps polling. A batch that is not finished in the database becomes stale_expired once a retrieve fails after 7 days, so an unreachable provider is not polled forever. An S3 NoSuchKey for the output object now counts as gone.
* fix(batches): expire an unfinished old batch only after 3 failed retrieves in a row
* fix(batches): keep retrying an unfinished old batch through timeouts, 429 and 5xx
* fix(batches): wait 3 polls before expiring an old batch whose output id lags
* fix(batches): match a resource id in a 404 message followed by punctuation
* fix(batches): keep refusal and pending-output expiry streaks apart, and void a pending-output retirement on a client write
* fix(batches): give up on unsettled batches past twice the staleness cutoff
Replace the per-reason refusal and pending-output streaks with one give-up age, and inject a clock into the poller and the delete check so tests pin exact age boundaries
* fix(batches): keep polling finished batches past the give-up age so their spend stays recoverable
* test(batches): expect a restarted poller's first page to split between old and new batches
* test(batches): pin the delete-guard tests to a fixed clock and type a new journal list
* test(batches): type the provider helper and the storage 404 cases
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* 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
* test(responses): the billed background response cost reaches the creating key's and team's loggers
* fix(responses): send the billed background response cost to the creating key's and team's loggers
* fix(responses): bill an unreadable or rejected creator through proxy loggers, redact and honor disabled callbacks on the billed event
* fix(responses): follow the creator's message logging setting on the billed event and read team logging for non-key creators
The billed event no longer forces redaction. It follows the creating key's or team's turn_off_message_logging, else the proxy's, and redacts when the creator cannot be read or its settings are rejected. A creator without a virtual key hash bills through its team's settings. function_setup keeps its original callback split, and the billed path uses a separate non-mutating helper.
* fix(responses): bill rotated, deleted, and custom auth creators through their own logging and retry failed creator lookups
* fix(responses): follow a key's whole grace-period rotation chain to the live key for its billed charge's logging
* fix(responses): bill a background response whose creator cannot be read, without the creator's settings
* docs(enterprise): say the background response row is claimed before its creator is read
* fix(responses): keep the loaded creator rows' budgets and aliases when one creator lookup fails
* test(responses): billed background responses count toward the creator's project and model budgets
* fix(responses): carry the creator's project and per-model budgets on the billed background response
* fix(responses): count a key's budget tier toward background per-model budgets
* fix(responses): bill a background response's project only while the key stays on its team
* revert(responses): keep billing the creating key's project after a team move
A key can only keep or detach its project, so the billed project always pairs with the team it was created under. This reverts commit ded4f084c5.
* fix(responses): bill a background response under the model name the client sent, with its project alias
* fix(responses): name the team's public model as a billed background response's model group
The model group lookup now passes the creating key's team, so a team model or team wildcard bills under the public name a normal call logs and per-model budgets on that name move
* fix(batches): apply the Vertex regional endpoint uplift to batch cost
batch_cost_calculator takes vertex_location and multiplies by the model's
regional_endpoint_uplift_multiplier through get_vertex_regional_endpoint_uplift,
and every batch cost path (aretrieve_batch pricing, completed-batch logging,
native Vertex batch rows, the proxy batch cost poll and its per-line items)
resolves the deployment's location and passes it down
Co-authored-by: Mrun25 <165297479+Mrun25@users.noreply.github.com>
* test(logging): point the resolver tests at resolve_vertex_location_for_cost
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Mrun25 <165297479+Mrun25@users.noreply.github.com>
* feat(batches): emit per-line JSONL batch records to callbacks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): only emit line items for final batches
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(deps): bump soupsieve to 2.9.2 for GHSA-gjv8-xp57-g29c and GHSA-j934-xhv5-fg8f
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(batches): satisfy ruff format for line item logging
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(ui): regenerate schema.d.ts for store_batch_line_items_in_callbacks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): cover line-item edge shapes and general settings propagation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): keep deployment credentials out of callback-visible params
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(batches): declare credential transport attribute on Logging
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): integration contract for per-line batch callback events
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): resolve store_batch_line_items_in_callbacks through the settings store
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): assert per-line events beside the aggregate and create events
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): drop resurrected use_legacy_interactions_schema shim from merge
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): assert line item events carry no credentials
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): reset batch line-item flag when the setting is absent
Removing store_batch_line_items_in_callbacks from the DB general settings left the module flag at its previous value because the effect early-returned when the key was neither in the DB nor owned by YAML. The proxy owns the global, so an absent resolved value now writes False.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): map anthropic batch lines through the anthropic message transformer
Anthropic result lines carry a message-shaped body, so ModelResponse(**body) produced empty choices and a usage key that blocked the batch-rate usage attach. Extract the existing AnthropicResponse -> ModelResponse conversion used for /v1/messages logging into anthropic_message_to_model_response and reuse it for anthropic line items.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: tag the anthropic result cast with a cast-ok reason
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: shorten cast-ok reason so ruff format passes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): skip line-item callbacks for providers without a line reconstruction
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): reconstruct bedrock and mistral batch lines through their provider transformations
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: wrap widened provider literals so ruff format passes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): pair bedrock lines by recordId and type them from the reconstructed response
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): keep line item events out of proxy limiters and strip credentials from child params
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): keep cast-ok tags on the flagged cast lines for the discipline gate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): skip failed line item events in parallel request limiter failure hooks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): tolerate lifecycle spend rows when asserting no line item rows
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): place mutable-ok tags on the lines the discipline gate flags
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): skip router budget accounting for batch line item events
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): keep anthropic line errors and skip native vertex batch rows
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): restore test-quality tags on line item tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: move batch line-item unit test to tests/unit after merging main
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): emit batch line-item callbacks once per batch
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): release line-item claim when fan-out emitted nothing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): make the line-item claim release ownership-safe
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): keep bodyless failed batch lines reaching callbacks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logging): seed batch line hidden params in get_hidden_params defaults
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* perf(batches): reuse fetched batch result files for line-item logging
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): release line-item claim when nothing was emitted
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): type batch line-item callback sites to satisfy basedpyright budget
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: wrap batch hidden-params cast for ruff format
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): reason suppressions for batch line-item lint deltas
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: drop stale mutable-ok suppressions after LIT002 removal
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(batches): skip batch line-item events in ClickHouse spend sink and router quota counters (#44486)
* fix(batches): skip batch line-item events in ClickHouse spend sink and router quota counters
Batch line-item callbacks (call_type=acompletion + litellm_params.batch_parent_id)
bypassed the call-type-only batch guards:
- ClickHouseSpendLogger wrote one spend row per line on top of the aggregate
aretrieve_batch row, billing every batch twice with the flag on.
- Router deployment callbacks and the routing-strategy usage handlers charged the
historical batch's tokens/rpm to the live TPM/RPM counters, so after
Router.aretrieve_batch the next chat raised RouterRateLimitError.
Skip these events wherever the aggregate batch retrieve is already skipped.
* fix(logging): keep internal litellm_params authoritative in model_call_details
A request body key named litellm_params lands in optional_params, and
update_environment_variables merged **optional_params after the internal
entry, so a caller could overwrite the logging kwargs' litellm_params and
forge markers like batch_parent_id. Live-reproduced: a Gemini chat whose
body carried {"litellm_params": {"batch_parent_id": ...}} returned 200
with no ClickHouse spend row. Re-assert the internal litellm_params after
the merge so every sink (ClickHouse, Postgres, router quota counters)
reads the same trusted value, and assert the aggregate aretrieve_batch
row still writes in the ClickHouse line-item test (review finding).
* fix(clickhouse): skip failed batch line items in the spend sink too
A failed JSONL line is part of the aggregate aretrieve_batch row's
request counts; writing it its own spend_logs row inflated request
counts with the line-item flag on. Extend the batch line-item guard to
the failure handler (review finding) and pin both directions: a failed
line item writes no row, a genuine live failure still does.
* fix(batches): declare batch_line_items service family on claim calls
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(integrations): keep batch line items out of the built-in metering sinks
With store_batch_line_items_in_callbacks on, per-line batch events carry a
real response_cost and reached six metering sinks that lacked the
is_batch_line_item_event guard, so a completed batch metered aggregate +
per-line (roughly 2x true spend): prometheus (litellm_spend_metric and
request counters), openmeter, lago, datadog cost management (FOCUS
BilledCost), newrelic metrics, and the OTel v1/v2 gen_ai.usage.cost
metrics. Skip line-item events in each sink's success/failure metering
entry points, matching the guards already on the Postgres and ClickHouse
spend sinks. OTel spans for line items are still emitted; only their
cost/token metrics are skipped. Tests drive real sink instances on the
real dispatch lists through a completed 2-line batch and assert each
sink meters exactly the aggregate.
* style: format metering-sinks test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): skip synthetic line-item durations in v2 metrics; isolate prometheus test
Follow-ups from review on the sink guards: record_failure() now skips
batch line items too (a failed line's interval measures retrieval and
emission, not its model call), and the prometheus guard test snapshots
and restores the process-wide registry collectors instead of leaving
them unregistered. The OTel v2 test is now a flag on/off A/B over the
whole metric snapshot: cost and usage values must match exactly and no
metric may gain datapoints with the flag on.
* chore: finish main merge conflict resolution for batch line items
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: sort imports in litellm_logging after main merge
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(batches): use the public hook class names main now exports
* fix(batches): only the batch writer can mark a callback event as a line item
amoderation, transcription and speech build litellm_params from every request kwarg,
so a body field named batch_parent_id reached Logging.litellm_params and every
spend, budget and rate-limit hook skipped the request. update_environment_variables
now drops an incoming batch_parent_id; the line-item writer sets it through
Logging.mark_batch_line_item. Batch line hidden params are emitted only when set.
* chore(batches): keep the lint gates within main's ceilings after the merge
Typed the helpers main now types (Mapping litellm_params, Any Span), replaced the
banned cast with a literal match, dropped isinstance checks main made redundant,
and moved test-quality reasons onto the lines the gate reads.
* fix(anthropic): read the message id off the validated message
The anthropic_messages logging path can hand over an already parsed message object,
which has no .get; main read its id through getattr, so take it from the validated
AnthropicResponse instead.
* fix(batches): an unreadable error file no longer drops the output line events
Costing counts an error file it could not fetch as no failed lines; line logging
refetched it and the raise aborted the whole fan-out, so the successful lines were
never emitted. The error file now reads as empty with a warning.
* test(batches): pin billing for batch_parent_id on every endpoint and value shape
Chat completions, embeddings, responses and messages join moderations, speech and
transcriptions, and speech is driven with an empty, int, list, object and 5 KB value.
* test(batches): bill every request of a concurrent burst mixing forged and plain bodies
* revert: keep the line-item fan-out all-or-nothing on an unreadable error file
85fc4498cc emitted the output lines and kept the batch claim when the error file
could not be read, so its failed lines were never retried. Raising releases the
claim and the next retrieve retries the whole fan-out.
* test(batches): pin the all-or-nothing retry and warm the burst model first
An unreadable error file emits no lines and the next retrieve emits all of them.
The burst cell drives one speech model after a warm-up request so a cold worker
cannot fail it, and waits for the batched key spend.
* fix(batches): run the line fan-out outside the aggregate event's deadline
The logging worker cancels a callback coroutine after its per-callback
deadline, and the line fan-out ran inside the aggregate aretrieve_batch event
before its callbacks, so a large batch or a slow sink could cancel the
aggregate billing event. The fan-out now runs in its own task, built from a
copy of the parent's litellm_params taken before the aggregate callbacks
write their request-local markers.
Anthropic keeps no input file and reports input_file_id "None", which the
fan-out fetched and failed on, so no Anthropic line ever arrived. That id is
now treated as no input file.
* fix(batches): let running line fan-outs finish before proxy shutdown closes their clients
A started fan-out keeps its batch claim, so a shutdown that cut it short
skipped the unsent lines until the claim expired. proxy_shutdown_event now
waits up to MAX_TIME_TO_CLEAR_QUEUE for them first. Also replace a test's
type: ignore with an isinstance check.
* fix(batches): keep batch line fields off callback kwargs and skip fan-outs at shutdown
Line bodies were spread into the callback kwargs, so a line's metadata could settle router rate limit reservations; they now stay in optional_params, and the router rate limit and prompt caching hooks skip line events.
A retrieve logged after the shutdown drain, or by the logging worker's exit flush, no longer starts a fan-out its loop would destroy while it holds the batch claim.
The output file is fetched before the error file again.
* fix(batches): log batch lines under the retrieve's callback settings and keep them out of alerting and shadow eval
Line events inherit the retrieve request's key and team callback settings, so turn_off_message_logging and per-team logging credentials apply to them, and they keep the system prompt in the logged messages.
Shadow eval, Datadog metrics, Slack daily reports and PagerDuty skip line events, since the batch API served them and the aggregate event already counts the batch.
* test(batches): line events follow the key's message logging opt-out
* test(batches): line events follow team logging settings, keep the line system prompt and survive a restart once
* fix(batches): keep in-memory line claims for 10,000 batches and pin managed batch emission across poller and retrieves
* Keep batch line unit tests in-process and drop repeated per-sink comments
* Share one batch provider alias across batch_utils and line item logging
* Report Bedrock line status codes, skip unknown Bedrock lines without raising, fetch the input file after the native Vertex check
* Read a swallowed Redis claim failure as unavailable, price unpriceable lines at zero, keep the OTel failure docstring
* Call handle_completed_batch when line items are off, keep a cache test from leaking Redis into the line claim cache, pin an unpriceable line's zero cost on the callback kwargs
* Hand the cost poller's credential snapshot to line item file reads, so a managed Bedrock batch's lines read its input from the deployment bucket
* Log batch lines through the sync callbacks a direct async call runs, keep failed lines out of router cooldown counts, and emit an error line whose body is text
* fix(batches): log failed Bedrock embedding lines as embeddings with their input
A Bedrock batch input record carries no url, so a failed Titan v2 line fell back to acompletion and its
inputText never reached the event messages. The failed line now takes aembedding from the deployment
model and the record's inputText is the line input
* fix(batches): keep a Bedrock line's system prompt in its logged messages
Bedrock batch input records hold the system prompt as content blocks, which logging only reads off the kwargs as text, so Claude and Nova lines dropped it
* feat(batches): store per-line batch requests and responses in S3/GCS via batch_line_item_callbacks
Replace the per-line logging path with a dedicated hook. When the hourly batch cost
poller finishes a managed batch, it pairs every output and error line with its input
line, prices each line, and hands one payload to every logger listed in
litellm_settings.batch_line_item_callbacks. s3_v2 and gcs_bucket write it as one
NDJSON object per batch under batch_line_items/<day>/<batch id>.jsonl.
Bodies are dropped and the header kept when the creator key or team, the global
setting, or the logger itself turns off message logging, and when the creator can
no longer be found. A failed upload is logged and never blocks spend tracking.
* fix(batches): store batch line items after the batch is billed and retired
Send a billed batch's lines only after its row is marked complete, so a slow or
failing sink never holds a claimed batch open. Skip reading the input file when
the bodies are dropped anyway, still send the error lines of a batch whose output
file is gone, and end every NDJSON record with a newline.
* test(batches): cover team-level and deleted-key redaction of batch line items
* fix(batches): store batch line items in the background so a hung bucket never holds up billing
The poller now retires a batch first and hands its line items to a per-worker background store that runs one batch at a time. A slow, hung or failing bucket no longer delays billing or retiring the other batches in the poll cycle. While a poll cycle's worth of batches is still waiting to store, the next batch's lines are dropped with an error.
* fix(batches): store an unbilled batch's line items only once it is retired
When retiring an expired, cancelled or all-failed batch fails, the batch stays on the poll page, so its lines are no longer read and stored again on every poll cycle until it is retired. The poller also releases a billed batch's output bytes before reading the next batch's output, as it did before line items existed.
* fix(batches): price and write batch line items off the event loop
Pricing every line of a large batch and serializing its object ran on the
proxy's event loop, so a 50k-line batch stalled the worker for seconds.
Both now run in a worker thread. An object the bucket refuses for good is
no longer kept in s3_v2's drop marks, which only a log-queue flush clears.
Vertex AI input rows carry the custom_id in their key or request labels, so
their lines now get the request too.
* fix(batches): pair no request for a shared custom_id and wait for an unclaimed batch's retry
A Vertex AI embeddings entry whose input is a list is split into one row per
item, all with the same custom_id, so its line now gets no request instead of
the last row. On a database without batch_processed nothing claims a billed
batch, so when marking it complete fails it stays in the poll page and its
lines now wait for the next poll instead of being written on every cycle.
* fix(batches): store batch line items only once the poll has billed every batch
Pricing a large batch's lines on a worker thread still competes with the poll for the GIL, so the next batches
in the same poll were billed and retired seconds later. The background stores now wait until the poll cycle that
queued them has finished.
* fix(batches): hash line-item objects off the event loop and keep lines with a lone surrogate
A batch's whole line-items object was hashed for its S3 PUT on the event loop, and a line
holding a lone surrogate from a provider's JSON escapes made the object impossible to
encode as UTF-8, so the batch's object was never written. The object is now prepared in a
worker thread, and only the line that cannot be encoded is written with escaped characters.
* fix(batches): keep request and response for batches created without a virtual key
A batch created with a JWT has no API key on its row, and its line items were stored without
request and response as if its creator had been deleted. Such a batch now follows its team's
and the proxy's message logging settings, the same as a master key batch. A deleted key or team
or a failed lookup still drops the bodies.
* fix(batches): pair line items with the right request on every deployment and skip empty objects
A batch retired with nothing billable now reads its input file by the id the provider reported, so a batch that
ran on the second deployment of a model group keeps each line's request. A Vertex AI line read as custom_id
"unknown" pairs with no input row, and a batch whose files hold no readable line writes no object
* fix(batches): let OAuth2 batches follow team and proxy message logging settings
The line-item redaction check looked up every saved creator credential other than the master key or a CLI session as a virtual key. An OAuth2 batch saves the raw token, so it read like a deleted key and lost its request and response
It now looks up only a saved value shaped like a virtual key's hash, reusing is_valid_sha256_hash, so OAuth2 batches follow their team's logging settings and the proxy-wide setting while deleted keys still fail closed
* fix(batches): hash the creator credential and write batch line items in parts
The creator credential reaches line metadata only as a sha256 hash, so an
OAuth2 token or the master key alias is never written to the bucket. A queued
store keeps only whether the batch was billed and downloads the output file
again at its turn, logging an error naming the batch if that fails. Lines are
built and uploaded one part at a time, each closing once its raw request and
result bytes reach BATCH_LINE_ITEMS_MAX_PART_BYTES (16 MiB by default), with
the input file indexed by byte span instead of parsed up front.
* docs(batches): say async_log_batch_line_items is called once per part
* fix(batches): log an error when a batch's deployment is gone before its line items are stored
---------
Co-authored-by: shivam <shivam@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: yucheng <yucheng@berri.ai>
* 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>
* fix(proxy): mark background responses stale_expired when provider returns 404
Responses deleted upstream (store=false / ZDR rows dropped after provider retention) now move to stale_expired on the poll instead of being retried every cycle until the 7 day stale cleanup.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(proxy): drop inline comment in check_responses_cost
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): drive _get_response seam in 404 stale_expired tests
Assigning AsyncMock on the instance keeps the new tests inside the TQ002/TQ008 test-quality ceilings
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): only expire 404 responses polled through a resolved deployment
A NotFoundError from the bare SDK fallback can mean a missing or misconfigured deployment, which a config fix inside the staleness window can still recover. Rows whose poll went through their router deployment are the ones the provider actually dropped, so only those move to stale_expired.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): resolve the deployment before fetching so via_router binds once
Drops the reinitialised loop flag flagged by review and modernizes the moved annotation.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): drive the real response fetch in the poll 404 regression tests
* fix(enterprise): expire background response rows on any provider 404 status
The GET path maps the provider's 404 body to litellm.BadRequestError that still carries status_code 404, so an except on NotFoundError never fired and the poll job kept retrying the row every cycle. Key the terminal decision on the status code instead of the class
* fix(enterprise): expire a background response only on a 404 naming it and skip a bad deployment entry per job
* chore(enterprise): record the poll-cycle bound on the managed-object IN lists
* test(integration): cover background response poll retirement on the real proxy
---------
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>
* refactor(types): prove runtime types at harness, search, rag and client boundaries
Replace Any with adapter-validated types in the litellm.agent() harness, the
search provider transformations, RAG ingestion and query, the vector store
pre-call hook and registry, the galileo and opik logging integrations and the
proxy client CLI. Each boundary gets unit tests for well-formed and malformed
payloads.
* chore(typing): prove types at more provider boundaries and restore search transformations
Second pass over a2a, embedding, rerank, image, audio and small provider
modules. Search transformations go back to their previous form because
validating their response bodies would change the proxy status for
malformed upstream bodies from 400 to 500.
* refactor(types): prove types at logging, files, rerank, image, audio and management boundaries
Replace Any with validated or annotation-only types in 37 more files: logging
integrations, token counters, provider files/rerank/image generation/audio
transcription transformations, pass-through logging handlers and management
endpoints. No proxy HTTP status or error type changes.
* refactor(types): prove types at repository, spend, files and router boundaries
Replace Any with repository table accessors, validated mappings and
annotation-only types in 33 more files: Prisma repositories, the enterprise
batch and responses cost checkers, budget reservation, files endpoints,
management endpoints, the policy registry, the adaptive and complexity routers
and the secret managers. No proxy HTTP status or error type changes.
* test(types): run the aiohttp transformation test in-process and cover repository row conversion
The aiohttp chat transformation test no longer starts a server. It feeds the
transformation a response whose json() returns the body under test.
The proxy unit shards now exercise stored model rows whose params are JSON
strings and the object permission create and update paths.
* fix(spend): attribute CLI session spend to the per-user cli-session alias instead of the hashed session token
A CLI session token is a fresh random secret on every login, so since v1.99 each
login's spend rows carried a different sha256 hash as api_key and the usage APIs
could resolve neither key_alias nor user_email for them. Spend rows and logging
callbacks now attribute a session request to its stable alias,
cli-session-<user_id>, and the usage endpoints derive that alias and owner from
the key itself instead of scanning for a matching digest
* fix(spend): resolve the CLI session team from the user's first team in usage metadata
A cli-session key carries no team of its own in the DB, so the usage
breakdown showed team_id None for it and the export grouped it as
Unassigned. The login attaches the user's first team to the session, so
the recovery mirrors that rule for cli-session keys only.
* fix(spend): claim the session team only for a single-team user
The CLI login attaches a team on its own only when the user has exactly
one; a user in several teams picks one per login, so usage metadata for
the alias would otherwise name a team the login may not have used.
* test(pass_through): mark the mocked auth object as a plain key
The logged key follows the alias only for a session token; a bare
MagicMock reads as one, so the test names the field it relies on.
* fix(spend): attribute CLI session pass-through, queue, and managed batch spend to the cli-session alias
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): only treat the exact cli-session-<created_by> value as a batch key alias
A managed object row written by an older build can still carry the raw per-login
session token, which shares the cli-session- prefix. Matching on the prefix alone
would have surfaced that token as a trusted alias and persisted it verbatim in the
batch cost spend log, so the alias check now requires the exact per-user value and
every other prefixed value keeps going through redaction
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): log proxy executed batch rows under the cli-session alias instead of the session token
_row_metadata set user_api_key from the raw bearer token while user_api_key_hash carried the alias, so the spend log redaction rejected the alias as untrusted and hashed the random session token instead
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): attribute semantic search embedding spend to the cli-session alias
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): scope /key/spend/report for a CLI session to the cli-session alias
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): use the cli-session alias for websearch spend, prometheus failure labels and the parallel limiter
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(spend): drop explanatory docstrings on get_logged_api_key and attach_user_details
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): only recover cli-session usage keys whose suffix is a known user
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>
Narrow or remove reportAny / reportExplicitAny sites in provider
transformations, caching, guardrails, proxy endpoints and enterprise
batch-cost polling. Public parameters widen to Mapping/Sequence rather
than dict/list so no caller signature breaks, and runtime behavior is
unchanged.
Batch cost attribution and the legacy queue endpoint already store the
VerificationToken hash in user_api_key, but omitted user_api_key_hash.
Since v1.99 the spend-log writer re-hashes any key without that provenance
flag, so DailyUserSpend.api_key no longer joins VerificationToken and Usage
shows key-hash-... rows with null api_key_alias / user_email.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Second pass over the highest-Any-density modules that the first pass left
untouched: guardrail hooks, the gemini and anthropic transformation layers,
the proxy spend-tracking and pass-through endpoints, and the caching clients.
Untyped `response.json()` bodies and `dict[str, Any]` request payloads are
described once at their boundary with a TypedDict or Protocol, so the fields
read downstream resolve to real types instead of Any. No cast, no type: ignore,
no noqa, and no new Any annotations.
* fix(logging): stop billing and logging response reads as LLM calls
Retrieving, deleting or cancelling a stored response, and vector store management calls, run through the same logging lifecycle as inference. A retrieved response replays the usage of the call that created it, so every read priced it again and wrote a second spend log row for the same tokens. Non-inference calls now cost 0, report no usage, log no placeholder chat message, and get a litellm.responses_management operation name instead of reading as chat.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): keep billing background response jobs after the poll
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logging): use an empty list for read-call messages
A tuple matches no branch in the loggers that walk this value, so lunary's
parse_messages falls through to clean_message and raises AttributeError on the
success hook. An empty list reads as no messages everywhere: it satisfies the
isinstance(list) checks in newrelic, mlflow and datadog, iterates zero times in
traceloop and helicone, and is what StandardLoggingPayload.messages is typed to
hold. None would be type-legal too but is not iterable, so it trades one crash
for another in mlflow and traceloop.
* fix(otel): stop the legacy emitter reporting replayed tokens on response reads
The zeroing so far lands in the standard logging payload, which the legacy
OpenTelemetry emitter does not read for usage: it takes prompt, completion and
total tokens straight off the response object, so a retrieval span still carried
the token counts of the call that produced the response, and the token usage
histogram still recorded them. That emitter is the default, so the spend row said
zero while the trace said otherwise. The background cost poller keeps its counts,
the same exemption the pricing path already makes.
* fix(logging): keep billing a background response when its retrieval is read
A response created with background=true comes back queued and carries no usage, so
its create bills nothing. The retrieval that first sees the finished job is the only
place that job's tokens are ever visible, and pricing every read at zero therefore
loses the spend outright rather than deduplicating it. On a proxy without the
enterprise cost poller a background job ended up costing $0 end to end.
is_unbilled_non_inference_call now takes the response it is deciding about and treats
a background response the same way it already treats the poller's own read, which is
the same exemption seen from the other side. The legacy OpenTelemetry emitter's time
per output token metric picks up the read gate it was missing, so it stops dividing a
read's latency by the replayed completion token count.
* test(proxy): pass the read response to the non-inference predicate
The poller test called is_unbilled_non_inference_call with the pre-background signature, so it broke when the predicate gained the response it classifies. It now hands the predicate a foreground read, and asserts that the same read is free without the origin stamp, so the stamp is what the test proves.
* fix(otel): stop the v2 metrics recorder reporting replayed tokens on response reads
The v2 span builder sources usage from the standard logging payload, so the
earlier fix already zeroes it there. The metrics recorder reads response_obj
directly, so a responses-management read still recorded the original
generation's tokens into gen_ai.client.token.usage and divided generation time
by them for gen_ai.server.time_per_output_token.
The read still records operation and response duration, under the
litellm.responses_management operation, so it stays observable.
* fix(proxy): keep the response-cost headers on calls priced at zero
Pricing responses reads and vector-store management routes at zero dropped the whole
x-litellm-response-cost family off those replies. The header build reads a falsy zero as
a cost this response never recorded and filters it out, and a call that returns before
pricing stores no cost breakdown for the component headers to read, so a client parsing
the cost off a read got a KeyError where it had previously been handed a number.
Those calls now advertise the family at zero. Retrieving a background response, and the
cost poller's read of one, still report their real cost.
The params-taking form of the predicate moves from opentelemetry into
internal_call_metadata so the proxy header build and the OTEL recorders share one copy.
* fix(proxy): report a zero cost split only under a zero cost total
The component headers were filled from call-type membership alone, while the
total they sit beside keeps its real value when the read priced normally, so a
breakdown that had not landed by the time headers were built could advertise a
real total next to an all-zero split. The split is now reported as zero only
when the total agrees with it, and is otherwise left absent.
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Yucheng Zhu <yucheng@berri.ai>
Every repository handed its `.table` back untyped, so a dozen modules had
each grown a private `_PrismaTableActions` Protocol to paper over it. They
had drifted: some declared `update` as returning the row, others the row or
None, and none agreed on whether `find_many` was covariant
Replace all of them with a single `TableActions[RowT_co]` in
`litellm/repositories/prisma_protocols.py`, keyed to the prisma row each
repository is bound to. Query inputs stay `Mapping[str, object]` so callers
keep passing plain dicts, and `find_many` returns `Sequence` so the row type
stays covariant
Typing the nullable returns honestly surfaced paths that were already
crashing. A team admin could never edit or delete a memory entry owned by
their team: the write-auth check fed a raw prisma row to a helper that
expects the domain model, so `members_with_roles` arrived as plain dicts and
the request died as a 500 instead of applying the edit. Non-admin members hit
the same 500 in place of the 403 they were owed, so refusal and breakage were
indistinguishable. `/v2/model/info?user_models_only=true` dereferenced a
missing user row rather than returning the 400 the route already had, three
team routes dereferenced a team deleted between the read and the write, and
the agent registry dereferenced a missing agent instead of naming it
basedpyright drops 2,132 errors, 1,454 of them reportAny and 73
reportExplicitAny. The dashboard's generated types pick up `string[]` where
they had `unknown[]` for a team's members, admins and models
Staging split batch output-line costing into _safe_output_line_stats /
_compute_output_line_stats / _output_line_cost so one uncostable line can no
longer zero a whole batch, and added _provider_output_file_id so model-encoded
output file ids decode before the fetch. This branch's pass/fail counting was
written against the pre-split shape, where every None line meant a provider
failure.
Keep staging's structure and layer the counts on a three-way classification: a
provider-reported failure yields PROVIDER_FAILED, a provider-successful line
litellm cannot price yields UNCOSTABLE and stays in successful_requests billed
at $0. Without that split a litellm-side pricing gap would be reported to the
customer as a failed request and the counts would stop reconciling with the
provider's own request_counts.
Route the error-file fetch through _provider_output_file_id too, and carry the
new dataclass return through the callers staging added after this branch
forked.
Every pod and uvicorn worker schedules its own CheckBatchCost poller against the
shared managed-object table, so two of them can select the same completed batch in
one polling window and both write an aretrieve_batch spend log for it, counting
that batch's cost twice.
Claim the row with a compare-and-swap on batch_processed, and skip the batch when
another pod already holds it. The claim sits immediately before the spend log is
written rather than before the results fetch, because batch_processed is also what
blocks deletion of the files the fetch reads and what keeps an unbilled row
selectable by later poll cycles, so claiming up front would strand the spend of any
worker that died mid-fetch. A failed spend log write hands the row back.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Batch retrieval already computed cost/usage on completion, but silently
dropped reasoning tokens and never counted per-line success/failure.
Adds BatchCostUsageResult (replacing bare cost/usage/models tuples) with
successful_requests/failed_requests, and threads reasoning_tokens through
the aggregated Usage. Both surface on SpendLogs the same way batch_models
already does.
Probe the column before the scheduler registers CheckBatchCost, closing the window where a retrieve that decided the poller was inactive billed a batch the first poll cycle then billed again. Also drop narration docstrings and section banners from the new tests.
