aiohttp 3.14.0 and 3.14.1 re-arm the sock_read timer on a keep-alive
connection after it has already been returned to the idle pool. The stray
timer stamps a SocketTimeoutError on the pooled connection without closing
it, so the pool keeps handing it out and the next request to pick it up
fails instantly on an error left behind by an earlier, unrelated request.
Because a single pool is shared across providers, the failures appear
simultaneously across Vertex AI, Bedrock, Anthropic and OpenAI-compatible
deployments as sub-millisecond "Connection timed out" errors.
uv.lock resolved aiohttp 3.14.1 and the published images install via
`uv sync --frozen`, so every image built from that lock shipped the
regression. The wheel's own metadata declared `aiohttp>=3.10,<4.0`, which
also left pip consumers free to resolve into the same broken window, so
both the runtime floor and the uv constraint move to >=3.14.2.
Upstream fixed this in aio-libs/aiohttp#12954, released in aiohttp 3.14.2;
the lock now resolves 3.14.3. Raising the floor rather than capping below
3.14 keeps the advisories that the existing 3.14.1 floor cleared, so no
osv-scanner ignores are needed. litellm requires Python >=3.10 and aiohttp
3.14.2 requires >=3.10, so no supported interpreter loses support.
Both new tests fail on the previous pins and pass on these.
(cherry picked from commit ffd6ac52c5)
A single ddtrace constraint now covers every supported Python version, so this collapses the version split introduced in #33438. Also aligns the build_from_pip image pin and updates the type-only Tracer import to its current module path
(cherry picked from commit edc38eab34)
Root cause: PR #30867 removed request-time os.environ/ expansion in
BaseAWSLLM.get_credentials. That is only safe if config-load pre-resolves
os.environ/ refs so the value reaching get_credentials is already the real
secret. The YAML config path has always done this. The DB-load path
(ProxyConfig._resolve_db_litellm_param) only re-expanded keys in a hardcoded
whitelist (_DB_LITELLM_PARAM_ENV_REF_KEYS) plus short-circuited env-ref
resolution entirely for team-scoped rows. PR #32256 extended that whitelist
to 18 keys to unblock a customer whose Bedrock model with aws_role_name:
os.environ/BEDROCK_ASSUME_ROLE_ARN broke on v1.90+, but the whitelist is
structurally fragile: every future auth field breaks the same way until
someone remembers to add it
Fix: remove the whitelist and the team-scope short-circuit. The DB-load
resolver now expands os.environ/ on every string field, matching the YAML
path. Trust boundary stays on the write side: only PROXY_ADMIN can create
team_id=None rows, only team admins of a team can create rows scoped to
that team, and the request-body vector is still blocked by
_BANNED_REQUEST_BODY_PARAMS. Team-scoped rows now resolve env refs — this
is a deliberate LIT-3831 threat-model expansion trusting team admins for
env-var reads
Regression tests in tests/test_litellm/proxy/proxy_server/test_proxy_config.py:
- test_ProxyConfig__add_deployment_resolves_env_refs_after_db_decrypt pins
admin-scoped rows resolve every field (previously api_base stayed literal)
- test_ProxyConfig__add_deployment_resolves_team_env_refs pins team rows
resolve env refs (previously stayed literal)
- test_ProxyConfig__add_deployment_resolves_env_refs_on_arbitrary_field pins
the no-whitelist invariant against a made-up field name
- test_ProxyConfig__add_deployment_resolves_env_refs_for_aws_bedrock_auth_params
(from #32256) still passes
- Path B counterparts (decrypt_model_list_from_db) mirror the above
Left as followups (not fixed here):
- /model/info and /v2/model/info still echo resolved values for fields not
in the current pop-list (aws_role_name, aws_sts_endpoint, api_base, etc.).
Fix is to extend remove_sensitive_info_from_deployment; separate PR
- Master-key rotation reads DB rows via decrypt_model_list_from_db which
now resolves universally, so rotation collapses env-refs into hardcoded
values. Pre-existing bug for the 6 previously-whitelisted fields; wider
surface after this PR. Separate PR
(cherry picked from commit 5862be3e79)
* fix(anthropic): require caller api_key and SSRF-validate api_base in advisor tool
The advisor_20260301 interceptor honored a caller-supplied api_base once
allow_client_side_credentials was enabled, even without a caller-supplied
api_key. AnthropicModelInfo.get_auth_header() then fell back to the proxy's
own ANTHROPIC_API_KEY/ANTHROPIC_AUTH_TOKEN, so the server's real credentials
plus the conversation history got sent to a caller-chosen destination
_resolve_advisor_credentials() now only honors api_base alongside a
non-empty caller-supplied api_key, requires the https scheme, and validates
api_base via validate_url() before use, mirroring check_complete_credentials
in auth_utils.py. https is required because validate_url only DNS-pins the
connection for http; for https with TLS verification on it returns the URL
unchanged and relies on certificate validation to block DNS rebinding
* fix(anthropic): also reject advisor api_base when ssl_verify is disabled
validate_url only DNS-pins the connection for http, or for https with
litellm.ssl_verify disabled; the previous https-only check missed the
ssl_verify=False case, where validate_url's rewritten URL was still being
discarded, per Greptile's review of this PR. Reject api_base outright when
ssl_verify is False so the discarded rewrite can no longer matter
(cherry picked from commit 07b9ea8c3b)
The security fix in 34e9be1ba7 removed turn_off_message_logging from
_supported_callback_params to stop callers bypassing global redaction via
the request body. That also killed the documented admin-only per-key or
per-team override because both flows resolve through the same allowlist
in initialize_standard_callback_dynamic_params.
Put turn_off_message_logging back in _supported_callback_params so an
admin-configured metadata.logging[].callback_vars.turn_off_message_logging
survives into StandardCallbackDynamicParams and can override the global
setting for that key or team, as documented at
docs/proxy/team_logging#disableenable-message-redaction.
Consolidate the metadata traversal so the extractor and the proxy strip
walk the same set of client-controllable slots. iter_client_callback_metadata_dicts
in litellm_core_utils/initialize_dynamic_callback_params.py is the single
source of truth for metadata, litellm_metadata, and litellm_params.metadata;
_strip_client_message_redaction_opt_out imports it so a future addition
to one side automatically reaches the other. The extractor iterates the
helper in reversed order so litellm_params.metadata keeps overriding
metadata, matching the pre-refactor merge precedence.
Client bypass stays blocked. Restoring the field re-enrolls it in the
auth layer's _BANNED_REQUEST_BODY_PARAMS (derived from
_supported_callback_params via _build_banned_observability_params), so
client submissions at the top level, inside metadata, or inside a
JSON-string litellm_metadata all 401 at ingress. is_request_body_safe
also now descends into litellm_params.metadata for the same 401 defense
against the nested-body attack vector, matching how the metadata and
litellm_metadata slots are handled. _strip_client_message_redaction_opt_out
runs after the litellm_metadata JSON parse and before the admin callback_vars
unpack, so admin values survive while any leftover client-supplied
opt-out is dropped when global redaction is on and the key or team
lacks allow_client_message_redaction_opt_out.
Flip the two dynamic-param e2e tests added by the security fix to
reflect the restored override behavior, keeping the invariant that
proxy client bypass is stopped by the auth layer 401 above.
Co-authored-by: yucheng <yucheng@yuchengs-MBP.attlocal.net>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
(cherry picked from commit 8e6098adc3)
AWS auth parameters in the Bedrock and SageMaker path could be expanded against
the process environment when credentials were built. Config-sourced references
are already expanded at load time, so restrict expansion to that path: a
reference still present at request time is treated as caller-supplied input and
is left as-is, and the web-identity helper rejects environment-variable
references before resolving the token.
Also rework the ambient AWS_* fallback as a single pass that pairs each value
with its own env-var name, fixing a latent index misalignment that left
AWS_EXTERNAL_ID unresolved.
Adds regression tests covering the resolution behavior.
(cherry picked from commit 4ef7d0815b)
* fix: validate proxy request body and nested fields
Ensure caller-supplied request fields cannot override server-side deployment
configuration, and apply request-body validation consistently to nested
structures. Adjusts router kwarg handling and client-side credential handling
for base-url overrides
* test: cover router strip ordering and advisor clientside credential gate
* fix: clear deployment credentials on client base-url override
When a request overrides api_base/base_url, recompute the deployment's
litellm_params (clearing the deployment's own api_key) and drop the cached
client built for the original endpoint, so the deployment credential is not
reused for the client-supplied endpoint. Adds regression tests that assert the
credentials actually forwarded to litellm.completion/acompletion.
* fix(proxy): require api_key alongside api_base override
A request that overrides api_base/base_url but supplies no api_key still
left the proxy carrying a server credential: once the override clears the
banned-param opt-in, the provider re-resolves a key from the environment
(api_key or get_secret("OPENAI_API_KEY") and ~30 sibling chains in
main.py) and forwards it to the caller-controlled URL. Popping the
deployment api_key only changed which server key leaked.
Gate is_request_body_safe so a permitted api_base/base_url override must
also carry a non-empty caller api_key; reject otherwise. The env
resolution in main.py is left as the provider boundary.
* fix(proxy): extend request-body banlist with five additional credential and session targeting fields
Yuneng's review found five deployment-owned request-body params still missing
from the denylist and the router strip set. Each lets a caller reach the
operator's provider credentials or retarget the outbound request:
aws_profile_name selects a local AWS profile, oci_compartment_id and oci_region
retarget the OCI request, litellm_credential_name selects any server-loaded
credential by name with no ownership check, and runtimeSessionId resumes a
Bedrock AgentCore runtime session (AWS does not enforce session-to-user
mapping, so this is a cross-tenant session-resume vector).
Add all five to _BANNED_REQUEST_BODY_PARAMS in auth_utils.py and to
_DEPLOYMENT_OWNED_CREDENTIAL_KWARGS in router.py. Deployment litellm_params and
SDK direct calls are unaffected: the banlist gates the request body only, and
the router strip drops caller kwargs, never deployment["litellm_params"].
* test: rename arbitrary canary values in security tests to neutral placeholders
* fix(proxy): apply api_key co-presence to nested base override and warn on Router credential strip
P1-A: is_request_body_safe descended into _NESTED_CONFIG_KEYS
(litellm_embedding_config, extra_body) for the banned-param check but not for
the api_key co-presence check, so a base override smuggled into one of those
nested dicts cleared the client-side-credentials opt-in without a paired
api_key and let the provider re-resolve a server credential from the
environment. Run _check_base_override_has_api_key on each nested config dict
too, so the requirement applies wherever a base override is permitted.
P1-B: the deployment-owned credential strip in the Router runs unconditionally
on every _completion/_acompletion, which is security-correct but silently
drops per-call api_version/vertex_project/etc. for SDK Router callers. Emit a
single warning (key names only, never values) when the strip removes a
non-empty value, so the backwards-incompatible behavior is visible without
gating the strip on a context flag that does not exist.
* fix(proxy): apply api_key co-presence to tool-entry base override
is_request_body_safe scans three surfaces (root, _NESTED_CONFIG_KEYS, and
tools[]); the previous commit extended the api_key co-presence rule to root
and nested config dicts but not to tool entries. With
allow_client_side_credentials enabled, a tool entry carrying api_base/base_url
and no paired api_key cleared the gate, letting a provider interceptor fall
back to a server-side credential for a caller-controlled URL. Add the same
_check_base_override_has_api_key call to each tool dict and its nested function
dict, mirroring the symmetry already applied to the nested config keys. The
rule is unchanged: api_key must live in the same dict as the base override it
accompanies.
* test(proxy/auth): require paired api_key under extra_body opt-in
* fix(router): gate deployment-owned kwarg strip on litellm.proxy_is_running
* fix(advisor): narrow proxy-import guard to ImportError-family
* fix(router): gate api_key clear on base override behind litellm.proxy_is_running
* test(proxy/auth): scope proxy_is_running flag to dynamic-params class with autouse fixture
* style: use built-in generics in PR-added type annotations
* revert: drop proxy_is_running flag and router-level credential strip; rely on proxy gate
* revert: scope PR to LIT-3828 + LIT-3834 only; drop LIT-3830/LIT-3833 changes
* style: black-format advisor orchestration test
(cherry picked from commit 1667b8f740)
The MCP client logged the full tool arguments (and prompt arguments) at INFO on every call, so caller input such as user queries, model names, and instructions landed in the proxy application logs and any downstream log aggregator
Log only the tool or prompt name and drop the arguments from these INFO lines
(cherry picked from commit 7acc0157df)
* fix(vertex_ai/files): upload batch files in a single media request to fix 499s on large uploads
PR #31036 switched the vertex batch file upload from a single GCS media
upload to a chunked resumable session. The resumable path sends the body as
many sequential PUTs, each waiting a full round-trip to GCS before the next,
so a multi-GB upload accumulates hundreds of round-trips and overruns the
client/load-balancer request timeout, surfacing as 499s (client closed
connection) on files as small as 500MB. This was a regression from the
last-known-good commit, where the upload completed as one continuous request.
Revert the batch upload to a single uploadType=media request, but stage the
transformed payload to a temp file first so peak memory stays bounded (the
goal of the resumable rewrite) without the per-chunk round-trips. The temp
file is closed deterministically (TemporaryFile unlinks on close), not left
to the GC. The now-unused resumable chunked-upload plumbing is removed.
Also swap the per-row transform's stdlib json for orjson (parse + serialize),
which is ~4x faster on this hot path; the streaming body now emits compact
orjson bytes.
The request stays synchronous, so the returned file object is real and
POST /v1/batches keeps working immediately against the uploaded object.
Tests: single media request carries the whole payload with a real
Content-Length (no chunked transfer-encoding); failed upload raises; the
staged temp file is closed deterministically; byte-for-byte transform parity.
* test(vertex_ai/files): mock single media upload POST instead of removed resumable method
test_avertex_batch_prediction patched BaseLLMHTTPHandler._aresumable_chunked_upload, which was removed when the batch jsonl upload moved from a chunked resumable GCS session to a single uploadType=media request. Patch the raw httpx.AsyncClient.post that _astage_and_upload_media issues so the real staging, upload and response transform run while the GCS object response is mocked, and assert the media URL and Content-Type.
* fix(vertex_ai/files): forward request timeout to media upload, drop orjson, sort imports
Forward the per-request timeout through _stage_and_upload_media /
_astage_and_upload_media to the GCS POST. Every other upload branch forwards
it; the new media path was dropping it, so a caller-provided timeout was
silently ignored (the files path passes 600s by default, but a custom
request_timeout would not have reached this upload). Regression test asserts
the resolved timeout reaches the request (mutation-verified).
Revert the orjson swap in the batch transform: importing orjson at module load
in this core-path file broke `import litellm` on environments without orjson
(the Windows import test). Back to stdlib json; the upload leg dominates large
uploads anyway, so the transform-side win was marginal.
Fix import ordering in llm_http_handler.py (I001) introduced by the new imports.
* fix(vertex_ai/files): stream batch upload to GCS instead of staging to a temp file
Addresses a disk-exhaustion concern: staging the full transformed batch body to
a local temp file before the GCS request meant an authenticated user could fill
the proxy's temp volume with large concurrent uploads (on top of Starlette's
input spool).
GCS's simple/media upload accepts chunked transfer-encoding, so stream the
transform straight to the single media request instead. Each block is produced
on a worker thread (the transform never runs on the event loop) and sent
chunked, so the body is neither buffered in memory nor written to disk, and the
upload is still one continuous request (no per-chunk round-trips, no 499). Drops
the temp-file staging, the tempfile/IO imports, and Content-Length computation.
Regression test asserts the upload streams (chunked transfer-encoding, no
Content-Length) and creates no temp file; mutation-verified that reintroducing
staging fails it.
(cherry picked from commit 85840aef51)
* fix(proxy/client): redact api key from key/info client error messages
The keys management client builds GET /key/info?key=<key> and lets the
requests HTTPError propagate. str(HTTPError) renders the failing request URL
verbatim ("... for url: .../key/info?key=sk-..."), so any caller that logs the
exception leaks the full key; the 401 branch leaked the same way through
UnauthorizedError(str(orig_exception))
Redact both branches with the existing redact_secrets helper so the
secret-bearing query param is scrubbed to ?REDACTED while the status code,
reason, and response object are preserved. Server-side responses already mask
the key, so this closes the remaining client-side surface
* fix: preserve key info unauthorized response
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
(cherry picked from commit 71ee1a852a)
The #31122 cherry-pick bumps the deps it pins (cryptography 48.0.1, aiohttp 3.14.1,
vcrpy 8.2.1, the langchain/langgraph stack) and relocks, but this line's lock baseline
kept several ranged runtime deps at versions the ranges still allow, so osv-scanner still
flagged them. Pull them to their fixed releases so the scan is clean:
- starlette 1.1.0 -> 1.3.1 (GHSA-82w8-qh3p-5jfq, GHSA-jp82-jpqv-5vv3)
- python-multipart 0.0.27 -> 0.0.32 (GHSA-5rvq-cxj2-64vf and three others)
- pydantic-settings 2.14.1 -> 2.14.2 (GHSA-4xgf-cpjx-pc3j)
- pypdf 6.13.2 -> 6.13.3 (GHSA-jm82-fx9c-mx94)
- pyjwt 2.12.0 -> 2.13.0 (PYSEC-2026-175/177/178/179)
- langsmith 0.8.3 -> 0.8.18 (GHSA-f4xh-w4cj-qxq8)
Dashboard build deps (not in the shipped bundle; lockfile hygiene, no UI rebuild):
- vite 7.3.2 -> 7.3.5 (GHSA-fx2h-pf6j-xcff, GHSA-v6wh-96g9-6wx3)
- esbuild override 0.28.1 (GHSA-g7r4-m6w7-qqqr)
- form-data override 4.0.6 (GHSA-hmw2-7cc7-3qxx)
After this the only osv-scanner finding is diskcache GHSA-w8v5-vhqr-4h9v, which has no
fixed release and is the entry staging's osv-scanner.toml already ignores until a fix lands.
Bumps the 12 packages osv-scanner flags on litellm_internal_staging, taking
the scan from 24 known vulnerabilities to zero. vcrpy goes to 8.2.1 first so
aiohttp can move to 3.14.1 (vcrpy <= 8.1.1 cannot import aiohttp 3.14), then
the two aiohttp ignore entries are dropped from osv-scanner.toml. The
langchain stack moves together since langchain 1.3.9 requires langgraph 1.2.x.
Runtime deps cryptography (48.0.1), starlette (1.3.1), python-multipart
(0.0.32), pydantic-settings (2.14.2) and pypdf (6.13.3) are bumped via relock,
and the dashboard's js-yaml, ws and form-data overrides are bumped too.
Also removes the paths filter on the OSV workflow so it runs on every PR
rather than only when a lockfile changes, which is why it never showed up on
recent code-only PRs
(cherry picked from commit a8a1472428)
* fix(vertex/files): stream OpenAI->Vertex batch JSONL uploads to fix OOM on large files
Large (1GB+) batch JSONL uploads to Vertex AI / GCS caused OOM or killed the worker
because the request body was buffered and multiplied 2-3x in size. The create-file
path is now streaming end-to-end: transform_create_file_request returns a
ResumableChunkedUploadConfig carrying a lazy _OpenAIToVertexBatchUploadStream, and the
HTTP handler opens a GCS resumable session and PUTs the body in bounded 8 MiB chunks
(Content-Range, 308 between chunks) so the transformed payload is never held in full.
The proxy /v1/files endpoint streams from Starlette's spooled upload handle instead of
reading the whole body, and batch rate limiting counts tokens and models in a single
streaming pass.
Only gcs_bucket_name is supported for the GCS target; the legacy bucket_name key is
intentionally not read.
Also removes the unreachable VertexAIFilesHandler create path and everything only it
kept alive (VertexAIJsonlFilesTransformation, _stream_openai_jsonl_to_vertex, the legacy
transform helpers), plus the orphaned batch_utils helpers the streaming rewrite replaced.
* fix(batches): return original JSONL on unparseable row to avoid silent batch truncation
The streaming rewrite of replace_model_in_jsonl accumulated physical lines and
skipped a row on JSONDecodeError to support multi-line objects, but a genuinely
malformed or truncated row never completes: it poisons the buffer, swallows every
following row, and the function still returned the partial rewrite (the rows before
the bad one, already model-rewritten) as if the batch were complete. That turned the
pre-rewrite behavior of returning the original file unchanged (so the provider rejects
the bad batch loudly) into a silent partial submission.
Restore the original-content fallback: when an unparseable remainder is left after the
loop, return the original file_content (rewinding a consumed seekable source) instead of
the truncated output. The multi-line happy path is unchanged.
* test(batches): mock resumable GCS upload in vertex batch prediction test
The vertex batch file-create path now streams to a GCS resumable session via
_aresumable_chunked_upload (httpx send) instead of AsyncHTTPHandler.post, so the
existing test's post mock no longer intercepted the upload and a real request hit
GCS (401). Mock _aresumable_chunked_upload to return the GCS object response; the
resumable protocol itself is covered in test_vertex_ai_files_streaming.py.
* fix(batches): resilient per-row token accounting; no hard-block on count failure
The batch input-file pass iterated a generator whose json.loads raised on a
malformed line; the outer except caught it and stopped the loop, so any body.model
on rows after a bad line was never collected and the model allowlist check ran
against a partial set. It also hard-blocked the batch with a 400 whenever token
counting raised, a backwards-incompatible change from the prior swallow-and-proceed
behavior that breaks legitimate rows the token counter cannot measure (e.g. some
multimodal content).
Iterate the JSONL line-by-line and account each row independently. A malformed line
is skipped (its request cannot run upstream anyway) and a row the counter cannot
measure falls back to a conservative size-based estimate. The loop never aborts, so
the allowlist check always sees every parseable model, and the token total is never
zeroed, so a crafted uncountable row still cannot evade the TPM limit, without
hard-rejecting a legitimate batch.
* perf(vertex/files): unblock async upload; drop empty finalize; widen batch MIME types
Three review follow-ups on the resumable batch upload:
- _aresumable_chunked_upload pulled chunks from a synchronous generator that runs
the per-row transform inline on the event loop thread, blocking other requests
between PUTs on large uploads. Each chunk is now produced via asyncio.to_thread.
- _iter_resumable_chunks no longer yields a trailing empty chunk, so an exactly
chunk-aligned upload finalizes on its last data chunk instead of an extra
zero-byte PUT; a 0-byte stream still finalizes via the caller's empty request.
- valid_content_type now accepts the MIME types clients label .jsonl batch uploads
with (text/plain, application/json, ndjson, ...), so such a batch file no longer
silently bypasses the streaming path into the buffered media upload.
* fix(vertex/files): keep legacy bucket_name as GCS bucket fallback
The rename to gcs_bucket_name dropped the legacy bucket_name key entirely, so an SDK caller passing bucket_name to a Vertex AI file create/retrieve/content call with GCS_BUCKET_NAME unset got ValueError("GCS bucket_name is required") where it previously resolved the bucket. _get_configured_bucket_name now reads gcs_bucket_name, then bucket_name, then the env var, and bucket_name is restored to OPTIONAL_KWARGS_KEYS so it survives get_litellm_params on the retrieve and content paths. gcs_bucket_name keeps precedence when both are present
* style: sort imports in llm_http_handler to satisfy I001 budget
---------
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
(cherry picked from commit 56825926af)
Re-pins LITELLM_BUILD_IMAGE and LITELLM_RUNTIME_IMAGE across all 6 Dockerfiles
from the prior digests (openssl 3.6.2-r3) to the current chainguard wolfi-base
digest c61ac691 (openssl 3.6.3-r2, >= the fixed 3.6.3-r0). The runtime stage is
the shipped image, so the runtime digest is what actually resolves the
customer-facing CVE; the build image is bumped too for hygiene. Two Dockerfiles
tracked a second equally-stale digest; both are unified onto the patched one.
(cherry picked from commit fda08dd727)
Streaming and pass-through requests could be logged with $0 cost or dropped from
SpendLogs entirely while the upstream provider still billed every token. This
closes the leak paths not already covered by #30160, #30787 and #30788.
- Catch a stream_chunk_builder raise in the core CustomStreamWrapper (sync and
async). Large agentic tool-use / thinking streams can make assembly re-raise
as APIError from inside the except-StopIteration handler, where the sibling
except does not catch it, so it escaped __next__/__anext__ and dropped the
request; recover best-effort usage from the raw chunks instead
- Add a usage-only fallback for Anthropic streaming pass-through: when
stream_chunk_builder returns None or raises, rebuild usage from the
message_start / message_delta SSE events via AnthropicConfig.calculate_usage so
cache, web-search and geo tokens are priced instead of left at $0
- Decode buffered pass-through bytes with errors="replace" so a stream cut
mid-multibyte-sequence still logs the usage events already received
- Record response_cost into model_call_details on the pass-through success path
(it is read from there, not from kwargs), matching the gemini/cohere/openai
handlers
- Name the key (alias + masked key) in the virtual-key BudgetExceededError so
operators don't have to reverse-map spend back to a key
(cherry picked from commit b24b964e04)
A streaming request that breaks mid-flight, for example on a mid-stream read
timeout, still bills the provider for the chunks already delivered, yet the proxy
recorded that interrupted request as a zero-spend failure. An earlier revision
logged the recovered partial usage through the success path, which mislabeled a
failed request as a success and produced a misleading spend row
This recovers the partial usage where the failure is actually logged. The
streaming handler assembles the usage from the chunks seen so far and stashes it,
with its cost, on the logging object before firing the failure handlers. The
proxy failure hook lifts that usage and cost onto request_data before the
non-serialisable logging object is popped, and the spend-log writer records the
real partial spend on the failure row instead of a hardcoded zero;
get_logging_payload honors the recovered usage for the token columns and
_failure_handler_helper_fn preserves the recovered cost so the non-DB failure
loggers stay consistent
A request that recovers via a successful fallback is unaffected: the failure hook
only fires when the whole request fails, so the fallback's combined-usage success
row stays the single source of truth and there is no double counting
Resolves LIT-3825
Co-authored-by: veria-ai[bot] <224490171+veria-ai[bot]@users.noreply.github.com>
(cherry picked from commit 4847fa5dd5)
