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yuneng-jiang 6ff668c7aa [Infra] Promote internal staging to main (#27245) 
* default requested_model to empty string on litellm-side rejects

* Update litellm/router.py

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* fix: scope key access_group_ids override by team's assigned groups

A team member could set any access_group_ids on their key (e.g. a group
assigned only to a different team) and override the team's model
restriction. Intersect the key's access_group_ids with team_object.access_group_ids
in _key_access_group_grants_model so foreign groups are dropped before
model expansion. Adds a regression test that asserts expansion is never
called for foreign groups.

* [Fix] Proxy: Skip Personal Budget Hook When Reservation Covers Counter

The reservation path (PR #26845) atomically pre-fills `spend:user:{user_id}`
and admits at the strict-`<` boundary. The legacy `_PROXY_MaxBudgetLimiter`
pre-call hook re-reads the same counter with `>=`, so a reservation that
fills the counter to exactly `max_budget` (e.g. a request without a
`max_tokens` cap that falls back to reserving the smallest remaining
headroom) is rejected by the hook even though the reservation already
admitted it.

Skip the hook when the request's active `budget_reservation` covers
`spend:user:{user_id}`. The reservation is the source of truth for that
counter cross-pod; the legacy `>=` path remains in place for requests
without a reservation (e.g. paths that bypass the reservation entirely).

Reproduces as `tests/otel_tests/test_prometheus.py::test_user_budget_metrics`
on a fresh user with `max_budget=10` calling `fake-openai-endpoint` without
`max_tokens`. Adds focused unit coverage in
`tests/test_litellm/proxy/hooks/test_max_budget_limiter.py`.

* harden bedrock file bucket validation

* Fix syntax errors from botched merge in router.py

* Fix Vertex batch output edge cases

* [Fix] RBAC: Drop management_routes Write Fallback for Admin Viewer

Greptile P1: the unsafe-method branch of `_check_proxy_admin_viewer_access`
ended with a blanket `if route in management_routes: return`. That set is a
mix of reads (info/list — handled via the safe-method GET branch above) and
writes. The fallback let Admin Viewer POST to write endpoints not enumerated
in `_ADMIN_VIEWER_BLOCKED_WRITE_ROUTES`, including:
  - /team/block, /team/unblock, /team/permissions_update
  - /jwt/key/mapping/{new,update,delete}
  - /key/bulk_update
  - /key/{key_id}/reset_spend

Remove the fallback. The two remaining allow sets (admin_viewer_routes and
global_spend_tracking_routes) are both read-only, so removal does not affect
the legitimate POST-as-read cases (e.g. /spend/calculate, which is in
spend_tracking_routes ⊂ admin_viewer_routes).

Tests:
  - 8 new parametrized cases pinning each previously-leaking management write
    endpoint to 403 on POST for PROXY_ADMIN_VIEW_ONLY.

* fix(tests): anchor VCR redis cassette key to repo root

`os.path.relpath` with no `start` arg uses the current working
directory, so running pytest from a subdirectory produced a
different Redis key than running from the repo root. CI-recorded
cassettes and locally-replayed runs would silently miss each
other's cache.

Anchor the path to the repo root (derived from `__file__`) so the
key is stable regardless of CWD.

https://claude.ai/code/session_018uCx7pcrkdUJZrCVMaTdPx

* fix: gate key access_group override on group's own assignment

Replaces the previous intersect-with-team.access_group_ids check, which
made the override unreachable in practice (the team-gate fallback already
covered every case the intersection allowed). The override now resolves
each of the key's access_group_ids via get_access_object and accepts the
group only if its assigned_team_ids includes the key's team_id, or its
assigned_key_ids includes the key's token. This fulfills the original ask
(a key can extend a team's allow-list via a group the admin granted to
that team or that specific key) while still rejecting foreign groups
referenced by team members of other teams.

* [Fix] Proxy/Key Management: Honor team_member_permissions /key/list In /key/list Endpoint

When a team grants /key/list via team_member_permissions, non-admin members
should see all keys for that team — same as a team admin. Previously the
classification in list_keys() only checked admin status, so permitted
members fell into the service-account-only path and could not see other
members' personal keys. Routes those members into the full-visibility set.

* Fix access-group bypass via litellm-model fallback path

When _get_all_deployments returns 0 candidates and the litellm-model
fallback branch (_get_deployment_by_litellm_model) finds deployments that
the access-group filter then empties, _access_group_filter_emptied_candidates
remained False (it was captured before that branch ran). The router would
then proceed to default fallbacks; the fallback model could have no
access_groups and short-circuit the filter, silently serving a caller
blocked by access-group restrictions.

Update the flag inside the litellm-model branch when filtering empties a
non-empty candidate set so the default-fallback guard still triggers.

* fix(proxy): redact MCP server URL and headers for non-admin viewers (VERIA-8)

Many MCP integrations (Zapier, etc.) embed an upstream API key
directly in the server URL, e.g.
``https://actions.zapier.com/mcp/<api-key>/sse``. The list and
single-server endpoints were returning the full URL to any
authenticated user — `_redact_mcp_credentials` only stripped the
explicit ``credentials`` field, and `_sanitize_mcp_server_for_virtual_key`
only ran for restricted virtual keys. Non-admin internal users could
read the dashboard, click the unmask toggle, and exfiltrate the raw
token.

Add `_sanitize_mcp_server_for_non_admin` that runs on top of the
existing credential redaction and clears the credential-bearing
fields:

- ``url`` (the primary leak vector)
- ``spec_path`` (OpenAPI spec URLs that may carry tokens)
- ``static_headers`` / ``extra_headers`` (Authorization)
- ``env`` (arbitrary secrets)
- ``authorization_url`` / ``token_url`` / ``registration_url``

Identity fields (``server_id``, ``alias``, ``mcp_info``, etc.) are
preserved so the UI can still list servers a non-admin's team has
access to.

Apply the new sanitizer in `fetch_all_mcp_servers` and the per-server
fetch path right after the existing virtual-key branch. Update the
existing `test_list_mcp_servers_non_admin_user_filtered` assertions
that previously checked URL visibility.

Frontend defense-in-depth: hide the URL unmask toggle on
`mcp_server_view.tsx` unless the viewer is a proxy admin.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* Fix runtime policy attachment initialization

Mark runtime-created policies and attachments initialized so global policy attachments created from the policy builder apply immediately without requiring a restart.

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(router): cover _try_early_resolve_deployments_for_model_not_in_names

The router_code_coverage CI check requires every function in router.py to
be referenced by at least one test under tests/{local_testing,
router_unit_tests,test_litellm} in a file with "router" in its name.
The recently-extracted helper had no direct test, so the check failed
with "0.45% of functions in router.py are not tested".

Add a focused test that exercises the four return paths: model already
in self.model_names, no fallback applies, pattern-router match, and
default_deployment substitution (also asserting the stored default
isn't mutated).

https://claude.ai/code/session_019AVp1XL7RT9RxRe4qRLkay

* Fix policy registry teardown in tests

Reset the policy ID index during policy engine test cleanup so stale policy versions cannot leak between tests.

Co-authored-by: Cursor <cursoragent@cursor.com>

* fix(batches): count non-chat tokens, validate batch-file model access (VERIA-39) (#27015)

* fix(batches): count non-chat tokens and validate every model in batch file

Two security control bypasses on POST /v1/batches:

1. `_get_batch_job_input_file_usage` only summed tokens for
   `body.messages` (chat completions). Embedding (`input`) and text
   completion (`prompt`) batches reported zero, letting massive
   non-chat workloads slip past TPM rate limits. Extend the counter
   to handle string and list shapes for both fields.

2. The batch input file was forwarded to the upstream provider
   without inspecting the models named inside the JSONL — only the
   outer `model` query parameter was checked against the caller's
   allowlist. A caller restricted to gpt-3.5 could submit a batch
   targeting gpt-4o and the upstream would execute it under the
   proxy's shared API key.

Add `_get_models_from_batch_input_file_content` (returns the
distinct `body.model` values) and call it from
`_enforce_batch_file_model_access` in the pre-call hook, which runs
each model through `can_key_call_model` so the same allowlist
semantics (wildcards, access groups, all-proxy-models, team aliases)
the proxy enforces on `/chat/completions` apply here too. Any
unauthorized model raises a 403 before the file is forwarded.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(batches): count pre-tokenized prompt/input shapes, classify 403 logs

Two follow-ups from the Greptile review on the batch validation PR:

1. P1 TPM bypass via integer token arrays. The OpenAI batch schema
   accepts ``prompt`` and ``input`` as ``list[int]`` (a single
   pre-tokenized prompt) or ``list[list[int]]`` (multiple) in addition
   to the string and ``list[str]`` shapes. Pre-fix only the string
   shapes were counted, so a caller could submit a batch with hundreds
   of millions of pre-tokenized tokens and the rate limiter would
   record zero. Extract the per-field logic into
   ``_count_prompt_or_input_tokens`` and count each int as one token.

2. P2 access-denial logs were indistinguishable from I/O failures.
   ``count_input_file_usage`` caught every exception under a generic
   "Error counting input file usage" message, so an intentional 403
   from ``_enforce_batch_file_model_access`` looked the same in the
   logs as a missing file or a Prisma timeout. Catch ``HTTPException``
   separately and log 403s at WARNING level with a security-relevant
   message before re-raising.

Tests cover the new shapes: single ``list[int]``, ``list[list[int]]``
(the worst-case bypass vector), and embeddings ``input`` with
pre-tokenized arrays.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(proxy): re-validate user_id after /user/info re-parses query (#27009)

* fix(proxy): re-validate user_id ownership after /user/info re-parses query

The route-level access check in `RouteChecks.non_proxy_admin_allowed_routes_check`
reads `request.query_params.get("user_id")`, which decodes literal `+` to
spaces. The endpoint then re-parses the raw query string with `urllib.unquote`
in `get_user_id_from_request` to preserve `+` characters (so plus-addressed
emails work as user_ids). Those two paths produce different ids: a caller
who registered a user_id containing a literal space could pass the route
check and then read another user's row by sending the encoded `+` form.

Add `_enforce_user_info_access` and call it after `_normalize_user_info_user_id`
returns the final id. Proxy admin / view-only admin still bypass; everyone
else must match the resolved user_id (or have no user_id, which falls back
to the caller's own id later in the handler).

Tests cover the admin bypass, owner-match path, and the cross-user lookup
that this change blocks.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(proxy): apply user_info ownership check to PROXY_ADMIN_VIEW_ONLY

`_enforce_user_info_access` was bypassing both PROXY_ADMIN and
PROXY_ADMIN_VIEW_ONLY, but the upstream route check in
`RouteChecks.non_proxy_admin_allowed_routes_check` only treats
PROXY_ADMIN as a true admin for the `/user/info` route — view-only
admins go through the `user_id == valid_token.user_id` enforcement
along with regular users. Mirroring that asymmetry left the same
encoded-`+` bypass open for view-only admins whose user_id contains a
literal space.

Drop the PROXY_ADMIN_VIEW_ONLY exemption so the post-decode re-check
matches the upstream rule. Update tests: a view-only admin must now
be blocked from cross-user lookups but still allowed to read their
own row.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat(spend-logs): opt-in suppression of stack traces in spend-tracking error logs

Adds LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS env var. When set to true and the
proxy log level is INFO or above, spend-tracking error paths emit a single
ERROR line without the full traceback. Stack traces are preserved at DEBUG
and the Sentry / proxy_logging_obj.failure_handler path is unchanged.

The new spend_log_error helper is wired through the spend write hot path:
  - DBSpendUpdateWriter (update_database, _update_*_db, batch upsert,
    redis-commit fallbacks)
  - _ProxyDBLogger._PROXY_track_cost_callback
  - get_logging_payload exception path
  - update_spend / update_daily_tag_spend / spend logs queue monitor

Resolves LIT-2704.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend

This call site previously logged a single-line error via verbose_proxy_logger.error()
with no traceback. Switching it to spend_log_error(..., exc=e) caused a full stack
trace to render by default (when LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS is unset),
which contradicts the PR goal of leaving default behavior unchanged. Revert this
specific site to the original error log call.

* fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend

Bugbot caught a regression: the previous error log here was a single-line
verbose_proxy_logger.error(...) with no traceback. spend_log_error attaches
the active exception's traceback by default (when the suppression env var
is unset), so swapping it in changed default behavior. Revert this one site
to its original .error() call to keep the PR strictly opt-in.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* feat(spend-logs): suppress traceback in SpendLogs error_information row

Extend LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS to the failure callback so the
per-row Metadata pane in the UI no longer shows the stack trace when the
opt-in env var is set, matching the existing console-side suppression.

https://claude.ai/code/session_014dztoRbRnRvq54HL9EyHx6

* [Fix] Proxy: Repair Merge Fallout In Router-Override Fallback Auth

Conflict resolution for #26968 dropped the `Iterator` typing import
(NameError at module load), left a dead `fallback_models = cast(...)`
block, and the new tests called `_enforce_key_and_fallback_model_access`
without the now-required `request` kwarg.

* isolate dual OTEL handlers

* harden cloud file compatibility path

* harden cloud file compatibility path

* [Fix] Proxy/Key Management: Align Key-Org Membership Checks On Generate And Regenerate

Mirrors the membership rule on /key/update so that /key/generate and
/key/{key}/regenerate apply the same `_validate_caller_can_assign_key_org`
gate when the caller specifies an `organization_id`. Proxy admins bypass.
The check no-ops when `organization_id` is not being set.

* thread trusted params through vertex file content

* trust only server legacy file flag

* chore(proxy): keep public AI hub unauthenticated

* fix(proxy): preserve low-detail readiness status

* [Test] Anthropic: Replace Legacy Claude-4-Sonnet Alias With Haiku 4.5

Three live-API tests pinned to claude-4-sonnet-20250514, which is a
non-canonical alias of claude-sonnet-4-20250514. Anthropic's main API
no longer resolves the legacy form under freshly issued keys, so the
tests fail with not_found_error. The token counter test pinned to
claude-sonnet-4-20250514 itself (deprecation_date 2026-05-14, two weeks
out) was on borrowed time too.

Bump all four to claude-haiku-4-5-20251001 — capability superset for what
these tests exercise (streaming, parallel tool calling, extended thinking,
token counting), no upcoming deprecation, cheaper per-token.

* chore(proxy): move URL-valued model/file_id guard from SDK to proxy

The previous per-provider guards in HuggingFace, Oobabooga, and Gemini
files lived in the SDK layer, breaking SDK callers who legitimately pass
URL-valued model identifiers. Move the check to the proxy boundary in
add_litellm_data_to_request so SDK users keep working while proxy users
default-deny URL-valued model and file_id, with admin opt-in via
litellm.provider_url_destination_allowed_hosts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* [Chore] Proxy/UI: Drop stray _experimental/out/chat/index.html

This file is a regenerable UI build artifact that should not be tracked
in source. Removing so the merge into litellm_internal_staging stays clean.

* [Test] Anthropic Passthrough: Bump Streaming Cost-Injection Test To Haiku 4.5

test_anthropic_messages_streaming_cost_injection hits the proxy's
/v1/messages route, which routes via the anthropic/* wildcard to
api.anthropic.com. The 404 surfaced in the test was Anthropic's own
not_found_error propagated back through the proxy (visible from the
x-litellm-model-id hash on the response — the proxy did route).

Same root cause as the prior commit: the legacy claude-4-sonnet-20250514
alias is no longer recognized by Anthropic's main API under the new key.
Swap to claude-haiku-4-5-20251001 — same routing path, canonical model.

* fix(proxy): handle ownership-recording failures after upstream create

If record_container_owner raises after the upstream container is created,
the user previously got a 500 with no usable container — they were billed
for an unreachable resource. Move ownership recording into the create
path's exception handling and split the two failure modes:

- HTTPException from the recorder (auth conflicts) propagates verbatim
  so the client sees the real status code, not a generic LLM error.
- Unexpected exceptions are logged and swallowed; the response is
  returned to the caller so they aren't billed for a container they
  can't address. The DB row stays untracked until an operator reconciles.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(guardrails): close post-call coverage gaps

* fix(types): add /team/permissions_bulk_update to management_routes

The blocklist check in _check_proxy_admin_viewer_access only fires for
routes that match LiteLLMRoutes.management_routes — the bulk-update
endpoint was missing from that list, so the test for view-only admins
on /team/permissions_bulk_update fell through to "allow."

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* [Test] Anthropic Passthrough: Bump Thinking Tests Off Legacy Sonnet 4 Alias

base_anthropic_messages_test.test_anthropic_messages_with_thinking and
test_anthropic_streaming_with_thinking still pinned to
claude-4-sonnet-20250514 — the same legacy alias Anthropic no longer
recognizes under freshly issued keys. The other four tests in this base
class already use claude-sonnet-4-5-20250929; these two were missed.

Bump to claude-haiku-4-5-20251001 (supports_reasoning=true, no upcoming
deprecation). Subclasses including TestAnthropicPassthroughBasic
inherit these methods.

* fix(guardrails): cover multi-choice output variants

* fix(proxy): preserve public ai hub ui setting

* fix(scim): cascade FK cleanup on user delete and surface block status in UI

SCIM DELETE /Users/{id} previously called litellm_usertable.delete without
clearing rows that FK back to the user, so Postgres rejected the delete with
LiteLLM_InvitationLink_user_id_fkey and the SCIM caller saw a 500. Add a
helper to drop invitation_link, organization_membership, and team_membership
rows before the user delete (mirrors /user/delete in internal_user_endpoints).

Also add a Status column to the Virtual Keys and Internal Users tables so
admins can see at a glance which keys are blocked and which users SCIM has
deactivated. SCIM-blocked keys carry a tooltip explaining the origin.

Pin the dashboard's Node version to 20 via .nvmrc to match CI.

* chore: update Next.js build artifacts (2026-05-02 03:21 UTC, node v20.20.2)

* perf(proxy): cache container/skill ownership reads on the hot path

Container ownership and skill rows are looked up on every retrieve /
delete / list / file-content / chat-completion-with-skill call. The new
stores wrapped raw Prisma queries with no cache, putting one DB
round-trip on each request. Add an in-process TTL'd cache mirroring the
_byok_cred_cache pattern in mcp_server/server.py: per-key (value,
monotonic_timestamp), 60s TTL, 10000-entry cap with full-clear on
overflow, invalidated by every write. Negative results (`None`) are
cached too so untracked-resource checks also skip the DB.

Tests cover: cache-after-first-hit, negative caching, write
invalidation, no-caching-on-DB-error, TTL expiry, capacity eviction.
56 tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore: update Next.js build artifacts (2026-05-02 03:39 UTC, node v20.20.2)

* fix: remove traceback key instead of it being ""

* fix: linting error

* fix(scim): preserve scim_active on PUT when client omits the field

A SCIM PUT may legally omit `active` (full-replace with the field
absent). Pydantic fills the SCIMUser.active default of True, so the PUT
handler was overwriting metadata.scim_active with True even when the
client never sent it — silently reactivating a previously SCIM-blocked
user and unblocking their keys.

Use model_fields_set to detect whether the client actually sent
`active`. If omitted, preserve the prior scim_active value and skip
the cascade to virtual keys.

Also drop comments added in this PR that just narrate what the code
does; keep only the docstrings and the SQL-NULL pitfall note that
explain non-obvious behaviour.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(proxy): use set lookup for permitted agent filters

* fix(mcp): redact command fields for non-admin server views

* fix(proxy): forward decoded container ids after ownership checks

* fix(caching): handle stale isolated Redis semantic index

* fix(cloudflare): support response_text in streaming chunk parser

Newer Cloudflare Workers AI models (e.g. Nemotron) emit 'response_text'
instead of 'response' on streamed chunks. The non-streaming path was
already updated to fall back to 'response_text' (#26385), but the
streaming chunk parser still only read 'response', which caused
streaming requests against those models to silently produce empty
content.

Mirror the non-streaming fallback in CloudflareChatResponseIterator.chunk_parser
and add a streaming test for the response_text shape.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* Fix code qa

* Address bugbot: drop dead encode/decode helpers; preserve empty custom_id

- Remove unused _encode_gcp_label_value / _decode_gcp_label_value singular
  helpers; only the _chunks variants are actually called.
- Use 'is not None' check for custom_id so empty-string custom_ids are
  still labeled and round-trip through batch outputs.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* Forward Vertex file content logging context

* test vertex file content logging forwarding

Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>

* Fix Vertex batch output logging mutation

* fix: don't mutate caller's logging_obj in _try_transform_vertex_batch_output_to_openai

The method was overwriting logging_obj.optional_params, logging_obj.model,
and logging_obj.start_time on the caller's Logging instance. When invoked
from llm_http_handler.py's generic framework path, the framework's own
logging_obj (which already went through pre_call) had its properties
clobbered, causing model and start_time to reflect the last batch line's
values rather than the original call context.

Fix: create a fresh local Logging instance for the per-line transformation
instead of mutating the incoming logging_obj. The caller's object is now
left entirely untouched regardless of whether a logging_obj was passed in
or not.

Regression tests added to verify model, start_time, and optional_params
are not mutated on the caller's logging_obj.

Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>

* feat: add opt-out flag for Vertex batch output transformation

Adds litellm.disable_vertex_batch_output_transformation (default False).
When True, afile_content returns raw Vertex predictions.jsonl untouched
so users that parse candidates/modelVersion directly are not broken.

* fix(anthropic,bedrock): omit thinking/output_config when reasoning_effort="none"

Setting reasoning_effort="none" on Anthropic chat models (direct, Bedrock
Invoke, Bedrock Converse, Vertex AI Anthropic, Azure AI Anthropic) crashed
LiteLLM with:

  litellm.APIConnectionError: 'NoneType' object has no attribute 'get'

Both the Anthropic chat transformation and Bedrock Converse called
``AnthropicConfig._map_reasoning_effort`` and assigned the ``None`` it returns
for ``"none"`` directly to ``optional_params["thinking"]``. Downstream
``is_thinking_enabled`` then did ``optional_params["thinking"].get("type")``
and crashed.

Pop ``thinking`` (and on Claude 4.6/4.7, ``output_config``) instead of
assigning ``None``, restoring the documented contract that
``reasoning_effort="none"`` means "do not enable thinking". This also
prevents downstream Anthropic 400s ("thinking: Input should be an object",
"output_config.effort: Input should be ...") if the bug were ever masked.

Verified end-to-end against the live Anthropic API and Bedrock Converse
on claude-opus-4-{5,6,7} and claude-sonnet-4-6, plus Bedrock Invoke for
Claude 4.5/4.6. Vertex AI Anthropic and Azure AI Anthropic inherit the
fixed ``map_openai_params`` from ``AnthropicConfig`` and need no further
changes.

* fix(vertex-ai): set response=null on batch error entries per OpenAI spec

The Vertex batch output transformer was emitting both a populated 'response' and 'error' for failed batch entries. The OpenAI Batch output spec defines them as mutually exclusive: on error 'response' MUST be null. This broke any consumer using 'result["response"] is None' to detect failures.

* test(vertex-ai): cover transformation_error path emits response=null

* fix(security): sandbox jinja2 in gitlab/arize/bitbucket prompt managers

DotpromptManager was hardened to render through
ImmutableSandboxedEnvironment. The three sibling managers (gitlab,
arize, bitbucket) were missed and still instantiate plain
jinja2.Environment(), leaving the same attribute-traversal SSTI
primitive open: a template fetched from a GitLab/BitBucket repo or
Arize Phoenix workspace can reach __class__.__init__.__globals__ and
execute arbitrary Python on the proxy host.

Match the dotprompt pattern by switching all three to
ImmutableSandboxedEnvironment. The sandbox blocks the dunder-traversal
chain while leaving normal {{ var }} substitution intact, so the
template surface is unchanged for legitimate use.

Adds tests/test_litellm/integrations/test_prompt_manager_ssti.py
(18 cases) verifying each manager's jinja_env is a sandbox, that
classic SSTI payloads raise SecurityError, and that ordinary variable
rendering still works.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore(proxy): drop client-supplied pricing fields from request bodies

The proxy currently forwards request-body pricing parameters (the fields
on `CustomPricingLiteLLMParams`, plus `metadata.model_info`) into the
core call path. Those fields belong to deployment configuration, not to
per-request input — sending them from a client mutates the request's
recorded cost and, via `litellm.completion` → `register_model`, the
process-wide `litellm.model_cost` map for every later caller in the
worker. Strip them at the boundary.

The strip set is built from `CustomPricingLiteLLMParams.model_fields` so
pricing fields added later are covered automatically. Operators who do
want clients to supply per-request pricing can opt back in per key or
team via `metadata.allow_client_pricing_override = true`, mirroring the
existing `allow_client_mock_response` and
`allow_client_message_redaction_opt_out` flags.

Tests cover the strip set's coverage, root and metadata strips, the
opt-in skip on both key and team metadata, and a regression check that
the global `litellm.model_cost` map is unmutated after a stripped
request.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore(proxy): log stripped pricing fields at debug for operator visibility

Operators upgrading would otherwise see client-supplied pricing overrides
silently stop applying with no diagnostic. Emit a debug-level line listing
the dropped fields and pointing at the opt-in flag when any are stripped;
stay silent on the no-op path so the log isn't filled with noise.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(proxy): move pricing strip below the litellm_metadata JSON-string parse

The strip ran before the proxy parses ``litellm_metadata`` from a JSON
string into a dict (a path used by multipart/form-data and ``extra_body``
callers), so ``isinstance(metadata, dict)`` was False and ``model_info``
survived the strip. Move the call to the same post-parse position the
``user_api_key_*`` strip already uses for the same reason. Adds a
regression test exercising the JSON-string ``litellm_metadata`` path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test(responses): replace legacy claude-4-sonnet alias in multiturn tool-call test

Anthropic's main API no longer resolves the non-canonical 'claude-4-sonnet-20250514'
alias for freshly issued keys, returning 404 not_found_error. PR #27031 already
swept three other live tests pinned to this alias to claude-haiku-4-5-20251001
but missed test_multiturn_tool_calls in the responses API suite, which is now
failing reliably on PR CI runs (e.g. PR #27074, job 1603363).

Bump the two model references in test_multiturn_tool_calls to the same
claude-haiku-4-5-20251001 snapshot used by PR #27031 -- it covers everything
this test exercises (tool calling, multi-turn) and isn't on a deprecation
schedule.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* chore(proxy): close callback-config and observability-credential side channels

Two related gaps in the proxy's request bouncer:

1. ``is_request_body_safe`` (auth_utils.py) walked the request-body root
   and the ``litellm_embedding_config`` nested dict, but not ``metadata``
   or ``litellm_metadata``. The same fields it bans at root — Langfuse /
   Langsmith / Arize / PostHog / Braintrust / Phoenix / W&B Weave / GCS /
   Humanloop / Lunary credentials and routing — were silently accepted
   when the caller put them inside metadata, retargeting observability
   callbacks to a caller-controlled host with caller-supplied creds.
   Walk both metadata containers (and parse the JSON-string form sent via
   multipart / ``extra_body``) through the same banned-params helper, so
   the existing ``allow_client_side_credentials`` opt-in covers both
   paths consistently.

2. The banned-params list was hand-maintained and lagged the canonical
   ``_supported_callback_params`` allow-list in
   ``initialize_dynamic_callback_params``. Derive the observability bans
   from that allow-list (minus a small ``_SAFE_CLIENT_CALLBACK_PARAMS``
   set for informational fields like ``langfuse_prompt_version`` and
   ``langsmith_sampling_rate``) so future integrations are covered
   automatically; ``_EXTRA_BANNED_OBSERVABILITY_PARAMS`` carries the
   handful of fields integrations read but the allow-list hasn't caught
   up to. A guard test fails CI if a new entry is added to
   ``_supported_callback_params`` without an explicit safe-list decision.

Separately in ``litellm_pre_call_utils.py``: add ``callbacks``,
``service_callback``, ``logger_fn``, and ``litellm_disabled_callbacks``
to ``_UNTRUSTED_ROOT_CONTROL_FIELDS``. The first three are appended to
worker-wide ``litellm.{input,success,failure,_async_*,service}_callback``
lists / ``litellm.user_logger_fn`` from inside ``function_setup`` — one
request poisons every subsequent caller in that worker. The last is the
inverse primitive: the legitimate path reads it from key/team metadata,
the request-body version silently disables admin-configured audit /
observability for the call.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(auth): per-param allow must continue, not return early

A pre-existing logic bug in ``_check_banned_params``: when the
deployment-level ``configurable_clientside_auth_params`` permitted one
banned field, the loop ``return``-ed on the first match instead of
``continue``-ing, so any other banned param later in the same body or
metadata dict was never checked. This PR's metadata walk multiplies the
surface where that bypass matters — a body pairing an allowed
``api_base`` with an observability credential like ``langfuse_host``
would silently pass.

Proxy-wide ``allow_client_side_credentials`` keeps ``return`` (it's a
global opt-in for every banned param). The per-param branch becomes
``continue`` so only the one explicitly-permitted field is skipped.

Adds a regression test that exercises the api_base + langfuse_host pair.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(vector_store): resolve embedding config at request time, never persist creds

The vector store create/update path previously called
``_resolve_embedding_config`` against the admin-configured router/DB
model and persisted the resolved ``litellm_embedding_config`` dict
(``api_key`` / ``api_base`` / ``api_version``) into the
``litellm_managedvectorstorestable.litellm_params`` column. Because the
resolver expanded ``os.environ/...`` references via ``get_secret``, the
DB row carried cleartext provider credentials, and the
``/vector_store/{new,info,update,list}`` responses returned them to any
authenticated caller who could supply a known admin model name.

Move the auto-resolve out of ``create_vector_store_in_db`` and out of
the update path. Persist only the user-supplied ``litellm_embedding_model``
reference. Resolve at request-handling time inside
``_update_request_data_with_litellm_managed_vector_store_registry`` so
the resolved config lives in the per-request ``data`` dict and is
garbage-collected after the response. Legacy rows that were created by
an earlier proxy version and already carry a resolved
``litellm_embedding_config`` skip the re-resolution and pass through
unchanged so embedding calls keep working.

The ``new_vector_store`` response now also runs the existing
``_redact_sensitive_litellm_params`` masker (already used by ``info``,
``update``, and ``list``), defending against caller-supplied cleartext
on the create path and against legacy rows whose persisted credentials
are still in the database.

Existing tests that asserted the old write-time-resolve behaviour are
updated to assert the new persistence shape (no embedding config
stored, just the model reference). Two new tests cover the use-time
path: one asserting fresh resolution happens when a row carries only
the model reference, the other asserting legacy rows with persisted
config skip re-resolution and continue to work.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(vector_store): tighten registry-mutation comment and dedupe test helpers

* fix(vector_store): cache use-time embedding-config resolution

Hold the resolved config in a process-memory TTL cache so the
request-handling path doesn't run litellm_proxymodeltable.find_first
on every vector-store call.

* fix(anthropic,bedrock,vertex): forward output_config.effort + 400 on garbage reasoning_effort

Follow-up bugs surfaced by the QA sweep on PR #27039
(https://github.com/BerriAI/litellm/pull/27039#issuecomment-4363363610).

1. Stop stripping output_config.effort on Bedrock + Vertex adaptive routes.
   - Vertex AI Claude 4.6/4.7 accepts output_config.effort on rawPredict
     (verified end-to-end against us-east5 / global). The strip helper now
     no-ops for effort.
   - Bedrock Converse routes output_config into additionalModelRequestFields
     for anthropic base models so the requested adaptive tier (low/medium/
     high/xhigh/max) actually reaches the wire instead of all collapsing to
     identical thinking.
   - Bedrock Invoke chat transformation (AmazonAnthropicClaudeConfig) stops
     popping output_config from the post-AnthropicConfig request body.
   - Bedrock Invoke /v1/messages allowlist (BedrockInvokeAnthropicMessagesRequest)
     now lists output_config so the runtime allowlist filter forwards it.

2. Validate effort across Bedrock Converse so 'disabled' / 'invalid' / '' /
   unsupported tiers (xhigh/max on Sonnet 4.6 or budget-mode 4.5 models)
   surface as a clean 400 BadRequestError instead of 500.

3. ValueError -> BadRequestError throughout (AnthropicConfig.map_openai_params,
   _apply_output_config, AmazonConverseConfig._handle_reasoning_effort_parameter).
   Empty-string effort is now rejected (was silently passing the
   'if effort and ...' short-circuit).

4. Floor reasoning_effort='minimal' at the Anthropic provider minimum
   (1024 budget_tokens) via new ANTHROPIC_MIN_THINKING_BUDGET_TOKENS so it's
   a usable tier on direct Anthropic / Azure AI Anthropic / Vertex AI Anthropic /
   Bedrock Invoke (all of which 400 below 1024).

5. model_prices: dedupe duplicate supports_max_reasoning_effort key on
   claude-opus-4-7 / claude-opus-4-7-20260416.

Adds regression tests across all five affected paths; existing tests asserting
the silent-strip behavior were updated to reflect the new pass-through and
clean 400 surfaces.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(constants): make ANTHROPIC_MIN_THINKING_BUDGET_TOKENS a plain constant

The documentation CI test (tests/documentation_tests/test_env_keys.py)
asserts every os.getenv() key in the source has a matching entry in the
litellm-docs config_settings.md table. ANTHROPIC_MIN_THINKING_BUDGET_TOKENS
tracks Anthropic's published wire-protocol minimum (1024) — it's not a
user-tunable, so making it env-overridable was wrong anyway. Drop the
os.getenv() wrapper; the value is now a plain literal.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(anthropic,bedrock): correct effort error message and dedupe effort_map

- Remove 'none' from the Bedrock _validate_anthropic_adaptive_effort error
  message; it was listed as a valid value but rejected by the membership
  check, leaving users in a feedback loop if they tried 'none'.
- Hoist the duplicated reasoning_effort -> output_config.effort mapping
  out of AnthropicConfig.map_openai_params and
  AmazonConverseConfig._handle_reasoning_effort_parameter into a single
  AnthropicConfig.REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT class constant
  so the two routes cannot drift.

* fix(anthropic): translate reasoning_effort on /v1/messages route

Closes the remaining QA-sweep gap on PR #27074: Bedrock Invoke
/v1/messages was silently ignoring ``reasoning_effort`` because the
shared param filter only kept native Anthropic keys, so every effort
tier collapsed to the same behavior on the wire (27/231 cells failing
across opus-4-5 / opus-4-6 / sonnet-4-6).

Map ``reasoning_effort`` to native Anthropic ``thinking`` /
``output_config.effort`` at the ``AnthropicMessagesConfig`` layer so
all four /v1/messages routes (direct Anthropic, Azure AI, Vertex AI,
Bedrock Invoke) inherit the same translation:

- Add ``reasoning_effort`` to ``AnthropicMessagesRequestOptionalParams``
  so the param filter in
  ``AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param``
  no longer drops it before the transformation runs.

- Add ``_translate_reasoning_effort_to_anthropic`` and call it from
  ``transform_anthropic_messages_request``. Mirrors
  ``AnthropicConfig.map_openai_params`` on the chat completion path
  (re-uses ``_map_reasoning_effort`` and
  ``REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT``) so the two routes
  cannot drift. Pops ``reasoning_effort`` so it never reaches the wire.

- Caller-supplied native ``thinking`` / ``output_config.effort`` always
  win — same precedence as
  ``_translate_legacy_thinking_for_adaptive_model``.

- Garbage values (``""``, ``"disabled"``, ``"invalid"``) raise
  ``AnthropicError(status_code=400)`` instead of falling through and
  surfacing as 500s from the provider.

- ``"none"`` clears thinking + output_config so callers can opt out
  per request.

Also restores the non-adaptive-model test coverage on Bedrock Invoke
/v1/messages that the previous commit lost when
``test_bedrock_messages_strips_output_config`` was renamed to the
``forwards`` variant on Opus 4.7.

Adds a new test file
``test_reasoning_effort_translation.py`` covering the translation at
the shared config level (adaptive + non-adaptive models, none, garbage,
caller precedence) so all four /v1/messages routes are exercised by a
single suite.

Adds parametrized + behavioral tests on the Bedrock Invoke /v1/messages
suite covering: minimal/low/medium/high/xhigh/max mapping for adaptive
models, thinking-budget mapping for non-adaptive Opus 4.5, ``none``
clears both, garbage raises 400, explicit ``output_config`` wins.

Refs: https://github.com/BerriAI/litellm/pull/27074

* fix(anthropic,bedrock): reject unmapped reasoning_effort at mapping site

Both the chat completion path (AnthropicConfig.map_openai_params) and the
Bedrock Converse path (_handle_reasoning_effort_parameter) used
REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get(value, value) which falls
back to the raw input on unmapped keys. Combined with _map_reasoning_effort
returning type='adaptive' for any string on Claude 4.6/4.7, garbage values
(e.g. 'disabled') could leak into optional_params['output_config']['effort']
unvalidated if map_openai_params ran without the downstream transform_request
or _validate_anthropic_adaptive_effort check.

Mirror the /v1/messages pattern: use .get(value) (no fallback) and raise
BadRequestError immediately when the value is unmapped, co-locating
validation with the mapping for defense in depth.

* style: black formatting

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(anthropic): stop class-attr leak; gate xhigh/max on every route

The reasoning-effort mapping dict was a public class attribute on
AnthropicConfig, so BaseConfig.get_config returned it as a request
parameter and every Anthropic-backed call (Anthropic / Azure / Vertex /
Bedrock Invoke) hit a 400 'REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT:
Extra inputs are not permitted' from the provider. Move the mapping
to a module-level constant.

_supports_effort_level only looked the model up under
custom_llm_provider='anthropic', so bedrock-prefixed model ids
(e.g. bedrock/invoke/us.anthropic.claude-opus-4-7) returned False
for both 'max' and 'xhigh' even when the underlying model entry has
the flag set. Strip known provider prefixes and retry the lookup
against litellm.model_cost directly so per-model gating works on
every route.

Mirror the per-model xhigh/max gate from
AnthropicConfig._apply_output_config in
AnthropicMessagesConfig._translate_reasoning_effort_to_anthropic so
the /v1/messages route also raises a clean 400 instead of forwarding
the unsupported tier.

* feat(anthropic,bedrock): strip output_config under drop_params for non-effort models

When a proxy fronts Claude Code (which always sends `output_config.effort`)
at a pre-4.5 Anthropic model — haiku-3, sonnet-3.5, opus-3, sonnet-4 — the
forwarded knob causes a forced 400 the client can't fix. Gating a strip
behind the existing `drop_params` flag lets operators opt into silent
fixup once and stop worrying about per-model param hygiene.

Default (`drop_params=False`) still forwards and surfaces the provider's
error, preserving the strict, debuggable contract from #27074.

Per https://platform.claude.com/docs/en/build-with-claude/effort the
supporting set is Opus 4.5+, Sonnet 4.6+, and Mythos Preview; everything
else is dropped (with a verbose_logger warning so the strip is visible).
Recognition uses model-name patterns plus a fallback to any
`supports_*_reasoning_effort` flag in the model map for forward
compatibility with new entries.

https://claude.ai/code/session_01WjHq31rvXT6xYNdVmSJvRp

(cherry picked from commit 1233943e78)

* fix(base_llm): filter all _-prefixed class attrs from get_config

The drop_params strip work added `AnthropicConfig._EFFORT_SUPPORTING_MODEL_PATTERNS`
as a private class-level lookup tuple. `BaseConfig.get_config()` only
filtered the `__`-prefixed names plus `_abc` / `_is_base_class`, so
`_EFFORT_SUPPORTING_MODEL_PATTERNS` would have leaked into the request
body the same way `REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT` did before
the previous commit.

Generalize the existing `_abc` / `_is_base_class` carve-outs to skip
every `_`-prefixed name. `AmazonConverseConfig.get_config()` overrides
the base method, so apply the same change there.

Also unblocks future internal helpers from accidentally serialising into
the wire body.

* fix(anthropic): drive output_config.effort support from model map flags

Replace hardcoded _EFFORT_SUPPORTING_MODEL_PATTERNS with a JSON-backed
check that uses supports_*_reasoning_effort flags from the model map.
Add supports_minimal_reasoning_effort: true to opus-4-5 and mythos-preview
entries (which previously only carried supports_reasoning) so the JSON
remains the single source of truth for effort capability.

* fix(anthropic,bedrock,databricks): four reasoning_effort follow-ups

- claude-sonnet-4-6 + reasoning_effort=max no longer 400s. Renamed
  _is_opus_4_6_model to _is_claude_4_6_model at three sites and added
  supports_max_reasoning_effort: true to 12 model entries in the JSON
  cost map (10 sonnet 4.6 ids + OpenRouter opus 4.6/4.7).
- _map_reasoning_effort now raises BadRequestError(400) directly with
  llm_provider, instead of letting Databricks (and similar callers)
  surface its raw ValueError as a 500.
- output_config.effort on Opus 4.5 over Bedrock no longer 400s for
  missing effort-2025-11-24 beta. Flipped JSON to "effort-2025-11-24"
  for bedrock + bedrock_converse and added an auto-attach branch in
  _process_tools_and_beta for non-adaptive Anthropic + output_config
  on Converse.
- reasoning_effort=xhigh / =max on legacy budget-mode models
  (Haiku 4.5, Sonnet 4.5, Opus 4.5) now map to thinking.budget_tokens
  8192 / 16384 instead of returning 400. Added two constants in
  litellm/constants.py.

Tests updated for all four flips. Validated end-to-end via 306-cell
live proxy matrix (6 model families x 3 routes x 17 effort cases),
all pass.

* fix(databricks): validate reasoning_effort and set output_config on adaptive Claude

The Databricks path called `AnthropicConfig._map_reasoning_effort` for
Claude models but never validated the effort string nor set
`output_config.effort` for adaptive models (Claude 4.6/4.7). Since
`_map_reasoning_effort` returns `type=adaptive` for ANY non-None /
non-"none" string on adaptive models (including "disabled",
"invalid", ""), Databricks silently accepted garbage and emitted a
request without an `output_config.effort`, collapsing every adaptive
tier to identical behavior.

Match the Anthropic native, Bedrock Converse, Bedrock Invoke, and
/v1/messages paths: when the resolved `thinking` is non-None on a
4.6/4.7 model, look up the value in
`REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT` and either raise a clean
`BadRequestError` or set `optional_params["output_config"]`.

* fix(azure): omit model from image generation and image edit deployment requests

Azure OpenAI routes image gen/edit by deployment in the URL; sending the
deployment id in model breaks gpt-image-2 (invalid_value). Strip model from
JSON for deployments/.../images/generations and from multipart data for
.../images/edits. Non-deployment URLs (e.g. Azure AI FLUX) unchanged.

Fixes #26316.

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(azure): exercise image gen JSON filter via HTTP client; dedupe image edit URL

- Image generation tests patch HTTPHandler.post / get_async_httpx_client so
  make_*_azure_httpx_request runs and wire json is asserted on call kwargs.
- Azure image edit: strip model in finalize_image_edit_multipart_data using the
  same URL string the handler passes to POST (no second get_complete_url in
  transform). BaseImageEditConfig default finalize is a no-op.

Co-authored-by: Cursor <cursoragent@cursor.com>

* fix(azure_ai/anthropic): promote output_config out of extra_body so validation runs

`azure_ai` is registered in `litellm.openai_compatible_providers`, so
`add_provider_specific_params_to_optional_params` (litellm/utils.py)
auto-stuffs any non-OpenAI kwarg (e.g. `output_config={"effort": "..."}`)
into `optional_params["extra_body"]`. `AzureAnthropicConfig.transform_request`
then strips `extra_body` entirely on the way out, silently dropping the
param — and `AnthropicConfig._apply_output_config` never sees it, so
`effort="invalid"` / `effort="xhigh"` on a non-supporting model
quietly reaches the model with default behavior instead of returning a
clean 400 (as the native `anthropic` provider does).

Promote the keys back to top-level `optional_params` (using `setdefault`
so explicit top-level values win) before delegating to the parent
`AnthropicConfig`. Apply in both `validate_environment` and
`transform_request` so flag detection (`is_mcp_server_used`, etc.) and
output-config validation both run.

Surfaced by the QA matrix expansion on PR #27074: 20 cells where Azure
returned 200 while `anthropic` returned 400 — all `output_config` mode
across haiku_4_5, sonnet_4_5, opus_4_5, sonnet_4_6, opus_4_6, opus_4_7
families with `effort` in {invalid, xhigh, max, low, medium, high}.

Tests:
* `test_output_config_promoted_from_extra_body`: valid effort reaches data
* `test_invalid_output_config_effort_raises_via_extra_body`: 400 on bad effort
* `test_unsupported_effort_xhigh_raises_via_extra_body`: 400 on xhigh-on-Sonnet-4.6
* `test_extra_body_promotion_does_not_clobber_top_level`: setdefault semantics

* test(image_gen): expect no model in Azure image edit multipart (#26316)

Align test_azure_image_edit_litellm_sdk with deployment-scoped Azure edits.

Co-authored-by: Cursor <cursoragent@cursor.com>

* refactor(anthropic): extract _validate_effort_for_model to prevent drift

The chat completion path (`_apply_output_config`) and the /v1/messages
pass-through (`AnthropicMessagesConfig._translate_reasoning_effort_to_anthropic`)
both gate `max` / `xhigh` per model. The two sites had diverged from
near-identical copies into separately maintained blocks, creating a real
drift risk when a new model tier (e.g. Claude 4.8) lands -- a contributor
could update one site and miss the other.

Centralise the gating in `AnthropicConfig._validate_effort_for_model`,
which returns an error message string or `None`. Each call site keeps
its own provider-appropriate exception type (`BadRequestError` for the
chat path, `AnthropicError` for the /v1/messages pass-through) but the
gating decision now comes from one place. Net -11 LOC.

Adds a parametrised unit test exercising the helper directly across
4.5 / 4.6 / 4.7 model families and `max` / `xhigh` / lower-effort
inputs. Existing tests at both call sites continue to pass unchanged.

Addresses Greptile finding on PR #27074.

* fix(databricks): narrow reasoning_effort_value to str for mypy

`non_default_params.get("reasoning_effort")` returns `Any | None`,
but `REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get()` expects `str`.
Mypy flagged this on the strict pass. Narrow with `isinstance` before
the lookup; non-strings fall through to the existing `BadRequestError`
below with a clean validation message, so behavior is unchanged.

Fixes a regression introduced by 1a10746e95 in this PR.

* feat(proxy): add health_check_reasoning_effort for model health checks

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(image_gen): align Azure image gen fixture with body omitting model

Expected JSON matches deployment-scoped Azure POST (#26316).

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(anthropic/chat): force PR-local model_cost map via autouse fixture

CI runs without LITELLM_LOCAL_MODEL_COST_MAP=True, so litellm.model_cost
is loaded from main-branch JSON (default model_cost_map_url) instead of
the PR's checked-out model_prices_and_context_window.json. Tests that
assert per-model flags added in this PR (supports_max_reasoning_effort,
supports_xhigh_reasoning_effort) therefore pass locally but fail in CI
with 'AssertionError: assert False is True' on 5 cases:

  - test_anthropic_model_supports_effort_param_recognizes_supporting_models
    [anthropic.claude-mythos-preview, bedrock/.../mythos-preview,
     claude-opus-4-5-20251101]
  - test_supports_effort_level_handles_provider_prefixes
    [bedrock/invoke/us.anthropic.claude-sonnet-4-6-max-True,
     claude-sonnet-4-6-max-True]

Add an autouse fixture at tests/test_litellm/llms/anthropic/chat/conftest.py
that monkey-patches litellm.model_cost to the PR-local JSON for every test
in this directory. The parent conftest already snapshots+restores
litellm.model_cost per-function, so the mutation is contained.

This is a scoped workaround. The proper fix is to set the env var
globally in the test workflow once the ~10 inline self-set test files
are audited; tracking that as a follow-up issue.

* [Fix] Docker: Pin Wolfi And Uv To Multi-Arch Index Digests

The previous pins resolved to single-platform amd64 manifests, so buildx
pulled the same amd64 base for both linux/amd64 and linux/arm64 targets.
The published OCI index then advertised an arm64 entry whose layers are
byte-identical to amd64 -- arm64 users got an amd64 binary.

Switch all three Dockerfiles to the multi-arch image-index digests:
  - cgr.dev/chainguard/wolfi-base   (index has linux/amd64 + linux/arm64)
  - ghcr.io/astral-sh/uv:0.11.7     (index has linux/amd64 + linux/arm64)

Resolved with `docker buildx imagetools inspect <ref>` -- that returns
the index digest. `docker pull` + `docker inspect` returns the per-host
platform digest, which is what slipped in last time.

* [Fix] Docker: Pin Uv To Multi-Arch Index Digest In Remaining Dockerfiles

Apply the same fix to the three Dockerfiles not in the release pipeline
today (alpine, dev, health_check) so they stay correct if/when they're
built for arm64 in the future.

Wolfi pins are not present in these files; the python:3.11-alpine and
python:3.13-slim digests they already use are multi-arch indexes that
include arm64/v8, so only the uv pin needed swapping.

* fix(xai): fold reasoning_tokens into completion_tokens to satisfy OpenAI invariant

xAI's chat completions API accounts reasoning_tokens separately from
completion_tokens, but rolls them into total_tokens. This breaks the
OpenAI invariant total_tokens == prompt_tokens + completion_tokens
that downstream consumers (including litellm's own _usage_format_tests
in tests/llm_translation/base_llm_unit_tests.py:58) rely on.

Live capture (grok-3-mini-beta, 2026-05-04):
    prompt=14, completion=10, total=336, reasoning=312
    14 + 10 = 24, NOT 336.

OpenAI's o1/o3 reasoning models include reasoning_tokens in
completion_tokens, leaving the prompt+completion=total invariant
intact. xAI deviates. This patch aligns xAI to OpenAI semantics by
folding reasoning_tokens into completion_tokens after the parent
OpenAI parser runs.

The fold is idempotent and defensive:
- Only fires when total_tokens == prompt_tokens + completion_tokens
  + reasoning_tokens (the documented xAI shape). Refuses to fold if
  the gap doesn't match, guarding against silent corruption when xAI
  changes accounting.
- Skips if completion_tokens already covers the gap (already
  normalised — e.g. cost calc replays a previously-folded Usage).

xai.cost_calculator.cost_per_token already added reasoning_tokens to
the visible completion count for billing. Post-fold the Usage block
now satisfies that invariant directly, so the cost calc would
double-bill. Updated cost_per_token to detect the OpenAI-normalised
shape (total == prompt + completion) and skip the reasoning add-on
in that case, falling through to the legacy raw-shape behaviour for
callers that bypass the transformation (e.g. proxy log replay).

Tests:
- Adds TestXAIReasoningTokenFolding covering: gap-explained-fold,
  idempotent-no-double-fold, no-reasoning-skip, gap-mismatch-skip.
- Adds test_already_normalised_usage_does_not_double_count_reasoning
  to lock the cost-calc idempotency.
- Updates 7 pre-existing cost-calc tests whose total_tokens was
  internally inconsistent (used the OpenAI-normalised total but kept
  reasoning_tokens external) to use the documented xAI raw shape
  total = prompt + visible completion + reasoning. Pre-existing
  values masked the missing-fold by accident.

Verified end-to-end against the live xAI API:
    LITELLM_LOCAL_MODEL_COST_MAP=False (CI default) +
    XAI_API_KEY set +
    pytest tests/llm_translation/test_xai.py::TestXAIChat::test_prompt_caching
        -> PASSED in 18.81s (was: AssertionError on
        usage.total_tokens == usage.prompt_tokens + usage.completion_tokens)

20/20 tests in tests/test_litellm/llms/xai/test_xai_cost_calculator.py
and 8/8 in tests/test_litellm/llms/xai/test_xai_chat_transformation.py
pass.

* refactor(bedrock/converse): delegate effort gating to AnthropicConfig._validate_effort_for_model

Removes the duplicated max/xhigh gating logic in
_validate_anthropic_adaptive_effort and the now-unused
_supports_effort_level_on_bedrock helper. Per-model gating now flows
through the centralized AnthropicConfig._validate_effort_for_model
(whose _supports_effort_level already strips Bedrock prefixes), so the
chat completion, /v1/messages, and Bedrock Converse paths can't drift
when a new gated effort tier is added.

* Implement normalize_nonempty_secret_str function to trim whitespace from secrets and treat empty values as unset. Update proxy_server to use this function for Grafana credentials. Enhance tests to validate the new normalization behavior.

* Fix qdrant semantic cache miss metadata

* chore(deps): refresh dependency locks

* chore(deps): authorize pytest license

* fix: preserve tokenizer decode round trips

* refactor(anthropic): drive adaptive-thinking gate via supports_adaptive_thinking flag

Three of greptile's open comments on #27074 (P2 converse:512, P1
databricks:361, and the underlying capability-flag policy rule) flagged
the same pattern: _is_claude_4_6_model(...) or _is_claude_4_7_model(...)
used inline as a runtime 'is this an adaptive-thinking model?' check.
That requires a code release each time a new adaptive Claude lands.

Consolidate the inline gating to AnthropicModelInfo._is_adaptive_thinking_model,
and switch the helper itself to read a new supports_adaptive_thinking
flag from `model_prices_and_context_window.json` via `_supports_factory`,
falling back to the family pattern only when the model-map entry doesn't
carry the flag (preserves OpenRouter / Vercel / Bedrock-prefixed variants
that route through the same code path with non-canonical ids).

Adds `supports_adaptive_thinking: true` to the four 4.6/4.7 anthropic
entries (opus-4-6 + dated, opus-4-7 + dated, sonnet-4-6). Bedrock-prefixed
and Vertex-prefixed entries don't need the flag because both fall back
through the family pattern (the helper short-circuits early on True from
either path) and the bedrock/vertex Claude IDs all match the existing
opus-4-{6,7} / sonnet-4-{6,7} pattern.

Affected call sites:

- `bedrock/chat/converse_transformation.py:_handle_reasoning_effort_parameter`
- `anthropic/chat/transformation.py:_map_reasoning_effort`
- `anthropic/chat/transformation.py:map_openai_params` (output_config branch)
- `databricks/chat/transformation.py:map_openai_params` (output_config branch)

The remaining `_is_claude_4_6_model` / `_is_claude_4_7_model` references
in `AnthropicConfig._validate_effort_for_model` and
`AnthropicConfig.get_supported_openai_params` are intentionally retained:
they're per-model gating fallbacks for variants whose model-map entries
don't yet carry the `supports_max_reasoning_effort` /
`supports_reasoning` flag. Those are documented in-place.

Tests: 537 anthropic/bedrock/databricks/vertex/messages tests pass.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* chore(deps): address dependency review notes

* test(model_prices): add supports_adaptive_thinking to schema

`test_aaamodel_prices_and_context_window_json_is_valid` validates the
model-map JSON against an explicit schema with `additionalProperties`,
so the new `supports_adaptive_thinking` flag added in
98ced0ae43 needs a matching schema entry.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* refactor: remove unnecessary comments from #27074

Strip out the explanatory and historical comments that don't carry
business-logic justification. Comments that simply narrate what code
does — or that explain prior behavior, what was changed, or which PR
introduced a fix — are removed. Docstrings are reduced to a one-line
summary where the long form repeated information already evident from
the code or test data.

No code-behavior changes. All 643 affected unit tests still pass.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test: keep decode token test local

* chore(deps): align dashboard node engine

* feat: selectively apply routing strategy according to model name

* style: make _model_supports_effort_param more concise

* refactor(anthropic,bedrock): hoist drop_params output_config warning to module constant

Three call sites (anthropic chat, bedrock converse, bedrock invoke messages)
emitted the same '...Effort is only supported on Opus 4.5+, Sonnet 4.6+, and
Mythos Preview' warning verbatim. Extract DROP_UNSUPPORTED_OUTPUT_CONFIG_WARNING
in litellm/llms/anthropic/chat/transformation.py and import it from the bedrock
sites so future copy edits live in one place.

Addresses Michael's review on PR #27074.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* refactor(anthropic,bedrock,databricks): factor BadRequestError for unknown reasoning_effort

Three call sites raised the same BadRequestError("Invalid reasoning_effort:
... Must be one of 'minimal', 'low', ...") block when REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT
returned None: anthropic chat map_openai_params, bedrock converse
_handle_reasoning_effort_parameter, and databricks chat reasoning_effort path.

Extract AnthropicConfig._raise_invalid_reasoning_effort(model, value, llm_provider)
so future copy edits / valid-set changes happen in one place. Typed as NoReturn
so type-checkers correctly narrow control flow at call sites.

Addresses Michael's review on PR #27074.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* Clean up Redis semantic cache isolation fallback

* fix(guardrails): align banned_keywords + azure_content_safety call_type gates with runtime route_type

The hooks gated on ``call_type == "completion"`` but the proxy ingress
passes ``route_type`` straight through as ``call_type`` —
``"acompletion"`` for /v1/chat/completions and ``"aresponses"`` for
/v1/responses. Tests passed because they used the literal sync
``"completion"`` value, masking the gap.

Switch both hooks to ``is_text_content_call_type`` (matches the
canonical runtime values: completion / acompletion / aresponses) and
update existing tests to assert against runtime values, plus parametrize
a regression test that pins the gate.

* fix: remove unused import

* Add semantic cache legacy migration flag

* Treat 0 team_member_budget as no cap

* chore(caching): annotate qdrant quantization_params dict type

Mypy infers the dict's value type from the first branch
(Dict[str, bool]) which clashes with the scalar branch's mixed-type
inner dict. Explicit Dict[str, Any] annotation lifts the inference.

* chore(caching): remove allow_legacy_unscoped_cache_hits opt-in

The flag was an opt-in escape hatch for the cross-tenant leak the rest
of the patch closes — flipping it on (env var or constructor param)
re-enables exactly the VERIA-54 primitive on either backend. There is
no operational need that the secure path doesn't already meet:

- Qdrant: legacy points without ``litellm_cache_key`` payload are
  excluded by the must-clause filter and treated as misses; new sets
  populate the cache key, so cold-start lasts only as long as the
  natural cache rebuild.
- Redis: existing unscoped index can't carry the new schema; the init
  path falls back to ``{name}_isolated`` (and recreates it on stale
  schema), leaving the legacy index untouched.

Drop the constructor param, env-var fallback, ``_using_legacy_unscoped_index``
flag, the legacy-reuse branch in ``_init_semantic_cache``, and the
matching guards in set/get paths. Update tests to drop the legacy-mode
cases and assert the secure-only behaviour.

* fix(container): keep ownership-filter exceptions out of the LLM-error path

filter_container_list_response runs after the upstream call has
already succeeded; treating an ownership-lookup failure as an LLM-API
error fires post_call_failure_hook for a successful upstream call and
returns a misleading provider-shaped error to the client. Run the
filter outside the try/except so genuine LLM errors stay scoped to
the upstream call.

* chore(container,skills): LRU eviction for owner caches; widen file_purpose Literal

Two cleanups from the /simplify pass:

* ``_CONTAINER_OWNER_CACHE`` and ``_SKILL_CACHE`` now LRU-evict via
  ``OrderedDict.popitem(last=False)`` instead of full ``clear()`` at
  capacity. Full clears converted a steady-state cached workload into a
  periodic full-DB-load oscillation as the cache repopulated from zero
  and cleared again. Reads now ``move_to_end`` so the just-touched
  entry survives the next eviction. Mirrors the pre-existing LRU
  pattern in ``_remember_container_owner``.

* ``LiteLLM_ManagedObjectTable.file_purpose`` Literal now includes
  ``"container"`` so Pydantic validation accepts rows written by the
  ownership store.

* chore(container,skills): drop legacy-access opt-out env vars

LITELLM_ALLOW_UNTRACKED_CONTAINER_ACCESS and
LITELLM_ALLOW_UNOWNED_SKILL_ACCESS were operator-toggleable opt-outs
for the cross-tenant access primitive this PR closes — flipping either
on re-enabled exactly the VERIA-20 read path. Default-secure with no
escape hatch matches sibling fixes (vector-store cred isolation, semantic
cache key isolation, user_config strip): all rejected the
opt-out-of-security pattern.

Untracked containers and unowned skills (rows that pre-date this
enforcement) are admin-only. Non-admin owners need to either re-create
via the now-tracked flow or have an admin assign ``created_by`` on the
existing row. Update tests to assert the strict-only behaviour.

* fix(ownership): reject identity-less callers instead of sharing a sentinel scope

UNSCOPED_RESOURCE_OWNER_SCOPE collapsed every caller without an
identity field (no user_id / team_id / org_id / api_key / token) into
a single shared owner — a cross-tenant access primitive: any two such
callers could see and delete each other's containers and skills.

Drop the sentinel. ``get_primary_resource_owner_scope`` returns
``None`` and ``get_resource_owner_scopes`` returns ``[]`` for
identity-less callers. ``record_container_owner`` and
``LiteLLMSkillsHandler.create_skill`` now reject creates from
identity-less callers with a 403 instead of stamping the placeholder.
Read paths already deny ``owner is None`` correctly so legacy rows
(if any) are admin-only.

* fix(proxy): include request-blocked callback params in auth bans

* fix: keep skills handler FastAPI-free; fold gcs deny list into the body bouncer

Two cleanups:

* ``LiteLLMSkillsHandler.create_skill`` raised ``HTTPException`` for
  identity-less callers, importing FastAPI from a ``litellm/llms/``
  module — that violates the project rule that FastAPI lives only
  under ``proxy/``. Switch to ``ValueError`` (the same shape the rest
  of the handler uses for not-found/forbidden) and update the test.

* The proxy-auth body bouncer derived its observability ban list from
  ``_supported_callback_params`` only, missing
  ``_request_blocked_callback_params`` (where ``gcs_bucket_name`` and
  ``gcs_path_service_account`` live). Two recently-merged sibling PRs
  (#27019 added the deny list, #27081 added the test asserting these
  are rejected at the request body root) crossed without folding them
  together. Union the GCS deny list into the bouncer's derivation so
  the single source of truth covers both code paths.

* fix(proxy): normalize managed resource team owner field

* chore: simplify ownership tracking — drop thin stores, in-memory fallback, hand-rolled cache

Substantial reduction (~765 LOC) without changing the security
boundary:

* Drop ContainerOwnershipStore and LiteLLMSkillsStore — both were
  one-method-per-Prisma-call wrappers. Inline the calls instead,
  matching the established pattern in vector_store_endpoints,
  agent_endpoints, and mcp_server/db.py.

* Drop the prisma_client is None in-memory fallback. Production
  deploys always have Prisma; running ownership-critical paths on a
  process-local dict is a security footgun in the dev-mode case it
  was meant to support, and complicates every code path with a
  branch. Fail-secure: skip recording if Prisma is unavailable, and
  treat reads as "not found" (admin-only).

* Drop the hand-rolled module-level cache. Replace with the existing
  litellm.caching.in_memory_cache.InMemoryCache, which already has
  TTL + max-size + eviction tested in its own module. Sentinel string
  for negative caching since InMemoryCache can't disambiguate "miss"
  from "cached as None".

* Tests: drop coverage for removed code paths (in-memory fallback,
  hand-rolled cache internals). Keep tests for actual behavior (cache
  hit-rate, negative caching, owner check, list filtering,
  identity-less reject, admin bypass).

* fix(container): cache list-allow-set, track admin-created containers

Address Greptile P2 follow-ups from the prior round:

* Cache ``_get_allowed_container_ids`` (60s LRU/TTL keyed by sorted
  owner-scope tuple) so ``GET /v1/containers`` doesn't issue a fresh
  ``find_many`` against ``litellm_managedobjecttable`` on every list
  call. Invalidate the caller's own cache entry when they record a
  new owner so the just-created container shows up on their next list.

* Tighten the admin early-return in ``record_container_owner`` to skip
  ONLY when there's literally no container ID to stamp. An admin with
  identity (the master-key path populates ``user_id`` + ``api_key``)
  flows through the normal record path so admin-created containers are
  tracked like any other caller's. The truly-identity-less admin case
  still falls through to the 403 below — correct fail-secure default.

Skill-cache invalidation gap (also flagged by Greptile) is moot: there
is no skill update endpoint exposed; ownership-affecting mutations are
only delete (already invalidates) and create (new ID, no cache entry
to update).

* chore(container): use delete_cache, json-encode scope key, clean test

/simplify follow-ups:

* Replace the two-``pop`` reach into ``cache_dict``/``ttl_dict`` with
  the existing public ``InMemoryCache.delete_cache(key)`` — the same
  idiom used elsewhere in the proxy. Bonus: ``delete_cache`` calls
  ``_remove_key`` which also handles ``expiration_heap`` consistency
  the direct pops were silently leaking.

* JSON-encode the sorted scope list for the cache key instead of
  ``"|".join``. ``user_id`` / ``team_id`` / ``org_id`` / ``api_key``
  are free-form strings and could contain a literal ``|`` — JSON
  quoting escapes any in-string separator unambiguously.

* Extract ``_allowed_container_ids_cache_key()`` so the read and
  invalidation sites compute the key the same way.

* Fix a placeholder-then-overwrite test construction: the
  ``__module__.split(".")[0] and "proxy_admin"`` line evaluated to a
  literal string that was immediately overwritten with the real enum
  value. Hoist the import and construct directly.

* [Fix] Tests: Replace deprecated openrouter/claude-3.7-sonnet with claude-sonnet-4.5

OpenRouter has dropped active endpoints for anthropic/claude-3.7-sonnet,
causing test_reasoning_content_completion to fail with a 404 "No endpoints
found" error. Switch to anthropic/claude-sonnet-4.5, which is current and
supports reasoning streaming.

* feat: routing groups ui

* fix(security): prevent secret_fields from leaking into spend logs

secret_fields (containing raw HTTP headers including Authorization
Bearer tokens) was being included in proxy_server_request['body']
because the body snapshot was a copy.copy(data) of the full request
dict. This body gets serialized and persisted in the LiteLLM_SpendLogs
table, exposing user credentials in the database.

Root cause: data['secret_fields'] was set before the body snapshot at
data['proxy_server_request']['body'] = copy.copy(data), so the full
raw headers (including auth tokens) ended up in the snapshot.

Fix (defense in depth):
1. Exclude 'secret_fields' when creating the body snapshot in
   litellm_pre_call_utils.py (primary fix)
2. Strip 'secret_fields' in _sanitize_request_body_for_spend_logs_payload
   as a secondary safeguard

secret_fields remains available on the live data dict for legitimate
downstream consumers (MCP, Responses API).

Co-authored-by: Krrish Dholakia <krrish-berri-2@users.noreply.github.com>

* chore: update Next.js build artifacts (2026-05-05 02:13 UTC, node v20.20.2)

* [Fix] Proxy: Break managed-resources import cycle on Python 3.13

The Python 3.13 CCI smoke matrix surfaces a partially-initialized-module
ImportError when loading the managed files hook chain:

  litellm.proxy.hooks/__init__ (mid-import)
    -> enterprise.enterprise_hooks
    -> litellm_enterprise.proxy.hooks.managed_files
    -> litellm.llms.base_llm.managed_resources.isolation
    -> litellm.proxy.management_endpoints.common_utils
    -> litellm.proxy.utils  (re-enters litellm.proxy.hooks)

The except ImportError block in hooks/__init__.py silently swallowed the
failure, leaving managed_files unregistered and POST /files returning
500 "Managed files hook not found".

Two-layer fix:
- Inline the 3-line _user_has_admin_view check in isolation.py instead
  of importing it from litellm.proxy.management_endpoints.common_utils.
  litellm.llms.* should not depend on litellm.proxy.* — removing this
  layering violation breaks the cycle at its root.
- Define PROXY_HOOKS and get_proxy_hook before the conditional
  enterprise import in litellm/proxy/hooks/__init__.py, so any future
  re-entry resolves the public names instead of hitting an
  ImportError on a partially-initialized module.

Also fold in two unrelated CCI repairs surfaced in the same staging run:
- tests/otel_tests/test_key_logging_callbacks.py: per-key
  gcs_bucket_name / gcs_path_service_account are now stripped by
  initialize_dynamic_callback_params, so the GCS client falls through
  to the env-only branch. Update the assertion to match the new
  "GCS_BUCKET_NAME is not set" message.
- .circleci/config.yml: tests/pass_through_tests now resolves
  google-auth-library@10.x via the @google-cloud/vertexai 1.12.0 bump,
  which uses dynamic ESM imports Jest 29 cannot load without
  --experimental-vm-modules. Pass that flag in the Vertex JS test step.

Adds tests/test_litellm/proxy/hooks/test_proxy_hooks_init.py as a
regression guard: managed_files / managed_vector_stores must register,
and isolation.py must not transitively import litellm.proxy.utils.

* [Fix] Proxy: Address Greptile feedback on hook-cycle PR

- Move _user_has_admin_view to litellm.proxy._types as
  user_api_key_has_admin_view (single source of truth). common_utils.py
  and isolation.py both import from there now, removing the duplicated
  role-check that could silently diverge if new admin roles are added.
- Add pytest.importorskip("litellm_enterprise") to the two regression
  tests that assert managed_files / managed_vector_stores are registered;
  those keys come from ENTERPRISE_PROXY_HOOKS so the tests would fail
  unconditionally in a checkout without the enterprise extra installed.

* [Fix] Lint: Mark _user_has_admin_view re-export in common_utils

Ruff F401 flagged the aliased import as unused within common_utils.py
because the name is consumed only by external modules (~15 callers
across guardrails, spend tracking, MCP, agents, management endpoints).
Add `# noqa: F401  re-exported` so the alias survives lint while
keeping a single source of truth in litellm.proxy._types.

* refactor(azure): move image gen JSON helper; rename image edit finalize hook

- Add image_generation/http_utils.azure_deployment_image_generation_json_body; call
  from azure.py (keeps AzureChatCompletion focused on chat).
- Rename finalize_image_edit_multipart_data to finalize_image_edit_request_data with
  docstring covering multipart and JSON POST payloads (review feedback).

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(proxy): cover health_check_reasoning_effort for completion mode

Co-authored-by: Cursor <cursoragent@cursor.com>

* [Fix] Tests: Use master key for /otel-spans in test_chat_completion_check_otel_spans

/otel-spans now requires proxy admin (returns 401 'Only proxy admin
can be used to generate, delete, update info for new keys/users/teams.
Route=/otel-spans' for non-admin callers). Switch the GET call to use
the master key sk-1234 while keeping the generated key for the
chat-completion request that produces the spans.

* [Fix] Tests: Pick chat-completion OTEL trace by content, not recency

The /otel-spans endpoint returns process-wide spans and tags
most_recent_parent by max start_time. After tightening that route to
proxy_admin (sk-1234), the GET /otel-spans request itself emits auth
spans that beat the chat-completion spans on start_time, so
most_recent_parent now points at the request's own auth trace
(['postgres', 'postgres']) and the >=5-span assertion fails.

Pick the chat-completion trace by content: it is the only trace whose
span list is a superset of {postgres, redis, raw_gen_ai_request,
batch_write_to_db}. Verified locally end-to-end against
otel_test_config.yaml + OTEL_EXPORTER=in_memory: 3/3 runs green.

* [Fix] CI: Enable VCR replay for test_azure_o_series

The Azure o-series tests were excluded from the conftest's VCR auto-marker
because of a respx/vcrpy transport-patching conflict, but the only respx
reference in the file was an unused `MockRouter` import. Drop the dead
import and remove the file from the conflict set so cassettes record on
first run and replay thereafter, eliminating the 60-95s live Azure latency
that was crashing xdist workers under --timeout=120 thread-mode timeouts.

* [Fix] Tests: Restore /metrics access for prometheus test suite

/metrics now requires auth by default; tests/otel_tests/test_prometheus.py
makes 4+ unauthenticated GETs against http://0.0.0.0:4000/metrics, so
every prometheus test in CI now fails the metric assertion.

Set require_auth_for_metrics_endpoint: false in otel_test_config.yaml
to opt out for this test job, which scrapes /metrics directly. Verified
locally: 8/8 prometheus tests green (one flaky retry on
test_proxy_success_metrics that pre-dates this PR).

Also drop the -x stop-on-first-failure flag from the otel test command
so all failures in the job surface in a single CI run rather than
hiding behind whichever one trips first.

* [Perf] CI: Skip Redundant Playwright Apt Install in E2E UI Job

The cimg/python:3.12-browsers base image already ships every Chromium
system dependency Playwright needs (libnss3, libatk-bridge2.0-0,
libcups2, etc. — the install log shows them all as "already the newest
version"). Passing --with-deps to `npx playwright install` therefore
runs an apt-get update + install for nothing, but pays the full cost of
hitting Ubuntu mirrors. On a recent run those mirrors stalled hard:
apt-get update alone took 6m53s at 81.5 kB/s with several archives
returning connection refused.

Drop --with-deps and persist ~/.cache/ms-playwright alongside
node_modules so the Chromium binary is also reused across runs. Bump
the cache key to v2 so the existing v1 entry (which only contained
node_modules) is not loaded and skipped over the new browser path.

* [Fix] Docker: Remove Hardcoded Prisma Binary Target For Multi-Arch Builds

PRISMA_CLI_BINARY_TARGETS="debian-openssl-3.0.x" was hardcoded in
docker/Dockerfile.non_root by #17695. On a buildx linux/arm64 leg this
forces prisma to download the amd64 schema-engine into an arm64 image,
so 'prisma migrate deploy' fails at startup with 'Could not find
schema-engine binary'.

Removing the env lets prisma auto-detect per build platform: amd64
builds still resolve to debian-openssl-3.0.x (Wolfi falls back to
debian, same binary as before), and arm64 builds now correctly fetch
linux-arm64-openssl-3.0.x. The offline-cache pre-warm goal of #17695 is
preserved — only which binaries fill the cache changes.

Fixes #19458

* [Fix] UI: Clear Admin Session Cookies Before Establishing Invited User's Session (#27227)

The invite-signup form was writing the new user's token via raw
`document.cookie` at `path=/`, while the rest of the auth surface uses
`storeLoginToken` (which writes at `path=/ui` and mirrors to
sessionStorage). After signup the inviter's `path=/ui` cookie kept
winning path-specificity matching, and sessionStorage still held the
inviter's token, so the dashboard rendered as the inviter rather than
the newly created user.

Treat invite signup as a principal-change boundary — clear prior
session cookies first, then store the new token via the canonical
helper.

* test: add 24hr Redis-backed VCR cache to additional test suites (#27159)

* test: add 24hr Redis-backed VCR cache to additional test suites

Extracts the existing llm_translation VCR plumbing into a reusable helper
(tests/_vcr_conftest_common.py) and wires it into the conftest.py files
of the test directories listed in LIT-2787:

  audio_tests, batches_tests, guardrails_tests, image_gen_tests,
  litellm_utils_tests, local_testing, logging_callback_tests,
  pass_through_unit_tests, router_unit_tests, unified_google_tests

The same helper is also adopted by the pre-existing llm_translation and
llm_responses_api_testing conftests to remove the copy-pasted VCR setup.

Each consuming conftest:
- registers the Redis persister via pytest_recording_configure
- auto-marks collected tests with pytest.mark.vcr (skipping respx-using
  files where applicable, since respx and vcrpy both patch httpx)
- gates cassette writes on test success via _vcr_outcome_gate

The cache is opt-in via CASSETTE_REDIS_URL; when unset, VCR is disabled
and tests hit live providers as before. LITELLM_VCR_DISABLE=1 still
forces a bypass for ad-hoc local runs.

Test directories that run LiteLLM proxy in Docker (build_and_test,
proxy_logging_guardrails_model_info_tests, proxy_store_model_in_db_tests)
are intentionally not included: VCR.py patches the in-process httpx
transport and cannot intercept calls made from inside a Docker container.
The installing_litellm_on_python* jobs make no LLM calls and don't
benefit from caching.

https://linear.app/litellm-ai/issue/LIT-2787/add-24hr-caching-to-additional-test-suites

* test(vcr): add safe-body matcher to handle JSONL and binary request bodies

vcrpy's stock body matcher inspects Content-Type and unconditionally
runs json.loads on application/json bodies. JSON Lines payloads (used
by the Bedrock batch S3 PUT and other upload paths) crash that with
json.JSONDecodeError: Extra data, before the matcher can return
'not a match'.

This was the root cause of the batches_testing CI job failing on
test_async_create_file once VCR auto-marking was applied to the
batches_tests directory.

Add a conservative byte-equality body matcher and use it in place of
'body' in the shared match_on tuple. The matcher is strictly more
conservative than vcrpy's default — the only thing it gives up is
'different JSON key order is treated as the same body', which doesn't
apply to deterministic litellm-built request payloads. It can never
produce a false positive that the default would have rejected, so
there is no cross-contamination risk.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): exclude tests that VCR replay actively breaks

A few tests are incompatible with cassette replay and were failing on
the latest CI run after VCR auto-marking was extended to local_testing
and logging_callback_tests:

- test_amazing_s3_logs.py (logging_callback_tests): the test asserts on
  a per-run response_id that should round-trip through a real S3
  PUT/LIST. vcrpy's boto3 stub intercepts the PUT and the LIST replays
  stale keys, so the freshly-generated id is never found.
- test_async_embedding_azure (logging_callback_tests) and
  test_amazing_sync_embedding (local_testing): the failure branches
  deliberately pass api_key='my-bad-key' to assert that the failure
  callback fires. We scrub auth headers from cassettes (so the bad-key
  request matches the prior good-key request), and vcrpy replays the
  recorded 200 — the failure callback never fires.
- test_assistants.py (local_testing): the OpenAI Assistants polling
  APIs mint fresh thread/run IDs every recording session and then poll
  until status=='completed'. Replays of those polled GETs can never
  match a freshly-generated run id, so every CI run effectively
  re-records and the suite blows past the 15m no_output_timeout.

Skip these from VCR auto-marking so they continue to hit live providers
as they did before this change. The remaining tests in each directory
still get cached.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): expand skip lists for second batch of incompatible tests

Followup to the previous commit. After re-running CI on the rebuilt
branch, three more tests surfaced as VCR-replay-incompatible:

- litellm_utils_testing :: test_get_valid_models_from_dynamic_api_key
  Calls GET /v1/models with api_key='123' to assert the result is empty.
  We scrub auth headers, so the bad-key request matches the prior
  good-key cassette and replays the recorded model list.
- litellm_utils_testing :: test_litellm_overhead.py
  Measures litellm_overhead_time_ms as a percentage of total wall-clock
  time. With cached responses the upstream 'network' time collapses to
  microseconds, blowing past the 40%% threshold the test asserts on.
  Skip the whole file (every parametrization is at risk).
- local_testing_part1 :: test_async_custom_handler_completion and
  test_async_custom_handler_embedding
  Same bad-key failure-callback pattern as the already-skipped
  test_amazing_sync_embedding.
- litellm_router_testing :: test_router_caching.py
  Asserts on litellm's own router-level response cache by comparing
  response1.id to response2.id across repeat upstream calls (test
  bypasses litellm cache via ttl=0 and expects upstream to return a
  *new* id). With VCR replay both upstream calls return the same
  cassette body, so the ids are identical. Skip the whole file.
- logging_callback_tests :: test_async_chat_azure (preemptive)
  Same shape as already-skipped test_async_embedding_azure; was masked
  by upstream OpenAI rate-limit failures on baseline.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): use item.path and tighten matcher docstring

- Replace pytest's deprecated item.fspath with item.path in
  apply_vcr_auto_marker_to_items so we don't emit deprecation
  warnings under pytest 8.
- Clarify _safe_body_matcher docstring to reflect actual behavior
  (direct == first, then UTF-8 bytes comparison, no repr fallback).

Addresses Greptile review feedback on PR #27159.

* test(vcr): swallow all RedisError on cassette save/load

Cassette persistence is strictly best-effort: any Redis-side failure
(connection blip, timeout, OutOfMemoryError when the maxmemory cap is
hit, READONLY replicas, etc.) should degrade to 'test passed but
cassette not cached' rather than fail the test on teardown.

Previously the persister only caught ConnectionError and TimeoutError,
so OutOfMemoryError — which Redis Cloud raises when the cassette cache
hits its memory cap and there are no evictable keys — propagated out of
vcrpy's autouse fixture and ERRORed otherwise-passing tests on
teardown. This caused the litellm_utils_testing CircleCI job to fail on
the latest commit's run, even though the underlying test was a unit
test that used mock_response and produced no real upstream traffic
(the cassette was dirtied by a background langfuse callback). The
rerun only succeeded because Redis evictions happened to free enough
room before the SET — i.e. it was timing-dependent flakiness.

Catch redis.exceptions.RedisError (the common base of all server- and
client-side Redis exceptions) on both save and load, and parametrize
the regression tests across ConnectionError, TimeoutError, and
OutOfMemoryError to pin the new behavior.

* test(vcr): surface cassette-cache failures with warnings + session banner

When the persister silently swallows a Redis OOM (or any RedisError) on
save/load there is otherwise no visible signal that the cache is
degraded — tests pass, the cassette just isn't persisted, and the next
session still hits the same Redis at the same near-cap memory.

Add three layers of observability so that failure mode is loud:

1. Per-process health counters ("save_failures", "load_failures", and
   the last error string for each), exposed via cassette_cache_health()
   and reset via reset_cassette_cache_health(). The persister
   increments these in addition to logging.

2. VCRCassetteCacheWarning (UserWarning subclass) emitted via
   warnings.warn() inside the persister's except block. Pytest's
   built-in warnings summary at session end automatically lists every
   such warning, so the failure is visible in CI logs without any
   conftest-level wiring.

3. Session-end banner via emit_cassette_cache_session_banner() and a
   stderr-fallback atexit handler registered from
   register_persister_if_enabled(). Two states:
     - red "VCR CASSETTE CACHE DEGRADED" when save_failures or
       load_failures > 0
     - yellow "VCR CASSETTE CACHE NEAR CAPACITY" (no failures, but
       used_memory >= 85% of maxmemory) so the next session knows
       the Redis is approaching OOM before any SET actually fails

Capacity comes from a best-effort INFO memory probe
(cassette_cache_capacity_snapshot) that returns None on any failure or
when maxmemory is uncapped. The atexit handler skips xdist workers so
only the controller emits.

Tests: parametrize the existing save/load swallow-error tests across
ConnectionError/TimeoutError/OutOfMemoryError, add direct tests for
the health counters and warning emission, and a new
test_vcr_conftest_common_banner.py covering banner output for every
state (silent/red/yellow/disabled/xdist-worker).

* test(vcr): bucket cassettes by API key fingerprint, drop bad-key skips

Tests that deliberately call an LLM API with a bad key (e.g. to assert
that the failure callback fires, or that check_valid_key returns False)
were being silently served the prior good-key cassette: we scrub the
real Authorization / x-api-key header from the cassette before storing
it, so a follow-up bad-key call is byte-identical to the good-key call
under the existing match_on tuple.

Add a 'key_fingerprint' custom matcher that distinguishes requests by
the SHA-256 of their API-key headers. The fingerprint is stamped into
a synthetic 'x-litellm-key-fp' header by a new before_record_request
hook, which then strips the real auth headers (we have to do the
scrubbing here instead of via vcrpy's filter_headers knob, because
filter_headers runs *first* and would erase the value we want to hash).

Bad-key requests now get a different cassette bucket than good-key
requests, so vcrpy will not replay a recorded 200 in place of the
expected 401. The fingerprint is a one-way hash of the secret, so
cassettes never contain the key.

This permanently removes the 'bad-key' category of skips:

- tests/local_testing: dropped ::test_amazing_sync_embedding,
  ::test_async_custom_handler_completion,
  ::test_async_custom_handler_embedding
- tests/logging_callback_tests: dropped ::test_async_chat_azure,
  ::test_async_embedding_azure
- tests/litellm_utils_tests: dropped
  ::test_get_valid_models_from_dynamic_api_key

Coverage: 7 new unit tests in tests/test_litellm/test_vcr_safe_body_matcher.py
covering header stripping, fingerprint determinism, no-auth bucketing,
good-vs-bad key discrimination, x-api-key (Anthropic/Azure) discrimination,
and idempotence under replay.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): drop redundant comments and docstrings

Trim narration of code that is already self-evident from function and
variable names. Keep the two genuinely non-obvious bits:

- ordering constraint between filter_headers and before_record_request,
  which would invite a maintainer to re-introduce the bug if removed
- the per-directory _VCR_INCOMPATIBLE_FILES rationale, since 'why
  exactly is this skipped' is not knowable from the test name alone

Also drop the 40-line commented-out drop-in conftest snippet at the
bottom of _vcr_conftest_common.py — the consuming conftests are the
canonical reference.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): make _before_record_request idempotent

vcrpy invokes before_record_request more than once per request:
can_play_response_for calls it, then __contains__ /
_responses (reached via play_response) call it again on the
result. The second invocation sees a request whose auth headers we
already stripped, so a naive recompute yields "no-key" and
overwrites the real fingerprint stored in the header.

This makes can_play_response_for and play_response disagree on
matchability — the former says "yes, we have a stored response for
this" (matching no-key to no-key) and the latter throws
UnhandledHTTPRequestError because it computes a fresh real
fingerprint that doesn't match the stored no-key.

In CI this manifested as ~30 failing tests across guardrails_testing,
audio_testing, batches_testing, image_gen_testing, llm_responses_api,
litellm_router_unit_testing, etc. Skip the recompute when the header
is already set, so re-applying the hook is a no-op.

Adds a regression test that fires the hook twice on the same dict and
asserts the fingerprint stays put.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): drop more redundant docstrings and headers

* test(vcr): enable 24hr cache for ocr_tests and search_tests

These two directories were the only non-dockerized test suites in the
build_and_test workflow that make live LLM/provider API calls but were
not VCR-enabled by this PR. Together they account for 96 tests:

- tests/ocr_tests/ (31): Mistral OCR, Azure AI OCR, Azure Document
  Intelligence, Vertex AI OCR. Pure-unit tests inside the same files
  (e.g. TestAzureDocumentIntelligencePagesParam) make no HTTP calls
  and become benign VCR NOOPs.
- tests/search_tests/ (65): Brave, DataForSEO, DuckDuckGo, Exa,
  Firecrawl, Google PSE, Linkup, Parallel.ai, Perplexity, SearchAPI,
  Searxng, Serper, Tavily.

Both directories use the canonical minimal conftest pattern from
tests/audio_tests/conftest.py with no skip lists. None of the test
files use respx, none assert on per-call upstream non-determinism
(no response1.id != response2.id, no overhead-as-fraction-of-total,
no live polling), so the default match_on tuple should cache cleanly.
If a flake surfaces during the first cassette-recording CI run, we
can add a targeted skip the same way we did for the other dirs.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* [Fix] Team UI: handle legacy dict shape for metadata.guardrails (#27224)

* [Fix] Team UI: handle legacy dict shape for metadata.guardrails

A team can have metadata.guardrails stored as {"modify_guardrails": bool}
(the permission-flag shape introduced in PR #4810) rather than the
expected string[]. The opt-out logic added in PR #25575 calls .filter()
on this field, which throws TypeError on a dict and crashes the team
detail page.

Add a safeGuardrailsList helper that returns [] when the field is not
an array, and route the three read sites through it.

* [Fix] Team UI: inline Array.isArray guards for guardrails metadata

Replace the safeGuardrailsList helper with inline Array.isArray checks
at each call site, and apply the same guard to opted_out_global_guardrails
for consistency. No known legacy dict rows for opted_out_global_guardrails,
but the unguarded `|| []` pattern is the same shape risk.

Six call sites now defended directly: three for metadata.guardrails
and three for metadata.opted_out_global_guardrails.

* chore: update Next.js build artifacts (2026-05-05 22:45 UTC, node v20.20.2) (#27240)

* [Infra] Bump deps (#27157)

* bump: version 0.4.70 → 0.4.71

* bump: version 0.1.39 → 0.1.40

* uv lock

---------

Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: shivam <shivam@berri.ai>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
Co-authored-by: Michael-RZ-Berri <michael@berri.ai>
Co-authored-by: harish-berri <harish@berri.ai>
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
Co-authored-by: Michael Riad Zaky <michaelr@Michaels-MacBook-Air.local>
Co-authored-by: Krrish Dholakia <krrish-berri-2@users.noreply.github.com>
2026-05-05 16:15:03 -07:00

7094 lines
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