* 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.
* test(files): cover owner-scoped file listing under require_managed_files
* fix(files): list only the caller's managed files on every list route under require_managed_files
* fix(files): narrow owner-scoped managed file lists to the named provider or model and page with after_id and before_id
* fix(files): narrow scoped lists the way uploads route, and refuse lists that cannot be scoped
A model name now matches every deployment that serves it, wildcards and
aliases included, and a provider matches deployments by the provider
uploads resolve, so anthropic/* and unprefixed Claude models count. The
OpenAI and Azure lists also return the caller's pass-through uploads.
An unknown provider and different after and after_id cursors answer 400,
and a list with no matching deployment skips the database read.
* fix(files): match stored files by model name and keep flag-off lists as on main
Under require_managed_files, a narrowed list now matches a file's model
mappings by deployment id or model name, so files LiteLLM stores in its own
database show on their model and provider lists. The Anthropic list defaults
to 20 rows when no limit is sent, after_id, before_id and the cursor 400s
apply only under the flag, and an admin keeps the provider list when the
managed files hook is not loaded. List errors are returned as values and
mapped to HTTP errors in one place.
* fix(files): keep admin provider lists and index the owner-scoped walk
Under require_managed_files, an admin keeps the provider list as on main, and
only a non-admin list reads the caller's own and team managed files. A stored
file now also shows on the provider its model name routes to through a
wildcard, with exact model names first, and a list routed to a model takes the
default page size of the provider serving it. A new index on created_by and
created_at keeps each chunk of the walk an index read, and the model check
runs before the file object is parsed.
* fix(files): filter provider and model lists in the query
A non-admin list scoped to a provider or model now asks Postgres only for the
caller's rows that map to one of that scope's deployments or models, or that
live in file storage, instead of reading every owned row and filtering them in
Python. A caller with many files on other providers no longer waits for the
whole set to be read. Team members' files are matched in the same query.
* test(files): type the fake raw query in the files list tests
* refactor(proxy): list managed files through one typed database handle
* fix(files): list alias and routing-group storage uploads on their provider
* 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
* fix(managed_files): send provider file ids when creating a fine-tuning job from managed files
Fine-tuning job creation with a managed training file sent the gateway's managed id and the provider-prefixed deployment model to OpenAI, which rejected the job. The pre-call hook now builds the file id mapping for training_file and validation_file, the deployment hook swaps both, the SDK strips the provider prefix from the model, and the create response returns the caller's own file ids
* fix(managed_files): route managed fine-tuning creates only to deployments holding every file
Fine-tuning creates now narrow routing the same way managed batches do, so a
deployment added after the upload is never picked. Adds a two-worker chaos
integration test and runs tests/unit/fine_tuning in the endpoints shard.
* fix(managed_files): keep fine-tuning creates on the model group when no deployment holds the files
A managed file used on a model group it was never uploaded for kept failing
with the provider's 400 before the routing filter. The filter turned that into
a 429 no-deployments error, so fine-tuning now falls back to the whole group in
that case while batch input files keep routing only to deployments that hold
them.
* test(fine_tuning): cover the provider prefix strip for OpenAI and Azure creates through the proxy
* test(fine_tuning): start each multi-deployment case from an empty upstream log
* test(fine_tuning): boot both proxies of the late deployment cell on one scratch database
---------
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* 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(xai): report a completed xAI batch's results as its output file details
* fix(xai): keep a short results download and per-call timeouts out of the reported file details
* fix(xai): describe a batch's results file from the batch alone and let the batch job fill its size
Reading an xAI batch id as a file now costs one batch read and never downloads
the results: the file reports a 0 byte placeholder, the results filename and
the registration time. The managed proxy fills in the size the batch cost job
measures when it downloads the results, keeps a known size when a provider
reports none, and drops the per-process results download cache.
* fix(managed_files): keep a measured batch output size when a refresh races the batch job
A refresh that read the row before the batch cost job stored the measured size
could save the provider's unsized details over it. The refresh now reads the
row back from the writer and saves only while the row still holds what it read,
retrying when another write landed in between. The new tests drive the real
xAI and OpenAI retrieve paths through a fake HTTP upstream.
* fix(managed_files): guard the refresh save with the row the request already read
The conditional save first compares against the row the request read, so a
refresh adds no database read unless another write landed in between; only
then does it read the row back from the writer and try again.
* fix(managed_files): save a refreshed file object with one guarded write and no extra database reads
A refresh that loses its guarded write to a newer one now leaves that row
alone and drops this worker's cached copy, so the next read loads the newer
row instead of retrying against the database on the request path
* fix(managed_files): retry the batch cost job's measured size after a read refreshes the row first
The batch cost job re-reads the row from the writer and saves again when its
guarded write loses to a concurrent refresh, so its measured size is never
dropped. Reads without a measured size still make one write and no re-read
* fix(managed_files): size a concurrently refreshed row instead of restoring the batch job's placeholder copy
When the batch cost job loses its guarded write and the row it re-reads holds
refreshed details, it applies its measured size to those details, so the
results filename and any size the provider reported are kept
* fix(managed_files): keep a batch output's earlier created_at when a refresh replaces its placeholder
A refresh saved over a stored row now keeps the earlier of the two creation
times, so an xAI placeholder keeps the time the proxy registered it instead of
the read time, while a provider's own earlier creation time still wins
* test(integration): an xAI placeholder row keeps its registration time after the proxy refreshes it
* test(integration): drop the cached output row so the placeholder cell reads the seeded database row
* test(integration): drop the cached output row without requiring it to still exist
* fix(managed_files): limit the batch output size fill, guarded save and kept created_at to xAI rows
* fix(xai): keep the batch id as the batch output filename
Managed xAI batch output files keep the filename main already returns
(the batch id) instead of renaming them to <batch id>_results.jsonl.
---------
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* test(managed_files): pin ownership checks on batch and fine-tuning create
Tenant B can create a batch or fine-tuning job from tenant A's managed
file id today. These fail on main for acreate_batch input_file_id and
acreate_fine_tuning_job training_file and validation_file
* fix(managed_files): check input file ownership on batch and fine-tuning create
Batch create and fine-tuning create only mapped the managed input file to
provider ids and never checked who owned it, so any key with access to the
model could build a batch or job on another tenant's file and then own the
outputs. Both now run check_file_ids_access like chat and responses do,
which 403s a non-owner and 404s a managed id with no ownership row.
Fine-tuning also checks validation_file, which was never looked at
* test(batches): pin that a pre-call ownership denial stops every batch create branch
LIT-4797 noted an endpoint-level check missed the load-balanced branch
because it dispatches first. The ownership check lives in the pre-call
hook, which runs before branch selection, so a 403 there must keep both
the load-balanced and unified-file branches from reaching the router
* test(integration): pin managed-file ownership on batch and fine-tuning create
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(managed_files): check ownership before the batch rate limiter reads the input file and keep key-owned resources across key regenerate
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>
* refactor(proxy): expose public names for private proxy helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep original class names behind public aliases
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): preserve internal callback filtering
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep _PROXY_ class names for managed files hooks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep old private names in package exports
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): preserve recursive auth helper name
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): align MCP limiter tests with server enforcement
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): match main's MCP limiter tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep old private names bound in importing modules
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): preserve compatibility imports through strict lint
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): use exact pyright suppression in password helper test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(proxy): add reasons to compatibility import noqa comments
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): update IN-list baseline for renamed helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* 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.
Response cache reads and writes open cache.get llm_response and cache.set llm_response phase spans with their Redis spans nested underneath, on the Python path and on the native Rust path, and deployment selection runs inside a route {model_group} phase so the cooldown, usage and model-id reads the router issues nest under it before chat {model}. The autorouter classifier call nests under that route phase as well and carries its typed internal origin on litellm.request.purpose, so it is told apart from the provider attempt. Service spans are named {service}.{verb} {target} from a low-cardinality key family the producer declares (llm_response, auth_objects, spend_counters, router_cooldowns, claude_code_session_router_binding, rate_limits, pod_lock, budget_reset, ...) instead of the raw method or a per-request pipeline length; a pipeline flush is targeted by the one family its ops share or by mixed with the sorted families on litellm.redis.families, a batch op keeps the family it was declared under whichever pipeline or standalone read settles it, and the ambient family labels Redis spans only, never the DB write-back a task spawned inside that context performs later. The raw method stays on litellm.service.call_type and on the Prometheus and Datadog labels. Caller attribution is carried across asyncio task boundaries on a ContextVar so forwarder-only chains no longer surface, the raw cache key is dropped from Redis span metadata, pipeline op counts land as an integer attribute, every call_type the Redis cache layer emits maps to a verb, and a scan over litellm/ and enterprise/ fails when a Redis producer, batch reservation included, declares no key family.
A V2 logger built for a key or team logging entry while the operator's V2 logger is already registered keeps only the exporters its own preset contributed, whether or not the operator holds credentials for that backend, so every chat span no longer reaches the operator's collector twice. A span the success callback has to open itself, with no pre-call carrier, starts at the provider handoff (api_call_start_time) instead of the logging object's creation.
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(vector_stores): return managed file ids from vector store file list
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(vector_stores): cover managed file list route
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(vector_stores): only map round-trippable managed ids and index flat file ids
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy-extras): build managed file gin index concurrently
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(proxy-extras): move the managed file gin index migration after main's newest
* fix(vector_stores): satisfy lint gate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(proxy): drop the stale no-index note on the raw file-id guard
* test(vector_stores): cover managed file ids on the vector store file list end to end
Integration cells for GET /v1/vector_stores/{vs}/files mapping provider file ids back to
the caller's owner-scoped managed ids and decoding managed after and before cursors: raw
httpx, the OpenAI SDK sync and async pagers, the three credential routing modes, the owner
filter branches, raw and unmappable cursors, provider errors, duplicate and non-string ids,
a provider outage mid-burst, a worker SIGKILL mid-burst, and the GIN index migration applied
by the migration entrypoint and by db push
---------
Co-authored-by: shivam <shivam@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* 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>
The managed files hook's content read looped the file's model mappings and asked each deployment for the file. A file LiteLLM stored itself maps every model to its storage url, so the read sent that internal id to the upstream server, failed, and the batch rate limiter failed open: a key's TPM limit did not apply to a LiteLLM-executed batch. The hook now returns the stored bytes from the file's storage backend before it consults any deployment
vLLM serves no /v1/files or /v1/batches, so a hosted_vllm deployment can never
host a batch. Batch inputs for such a deployment now land in a LiteLLM-owned
storage backend, the batch is executed line by line through the deployment's
own chat, completion, embedding, or responses route, and the batch plus its
output and error files are served back from the database under the creating key
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.
Converge on staging's delete plumbing (_S3DeleteContext read from the logging call's additional_args, _sign_s3_request_without_body, the credential-stripping delete_data in the managed-files hook) and keep this PR's listing support, the 400 mapping for out-of-bucket file ids, the proxy-admin-only raw cloud id rule, and the OpenAI FileDeleted delete response.
Two staging tests move to this PR's contract: an out-of-bucket delete raises BedrockError 400 instead of ValueError, and deleting a stored provider output returns FileDeleted rather than the stored file object.
GET /v1/files through a provider config now returns the OpenAI page shape
(object list, data, first_id, last_id, has_more) instead of a bare array, and
DELETE /v1/files/{id} on a managed id answers the OpenAI FileDeleted shape with
deleted true instead of an empty body
Bedrock listing asks S3 for max-keys=0 when the purpose is one Bedrock never
stores under LiteLLM's prefixes, and batch_output listing no longer requires an
input bucket when only s3_output_bucket_name is configured. The mock request
behind the 400 for a foreign file id uses the same https://litellm.ai URL the
exception module uses
* fix(batches): register ownership for every batch create path
Since the team isolation change, the managed files hook decided whether a
response came from a create by looking for the managed input file id on it,
which only the unified input path sets. Batches created from a model-encoded
input file id, a model param, or a raw provider id with ?provider= never got
an ownership row, so they vanished from GET /v1/batches for the key that
created them.
The create endpoint now stamps a create marker on the response before the
hooks run, and the hook keys ownership registration and the batch-created
metric on that marker instead of on the input id format.
* test(batches): assert ownership registration through the managed files hook
The endpoint tests asserted the private create marker, which is wiring, not
behaviour. They now run the create through the real managed files hook and
assert the ownership row is written for the creating key on every create
path, with the unified path driven by a genuine encoded input file id
instead of patched decoders.
Batch creation snapshotted the team's organization with a direct
litellm_teamtable query on every create. Go through get_team_object
instead, which serves the team auth already cached and only falls back
to the database when the team was never cached.
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.
The managed batch listing fetched one page of rows, derived has_more from
that raw fetch, then dropped every row whose stored blob would not parse.
last_id came from the survivors, so a page of corrupt or legacy rows came
back as data [], last_id null, has_more true, and a client following
last_id could not advance. The OpenAI SDK's auto-paginator, which cursors
off the last item in data, stopped silently and returned a truncated list.
Read chunks until page_size + 1 batches survive parsing and file-id
resolution or the caller's rows run out, the way the managed file listing
already does, so a page carries data and a usable cursor while parseable
rows remain and has_more only says true when another one exists. The first
chunk keeps the old page_size + 1 size so a healthy page still costs one
query; a scan that has to continue widens to the file listing's
continuation chunk and stops resolving rows once the page is full.
