Commit graph

98 commits

Author SHA1 Message Date
Sameer Kankute
3b40ac987f
Litellm oss 090626 (#30021)
* fix(mcp): report scoped server name during initialize (#29865)

* fix mcp scoped server name

* Update litellm/proxy/_experimental/mcp_server/mcp_context.py

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

* test(mcp): cover scoped server name in the SSE initialize handler

---------

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

* fix(ui): show all session logs in the drawer, not just the first 50 (#29795)

* fix(ui): show newest session logs first

* test(ui): keep session log pagination coverage

* fix(ui): show all session logs in the drawer, not just the first page

The session detail drawer fetched session logs via sessionSpendLogsCall
without page/page_size, so it only ever received the backend default of one
page (50 rows). Sessions with more than 50 calls had the rest unreachable in
the UI (#29153).

sessionSpendLogsCall now takes page/page_size, and the drawer fetches the
first page, reads total_pages, then fetches the remaining pages and
accumulates them before the existing client-side sort. This keeps the single
continuous list (and the selected-log lookup and keyboard navigation, which
all assume the full session) correct. Fetching is bounded by a page cap, and
the sidebar shows a "showing most recent N" note if a session exceeds it.

The rows are lightweight metadata (the endpoint excludes messages/response),
so the full set is small; request/response bodies are still loaded per log on
demand.

* fix(ui): default session drawer to most recent log, newest first

Open a session with its most recent log selected, and order the sidebar
newest-first to match the all-sessions logs overview. MCP calls stay
grouped last. The latest log by time is computed explicitly, since the
MCP grouping means it is not always the first row.

* Apply fetching pages in batches suggestion from @greptile-apps[bot]

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

* fix(ui): derive session total from accumulated rows when backend omits it

Compute the session total after all pages are fetched, falling back to the
accumulated row count rather than the first page's. Guards the truncation
note against a backend response that omits total but spans multiple pages.

---------

Co-authored-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* fix(proxy): handle Mistral multipart passthrough (#29927)

* fix(proxy): handle Mistral multipart passthrough

* chore: satisfy passthrough ci formatting

* test(proxy): cover Mistral passthrough in CI shard

* fix(vertex_ai): use REP host for context caching on eu/us multi-region endpoints (#29573)

Context caching built the cachedContents URL as
https://{location}-aiplatform.googleapis.com, which is an invalid host for the
eu/us multi-region endpoints and returns 404. The inference path already
resolves these to the REP host (https://aiplatform.{geo}.rep.googleapis.com)
via get_vertex_base_url(); reuse that helper in
_get_token_and_url_context_caching so caching uses the same host as inference.

Adds tests covering the eu/us multi-region cachedContents URLs (v1 and
v1beta1).

Fixes #29571

* Support per-model encrypted content affinity config (#29760)

Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>

* fix: propagate upstream status code in proxy API exception handler (#29402)

* fix: propagate upstream status code in proxy API exception handler

When Google GenAI / Vertex returns a 404 for deprecated or missing
models via streamGenerateContent, the exception was falling through to
a generic handler that defaulted to 500. Now provider exceptions
carrying a valid HTTP status_code correctly propagate it through to
the ProxyException.

* fix: apply black formatting to common_request_processing.py

* fix: tighten status code range to 400-599 and deduplicate ProxyException raise

* fix(tests): use valid vertex_location in context caching tests

Replace "test_location" (contains underscore) with "us-central1" so tests
pass the regex validation added in get_vertex_base_url().

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat(sdk): add xAI OAuth provider (#29866)

* Add xAI OAuth provider

* Update oauth.py

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

* Fix xAI OAuth CI failures

* Add xAI OAuth coverage tests

* Move xAI OAuth coverage tests to core utils

* Address xAI OAuth review comments

* Prevent xAI OAuth api_base token exfiltration

* Treat blank xAI OAuth api keys as absent

* Wrap invalid xAI OAuth JSON responses

* Use xAI OAuth behind explicit flag

---------

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

* fix(proxy) #27734 allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update (#27751)

* fix(proxy): allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update

Fixes #27734

Sending null for budget_duration, team_member_budget,
team_member_budget_duration, team_member_rpm_limit, or
team_member_tpm_limit via /key/update or /team/update returned 200 OK
but silently ignored the null value. The fields remained unchanged in
the database.

Root causes:
- /key/update: prepare_key_update_data() popped budget_duration from the
  update dict but never re-added it (or budget_reset_at) when the value
  was None.
- /team/update: _set_budget_reset_at() only acted when budget_duration
  was non-None, leaving a stale budget_reset_at in the DB.
- /team/update: team_member_* null values bypassed the budget table
  update entirely because should_create_budget() requires at least one
  non-None field.

* test(proxy): cover no-budget-row path in clear_team_member_budget_fields

* fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes (#30028)

* fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes

When output_parse_pii=true on the Anthropic native path (anthropic/claude-*),
response chunks arrive as raw bytes in SSE format. _stream_pii_unmasking was
yielding those bytes unchanged, so <PERSON_1> tokens were never replaced with
the original values before reaching the caller.

Add _unmask_sse_bytes_chunk to parse each data: line, find content_block_delta
/ text_delta events, and apply _unmask_pii_text before re-encoding. Wire it
into _stream_pii_unmasking so bytes chunks are unmasked when pii_tokens exist.

* fix(presidio): handle CRLF line endings and non-ASCII PII in SSE unmask

Strip trailing \r before the [DONE] guard so CRLF-terminated SSE chunks
don't bypass it and silently swallow a JSONDecodeError. Add
ensure_ascii=False to json.dumps so non-ASCII replacement values like
accented names are preserved as UTF-8 on the wire rather than being
\uXXXX-escaped. Add regression tests for both cases.

* feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) (#29925)

* feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses)

Bedrock Mantle serves the Responses API on two upstream paths:
  - gpt frontier models (gpt-5.5 / gpt-5.4) on /openai/v1/responses
  - every other Responses-capable model (e.g. gpt-oss) on the standard /v1/responses

BedrockMantleResponsesAPIConfig gains a `use_openai_path` flag; the provider gate in
utils.py picks the path per model: openai.gpt-* (non gpt-oss) -> /openai/v1/responses;
any model declared mode=responses (price-map entry or user model_info) -> /v1/responses;
everything else returns None and keeps the existing chat-completions emulation.

Adds gpt-5.5 / gpt-5.4 price-map entries, registry wiring, and the routing-matrix tests.

* feat(bedrock_mantle): data-driven frontier routing via use_openai_responses_path

Addresses the Greptile review point that frontier detection should be a
price-map field rather than a hardcoded name match. The gate now routes a
model to /openai/v1/responses when its price-map entry declares
use_openai_responses_path, so a frontier model whose name does not follow the
openai.gpt- convention can be onboarded by JSON alone. The name-convention
check is kept as a fallback that needs no price-map entry, which preserves
zero-change routing for a future gpt-6 before its entry loads. gpt-5.5 / gpt-5.4
get the flag in both price maps. Adds tests for the data-driven flag path and
for the flag presence on the gpt-5.x entries; both branches are mutation-tested.

* test(model_prices): allow use_openai_responses_path in price-map schema

The model_prices_and_context_window.json schema validator
(test_aaamodel_prices_and_context_window_json_is_valid) enforces
additionalProperties: false, so the new use_openai_responses_path flag on the
gpt-5.5 / gpt-5.4 entries failed validation. Add it to the schema as a boolean,
alongside the other supports_* / capability flags.

* Add Tensormesh serverless models to the model cost map (#30037)

* Add Tensormesh serverless models to the model cost map

* Flag reasoning support on the Tensormesh models that expose thinking mode

* fix(proxy): invalidate stale key spend counter after budget reset or manual spend update (#30001)

* fix(proxy): reconcile stale key spend counter after budget reset

* fix(proxy): invalidate stale key spend counter after budget reset or manual spend update

* fix(proxy): remove read-time stale counter reconciliation to prevent budget bypass

* revert: undo unrelated formatting changes in enterprise directory

* test(proxy): add unit test for key spend update invalidating counter

* test(proxy): fix mocked update_data and hash token expectations in unit test

* fix(proxy): use Responses-API transformer in pass-through cost tracking (#29728)

The `elif is_responses:` branch of `openai_passthrough_handler` was
calling the chat-completions `transform_response` on a Responses API
payload. The chat-completions transformer expects `choices: [...]`
in the raw response; the Responses API uses `output: [...]` and
`usage.input_tokens` / `usage.output_tokens` (not
`prompt_tokens` / `completion_tokens`). The result was a
KeyError 'choices' deep inside `convert_to_model_response_object`,
swallowed by the surrounding `except Exception` in the handler, and
the SpendLogs row was written by the fallback path with zeroed-out
tokens, spend, and model.

This bug silently undercounts cost for every successful pass-through
call to either OpenAI's `/v1/responses` or Azure's
`/openai/v1/responses` (deployments configured for the Responses
API). Reproduced 2026-06-04 against a real Azure OpenAI Responses
API deployment proxied through LiteLLM v1.88.0.

Fix: use the dedicated
`OpenAIResponsesAPIConfig.transform_response_api_response` for the
Responses branch. This transformer already exists in LiteLLM
(`litellm/llms/openai/responses/transformation.py`) and knows the
Responses-API on-the-wire shape. `litellm.completion_cost` already
handles `ResponsesAPIResponse` natively with `call_type="responses"`,
so no downstream changes are needed.

Tests:

  test_responses_api_uses_responses_transformer_not_chat_completions
    NEW. Real regression test — exercises the openai_passthrough_handler
    with a real-shaped Responses payload (no `choices`, has `output`
    and Responses-API `usage` keys) and NO mocked `get_provider_config`.
    Pre-fix: raises KeyError 'choices' inside the chat-completions
    transformer (the bug). Post-fix: returns a ResponsesAPIResponse,
    completion_cost is called with call_type="responses" and a
    ResponsesAPIResponse instance (asserted).
    Verified to fail on un-fixed handler + pass on fixed handler
    before commit.

  test_responses_api_cost_tracking
    UPDATED. Old test mocked `get_provider_config` (no longer called
    in the responses branch post-fix). Now mocks the Responses
    transformer directly (`OpenAIResponsesAPIConfig.transform_response_api_response`)
    to test the downstream cost-calc contract.

Out of scope for this PR (separate followup):
  - Recognizing *.cognitiveservices.azure.com (the newer Azure
    OpenAI hostname) in the is_openai_*_route checks. Separate PR.

Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>

* fix(skills): execute DB skills by matching the litellm_skill_ tool name prefix (#30116)

Skill IDs are generated as litellm_skill_<uuid> and the model-facing
tool name is the sanitized skill ID, but the post-call execution gates
in SkillsInjectionHook only ran tools whose name starts with "skill_",
so DB skills were silently returned to the client as raw tool calls.

Fixes #28122.

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

* fix(anthropic): synthesize content_block_start when Responses stream omits output_item.added (#30115)

* fix(team): reserve team budget raises for proxy admins on /team/update (#30030)

The caller's PERSONAL max_budget was the wrong yardstick for /team/update: a
team's spend ceiling has nothing to do with the admin's own key budget. That
comparison was an unintended side effect of reusing _check_user_team_limits()
(which exists for the /team/new path) and broke the UI, which re-sends the
unchanged budget on every save.

New behavior on /team/update for standalone teams:
- A team admin (already authorized via _verify_team_access) may freely KEEP or
  LOWER the team budget, and change models/tpm/rpm, without being gated by their
  personal limits.
- GROWING a team's spend ceiling is a budget-authority action reserved for proxy
  admins -> 403 for team admins. "Growing" covers both raising max_budget above
  the team's current finite value and removing the cap entirely (max_budget=null,
  detected via model_fields_set so an explicit null is distinguished from an
  omitted field). For a team that currently has no cap, setting a finite value is
  a restriction and is allowed.
- Org-scoped teams remain governed by _check_org_team_limits() (capped by the
  org budget).

Also reverts the #29525 existing_team_max_budget workaround in
_check_user_team_limits() back to the create-only form; /team/new still enforces
the creator's personal caps.

docs(access_control): resolve the contradiction in the team-admin section —
team admins can keep/lower the budget and manage rate limits/models, but cannot
raise the team budget (proxy-admin only).

tests: unit + behavior coverage for raise-blocked, cap-removal-blocked (team
admin), raise/removal allowed (proxy admin), uncapped-team restriction allowed,
keep/lower/resend allowed, and unchanged create-path guards.

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

* test(ui): data-driven App Router migration E2E smoke (default + server-root-path) (#29974)

* test(ui): add a data-driven App Router migration E2E smoke

Add a growing Playwright smoke for migrated pages: for each segment it deep-links
to the path route, asserts the URL and that the dashboard shell rendered, then
clicks off to a legacy page and asserts navigation still works. Driven by
e2e_tests/fixtures/migratedPages.ts, so adding a page is one line.

Runs in two situations against the same proxy: the default mount (npm run
e2e:migration) and a non-root SERVER_ROOT_PATH mount (npm run e2e:migration:root).
globalSetup now logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin storage
state is valid under a prefix. Seeded with api-reference; append the rest as their
migrations merge.

* test(ui): support headed slow-motion + watch pauses in the migration smoke

Honor SLOWMO in the server-root-path config (the default config already did),
and add an env-gated E2E_WATCH_MS pause so a headed run lingers on each state.
Both are no-ops by default, so CI behavior is unchanged.

* test(ui): make the migration smoke a sidebar-click user journey

Rework the smoke from deep-linking to a real navigation journey: start at the
landing page, click the migrated page in the sidebar (expanding submenus for
nested items), assert the path route rendered, reload it (the check a wrong
server_root_path breaks), bounce to a legacy page and back, and — once two pages
are migrated — navigate directly between two migrated pages. Verifies via URL +
shell render, driven by the same fixture list.

* test(ui): address review on the migration smoke

Escape ROOT and segment before interpolating them into RegExp URL matchers so a
future segment containing regex metacharacters can't silently widen the match.
Make the server-root-path config fail fast when SERVER_ROOT_PATH is unset instead
of silently re-running the default mount and passing without exercising the prefix.

* test(ui): drop unused watch helper and fix stale smoke README

* test(ui): run the migration smoke under a server root path in CI

* test(ui): harden + instrument the server-root-path proxy reboot in CI

* test(ui): run the server-root-path migration smoke as its own CI job

Replace the in-place proxy reboot in e2e_ui_testing with a dedicated
e2e_ui_testing_server_root_path job that boots the proxy once with
SERVER_ROOT_PATH=/litellm, matching how every other proxy variant in the
config gets its own job rather than killing and relaunching the live proxy.

The reboot was failing deterministically: after pkill -9 and relaunch the
prefixed proxy never came back up on :4000 (connection refused), so the smoke
never ran. The readiness step that was supposed to surface the cause could
never reach its boot-log tail because CircleCI runs steps under bash -eo
pipefail and the preceding `curl -sv ... | tail` aborted the step with curl's
exit 7. Booting the proxy as the job's own background step lets any boot crash
land in that step's log instead of being swallowed.

The default e2e_ui_testing job is unchanged aside from dropping the reboot,
prefixed-readiness, and prefixed-smoke steps; the migration smoke still runs at
the root mount there via the default Playwright config.

* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232)

* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through

* test: mock post_call_response_headers_hook in audio speech route tests

* chore(ui): remove dead App Router route stubs under (dashboard) (#30045)

models-and-endpoints, organizations, and virtual-keys each had a page.tsx
route under (dashboard)/ that is not in MIGRATED_PAGES, so the sidebar and
deep links never resolve to it and the route is unreachable. Each was a thin
wrapper that handed the shared view empty or no-op props (empty modelData with
a no-op setModelData, hardcoded empty organizations, no-op
setUserRole/setUserEmail), so reaching one would render a degraded page in any
case. The real wrapper belongs in the PR that flips each page into
MIGRATED_PAGES, written with eyes on it and a test

This continues the dead-scaffolding cleanup from #28891. The shared components
these wrappers rendered (ModelsAndEndpointsView, OrganizationFilters) stay,
since the legacy ?page= switch in app/page.tsx and src/components still import
them

* fix(ui/mcp): reset OAuth state on create-server modal close so a prior server's token no longer leaks into the next add-server session (#30000)

* fix(ui/mcp): reset OAuth hook state on modal close so a prior server's token no longer leaks into the next add-server session

* fix(ui/mcp): clear in-flight OAuth guard on reset and reset form/tools on modal close so nothing leaks on a parent-driven dismiss

* fix(mcp): allow team access-group grants in OAuth authorize/token access check (#30041)

* fix(mcp): honor team access-group grants in OAuth authorize/token access check

* test(mcp): mock build_effective_auth_contexts in non-admin authorize tests for isolation

* docs(security): require a reproduction video for vulnerability reports (#30048) (#30063)

With AI models capable of automated vulnerability discovery now publicly
available, we expect a large increase in report volume, much of it
unverified. Requiring a video of the exploit running against a live
instance raises the bar for submissions and keeps triage focused on
reproducible issues. Reports without a video will be closed and reopened
if one is added later.

Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>

* feat(ui): add admin flag to disable in-product UI nudges for everyone (#29796)

* feat(ui): add admin flag to disable in-product UI nudges for everyone

Admins can now suppress the survey and Claude Code feedback popups for
all users via a single disable_ui_nudges UI setting, instead of relying
on each user dismissing them individually.

* fix(ui): suppress nudges while ui settings are loading

Gate nudgesDisabled on the ui-settings loading state so an admin with
disable_ui_nudges on doesn't see the survey prompt flash, and the
getInProductNudgesCall fetch doesn't fire, on a cold page load before
the flag resolves. Falls back to showing nudges if the fetch errors.

* test(ui): wrap CreateKeyPage test in QueryClientProvider

page.tsx now calls useUISettings (react-query), which needs a
QueryClient that layout.tsx supplies in production but the test did
not. Add the provider and mock getUiSettings so the query resolves.

* chore(ui): remove dead dashboard files and unused dependencies (#30047)

* chore(ui): remove dead dashboard files and unused dependencies

knip flagged seven orphaned source/config files with no importers and
five declared dependencies that nothing in the tree uses. Removing them
shrinks the dashboard bundle's source surface and keeps the manifest
honest; vite stays installed transitively via vitest, so test tooling is
unaffected.

* fix(ci): restore serverRootPath.config.ts referenced by SERVER_ROOT_PATH workflow

The dead-code sweep removed e2e_tests/serverRootPath.config.ts, but its spec
(tests/login/serverRootPathRedirect.spec.ts) and the test_server_root_path.yml
workflow step still depend on it, so the redirect e2e job failed to load a
config that no longer existed.

* fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009)

* fix(proxy): authorize batch files using upload target_model_names (LIT-3593)

After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead.

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

* fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)

Restores the reverse-lookup for the JSONL body.model fallback path so that
legacy/pre-target_model_names managed files still map stripped provider IDs
back to proxy aliases before auth. Also cleans up redundant `or None`.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)"

This reverts commit 30d2e96f77.

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI (#30064)

* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI

Adds cost map entries for claude-fable-5 ($10/$50 per MTok, 1M context,
128K output, adaptive thinking only) on the Anthropic API, Bedrock
converse (base, global, and us/eu geo inference profiles at the 10%
regional premium), Vertex AI, and Azure AI (Microsoft Foundry, which
serves Fable 5 with the full 1M context window unlike Opus 4.8).

Registers anthropic.claude-fable-5 in BEDROCK_CONVERSE_MODELS, lists the
model in the setup wizard, and extends the reasoning effort e2e grid.
The Bedrock, Vertex, and Azure grid cells carry fail_reason markers
until the CI accounts are provisioned: Bedrock needs the provider data
sharing opt-in Fable 5 requires, and the Foundry resource needs a
claude-fable-5 deployment.

The first-party entry carries provider_specific_entry {us: 1.1} for the
inference_geo premium and deliberately no fast multiplier since Fable 5
has no fast mode.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Drop removed sampling params for Claude 4.7+ when drop_params is set

Fable 5, Opus 4.7, and Opus 4.8 removed sampling params: the API rejects
top_p, top_k, and any temperature other than 1 with a 400. LiteLLM was
forwarding them even with drop_params enabled because the Anthropic and
Bedrock converse transformations passed temperature/top_p through
unconditionally.

Mirror the GPT-5/o-series handling: temperature=1 still passes through,
other values and any top_p are dropped when drop_params is set, and
without drop_params a clean client-side UnsupportedParamsError tells the
caller how to opt in, instead of surfacing the raw provider error.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Drive sampling param gating from the cost map and cover top_k

Greptile review follow-ups on the sampling param fix: the restriction for
Fable 5 / Opus 4.7 / 4.8 is now declared as supports_sampling_params: false
on every affected cost map entry (perplexity excluded; that route is
OpenAI-compatible and maps sampling params upstream) and read back through
a tri-state map lookup, keeping the name check only as a fallback for
provider-routed ids whose hosted map entries predate the flag, the same
layering supports_adaptive_thinking uses. top_k bypasses map_openai_params
as a provider-specific kwarg, so it is gated at the shared
AnthropicConfig.transform_request boundary (direct, Bedrock invoke, Vertex,
Azure) and in the Bedrock converse _handle_top_k_value path, with
drop_params threaded through the converse transform helpers.

Also updates the reasoning effort grid cell count assertion for the four
Fable 5 rows added on this branch (29 x 11 cells).

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Declare supports_sampling_params in the cost map schema

The model map validation schema uses additionalProperties: false, so the
new flag must be declared for the 28 entries that carry it; this was the
one failing job (misc / Run tests) on the previous commit.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* fix(bedrock): gate top_k=0 on converse to match Anthropic boundary

Truthiness check let top_k=0 silently disappear on models that removed
sampling params, while AnthropicConfig.transform_request treats 0 as
present and raises UnsupportedParamsError (or drops when drop_params is
set). Switch to 'is not None' so converse, direct Anthropic, invoke,
Vertex, and Azure all behave the same for top_k=0.

---------

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

* fix(anthropic): avoid index -1 content_block_delta in messages stream

When a /v1/messages request is routed through the Responses API
adapter, AnthropicResponsesStreamWrapper only emits content_block_start
on response.output_item.added. Some upstreams (LMStudio for example)
never send that event, so the text delta handler fell back to
_current_block_index, which starts at -1, and clients received
content_block_delta events with index -1 and no preceding
content_block_start. Anthropic SDKs then fail with "text part -1 not
found"

The text delta handler now synthesizes a content_block_start with a
fresh block index whenever the delta references an unregistered item_id
or no block is open yet, and registers the item_id so follow-up deltas
reuse the same index

Addresses the /v1/messages defect in #27442

* Make test sys.path shim resolve relative to the file, not the CWD

os.path.abspath("../../../../../../..") depends on where pytest is
invoked from; anchoring on os.path.dirname(__file__) makes the import
work from any working directory. Also corrects the depth: the repo root
is six levels above this file, not seven.

---------

Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: tin-berri <tin@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>

* fix: enable compact-2026-01-12 beta header for vertex_ai provider (#30114)

* fix(team): reserve team budget raises for proxy admins on /team/update (#30030)

The caller's PERSONAL max_budget was the wrong yardstick for /team/update: a
team's spend ceiling has nothing to do with the admin's own key budget. That
comparison was an unintended side effect of reusing _check_user_team_limits()
(which exists for the /team/new path) and broke the UI, which re-sends the
unchanged budget on every save.

New behavior on /team/update for standalone teams:
- A team admin (already authorized via _verify_team_access) may freely KEEP or
  LOWER the team budget, and change models/tpm/rpm, without being gated by their
  personal limits.
- GROWING a team's spend ceiling is a budget-authority action reserved for proxy
  admins -> 403 for team admins. "Growing" covers both raising max_budget above
  the team's current finite value and removing the cap entirely (max_budget=null,
  detected via model_fields_set so an explicit null is distinguished from an
  omitted field). For a team that currently has no cap, setting a finite value is
  a restriction and is allowed.
- Org-scoped teams remain governed by _check_org_team_limits() (capped by the
  org budget).

Also reverts the #29525 existing_team_max_budget workaround in
_check_user_team_limits() back to the create-only form; /team/new still enforces
the creator's personal caps.

docs(access_control): resolve the contradiction in the team-admin section —
team admins can keep/lower the budget and manage rate limits/models, but cannot
raise the team budget (proxy-admin only).

tests: unit + behavior coverage for raise-blocked, cap-removal-blocked (team
admin), raise/removal allowed (proxy admin), uncapped-team restriction allowed,
keep/lower/resend allowed, and unchanged create-path guards.

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

* test(ui): data-driven App Router migration E2E smoke (default + server-root-path) (#29974)

* test(ui): add a data-driven App Router migration E2E smoke

Add a growing Playwright smoke for migrated pages: for each segment it deep-links
to the path route, asserts the URL and that the dashboard shell rendered, then
clicks off to a legacy page and asserts navigation still works. Driven by
e2e_tests/fixtures/migratedPages.ts, so adding a page is one line.

Runs in two situations against the same proxy: the default mount (npm run
e2e:migration) and a non-root SERVER_ROOT_PATH mount (npm run e2e:migration:root).
globalSetup now logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin storage
state is valid under a prefix. Seeded with api-reference; append the rest as their
migrations merge.

* test(ui): support headed slow-motion + watch pauses in the migration smoke

Honor SLOWMO in the server-root-path config (the default config already did),
and add an env-gated E2E_WATCH_MS pause so a headed run lingers on each state.
Both are no-ops by default, so CI behavior is unchanged.

* test(ui): make the migration smoke a sidebar-click user journey

Rework the smoke from deep-linking to a real navigation journey: start at the
landing page, click the migrated page in the sidebar (expanding submenus for
nested items), assert the path route rendered, reload it (the check a wrong
server_root_path breaks), bounce to a legacy page and back, and — once two pages
are migrated — navigate directly between two migrated pages. Verifies via URL +
shell render, driven by the same fixture list.

* test(ui): address review on the migration smoke

Escape ROOT and segment before interpolating them into RegExp URL matchers so a
future segment containing regex metacharacters can't silently widen the match.
Make the server-root-path config fail fast when SERVER_ROOT_PATH is unset instead
of silently re-running the default mount and passing without exercising the prefix.

* test(ui): drop unused watch helper and fix stale smoke README

* test(ui): run the migration smoke under a server root path in CI

* test(ui): harden + instrument the server-root-path proxy reboot in CI

* test(ui): run the server-root-path migration smoke as its own CI job

Replace the in-place proxy reboot in e2e_ui_testing with a dedicated
e2e_ui_testing_server_root_path job that boots the proxy once with
SERVER_ROOT_PATH=/litellm, matching how every other proxy variant in the
config gets its own job rather than killing and relaunching the live proxy.

The reboot was failing deterministically: after pkill -9 and relaunch the
prefixed proxy never came back up on :4000 (connection refused), so the smoke
never ran. The readiness step that was supposed to surface the cause could
never reach its boot-log tail because CircleCI runs steps under bash -eo
pipefail and the preceding `curl -sv ... | tail` aborted the step with curl's
exit 7. Booting the proxy as the job's own background step lets any boot crash
land in that step's log instead of being swallowed.

The default e2e_ui_testing job is unchanged aside from dropping the reboot,
prefixed-readiness, and prefixed-smoke steps; the migration smoke still runs at
the root mount there via the default Playwright config.

* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232)

* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through

* test: mock post_call_response_headers_hook in audio speech route tests

* chore(ui): remove dead App Router route stubs under (dashboard) (#30045)

models-and-endpoints, organizations, and virtual-keys each had a page.tsx
route under (dashboard)/ that is not in MIGRATED_PAGES, so the sidebar and
deep links never resolve to it and the route is unreachable. Each was a thin
wrapper that handed the shared view empty or no-op props (empty modelData with
a no-op setModelData, hardcoded empty organizations, no-op
setUserRole/setUserEmail), so reaching one would render a degraded page in any
case. The real wrapper belongs in the PR that flips each page into
MIGRATED_PAGES, written with eyes on it and a test

This continues the dead-scaffolding cleanup from #28891. The shared components
these wrappers rendered (ModelsAndEndpointsView, OrganizationFilters) stay,
since the legacy ?page= switch in app/page.tsx and src/components still import
them

* fix(ui/mcp): reset OAuth state on create-server modal close so a prior server's token no longer leaks into the next add-server session (#30000)

* fix(ui/mcp): reset OAuth hook state on modal close so a prior server's token no longer leaks into the next add-server session

* fix(ui/mcp): clear in-flight OAuth guard on reset and reset form/tools on modal close so nothing leaks on a parent-driven dismiss

* fix(mcp): allow team access-group grants in OAuth authorize/token access check (#30041)

* fix(mcp): honor team access-group grants in OAuth authorize/token access check

* test(mcp): mock build_effective_auth_contexts in non-admin authorize tests for isolation

* docs(security): require a reproduction video for vulnerability reports (#30048) (#30063)

With AI models capable of automated vulnerability discovery now publicly
available, we expect a large increase in report volume, much of it
unverified. Requiring a video of the exploit running against a live
instance raises the bar for submissions and keeps triage focused on
reproducible issues. Reports without a video will be closed and reopened
if one is added later.

Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>

* feat(ui): add admin flag to disable in-product UI nudges for everyone (#29796)

* feat(ui): add admin flag to disable in-product UI nudges for everyone

Admins can now suppress the survey and Claude Code feedback popups for
all users via a single disable_ui_nudges UI setting, instead of relying
on each user dismissing them individually.

* fix(ui): suppress nudges while ui settings are loading

Gate nudgesDisabled on the ui-settings loading state so an admin with
disable_ui_nudges on doesn't see the survey prompt flash, and the
getInProductNudgesCall fetch doesn't fire, on a cold page load before
the flag resolves. Falls back to showing nudges if the fetch errors.

* test(ui): wrap CreateKeyPage test in QueryClientProvider

page.tsx now calls useUISettings (react-query), which needs a
QueryClient that layout.tsx supplies in production but the test did
not. Add the provider and mock getUiSettings so the query resolves.

* chore(ui): remove dead dashboard files and unused dependencies (#30047)

* chore(ui): remove dead dashboard files and unused dependencies

knip flagged seven orphaned source/config files with no importers and
five declared dependencies that nothing in the tree uses. Removing them
shrinks the dashboard bundle's source surface and keeps the manifest
honest; vite stays installed transitively via vitest, so test tooling is
unaffected.

* fix(ci): restore serverRootPath.config.ts referenced by SERVER_ROOT_PATH workflow

The dead-code sweep removed e2e_tests/serverRootPath.config.ts, but its spec
(tests/login/serverRootPathRedirect.spec.ts) and the test_server_root_path.yml
workflow step still depend on it, so the redirect e2e job failed to load a
config that no longer existed.

* fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009)

* fix(proxy): authorize batch files using upload target_model_names (LIT-3593)

After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead.

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

* fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)

Restores the reverse-lookup for the JSONL body.model fallback path so that
legacy/pre-target_model_names managed files still map stripped provider IDs
back to proxy aliases before auth. Also cleans up redundant `or None`.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)"

This reverts commit 30d2e96f77.

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI (#30064)

* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI

Adds cost map entries for claude-fable-5 ($10/$50 per MTok, 1M context,
128K output, adaptive thinking only) on the Anthropic API, Bedrock
converse (base, global, and us/eu geo inference profiles at the 10%
regional premium), Vertex AI, and Azure AI (Microsoft Foundry, which
serves Fable 5 with the full 1M context window unlike Opus 4.8).

Registers anthropic.claude-fable-5 in BEDROCK_CONVERSE_MODELS, lists the
model in the setup wizard, and extends the reasoning effort e2e grid.
The Bedrock, Vertex, and Azure grid cells carry fail_reason markers
until the CI accounts are provisioned: Bedrock needs the provider data
sharing opt-in Fable 5 requires, and the Foundry resource needs a
claude-fable-5 deployment.

The first-party entry carries provider_specific_entry {us: 1.1} for the
inference_geo premium and deliberately no fast multiplier since Fable 5
has no fast mode.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Drop removed sampling params for Claude 4.7+ when drop_params is set

Fable 5, Opus 4.7, and Opus 4.8 removed sampling params: the API rejects
top_p, top_k, and any temperature other than 1 with a 400. LiteLLM was
forwarding them even with drop_params enabled because the Anthropic and
Bedrock converse transformations passed temperature/top_p through
unconditionally.

Mirror the GPT-5/o-series handling: temperature=1 still passes through,
other values and any top_p are dropped when drop_params is set, and
without drop_params a clean client-side UnsupportedParamsError tells the
caller how to opt in, instead of surfacing the raw provider error.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Drive sampling param gating from the cost map and cover top_k

Greptile review follow-ups on the sampling param fix: the restriction for
Fable 5 / Opus 4.7 / 4.8 is now declared as supports_sampling_params: false
on every affected cost map entry (perplexity excluded; that route is
OpenAI-compatible and maps sampling params upstream) and read back through
a tri-state map lookup, keeping the name check only as a fallback for
provider-routed ids whose hosted map entries predate the flag, the same
layering supports_adaptive_thinking uses. top_k bypasses map_openai_params
as a provider-specific kwarg, so it is gated at the shared
AnthropicConfig.transform_request boundary (direct, Bedrock invoke, Vertex,
Azure) and in the Bedrock converse _handle_top_k_value path, with
drop_params threaded through the converse transform helpers.

Also updates the reasoning effort grid cell count assertion for the four
Fable 5 rows added on this branch (29 x 11 cells).

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Declare supports_sampling_params in the cost map schema

The model map validation schema uses additionalProperties: false, so the
new flag must be declared for the 28 entries that carry it; this was the
one failing job (misc / Run tests) on the previous commit.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* fix(bedrock): gate top_k=0 on converse to match Anthropic boundary

Truthiness check let top_k=0 silently disappear on models that removed
sampling params, while AnthropicConfig.transform_request treats 0 as
present and raises UnsupportedParamsError (or drops when drop_params is
set). Switch to 'is not None' so converse, direct Anthropic, invoke,
Vertex, and Azure all behave the same for top_k=0.

---------

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

* fix: enable compact-2026-01-12 beta header for vertex_ai provider

The vertex_ai block in anthropic_beta_headers_config.json mapped
compact-2026-01-12 to null, so update_headers_with_filtered_beta
stripped the header before the request reached Vertex while the
compact_20260112 context edit stayed in the body, and Vertex rejected
the request with HTTP 400. Vertex rawPredict accepts the header, and
the bedrock and databricks blocks already forward it. Mirrors #21867,
which enabled context-1m-2025-08-07 for vertex_ai the same way.

Fixes #27290.

---------

Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: tin-berri <tin@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>

* fix(proxy): coerce litellm_settings.max_budget env var to float (#30113)

* fix(team): reserve team budget raises for proxy admins on /team/update (#30030)

The caller's PERSONAL max_budget was the wrong yardstick for /team/update: a
team's spend ceiling has nothing to do with the admin's own key budget. That
comparison was an unintended side effect of reusing _check_user_team_limits()
(which exists for the /team/new path) and broke the UI, which re-sends the
unchanged budget on every save.

New behavior on /team/update for standalone teams:
- A team admin (already authorized via _verify_team_access) may freely KEEP or
  LOWER the team budget, and change models/tpm/rpm, without being gated by their
  personal limits.
- GROWING a team's spend ceiling is a budget-authority action reserved for proxy
  admins -> 403 for team admins. "Growing" covers both raising max_budget above
  the team's current finite value and removing the cap entirely (max_budget=null,
  detected via model_fields_set so an explicit null is distinguished from an
  omitted field). For a team that currently has no cap, setting a finite value is
  a restriction and is allowed.
- Org-scoped teams remain governed by _check_org_team_limits() (capped by the
  org budget).

Also reverts the #29525 existing_team_max_budget workaround in
_check_user_team_limits() back to the create-only form; /team/new still enforces
the creator's personal caps.

docs(access_control): resolve the contradiction in the team-admin section —
team admins can keep/lower the budget and manage rate limits/models, but cannot
raise the team budget (proxy-admin only).

tests: unit + behavior coverage for raise-blocked, cap-removal-blocked (team
admin), raise/removal allowed (proxy admin), uncapped-team restriction allowed,
keep/lower/resend allowed, and unchanged create-path guards.

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

* test(ui): data-driven App Router migration E2E smoke (default + server-root-path) (#29974)

* test(ui): add a data-driven App Router migration E2E smoke

Add a growing Playwright smoke for migrated pages: for each segment it deep-links
to the path route, asserts the URL and that the dashboard shell rendered, then
clicks off to a legacy page and asserts navigation still works. Driven by
e2e_tests/fixtures/migratedPages.ts, so adding a page is one line.

Runs in two situations against the same proxy: the default mount (npm run
e2e:migration) and a non-root SERVER_ROOT_PATH mount (npm run e2e:migration:root).
globalSetup now logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin storage
state is valid under a prefix. Seeded with api-reference; append the rest as their
migrations merge.

* test(ui): support headed slow-motion + watch pauses in the migration smoke

Honor SLOWMO in the server-root-path config (the default config already did),
and add an env-gated E2E_WATCH_MS pause so a headed run lingers on each state.
Both are no-ops by default, so CI behavior is unchanged.

* test(ui): make the migration smoke a sidebar-click user journey

Rework the smoke from deep-linking to a real navigation journey: start at the
landing page, click the migrated page in the sidebar (expanding submenus for
nested items), assert the path route rendered, reload it (the check a wrong
server_root_path breaks), bounce to a legacy page and back, and — once two pages
are migrated — navigate directly between two migrated pages. Verifies via URL +
shell render, driven by the same fixture list.

* test(ui): address review on the migration smoke

Escape ROOT and segment before interpolating them into RegExp URL matchers so a
future segment containing regex metacharacters can't silently widen the match.
Make the server-root-path config fail fast when SERVER_ROOT_PATH is unset instead
of silently re-running the default mount and passing without exercising the prefix.

* test(ui): drop unused watch helper and fix stale smoke README

* test(ui): run the migration smoke under a server root path in CI

* test(ui): harden + instrument the server-root-path proxy reboot in CI

* test(ui): run the server-root-path migration smoke as its own CI job

Replace the in-place proxy reboot in e2e_ui_testing with a dedicated
e2e_ui_testing_server_root_path job that boots the proxy once with
SERVER_ROOT_PATH=/litellm, matching how every other proxy variant in the
config gets its own job rather than killing and relaunching the live proxy.

The reboot was failing deterministically: after pkill -9 and relaunch the
prefixed proxy never came back up on :4000 (connection refused), so the smoke
never ran. The readiness step that was supposed to surface the cause could
never reach its boot-log tail because CircleCI runs steps under bash -eo
pipefail and the preceding `curl -sv ... | tail` aborted the step with curl's
exit 7. Booting the proxy as the job's own background step lets any boot crash
land in that step's log instead of being swallowed.

The default e2e_ui_testing job is unchanged aside from dropping the reboot,
prefixed-readiness, and prefixed-smoke steps; the migration smoke still runs at
the root mount there via the default Playwright config.

* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232)

* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through

* test: mock post_call_response_headers_hook in audio speech route tests

* chore(ui): remove dead App Router route stubs under (dashboard) (#30045)

models-and-endpoints, organizations, and virtual-keys each had a page.tsx
route under (dashboard)/ that is not in MIGRATED_PAGES, so the sidebar and
deep links never resolve to it and the route is unreachable. Each was a thin
wrapper that handed the shared view empty or no-op props (empty modelData with
a no-op setModelData, hardcoded empty organizations, no-op
setUserRole/setUserEmail), so reaching one would render a degraded page in any
case. The real wrapper belongs in the PR that flips each page into
MIGRATED_PAGES, written with eyes on it and a test

This continues the dead-scaffolding cleanup from #28891. The shared components
these wrappers rendered (ModelsAndEndpointsView, OrganizationFilters) stay,
since the legacy ?page= switch in app/page.tsx and src/components still import
them

* fix(ui/mcp): reset OAuth state on create-server modal close so a prior server's token no longer leaks into the next add-server session (#30000)

* fix(ui/mcp): reset OAuth hook state on modal close so a prior server's token no longer leaks into the next add-server session

* fix(ui/mcp): clear in-flight OAuth guard on reset and reset form/tools on modal close so nothing leaks on a parent-driven dismiss

* fix(mcp): allow team access-group grants in OAuth authorize/token access check (#30041)

* fix(mcp): honor team access-group grants in OAuth authorize/token access check

* test(mcp): mock build_effective_auth_contexts in non-admin authorize tests for isolation

* docs(security): require a reproduction video for vulnerability reports (#30048) (#30063)

With AI models capable of automated vulnerability discovery now publicly
available, we expect a large increase in report volume, much of it
unverified. Requiring a video of the exploit running against a live
instance raises the bar for submissions and keeps triage focused on
reproducible issues. Reports without a video will be closed and reopened
if one is added later.

Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>

* feat(ui): add admin flag to disable in-product UI nudges for everyone (#29796)

* feat(ui): add admin flag to disable in-product UI nudges for everyone

Admins can now suppress the survey and Claude Code feedback popups for
all users via a single disable_ui_nudges UI setting, instead of relying
on each user dismissing them individually.

* fix(ui): suppress nudges while ui settings are loading

Gate nudgesDisabled on the ui-settings loading state so an admin with
disable_ui_nudges on doesn't see the survey prompt flash, and the
getInProductNudgesCall fetch doesn't fire, on a cold page load before
the flag resolves. Falls back to showing nudges if the fetch errors.

* test(ui): wrap CreateKeyPage test in QueryClientProvider

page.tsx now calls useUISettings (react-query), which needs a
QueryClient that layout.tsx supplies in production but the test did
not. Add the provider and mock getUiSettings so the query resolves.

* chore(ui): remove dead dashboard files and unused dependencies (#30047)

* chore(ui): remove dead dashboard files and unused dependencies

knip flagged seven orphaned source/config files with no importers and
five declared dependencies that nothing in the tree uses. Removing them
shrinks the dashboard bundle's source surface and keeps the manifest
honest; vite stays installed transitively via vitest, so test tooling is
unaffected.

* fix(ci): restore serverRootPath.config.ts referenced by SERVER_ROOT_PATH workflow

The dead-code sweep removed e2e_tests/serverRootPath.config.ts, but its spec
(tests/login/serverRootPathRedirect.spec.ts) and the test_server_root_path.yml
workflow step still depend on it, so the redirect e2e job failed to load a
config that no longer existed.

* fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009)

* fix(proxy): authorize batch files using upload target_model_names (LIT-3593)

After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead.

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

* fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)

Restores the reverse-lookup for the JSONL body.model fallback path so that
legacy/pre-target_model_names managed files still map stripped provider IDs
back to proxy aliases before auth. Also cleans up redundant `or None`.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)"

This reverts commit 30d2e96f77.

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI (#30064)

* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI

Adds cost map entries for claude-fable-5 ($10/$50 per MTok, 1M context,
128K output, adaptive thinking only) on the Anthropic API, Bedrock
converse (base, global, and us/eu geo inference profiles at the 10%
regional premium), Vertex AI, and Azure AI (Microsoft Foundry, which
serves Fable 5 with the full 1M context window unlike Opus 4.8).

Registers anthropic.claude-fable-5 in BEDROCK_CONVERSE_MODELS, lists the
model in the setup wizard, and extends the reasoning effort e2e grid.
The Bedrock, Vertex, and Azure grid cells carry fail_reason markers
until the CI accounts are provisioned: Bedrock needs the provider data
sharing opt-in Fable 5 requires, and the Foundry resource needs a
claude-fable-5 deployment.

The first-party entry carries provider_specific_entry {us: 1.1} for the
inference_geo premium and deliberately no fast multiplier since Fable 5
has no fast mode.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Drop removed sampling params for Claude 4.7+ when drop_params is set

Fable 5, Opus 4.7, and Opus 4.8 removed sampling params: the API rejects
top_p, top_k, and any temperature other than 1 with a 400. LiteLLM was
forwarding them even with drop_params enabled because the Anthropic and
Bedrock converse transformations passed temperature/top_p through
unconditionally.

Mirror the GPT-5/o-series handling: temperature=1 still passes through,
other values and any top_p are dropped when drop_params is set, and
without drop_params a clean client-side UnsupportedParamsError tells the
caller how to opt in, instead of surfacing the raw provider error.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Drive sampling param gating from the cost map and cover top_k

Greptile review follow-ups on the sampling param fix: the restriction for
Fable 5 / Opus 4.7 / 4.8 is now declared as supports_sampling_params: false
on every affected cost map entry (perplexity excluded; that route is
OpenAI-compatible and maps sampling params upstream) and read back through
a tri-state map lookup, keeping the name check only as a fallback for
provider-routed ids whose hosted map entries predate the flag, the same
layering supports_adaptive_thinking uses. top_k bypasses map_openai_params
as a provider-specific kwarg, so it is gated at the shared
AnthropicConfig.transform_request boundary (direct, Bedrock invoke, Vertex,
Azure) and in the Bedrock converse _handle_top_k_value path, with
drop_params threaded through the converse transform helpers.

Also updates the reasoning effort grid cell count assertion for the four
Fable 5 rows added on this branch (29 x 11 cells).

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Declare supports_sampling_params in the cost map schema

The model map validation schema uses additionalProperties: false, so the
new flag must be declared for the 28 entries that carry it; this was the
one failing job (misc / Run tests) on the previous commit.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* fix(bedrock): gate top_k=0 on converse to match Anthropic boundary

Truthiness check let top_k=0 silently disappear on models that removed
sampling params, while AnthropicConfig.transform_request treats 0 as
present and raises UnsupportedParamsError (or drops when drop_params is
set). Switch to 'is not None' so converse, direct Anthropic, invoke,
Vertex, and Azure all behave the same for top_k=0.

---------

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

* fix(proxy): coerce litellm_settings.max_budget env var to float

When max_budget is set in litellm_settings via os.environ/MAX_BUDGET,
the env var resolves to a string and the generic setattr branch in
ProxyConfig.load_config stored it as-is, so the startup check
litellm.max_budget > 0 raised TypeError. The earlier fix (#23855) only
covered the CLI initialize() path. Coerce the value to float in the
settings loop, matching the existing max_internal_user_budget handling.

Fixes #26696.

---------

Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: tin-berri <tin@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>

* fix(router): don't drop bedrock pass-through deployments using IAM credentials (#30111)

* Fix Bedrock passthrough deployment dropped when using IAM credentials

Bedrock deployments with use_in_pass_through enabled and IAM/OIDC auth
(aws_role_name, no api_key) hit the generic pass-through branch in
Router._initialize_deployment_for_pass_through, which calls
set_pass_through_credentials and raises "api_key is required". The
exception drops the deployment from the router entirely, breaking both
passthrough and normal routing for that model.

Skip the credential store write when no api_key is set; the bedrock
passthrough route resolves AWS credentials at request time via
BedrockConverseLLM.get_credentials(), not the passthrough credential
store, so there is nothing to register here.

Fixes #27728.

* Reset passthrough credentials singleton before api_key credential test

The test reads the module-level passthrough_endpoint_router singleton,
so a stale "openai" entry written by an earlier test in the same
process could make the assertion pass without exercising the code path.
Clearing the credentials dict up front makes the test order-independent.

* fix(sdk): stop mirroring reasoning_content in provider_specific_fields (#30110)

The dict-to-response conversion path mirrored reasoning_content into
provider_specific_fields, while live provider transforms (Anthropic's
_build_provider_specific_fields) only set it top-level on the Message.
Cache-replayed messages therefore serialized differently from live
ones, breaking disk cache key stability for multi-turn conversations
with extended thinking.

The mirror was added for DeepSeek before Message.reasoning_content
existed as a top-level attribute. The top-level field is still set by
the converter, so DeepSeek's request-side promotion is unaffected.

Fixes #27337.

* fix(mcp): coerce mcp_server_cost_info values to float at ingest (#30109)

* fix(mcp): coerce mcp_server_cost_info values to float at ingest

YAML 1.1 parses scientific notation without a decimal point
(e.g. 7e-05) as a string, and MCPServerCostInfo is a TypedDict with no
runtime validation, so a string-typed default_cost_per_query from
config.yaml flowed through the proxy untouched and crashed the MCP
server settings page with '.toFixed is not a function'. Normalize
mcp_server_cost_info on both the config and DB load paths, dropping
non-numeric values with a warning instead of failing the server load.

Fixes #27097.

* fix(mcp): drop non-numeric default_cost_per_query instead of nulling it

Keeping the key with a None value still exposes a null to the UI,
which can crash .toFixed formatting when the consumer checks key
existence rather than truthiness. Delete the key on coercion failure,
matching how non-numeric per-tool cost entries are already omitted.

* fix(proxy): count embedding and text completion tokens toward TPM limits (#30105)

* fix(proxy): count embedding and text completion tokens toward TPM limits

The parallel request limiters only read token usage off ModelResponse,
so EmbeddingResponse and TextCompletionResponse objects left
total_tokens at 0 and the per key, user, team, and end user TPM
counters never incremented. Requests to /v1/embeddings and
/v1/completions were effectively free against any tpm_limit. In the v3
limiter this was worse: the post-call reconciliation computed actual
usage as 0 and refunded the pre-call reservation made at request time.

Broaden the isinstance checks to accept EmbeddingResponse and
TextCompletionResponse, which both expose a Usage object, at the four
per-scope sites in parallel_request_limiter.py and at the usage
extraction in parallel_request_limiter_v3.py. ResponsesAPIResponse was
already covered in v3 via BaseLiteLLMOpenAIResponseObject.

Fixes #27738.

* test(proxy): cover v1 limiter TPM counting for embedding and text completion responses

Exercise the broadened isinstance sites in parallel_request_limiter.py
by asserting that async_log_success_event adds total_tokens to the per
key, user, team, and end user TPM counters for EmbeddingResponse and
TextCompletionResponse objects. The counters are pre-seeded at zero so
the assertion is exactly the increment; on the pre-fix code these
responses left total_tokens at 0 and the test fails.

* fix(openai): forward client headers on the text completion path (#30103)

* fix(openai): forward client headers on the text completion path

litellm.completion() merges caller headers with extra_headers, but the
text-completion-openai branch never passed the merged dict to
openai_text_completions.completion(), and the handler only used its
headers argument for logging. Pass the merged headers through the call
site and set them as extra_headers on the outgoing request, mirroring
the chat completion handler, so x-* client headers forwarded by the
proxy reach the provider on /v1/completions.

Fixes #27410.

* Drop redundant extra_headers assignment and fix test module collision

completion() merges extra_headers into headers before the
text-completion-openai branch, and the handler now sets the merged
headers as extra_headers on the request, so the branch-local
optional_params["extra_headers"] assignment was a dead duplicate.
Removing it keeps the assignment in one place while both entry paths
(litellm.text_completion and direct handler callers) still forward
headers; a new regression test pins the extra_headers kwarg path.

Also rename the test module to test_completion_handler.py since its
basename collided with tests/test_litellm/llms/bedrock/batches/
test_handler.py and broke pytest collection.

* fix(bedrock): route Anthropic-shape count_tokens to InvokeModel and base64-encode the body (#30102)

* fix(bedrock): route Anthropic-shape count_tokens to InvokeModel

POST /v1/messages/count_tokens with Anthropic content blocks
({"type": "text"|"tool_use"|...}) was routed to the Converse input of
the Bedrock CountTokens API. The Converse transform copies list content
through verbatim, so Bedrock rejected the request with a 400 and the
caller silently fell back to the local tokenizer, returning counts that
can be off by ~50% on tool-heavy payloads.

_detect_input_type now routes messages whose content blocks carry a
"type" key (Anthropic shape) to the invokeModel input, which forwards
the body verbatim. The invokeModel body is now base64-encoded as the
CountTokens API requires (InvokeModelTokensRequest.body is a
base64-encoded blob), and Anthropic Messages bodies get the
anthropic_version and max_tokens fields Bedrock validates against.

Fixes #27632.

* refactor(bedrock): name the CountTokens max_tokens placeholder

Replace the magic 1024 with a module-level
DEFAULT_ANTHROPIC_INVOKE_MODEL_MAX_TOKENS constant so the intent is
explicit and there is a single place to update if Bedrock's InvokeModel
schema ever changes. Module-local rather than litellm/constants.py
because the value is only a schema-validation placeholder for token
counting, not a user-tunable generation default.

* Add above-512k pricing tier for MiniMax-M3 and correct its base rates (#30095)

* Add above-512k pricing tier support for MiniMax-M3

MiniMax-M3 doubles its per-token rates once a prompt exceeds 512k
input tokens. The tiered cost parser already handles arbitrary
thresholds, but get_model_info only copies whitelisted keys from
ModelInfoBase, which had no 512k variants, so above_512k keys were
silently dropped and long-context requests were priced at the flat
rate.

Add the input, output, and cache-read above_512k_tokens fields to
ModelInfoBase and pass them through in get_model_info. Update the
minimax/MiniMax-M3 entry with the tiered rates and correct the base
rates, which matched the above-512k tier instead of the published
base tier (https://platform.minimax.io/docs/guides/pricing-paygo).

Fixes #29663.

* Add above-512k keys to pricing schema, set MiniMax-M3 context to 1M

Register the three new above_512k_tokens cost keys in the INTENDED_SCHEMA
of test_aaamodel_prices_and_context_window_json_is_valid, declared the same
way as the existing above_200k/above_272k tier keys, so the schema check
accepts the MiniMax-M3 tiered pricing entry.

Also raise MiniMax-M3 max_input_tokens from 512000 to 1000000 in both
pricing JSONs. The MiniMax API docs
(https://platform.minimax.io/docs/guides/text-generation) state the model
supports a 1,000,000-token context window, and the pay-as-you-go pricing
page (https://platform.minimax.io/docs/guides/pricing-paygo) prices input
above 512k tokens, which only makes sense if inputs beyond 512k are
accepted. This makes the above-512k pricing tier reachable.

* fix(bedrock): make document names unique across conversation turns (#30093)

* fix(bedrock): make document names unique across conversation turns

PR #16275 derived Bedrock document names purely from a content hash so
that names stay deterministic for prompt caching. When the same PDF or
document appears in more than one conversation turn, every occurrence
gets the identical name and Bedrock rejects the request with "Messages
can not contain duplicate document names".

Add _rename_duplicate_bedrock_document_names, a post-pass over the
assembled message blocks that keeps the first occurrence's hash-based
name and appends a positional suffix (_2, _3, ...) to later
occurrences. Apply it in both _bedrock_converse_messages_pt and
_bedrock_converse_messages_pt_async. Names remain deterministic across
requests and the first occurrence is unchanged, so prompt cache
prefixes stay stable.

Fixes #29418.

* fix(bedrock): avoid suffix collisions with organic document names

A renamed duplicate could collide with a document whose hash-derived
name already ends in the same positional suffix (e.g. an organic
report_2 next to two documents named report). Collect every document
name up front and bump the suffix until the candidate is unused, so
renames can collide neither with organic names nor with each other.

* fix(_types): remove ResponsesAPIResponse from PassThroughEndpointLoggingResultValues

The import of ResponsesAPIResponse was removed from the file but a usage
was left in the Union type, causing a NameError on import and breaking
all CI tests. Remove the stale reference to match the cleanup intent.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(_types): restore ResponsesAPIResponse import and add use_xai_oauth to filter list

Two related fixes:
1. Re-add ResponsesAPIResponse import in _types.py — it was removed but still
   needed in PassThroughEndpointLoggingResultValues (used in
   openai_passthrough_logging_handler.py).
2. Add use_xai_oauth to all_litellm_params so it is filtered before forwarding
   kwargs to providers like OpenAI that do not recognize it.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Hari <kancharla.ha@northeastern.edu>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: Ceder Dens <ceder.dens@uantwerpen.be>
Co-authored-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
Co-authored-by: 冯基魁 <56265583+fengjikui@users.noreply.github.com>
Co-authored-by: victoruce <161634297+victoruce@users.noreply.github.com>
Co-authored-by: kejunleng <33445544+silencedoctor@users.noreply.github.com>
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Tyson Cung <45380903+tysoncung@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Jeremy Chapeau <113923302+jychp@users.noreply.github.com>
Co-authored-by: Daan <255322319+daanhendrio@users.noreply.github.com>
Co-authored-by: Avani Prajapati <143805019+Avani-prajapati@users.noreply.github.com>
Co-authored-by: Kent <72616338+kingdoooo@users.noreply.github.com>
Co-authored-by: daitran-tensormesh <dai@tensormesh.ai>
Co-authored-by: Dimitris Spachos <dspachos@gmail.com>
Co-authored-by: Liam Scott <liam@uilliam.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com>
Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: tin-berri <tin@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
2026-06-10 10:34:07 -07:00
Sameer Kankute
2cd7e87485
fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009)
* fix(proxy): authorize batch files using upload target_model_names (LIT-3593)

After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead.

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

* fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)

Restores the reverse-lookup for the JSONL body.model fallback path so that
legacy/pre-target_model_names managed files still map stripped provider IDs
back to proxy aliases before auth. Also cleans up redundant `or None`.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)"

This reverts commit 30d2e96f77.

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-10 08:22:15 +05:30
michelligabriele
fe60f9d0f1
fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232)
* fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through

* test: mock post_call_response_headers_hook in audio speech route tests
2026-06-09 22:10:23 +02:00
Mateo Wang
13924fa1d6
feat: standardize rate limit errors with category, rate_limit_type, model, and llm_provider fields (#27687)
* feat(exceptions): add RateLimitErrorCategory + headers/detail fields on RateLimitError

LiteLLM previously surfaced rate-limit conditions through several unrelated
error classes (RateLimitError, FastAPI HTTPException(429), BaseLLMException).
This commit adds the data model needed to consolidate them under a single
class:

* RateLimitErrorCategory enum exposing four categorical values
  (vendor_rate_limit, vendor_batch_rate_limit, litellm_rate_limit,
  litellm_batch_rate_limit) so callers can switch on the rate-limit source.
* New optional fields on RateLimitError:
  - category (defaults to vendor_rate_limit, preserving today's behavior for
    every existing call site in exception_mapping_utils);
  - headers (preserves retry-after / rate_limit_type / reset_at across the
    proxy boundary instead of dropping them on the floor);
  - detail (mirrors FastAPI HTTPException.detail so the same instance can be
    serialized through both paths).

litellm.RateLimitErrorCategory is re-exported at the package root to match
the existing exception-export pattern.

LIT-2968

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

* feat(proxy): add ProxyRateLimitError unifying RateLimitError + HTTPException

Adds a single proxy-side error class that subclasses BOTH
litellm.exceptions.RateLimitError AND fastapi.HTTPException via cooperative
multiple inheritance.

Why both bases:
* Subclassing RateLimitError lets user code catch every rate-limit source
  with one 'except RateLimitError' and switch on the new .category field.
* Subclassing HTTPException keeps every existing FastAPI plumbing path (the
  isinstance(e, HTTPException) branches in proxy_server.py route handlers,
  FastAPI's own dispatcher, and tests asserting pytest.raises(HTTPException))
  working without modification, and preserves retry-after / rate_limit_type /
  reset_at headers on the wire.

The class declaration order is (HTTPException, RateLimitError) so the MRO
puts HTTPException's no-super-call __init__ ahead of openai's cooperative
__init__ chain — preventing openai.APIError.super().__init__(message) from
landing in HTTPException.__init__(status_code=message).

LIT-2968

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

* refactor(proxy/hooks): raise ProxyRateLimitError from budget + iteration limiters

Replaces three bare HTTPException(status_code=429, ...) call sites with
ProxyRateLimitError, which is both a RateLimitError (catchable by category)
and an HTTPException (preserves existing FastAPI serialization). Drops the
now-unused HTTPException import in the iteration / per-session limiters.

LIT-2968

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

* refactor(proxy/hooks): raise ProxyRateLimitError from parallel-request limiters

Replaces HTTPException(status_code=429, ...) call sites in the v1 and v3
parallel-request limiters (key/team/user/model/customer rate limits) with
ProxyRateLimitError. Updates the raise_rate_limit_error helper's return type
annotation accordingly.

LIT-2968

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

* refactor(proxy/hooks): raise ProxyRateLimitError from dynamic rate limiters

Replaces HTTPException(status_code=429, ...) call sites in the v1 and v3
dynamic rate limiters (project-level TPM/RPM allocation, model-saturation
checks, priority-based limits, fail-closed guards) with ProxyRateLimitError.
The v3 limiter still imports HTTPException for an unrelated bare 'except
HTTPException:' branch.

LIT-2968

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

* refactor(proxy/hooks): raise ProxyRateLimitError from batch rate limiter

Replaces HTTPException(status_code=429, ...) in batch_rate_limiter._raise_rate_limit_error
with ProxyRateLimitError tagged as RateLimitErrorCategory.LITELLM_BATCH_RATE_LIMIT
so users can distinguish batch-level throttling (which counts requests/tokens
across an uploaded batch input file before submission) from the generic
key/team/user RPM/TPM limiter.

The HTTPException import is retained because the same module raises
HTTPException for unrelated 403/IO error paths.

LIT-2968

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

* test(rate-limit): pin down unified rate-limit error contract

Adds a dedicated test module covering the new RateLimitErrorCategory enum,
RateLimitError.category default + override behavior, ProxyRateLimitError's
dual nature (RateLimitError + HTTPException), and a parametrized regression
guard that asserts every proxy hook module imports the unified class.

The regression guard catches the failure mode the refactor is designed to
prevent: someone re-introducing a bare HTTPException(status_code=429, ...)
in one of the hook modules instead of going through ProxyRateLimitError.

LIT-2968

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

* feat(logging): expose rate-limit category via StandardLoggingPayload

Adds an optional 'error_rate_limit_category' field to
StandardLoggingPayloadErrorInformation, populated from the unified
RateLimitError.category attribute (introduced in the previous commits on
this branch).

Why: the .category attribute is reachable off the raw exception today via
getattr(e, 'category', None), but the structured contract that downstream
custom callbacks / loggers / spend log writers consume is the
StandardLoggingPayload. Without this field, a user building custom
rate-limit metrics on top of callback data has to special-case the raw
exception object — which defeats the purpose of the StandardLoggingPayload
abstraction.

The field is None for non-rate-limit exceptions (so consumers can read it
unconditionally without isinstance checks) and is one of the
RateLimitErrorCategory string values otherwise.

LIT-2968

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

* test(rate-limit): assert StandardLoggingPayload carries the category

Five tests covering: vendor default, explicit litellm_rate_limit and
litellm_batch_rate_limit values, None for non-rate-limit exceptions, and
None when no exception is provided. Pins down the contract that custom
callbacks can read 'error_information.error_rate_limit_category' off the
StandardLoggingPayload to drive custom rate-limit metrics without ever
reaching for the raw exception.

LIT-2968

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

* fix(types): silence mypy [misc] on intentional dual-base attr overlap

mypy emits two [misc] errors on the ProxyRateLimitError class line because
its two bases declare overlapping attributes with related-but-not-identical
annotations:

* status_code: int on starlette HTTPException vs. Literal[429] on openai's
  RateLimitError (every openai status-error subclass narrows it the same
  way and silences pyright with the same convention).
* headers: Mapping[str, str] | None on HTTPException vs. our Optional[
  Dict[str, str]] (the proxy hooks always carry a stringified dict).

Both narrowings are intentional and enforced at construction time. Add a
type: ignore[misc] with an inline explanation rather than relax the
annotations on the parent or change the wire-format guarantees.

LIT-2968

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

* test(rate-limit): add direct hook-invocation tests to lift patch coverage

Adds six end-to-end tests that drive each refactored hook past its
limit and assert the unified ProxyRateLimitError is raised with the
correct category and dual-base shape. Complements the
import-shape-only parametrized guard above by actually executing the
new 'raise ProxyRateLimitError(...)' lines so codecov's patch coverage
sees them as hit.

Hooks covered (one test each):
* parallel_request_limiter v1 — direct call to raise_rate_limit_error()
* parallel_request_limiter v3 — direct call to _handle_rate_limit_error
  with a fabricated OVER_LIMIT response
* max_iterations_limiter — full async_pre_call_hook with mocked agent
  registry, second call exceeds budget=1
* max_budget_limiter — async_pre_call_hook with mocked get_current_spend
* dynamic_rate_limiter v1 — async_pre_call_hook with mocked
  check_available_usage forcing available_tpm == 0
* batch_rate_limiter — direct _raise_rate_limit_error call, asserts
  category is the batch-specific LITELLM_BATCH_RATE_LIMIT (not the
  generic LITELLM_RATE_LIMIT)

LIT-2968

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

* fix: guard rate_limit_category extraction with isinstance check

* test(rate-limit): cover remaining hook raise sites for codecov

Adds five more direct hook-invocation tests so every PR-touched line
in the proxy hooks is exercised by tests in tests/test_litellm/, which
codecov measures:

* parallel_request_limiter v1 — check_key_in_limits inline raise
  (the second raise site, separate from the raise_rate_limit_error
  helper covered earlier)
* dynamic_rate_limiter v1 — RPM raise branch (TPM branch was already
  covered)
* dynamic_rate_limiter v3 — parametrized over all three raise sites:
  model_saturation_check, priority_model, and the fail-closed
  fallback for an unrecognized descriptor_key
* max_budget_per_session_limiter — full async_pre_call_hook with a
  mocked agent registry and over-budget cached spend

All 42 tests in test_rate_limit_error_unification.py now pass and
together exercise every changed import + raise line across the eight
refactored proxy hooks.

LIT-2968

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

* fix: use computed error_message in ProxyRateLimitError detail

* fix(parallel-request-limiter): drop None from detail; annotate raise_rate_limit_error as NoReturn

The v1 ' raise_rate_limit_error' helper built an unused 'error_message'
variable and then assembled the actual ' detail' via an f-string that
interpolated 'additional_details' verbatim — producing
'Max parallel request limit reached None' when invoked without
arguments (flagged by code review).

Fix the helper to:
- use the constructed 'error_message' as the detail
- annotate the helper as NoReturn since it always raises
- drop the redundant 'raise'/'return' at the two call sites

Add two regression tests covering both the with- and without-
additional_details paths.

LIT-2968

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

* fix(proxy/hooks): drop literal 'None' from raise_rate_limit_error detail

The v1 parallel_request_limiter's raise_rate_limit_error helper has a
long-standing bug: it computes a None-guarded 'error_message' string but
then ignores it and emits an f-string that interpolates the raw
'additional_details' arg. Callers that pass no argument get
'Max parallel request limit reached None' as the user-facing detail.

This commit:
* wires error_message into the detail kwarg so the None-guard actually
  applies and operators see a clean message;
* changes the return-type annotation from ProxyRateLimitError to NoReturn
  (the function always raises) so type-checkers know callers after this
  invocation are unreachable.

Greptile P1 + P2 review feedback on PR #27687.

LIT-2968

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

* fix(types): demote TypedDict floating string to a # comment

A string literal placed after a field declaration in a TypedDict body is
not a per-field docstring — it's an orphaned string expression Python
discards. Tools like mypy / pyright that inspect TypedDict fields won't
surface that text either.

Move the documentation for error_rate_limit_category to a real comment
so the intent is visible to readers and type-checker tooling without
the misleading docstring framing.

Greptile P2 review feedback on PR #27687.

LIT-2968

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

* security(exceptions): do not auto-copy vendor response headers to e.headers

A vendor 429 response can set arbitrary headers (Set-Cookie, CORS
overrides, …). Previously, when RateLimitError was constructed with only
a 'response=' (no explicit 'headers=' kwarg), self.headers fell back to
a copy of response.headers. If a downstream proxy serializer ever
forwarded e.headers to the client, a malicious upstream could inject
browser-interpreted headers for the proxy origin.

Drop the fallback. Only headers passed explicitly via the headers= kwarg
make it onto self.headers (proxy hooks pass retry-after etc. — they
control what's surfaced). Vendor response headers stay reachable on
e.response.headers for callers that explicitly want them.

Today's proxy_server.py route handlers don't actually forward e.headers
on the wire (they construct ProxyException without passing headers), so
no current behavior changes — this is a defensive narrowing so the
fallback can never be turned into a vector when someone wires
e.headers through later.

Veria-AI security review feedback on PR #27687.

LIT-2968

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

* test(rate-limit): regression guards for review-pass fixes

Pins down the three review-pass fixes:

* test_parallel_request_limiter_v1_helper_no_additional_details — calls
  raise_rate_limit_error() with no args and asserts the detail does NOT
  contain the literal string 'None'. Pre-fix, callers got 'Max parallel
  request limit reached None'.
* test_rate_limit_error_does_not_auto_copy_response_headers — passes a
  vendor httpx.Response with a Set-Cookie header to RateLimitError
  WITHOUT an explicit headers= kwarg, asserts self.headers stays None
  (no leak), then re-checks that an explicit headers= kwarg DOES
  populate self.headers. Vendor headers remain reachable on
  e.response.headers for callers that explicitly want them.
* The existing v1-helper test now also asserts the additional_details
  string makes it through to the detail.

LIT-2968

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

* feat(rate-limit): add orthogonal RateLimitType (requests/tokens/concurrent_requests/budget/max_iterations)

trho's last ask in the LIT-2968 thread: distinguish rate-limit failures by
the dimension that was exceeded, not just by who rate-limited (vendor vs.
litellm). Adds:

- RateLimitType str-enum exposed at `litellm.RateLimitType` with values
  requests / tokens / concurrent_requests / budget / max_iterations.
- `rate_limit_type` kwarg on litellm.RateLimitError + ProxyRateLimitError;
  None default so existing callers (vendor-429 path in exception_mapping_utils)
  remain a no-op.
- StandardLoggingPayloadErrorInformation.error_rate_limit_type so custom
  callbacks can split rate-limit failures by cause without parsing free-text
  error messages. Mirror to error_rate_limit_category extraction in
  get_error_information(); single isinstance(RateLimitError) check covers both.
- map_v3_rate_limit_type() helper to collapse the v3 limiter's internal labels
  ("requests", "tokens", "max_parallel_requests") onto the public enum so
  the v3 limiter and dynamic_rate_limiter_v3 share one mapping. Defensive
  None on unknown values rather than silently picking a wrong dimension.

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

* feat(proxy/hooks): wire rate_limit_type onto every limiter raise site

Each refactored proxy hook now populates rate_limit_type with the dimension
that actually tripped the limit, so downstream consumers (custom callbacks,
prometheus exporters via the StandardLoggingPayload) can split key/team/user
rate-limit failures by cause:

- parallel_request_limiter (v1): detect dimension from current vs. limit in
  the post-cache branch (concurrent_requests > tokens > requests, matches the
  boolean condition order). Base case (current is None, one limit set to 0)
  picks the most-specific zero. raise_rate_limit_error() helper accepts an
  explicit rate_limit_type kwarg with CONCURRENT_REQUESTS default (matches
  every existing internal call site, including the global-limit branch).
- parallel_request_limiter (v3): forward status["rate_limit_type"] through
  map_v3_rate_limit_type() so "max_parallel_requests" → CONCURRENT_REQUESTS
  for the public field while the raw v3 jargon stays on the HTTP header for
  wire-format backward compat.
- dynamic_rate_limiter (v1): TPM-zero → TOKENS, RPM-zero → REQUESTS. Pass
  data["model"] through so callbacks see the model that hit the limit
  (addresses the secondary "provider missing" complaint in the original
  Slack thread, partially — the model is what dashboards typically split on).
- dynamic_rate_limiter (v3): forward status["rate_limit_type"] via
  map_v3_rate_limit_type() at every raise site (model_saturation_check,
  priority_model, fail-closed unknown-descriptor guard). Also pass model.
- batch_rate_limiter: limit_type is hard-typed "requests"|"tokens" — map
  directly without going through the helper's None branch.
- max_budget_limiter, max_budget_per_session_limiter: BUDGET.
- max_iterations_limiter: MAX_ITERATIONS.

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

* test(rate-limit): cover RateLimitType enum, hook wiring, and StandardLoggingPayload propagation

27 new tests across five new test classes:

- TestRateLimitType: enum exposed at litellm.RateLimitType, all five values
  defined, RateLimitError default is None (vendor 429 path makes no claim
  about which dimension), accepts both string and enum forms with
  str-coercion guarantee for downstream JSON serializers.
- TestProxyRateLimitErrorType: ProxyRateLimitError default is None, accepts
  string or enum, doesn't break existing callers that pass nothing.
- TestMapV3RateLimitType: pins each v3-internal → public-enum mapping
  (tokens, requests, max_parallel_requests → concurrent_requests, unknown
  → None) so a future v3 refactor can't silently swap dimensions.
- TestStandardLoggingPayloadCarriesType: the new error_rate_limit_type
  field reaches the structured payload for both ProxyRateLimitError and
  plain RateLimitError, is None when unspecified, and is None for
  non-rate-limit exceptions (symmetric with error_rate_limit_category).
- TestProxyHooksWireTypeCorrectly: drives the actual raise sites in the
  v1 parallel_request_limiter helper, the v3 _handle_rate_limit_error
  (both "tokens" and "max_parallel_requests" paths), and the batch
  limiter (both tokens and requests paths) — coverage tools see the new
  rate_limit_type= kwargs as exercised, not just the import shape.

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

* test(rate-limit): cover _coerce_message branches and v1 dimension detection

Drives the patch coverage on the new orthogonal RateLimitType wiring up
to (or close to) 100% on the touched files.

ProxyRateLimitError._coerce_message — was 22% covered, now 100%:
* nested {error: {message}} dict
* nested {message: {message}} dict (alt key)
* dict without 'error'/'message' keys → JSON dump fallback
* non-JSON-serializable dict value → str() fallback
* non-string non-mapping detail (int) → str() coercion

v1 parallel_request_limiter dimension detection — was 0% covered, now
exercised across 6 parametrized cases:
* check_key_in_limits else-branch: current at concurrent / TPM / RPM cap
  → asserts rate_limit_type is concurrent_requests / tokens / requests.
* check_key_in_limits base case (current is None): max_parallel_requests
  / tpm_limit / rpm_limit set to 0 → asserts the most-specific zero
  attribution wins per the helper's order.

LIT-2968

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

* feat(proxy/hooks): add ProxyHTTPRateLimitError + provider resolver

Introduces a small helper layer used by every proxy-side rate-limit
hook so that the 429 they raise carries a populated llm_provider /
model — instead of an empty exception.llm_provider that downstream
loggers (Prometheus failure metric, observability callbacks) read as
'no provider attribution'.

ProxyHTTPRateLimitError inherits from both fastapi.HTTPException
(so the proxy server still renders it as a 429) and
litellm.exceptions.RateLimitError (so isinstance checks and
PrometheusLogger._get_exception_class_name pick up llm_provider).
We deliberately don't call RateLimitError.__init__ — it constructs
an httpx.Response we don't need and would just add failure surface;
attribute parity is what downstream consumers care about.

resolve_llm_provider_for_rate_limit() wraps litellm.get_llm_provider
defensively. Internal limiter hooks fire from async_pre_call_hook —
well before get_llm_provider runs anywhere else in the request
lifecycle — so we have to call it ourselves at raise time. If the
model is missing or unparseable (alias, router-only model) we fall
back to llm_provider='litellm_proxy' rather than letting a second
exception leak out and break the request path.

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

* fix(proxy/hooks): populate llm_provider on parallel-request 429s

Both v1 and v3 parallel-request limiters fired bare HTTPException(429)
from inside async_pre_call_hook. The downstream Prometheus failure
metric reads exception.llm_provider via _get_exception_class_name —
the empty value showed up as exception_class='HTTPException' and
left model_id='None' on the time series.

Threads requested_model through every raise site in:

* parallel_request_limiter.py:
  - check_key_in_limits (the per-key/per-model/per-user/per-team/
    per-customer over-limit path)
  - raise_rate_limit_error (zero-limit + global_max_parallel_requests
    paths) — now takes an optional requested_model kwarg
* parallel_request_limiter_v3.py:
  - _handle_rate_limit_error (the OVER_LIMIT translator), called
    from both the should_rate_limit pre-check and the TPM
    reservation path

Resolved via resolve_llm_provider_for_rate_limit so unknown / missing
models silently fall back to llm_provider='litellm_proxy' instead of
breaking the request path with a second exception.

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

* fix(proxy/hooks): populate llm_provider on dynamic-rate-limit 429s

Same plumbing change as the parallel limiters, applied to both
dynamic_rate_limiter (v1) and dynamic_rate_limiter_v3:

* v1: TPM-zero and RPM-zero paths in async_pre_call_hook now resolve
  data['model'] -> (model, llm_provider) once and pass it into both
  raises.
* v3: All three raise sites in _check_rate_limits — the
  model_saturation_check enforced raise, the priority_model
  enforced raise, and the fail-closed unknown-descriptor branch —
  now attribute the 429 to the actual provider.

Falls back to llm_provider='litellm_proxy' when the model can't be
resolved.

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

* fix(proxy/hooks): populate llm_provider on batch-rate-limit 429s

batch_rate_limiter._raise_rate_limit_error now takes a
requested_model kwarg threaded from data['model'] in
_check_and_increment_batch_counters. The batch-creation 429 is what
gets raised when the input file's tokens/requests count would push
the per-key TPM/RPM window over its limit.

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

* fix(proxy/hooks): populate llm_provider on budget/iterations 429s

Final batch of internal raise sites — the user/session-budget and
max-iterations hooks. Same pattern: resolve data['model'] once at
raise time, attach to ProxyHTTPRateLimitError so Prometheus and
observability callbacks can attribute the 429.

Hooks updated:
* max_budget_limiter (per-user max_budget exceeded)
* max_iterations_limiter (per-session agent iteration cap)
* max_budget_per_session_limiter (per-session dollar cap)

All three fall back to llm_provider='litellm_proxy' when data['model']
is missing or unparseable. Drops the now-unused HTTPException import
from each module.

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

* test(proxy/hooks): pin provider field on internal rate-limit 429s

Regression coverage for the 'provider field missing' bug across every
proxy-side rate-limit hook + the helper layer:

* ProxyHTTPRateLimitError class shape (HTTPException + RateLimitError,
  dict-detail stringification, None-provider normalization).
* resolve_llm_provider_for_rate_limit happy paths
  (gpt-4o-mini, anthropic/..., bedrock/...) plus all three fallback
  branches (None, '', unknown name) plus a 'get_llm_provider raises'
  case that asserts we swallow the secondary exception.
* For each limiter (parallel v1/v3, dynamic v1/v3, batch,
  max_budget, max_iterations, max_budget_per_session): assert the
  raised exception is a RateLimitError carrying the resolved
  model + llm_provider, and a sibling test that asserts the
  fallback path returns 'litellm_proxy' without leaking a second
  exception.
* Two PrometheusLogger._get_exception_class_name pins so the
  Prometheus failure metric label flips from 'HTTPException' to
  'Openai.ProxyHTTPRateLimitError' (or 'Litellm_proxy.*' on
  fallback) — that's what dashboards consume.

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

* perf(proxy/hooks): defer provider resolution to over-limit branches

* fix: use error_message in raise_rate_limit_error to avoid literal 'None' in detail

* Consolidate rate_limiter_utils imports in dynamic_rate_limiter

* fix(proxy): set num_retries/max_retries on ProxyHTTPRateLimitError

ProxyHTTPRateLimitError inherits from RateLimitError but did not call
RateLimitError.__init__, so num_retries/max_retries were never set.
When Starlette's HTTPException lacks __str__, MRO falls through to
RateLimitError.__str__, which unconditionally reads these attributes
and raises AttributeError during logging/traceback formatting.
Initialize them to None defensively.

* fix(mypy): silence base-class status_code conflict on ProxyHTTPRateLimitError

HTTPException declares 'status_code: int' while openai.RateLimitError
(via APIStatusError) declares 'status_code: Literal[429] = 429'. Mypy
flags the multi-base override as [misc] in CI lint. The runtime semantics
are fine (we set self.status_code in __init__), so silence the
class-level annotation conflict with a targeted ignore.

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

* fix: annotate batch limiter _raise_rate_limit_error as NoReturn

* feat(prometheus): rate-limit category/type labels + exception_class back-compat (follow-up to #27687) (#27706)

* feat(prometheus): add rate_limit_category and rate_limit_type labels

Adds two new labels to litellm_proxy_failed_requests_metric so dashboards
can split 429s by rate-limit source (vendor vs. litellm-internal) and by
the dimension that was exceeded (requests/tokens/concurrent_requests/
budget/max_iterations) without parsing free-text error messages.

Closes the Prometheus side of LIT-2718. The unified RateLimitError.category
and .rate_limit_type fields landed in PR #27687 but were only surfaced on
StandardLoggingPayload (custom-callback channel); this exposes them on
the metric label set as well.

Both labels are populated only when the underlying exception is a
litellm.RateLimitError; non-rate-limit failures keep them empty.

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

* feat(prometheus): populate rate-limit labels + preserve exception_class back-compat

Two coupled changes in the Prometheus integration:

1. async_post_call_failure_hook now extracts the new RateLimitError
   .category / .rate_limit_type fields (added in PR #27687) via a
   _extract_rate_limit_labels helper and forwards them through
   UserAPIKeyLabelValues onto litellm_proxy_failed_requests_metric.
   Empty for non-rate-limit failures.

2. _get_exception_class_name special-cases ProxyRateLimitError and
   keeps emitting 'HTTPException' for the exception_class label.
   Without this shim, ProxyRateLimitError (which multi-inherits from
   HTTPException + RateLimitError) would silently flip the label
   from 'HTTPException' (the historical value for proxy-side 429s)
   to 'ProxyRateLimitError', breaking existing dashboards / alerts
   that key off exception_class='HTTPException'. Distinguishing
   vendor vs. litellm 429s is now the job of the new
   rate_limit_category label.

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

* test(prometheus): cover rate-limit labels and exception_class back-compat

Adds 19 tests across:
- enum / label-list registration
- _extract_rate_limit_labels for vendor RateLimitError, ProxyRateLimitError,
  non-rate-limit and None inputs (incl. parametrized over every
  RateLimitErrorCategory x RateLimitType combo)
- _get_exception_class_name back-compat: ProxyRateLimitError keeps the
  legacy 'HTTPException' string while vendor RateLimitError keeps the
  historical 'Provider.ClassName' format
- end-to-end through async_post_call_failure_hook with both
  ProxyRateLimitError and vendor RateLimitError, asserting both new
  labels populate and exception_class stays back-compat

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

* fix(prometheus): tolerate missing fastapi in lazy ProxyRateLimitError import

Address greptile feedback:
- async_post_call_failure_hook docstring: drop the stale labelnames listing
  and reference PrometheusMetricLabels.litellm_proxy_failed_requests_metric
  as the source of truth so the doc cannot drift from the actual labelset.
- _get_exception_class_name: guard the lazy ProxyRateLimitError import with
  ImportError so router-side fallback callsites don't blow up in non-proxy
  installs that don't have fastapi (a transitive dep of
  proxy.common_utils.proxy_rate_limit_error). Behavior is unchanged when
  fastapi is available.

Also fix the existing enterprise callback test that asserted the old
labelset on litellm_proxy_failed_requests_metric — it now expects the new
rate_limit_category / rate_limit_type labels populated for vendor 429s.

---------

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

* fix(bugbot): simplify rate-limit label coercion + guard None detail

- prometheus.py _extract_rate_limit_labels: RateLimitError.__init__ already
  normalizes category/rate_limit_type to plain str, so the getattr(.value)
  + isinstance dance was dead code. Reduce to str(value) if not None.
- proxy_rate_limit_error.py _coerce_message: short-circuit None to ''
  instead of falling through to str(None) = 'None', which produced the
  literal message 'litellm.RateLimitError: None'.

* fix(rate-limit): surface unified category/type fields on BudgetExceededError

The most common budget cap (virtual-key max_budget enforcement in
auth_checks.py) raises litellm.BudgetExceededError, a bare Exception
subclass that bypassed the unified rate-limit error class introduced
by PR #27687. Custom callbacks reading
StandardLoggingPayload.error_information saw category=None and
rate_limit_type=None for these 429s, missing the most common budget
case (team / org / end-user budgets all hit the same code path).

Surface the fields off BudgetExceededError as plain attributes:
- category = RateLimitErrorCategory.LITELLM_RATE_LIMIT
- rate_limit_type = RateLimitType.BUDGET
- llm_provider = "" (or caller-supplied)

Switch get_error_information and _extract_rate_limit_labels from
isinstance(RateLimitError) gating to duck-typed attribute reads,
guarded by membership in the rate-limit enums so unrelated third-party
exceptions exposing a .category attribute can't leak garbage values
into the payload.

This is strictly additive: BudgetExceededError keeps its bare-Exception
base class, so `except BudgetExceededError:` handlers keep firing and
`except RateLimitError:` does not start catching budget errors.

* fix(rate-limit): validate enum membership at duck-typed read sites + enrich BudgetExceededError llm_provider

Two follow-ups uncovered during the second QA pass on PR #27687:

1. Guard third-party `.category` / `.rate_limit_type` attribute leakage.
   The duck-typed read in `get_error_information` and
   `_extract_rate_limit_labels` would forward any string attribute named
   `category` / `rate_limit_type` on an unrelated third-party exception
   into the StandardLoggingPayload and Prometheus labels — silently
   mislabeling custom-callback payloads and blowing out Prometheus label
   cardinality. Add `validate_rate_limit_category` /
   `validate_rate_limit_type` helpers that gate on the documented enum
   value sets; non-matching values are dropped to None.

2. Enrich BudgetExceededError.llm_provider from request_data.
   Budget checks live in tenant-scoped helpers (key / team / org / tag /
   end-user / project) that don't see the request model, so the
   BudgetExceededError they raise carried llm_provider="" — leaving
   custom-metrics consumers without provider attribution for the most
   common 429 case. Resolve it once at the central
   UserAPIKeyAuthExceptionHandler seam, before post_call_failure_hook
   fires, so the StandardLoggingPayload the callback sees has the same
   provider attribution as RPM/TPM 429s.

Regression tests pin both: 4 leakage tests + 4 enrichment tests. The
leakage tests would fail under the pre-validation version of either read
site; the enrichment tests would fail if the handler skipped the
resolver call.

* fix(rate-limit): resolve router model_name aliases to real provider (#27914)

* fix(rate-limit): resolve router model_name aliases to real provider

For nearly every real LiteLLM proxy deployment the request model is a
router model_name alias (e.g. 'tpm-locked' -> litellm_params.model:
openai/gpt-4o-mini), and 'litellm.get_llm_provider' doesn't know about
router aliases — it raises 'LLMProviderNotProvidedError'. The resolver
then fell through to the defensive 'litellm_proxy' fallback, so the
'llm_provider' field this PR adds was effectively always
'litellm_proxy' in the field, defeating its purpose for the most common
proxy configuration.

Add a router-alias fallback step: when 'get_llm_provider' raises, scan
the active 'llm_router.model_list' for a deployment whose 'model_name'
matches the request model and resolve from its 'litellm_params.model'
instead. If multiple deployments share the same alias (load-balancing
case) the first one wins — every deployment under one alias should
agree on provider in any sensible config, and 'first' is deterministic
so the Prometheus label stays stable.

Defensive throughout: an uninitialized router, a malformed deployment,
a 'litellm_params.model' that itself fails 'get_llm_provider' — every
branch falls through to the existing 'litellm_proxy' fallback rather
than letting a secondary exception escape and mask the rate-limit
error we're trying to surface.

Tests:
  - test_router_alias_resolves_to_underlying_provider: alias
    'tpm-locked' -> 'openai/gpt-4o-mini' produces provider='openai',
    model='gpt-4o-mini'.
  - test_router_alias_with_multiple_deployments_uses_first.
  - test_router_alias_unknown_falls_back.
  - test_router_alias_with_malformed_deployment_falls_back.
  - Existing fallback test updated to also stub
    'litellm.proxy.proxy_server.llm_router' so it exercises the
    full 'no resolution anywhere' path.

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

* fix(rate-limit): harden router alias resolver + test isolation

- Wrap _resolve_provider_from_router_alias loop in top-level try/except so
  a non-iterable model_list / unexpected deployment shape can't escape and
  mask the 429 with a 500.
- Type-check litellm_params before .get() to handle non-dict truthy values.
- Patch llm_router=None in the parametrized fallback test so a router left
  by another test in the session can't redirect the unknown-model path.

---------

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

* fix(bugbot): preserve "BudgetExceededError" Prometheus label

Adding llm_provider to BudgetExceededError (so callbacks get provider
attribution from StandardLoggingPayload) made the provider-prefix step in
_get_exception_class_name silently flip the label from "BudgetExceededError"
to e.g. "Openai.BudgetExceededError", breaking dashboards keyed on the
historical value.

Short-circuit BudgetExceededError in _get_exception_class_name the same way
ProxyRateLimitError already is. Provider/category attribution still lands on
the new rate_limit_category / rate_limit_type labels.

* test: fix invalid 'rpm' rate_limit_type in v3 limiter test mocks

The v3 rate limiter only emits 'requests', 'tokens', or
'max_parallel_requests'. Using 'rpm' caused map_v3_rate_limit_type to
return None, leaving the expected RateLimitType.REQUESTS untested.

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* fix(bugbot): hoist provider resolver + opt-in prom rate-limit labels

- dynamic_rate_limiter.py: hoist resolve_llm_provider_for_rate_limit
  above the TPM/RPM if/elif so the lookup runs once per request, matching
  the pattern in dynamic_rate_limiter_v3.py.
- prometheus.py: gate the new rate_limit_category / rate_limit_type
  labels on litellm_proxy_failed_requests_metric behind
  litellm.prometheus_emit_rate_limit_labels (default False). Mirrors the
  existing prometheus_emit_stream_label opt-in. Preserves the metric's
  pre-unification label set so existing dashboards / recording rules
  keep matching after upgrade; operators can enable the new labels once
  downstream consumers include them.
- Tests updated: default-off back-compat case, opt-in path enables the
  flag before asserting label presence.

* fix: stabilize prometheus label sets and drop redundant model normalization

- Cache PrometheusLogger.get_labels_for_metric per metric_name so that
  the label set used to construct counters at __init__ time stays in
  sync with the label set used at increment time, even if module-level
  toggles like prometheus_emit_rate_limit_labels or
  prometheus_emit_stream_label are flipped at runtime. Without this,
  toggling these flags after the logger was created would cause
  ValueError from prometheus_client because the runtime labels would
  not match the counter's declared labelnames.
- Drop redundant 'model or ""' guard in ProxyRateLimitError.__init__
  where model is already normalized one step earlier.

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* perf(dynamic_rate_limiter): only resolve provider when rate limit hit

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* test(prometheus): clear cached metric labels after toggling rate-limit flag

The PrometheusLogger caches each metric's label set at construction
time so that labels used at counter.labels(...) time stay consistent
with the labels the metric was registered with. The enterprise
async_post_call_failure_hook test toggles
litellm.prometheus_emit_rate_limit_labels = True AFTER the fixture
has already built the logger, so without invalidating the cache the
rate_limit_category / rate_limit_type labels never reach the mocked
counter and the assert_called_once_with check fails.

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* test: fix CI failures from prom label cache + flaky time-window assertion

PrometheusLogger.get_labels_for_metric now caches the per-metric label
set at first read so the labels passed to counter.labels(...) stay in
lock step with the labels the counter was registered with. This broke
two existing test patterns:

- test_prometheus_labels.py: tests bind the real method onto a
  MagicMock, but MagicMock auto-creates a Mock for _cached_metric_labels
  whose .get(...) returns a truthy Mock — treated as a populated cache
  and returned as the label set, producing empty filtered labels and
  KeyError on labels["requested_model"] / ["route"]. Seed real {}
  containers for _cached_metric_labels and label_filters before binding.

- test_prometheus_logging_callbacks.py::test_set_team_budget_metrics_with_custom_labels:
  the fixture builds the logger before the test monkeypatches
  litellm.custom_prometheus_metadata_labels, so the cached label set
  never picks up the new metadata labels. Clear the cache after the
  monkeypatch (same pattern already used for the rate-limit toggle in
  test_async_post_call_failure_hook).

UI: view_logs/index.test.tsx "Last Minute" window assertion is off by
one at the minute boundary. start_date is floored to the minute, so the
dropped sub-minute fraction can push the truncated-seconds diff up to
(minMinutes+1)*60 exactly when the click lands near a minute rollover.
Switch the upper bound to toBeLessThanOrEqual.

* feat(otel-v2): surface rate_limit_category + rate_limit_type on failed LLM-call spans

PR #28909 introduced the typed v2 OTel engine that builds spans from
StandardLoggingPayload, with SpanError carrying error_type + message and
the genai mapper stamping error.type onto every failed LLM-call span.
This PR's earlier commits added error_rate_limit_category and
error_rate_limit_type to the same StandardLoggingPayload.error_information
the v2 engine reads — but neither field reached a span attribute, so v2
OTel traces stayed opaque about *why* a 429 fired (vendor vs litellm,
RPM vs TPM vs concurrent vs budget vs max_iterations) even after the
custom-callback and prometheus surfaces gained that decomposition.

Three coupled changes:

1. semconv.py: add LiteLLM.ERROR_RATE_LIMIT_CATEGORY /
   LiteLLM.ERROR_RATE_LIMIT_TYPE under the litellm.* vendor namespace
   (no GenAI semconv equivalent exists for who-rate-limited /
   which-dimension).

2. payloads.py: extend SpanError with rate_limit_category +
   rate_limit_type, populated by _parse_error() from the same
   error_information.error_rate_limit_* fields the custom-callback
   channel and prometheus rate_limit_category / rate_limit_type labels
   read. Single source of truth across all three observability surfaces.

3. mappers/genai.py: stamp the two attributes on the LLM-call span when
   present. drop_none guarantees they stay absent (not 'None') for
   non-rate-limit failures so trace consumers can read them
   unconditionally.

Three regression tests in test_otel_v2_emitter.py pin: a vendor /
litellm-internal RateLimitError lands category=litellm_rate_limit +
rate_limit_type=requests on the span; a BudgetExceededError lands
rate_limit_type=budget; a non-rate-limit failure (BadRequestError)
keeps the rate_limit_* attributes absent. Mutation-tested against
reverting either the SpanError extension or the _parse_error read site
— both new tests fail under either mutation.

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

* test: align prometheus user-budget + logs quick-select tests with merged code

The merge into this branch left two test patterns out of step with the code
they exercise.

test_set_user_budget_metrics_includes_user_email_and_alias_labels_when_opted_in
flipped litellm.prometheus_user_budget_label_include_email_alias after the
fixture had already built the PrometheusLogger. get_labels_for_metric now
snapshots each metric's label set at construction time, so the runtime flip
no longer reached the cached labels. Enable the flag before constructing the
logger, matching how the proxy applies config at startup.

view_logs/index.test.tsx referenced uiSpendLogsCall and moment without
importing them, and the merged index.tsx now fetches through
useLogFilterLogic (the hook the file stubs out) rather than calling
uiSpendLogsCall directly. Add the imports and restore the real hook for the
Quick Select window assertions so the call is actually observed.

* refactor(otel/v2): drop rate-limit decomposition from the LLM-call span

Proxy-side rate limits (litellm_rate_limit, budget, max_iterations) are
rejected at the gate before any upstream call, so async_post_call_failure_hook
tags the synthetic failure log with LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL and the
v2 OTel logger never opens an LLM-call span for them; the
litellm.error.rate_limit_category / litellm.error.rate_limit_type attributes
were dead for exactly the cases they were meant to surface. The only failure
that does open an LLM-call span carrying a RateLimitError is a vendor 429, where
rate_limit_type is always None and the category just restates
error.type=RateLimitError.

The decomposition still reaches downstream consumers through
StandardLoggingPayload.error_information.error_rate_limit_* and the prometheus
rate_limit_category / rate_limit_type labels, both unchanged.

Removes the SpanError fields, the _parse_error reads, the genai mapper
attributes, the semconv keys, and the three span tests that asserted a scenario
that never reaches the mapper in production.

* fix(batch_rate_limiter): map max_parallel_requests to concurrent_requests

* refactor(prometheus): drop transitive fastapi import from _get_exception_class_name

Read the legacy exception_class label from a prometheus_exception_class_name
marker on ProxyRateLimitError instead of importing the proxy module, keeping
the integrations layer free of a transitive fastapi dependency.

* chore(ui): sync schema.d.ts with unified rate-limit error spec

The ProxyRateLimitError docstring flows into the proxy OpenAPI spec's 429
response description, so the generated dashboard types were out of sync.
Regenerated via npm run gen:api (Check UI API Types Sync).

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
2026-06-06 17:50:29 -07:00
Sameer Kankute
074455c138
fix(auth): expand all-team-models sentinel in can_key_call_model for batch validation (#29746)
* fix(auth): expand all-team-models sentinel in can_key_call_model

Keys with models=["all-team-models"] were denied during batch JSONL
model validation because can_key_call_model matched the literal string
against the model name. Add _resolve_key_models_for_auth_check to
expand the sentinel to team_models before the check, consistent with
get_key_models in model_checks.py and the completion-route bypass.

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

* docs(auth): document empty team_models unrestricted access behavior; add regression test

Adds a docstring note to _resolve_key_models_for_auth_check explaining that
when team_models is empty, all-team-models resolves to [] which is treated as
unrestricted access (consistent with get_key_models behavior on other auth
paths). Adds a test to lock in this behavior.

* fix(auth): deny all-team-models access when key has no team_id

A key configured with models=["all-team-models"] but no team_id could
previously resolve to an empty allowlist, which _check_model_access_helper
treats as unrestricted access. Now the sentinel is only expanded when
team_id is set; otherwise the unresolved sentinel stays in the model list
and causes a deny (no real model name matches it). Same fix applied to
get_key_models in model_checks.py for consistency across batch and
non-batch auth paths.

* style: black format model_checks.py

* Fix batch all-team-models auth

* style: black format batch_rate_limiter.py

* fix(test): add tool_use_system_prompt_tokens to model prices schema validator

* fix(batch): catch get_team_object errors to avoid 404 escaping batch auth

* fix(batch): apply per-member model scope check after team auth in batch validation

* Fail closed on batch team auth fetch errors

* test(batch): cover team_object grant and member-scope denial in batch auth

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-06-05 09:04:45 -07:00
Mateo Wang
df704d9016
fix(proxy/hooks): populate llm_provider on internal rate-limit errors (#27707)
* feat(proxy/hooks): add ProxyHTTPRateLimitError + provider resolver

Introduces a small helper layer used by every proxy-side rate-limit
hook so that the 429 they raise carries a populated llm_provider /
model — instead of an empty exception.llm_provider that downstream
loggers (Prometheus failure metric, observability callbacks) read as
'no provider attribution'.

ProxyHTTPRateLimitError inherits from both fastapi.HTTPException
(so the proxy server still renders it as a 429) and
litellm.exceptions.RateLimitError (so isinstance checks and
PrometheusLogger._get_exception_class_name pick up llm_provider).
We deliberately don't call RateLimitError.__init__ — it constructs
an httpx.Response we don't need and would just add failure surface;
attribute parity is what downstream consumers care about.

resolve_llm_provider_for_rate_limit() wraps litellm.get_llm_provider
defensively. Internal limiter hooks fire from async_pre_call_hook —
well before get_llm_provider runs anywhere else in the request
lifecycle — so we have to call it ourselves at raise time. If the
model is missing or unparseable (alias, router-only model) we fall
back to llm_provider='litellm_proxy' rather than letting a second
exception leak out and break the request path.

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

* fix(proxy/hooks): populate llm_provider on parallel-request 429s

Both v1 and v3 parallel-request limiters fired bare HTTPException(429)
from inside async_pre_call_hook. The downstream Prometheus failure
metric reads exception.llm_provider via _get_exception_class_name —
the empty value showed up as exception_class='HTTPException' and
left model_id='None' on the time series.

Threads requested_model through every raise site in:

* parallel_request_limiter.py:
  - check_key_in_limits (the per-key/per-model/per-user/per-team/
    per-customer over-limit path)
  - raise_rate_limit_error (zero-limit + global_max_parallel_requests
    paths) — now takes an optional requested_model kwarg
* parallel_request_limiter_v3.py:
  - _handle_rate_limit_error (the OVER_LIMIT translator), called
    from both the should_rate_limit pre-check and the TPM
    reservation path

Resolved via resolve_llm_provider_for_rate_limit so unknown / missing
models silently fall back to llm_provider='litellm_proxy' instead of
breaking the request path with a second exception.

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

* fix(proxy/hooks): populate llm_provider on dynamic-rate-limit 429s

Same plumbing change as the parallel limiters, applied to both
dynamic_rate_limiter (v1) and dynamic_rate_limiter_v3:

* v1: TPM-zero and RPM-zero paths in async_pre_call_hook now resolve
  data['model'] -> (model, llm_provider) once and pass it into both
  raises.
* v3: All three raise sites in _check_rate_limits — the
  model_saturation_check enforced raise, the priority_model
  enforced raise, and the fail-closed unknown-descriptor branch —
  now attribute the 429 to the actual provider.

Falls back to llm_provider='litellm_proxy' when the model can't be
resolved.

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

* fix(proxy/hooks): populate llm_provider on batch-rate-limit 429s

batch_rate_limiter._raise_rate_limit_error now takes a
requested_model kwarg threaded from data['model'] in
_check_and_increment_batch_counters. The batch-creation 429 is what
gets raised when the input file's tokens/requests count would push
the per-key TPM/RPM window over its limit.

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

* fix(proxy/hooks): populate llm_provider on budget/iterations 429s

Final batch of internal raise sites — the user/session-budget and
max-iterations hooks. Same pattern: resolve data['model'] once at
raise time, attach to ProxyHTTPRateLimitError so Prometheus and
observability callbacks can attribute the 429.

Hooks updated:
* max_budget_limiter (per-user max_budget exceeded)
* max_iterations_limiter (per-session agent iteration cap)
* max_budget_per_session_limiter (per-session dollar cap)

All three fall back to llm_provider='litellm_proxy' when data['model']
is missing or unparseable. Drops the now-unused HTTPException import
from each module.

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

* test(proxy/hooks): pin provider field on internal rate-limit 429s

Regression coverage for the 'provider field missing' bug across every
proxy-side rate-limit hook + the helper layer:

* ProxyHTTPRateLimitError class shape (HTTPException + RateLimitError,
  dict-detail stringification, None-provider normalization).
* resolve_llm_provider_for_rate_limit happy paths
  (gpt-4o-mini, anthropic/..., bedrock/...) plus all three fallback
  branches (None, '', unknown name) plus a 'get_llm_provider raises'
  case that asserts we swallow the secondary exception.
* For each limiter (parallel v1/v3, dynamic v1/v3, batch,
  max_budget, max_iterations, max_budget_per_session): assert the
  raised exception is a RateLimitError carrying the resolved
  model + llm_provider, and a sibling test that asserts the
  fallback path returns 'litellm_proxy' without leaking a second
  exception.
* Two PrometheusLogger._get_exception_class_name pins so the
  Prometheus failure metric label flips from 'HTTPException' to
  'Openai.ProxyHTTPRateLimitError' (or 'Litellm_proxy.*' on
  fallback) — that's what dashboards consume.

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

* perf(proxy/hooks): defer provider resolution to over-limit branches

* fix: use error_message in raise_rate_limit_error to avoid literal 'None' in detail

* Consolidate rate_limiter_utils imports in dynamic_rate_limiter

* fix(proxy): set num_retries/max_retries on ProxyHTTPRateLimitError

ProxyHTTPRateLimitError inherits from RateLimitError but did not call
RateLimitError.__init__, so num_retries/max_retries were never set.
When Starlette's HTTPException lacks __str__, MRO falls through to
RateLimitError.__str__, which unconditionally reads these attributes
and raises AttributeError during logging/traceback formatting.
Initialize them to None defensively.

* fix(mypy): silence base-class status_code conflict on ProxyHTTPRateLimitError

HTTPException declares 'status_code: int' while openai.RateLimitError
(via APIStatusError) declares 'status_code: Literal[429] = 429'. Mypy
flags the multi-base override as [misc] in CI lint. The runtime semantics
are fine (we set self.status_code in __init__), so silence the
class-level annotation conflict with a targeted ignore.

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

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-06-04 22:46:08 -07:00
Mateo Wang
812a2217ca
[internal copy of #29511] feat(guardrails): add sensitive data routing to on-premise models (#29531)
* feat(guardrails): add sensitive data routing to on-premise models

When a guardrail detects sensitive data, route to an on-premise model
instead of blocking or redacting. All subsequent requests in that
session continue routing to the same model (sticky routing).

New config options for guardrails:
- on_sensitive_data: 'block' (default) or 'route'
- sensitive_data_route_to_model: target model for rerouting
- sticky_session_routing: persist routing for session (default: true)

New exception SensitiveDataRouteException triggers rerouting when raised
by guardrails. The proxy catches it, stores the routing decision in
cache, and modifies the request's model field.

New hook _PROXY_SensitiveDataRoutingHandler checks incoming requests
against cached routing decisions and applies sticky routing.

https://claude.ai/code/session_01SQd4isBa3UyouRoGVou9dK

* fix: black formatting for custom_guardrail.py

https://claude.ai/code/session_01SQd4isBa3UyouRoGVou9dK

* test: improve test coverage for sensitive data routing feature

Add additional tests for:
- Cache key format and TTL constants
- Session ID extraction from multiple locations
- Custom guardrail initialization with routing config
- Exception string representation and custom messages
- Redis cache paths including fallback behavior
- Edge cases in pre-call hook

https://claude.ai/code/session_01SQd4isBa3UyouRoGVou9dK

* fix: use correct GuardrailRaisedException parameters

Replace invalid 'source' parameter with 'guardrail_name' to match
the exception's actual signature.

https://claude.ai/code/session_01SQd4isBa3UyouRoGVou9dK

* test: move sensitive data routing tests to hooks directory

Move test file to align with source code structure.

https://claude.ai/code/session_01SQd4isBa3UyouRoGVou9dK

* fix(guardrails): honor sticky_session_routing flag and scope session routing per API key

Propagate sticky_session_routing through SensitiveDataRouteException so a
guardrail configured with sticky_session_routing=False reroutes only the
triggering request without persisting a session override. Scope the routing
cache key to the requesting API key so sessions from different tenants cannot
collide, and warn when sticky routing is requested but the hook is not
registered.

* refactor(guardrails): dedupe session-id extraction and drop redundant import

Extract the shared session-id lookup into get_session_id_from_request_data
so the sensitive-data routing hook and CustomGuardrail no longer keep two
identical copies of the logic. Remove the redundant local import of
GuardrailRaisedException in handle_sensitive_data_detection, and document
that detection_info is surfaced in request metadata and logs so it must not
carry raw sensitive values.

* fix(guardrails): guard None user_api_key_dict in sensitive data route handler

* fix(responses): send application/json Content-Type on responses DELETE

OpenAI's responses DELETE endpoint now rejects requests that arrive without
a Content-Type header, defaulting them to application/octet-stream and
returning 'Unsupported content type: application/octet-stream'. The delete
handler sent no body and therefore no Content-Type, so the request failed.
Declare application/json on the delete request, matching the OpenAI SDK.

* fix(guardrails): backfill in-memory cache after redis hit in sensitive data routing

When _get_routed_model resolves a routing override from Redis it now also
populates the local in-memory cache. Without the write-back, a non-writing
instance that only ever reads from Redis would lose the sticky routing
decision the moment Redis became unavailable, silently reverting sensitive
sessions to the default model.

* fix(guardrails): scope sticky sensitive-data routing to JWT principal

Keyless auth (JWT and similar) has no api_key, so every such caller shared
the "default" cache namespace. One authenticated user could reuse another
user's session_id, trip the guardrail, and silently force the other user's
subsequent requests onto the cached on-prem model for the TTL.

Resolve the routing tenant from the api_key when present, otherwise from a
stable principal built from the user/team/org identity, before reading or
writing the session route.

* fix(guardrails): require route target model when on_sensitive_data='route'

* fix(guardrails): mark user_api_key_dict Optional in sensitive-data route handler

* fix(guardrails): use remaining redis ttl for local backfill and str env default

* fix(guardrails): graceful block when routing configured but no session_id

handle_sensitive_data_detection promised to raise only SensitiveDataRouteException
or GuardrailRaisedException, but when routing was configured and the request had no
session_id it let a ValueError from raise_sensitive_data_route_exception propagate,
surfacing as an HTTP 500 instead of a block. Fall back to a graceful block in that
case so the documented contract holds.

* fix(guardrails): run remaining guardrails after sensitive-data reroute

Defer the SensitiveDataRouteException until every guardrail in the
pre-call loop has run, so downstream security guardrails are no longer
skipped when an earlier guardrail triggers routing. The first reroute
wins and a later guardrail that blocks still propagates.

Also normalize on_sensitive_data to lowercase like sibling on_* config
fields so case-insensitive values are accepted.

* fix(guardrails): classify sensitive-data reroute as guardrail intervention

* fix(guardrails): record sensitive-data reroute as prometheus intervention not error

* fix(guardrails): record service span for routing guardrail and move case-normalizer to base params

Drop the early continue so a guardrail that signals sensitive-data routing still
emits its PROXY_PRE_CALL service span like every other callback.

Move the lowercase normalizer onto BaseLitellmParams so on_sensitive_data is
normalized consistently when BaseLitellmParams is constructed directly, matching
the cross-field route->model validator that already lives on the base.
2026-06-04 22:22:28 -07:00
Sameer Kankute
4a81ec4982
feat(proxy): add per-MCP-server RPM rate limiting for keys and teams (#29482)
* feat(proxy): add per-MCP-server RPM rate limiting for keys and teams

Adds mcp_rpm_limit, a dict keyed by MCP server name (alias if set, else the
configured name) that caps requests per minute per server for a key or team.
The v3 rate limiter builds a per-server descriptor only when a limit is
configured for the server being called, so other servers stay uncapped and no
TPM reservation is engaged. Server identity is surfaced into the request data
via mcp_rate_limit_server_name so the limiter can resolve it.

* fix(proxy): gate MCP rpm descriptors on call_mcp_tool; document mcp_rpm_limit param

Only honor mcp_server_name when the call is an actual MCP tool call. Without
this, a normal LLM request could inject mcp_server_name in its body to consume
a target server's MCP quota and 429 legitimate tool calls. Also adds the
mcp_rpm_limit parameter docstring to update_key, new_user, and user_update so
the API docs validator passes.

* Fix MCP rate limit quota handling

* Delete scripts/test_mcp_rpm_limit.sh

* docs(proxy): clarify mcp_rpm_limit is enforced for keys and teams, not per user

* fix(proxy): accept mcp_rpm_limit in generate_key_helper_fn

NewUserRequest and GenerateKeyRequest inherit mcp_rpm_limit from
GenerateRequestBase, so /user/new and /key/generate forwarded the field
to generate_key_helper_fn, which did not accept it and returned a 500
("unexpected keyword argument 'mcp_rpm_limit'"). Accept the param and
store it in metadata, matching model_rpm_limit/model_tpm_limit, so the
limit is persisted where get_key_mcp_rpm_limit reads it.

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-06-02 12:52:10 -07:00
Sameer Kankute
c233cbbc2a
fix(batches): skip unnecessary batch input file reads (#29114)
* fix(batches): skip unnecessary batch input file reads

Skip expensive pre-read of batch input files when no batch limits apply and model allowlist checks are not required, and decode model-embedded file IDs before file-content fetches to prevent upstream 404s.

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

* fix(batch-rate-limiter): prevent user metadata flag from bypassing model allowlist

The skip_batch_input_file_rate_limiting flag in litellm_metadata is
user-controllable for batch requests (request-body metadata lands in
litellm_metadata via LITELLM_METADATA_ROUTES). Honoring it
unconditionally also skipped _enforce_batch_file_model_access, letting
a restricted key submit a JSONL referencing models outside its
allowlist. Only honor the metadata-based skip when the key has no
model allowlist to enforce.

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* fix(batch_rate_limiter): enforce model access check before honoring skip paths

Admin-configured skips (disable_batch_input_file_rate_limiting,
skip_batch_input_file_rate_limiting_for_models/_for_providers) and the
no-applicable-rate-limits short-circuit previously bypassed
_enforce_batch_file_model_access. A key with a restricted model
allowlist could therefore submit a batch JSONL referencing models
outside its allowlist whenever any of these skip paths fired, and the
provider-skip path was attacker-controllable via the request body's
custom_llm_provider field. Hoist the model-access guard to the top so
restricted keys always have their JSONL validated regardless of which
skip would otherwise apply.

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* fix(batch_rate_limiter): wildcard model bypass + fail-open embedded model creds

- _key_requires_batch_model_access_check: check '*' / all-proxy-models
  before access_group_ids so wildcard keys skip the JSONL download.
- _resolve_batch_input_file_fetch_params: wrap embedded-model
  get_credentials_for_model in try/except HTTPException, mirroring the
  request-model fallback path, and always decode the file id.

Co-authored-by: Yassin Kortam <yassin@berri.ai>

* perf(batch_rate_limiter): reuse rate-limit descriptors across skip check and counter increment

* test(batch_rate_limiter): cover skip-path and file-fetch helpers

Add unit tests for the batch rate limiter's new skip/routing helpers so
the diff's patch coverage no longer depends on the CircleCI batches job,
whose coverage upload is blocked when an unrelated Bedrock integration
test aborts the run. Covers _get_batch_routing_model, _matches_skip_list,
_key_requires_batch_model_access_check, _has_applicable_batch_rate_limits,
_should_skip_batch_input_file_processing, _resolve_batch_input_file_fetch_params,
the descriptor-reuse path of _check_and_increment_batch_counters, and the
non-bytes file content guard in count_input_file_usage.

* fix(batch_rate_limiter): resolve provider skip from trusted deployment creds

Resolve the batch provider from router deployment credentials instead of
the user-supplied custom_llm_provider request field, so an unrestricted
key cannot spoof a skip-listed provider to bypass batch rate limiting.

Strengthen the provider-skip test to assert the file download and
descriptor work were short-circuited, and add a test that a spoofed
provider still falls through to rate-limit evaluation.

* fix(batch_rate_limiter): guard model-embedded credential lookup on llm_router presence

* test(batch_rate_limiter): drive real no-skip fetch path and pin wildcard+access-group predicate

The spoofed-provider test configured empty descriptors, so the no-limits
shortcut skipped the file fetch and the assertion only proved the provider
allow-list did not short-circuit before descriptor evaluation. Give the key an
applicable rate limit so the only thing that can prevent the fetch is the
provider skip, then assert afile_content is awaited and the counters are
incremented; the spoofed custom_llm_provider must not skip processing.

Also cover the wildcard / all-proxy-models plus access_group_ids combination in
the model-access predicate so the wildcard-wins behavior is locked down.

* fix(batch_rate_limiter): drop client-controlled skip flag to close quota bypass

The litellm_metadata.skip_batch_input_file_rate_limiting flag was read
straight from the request body, so any caller whose key had unrestricted
model access could send it and skip the input-file download, token count,
and RPM/TPM reservation, bypassing their batch rate limits. Skip decisions
now derive only from server-controlled general_settings.

* fix(batch_rate_limiter): match per-model skip on file-bound model only

The per-model skip resolved its model from _get_batch_routing_model, which
prefers the client-supplied top-level model field. That field only selects
routing credentials; the models a batch actually runs are the body.model
entries in the input JSONL. An unrestricted key could therefore name a
skip-listed deployment at the top level while routing a different,
same-provider model through the file, skipping the download, token count
and rate-limit reservation to bypass batch RPM/TPM limits.

Match the per-model skip against the file-bound model only (model-embedded
file id or unified managed file target), which is fixed when the file is
created and reflects the model the batch runs. The provider skip keeps using
the routing model since an admin opting out of a whole provider already
accepts any of that provider's models.

* fix(batch_rate_limiter): drop forgeable per-model skip to close quota bypass

The per-model skip matched skip_batch_input_file_rate_limiting_for_models
against the model bound to the input file id. That model comes from
decode_model_from_file_id / the unified file id, both unsigned base64 the
caller fully controls, so a caller could re-encode an accessible provider
file id with a skip-listed model while the JSONL still routes rate-limited
body.model entries and bypass the batch RPM/TPM counters. The models a batch
actually runs are its JSONL body.model entries, which cannot be known without
reading the file, so no caller-influenced model identifier can safely gate a
skip.

Remove the per-model skip entirely. The provider skip stays because the
provider is resolved from trusted deployment credentials and the batch is
constrained to run on that provider; the global disable and
no-applicable-limits skips stay because they do not depend on caller input.

* fix(batch_rate_limiter): warn when no-op per-model skip key is configured

* test(batch_rate_limiter): patch llm_router so model-embedded credential-error test hits fallback

* fix(batch_rate_limiter): resolve provider skip from file-bound model

create_batch routes a model-embedded or unified file id on the model
bound to that file and ignores the top-level model, so deriving the
provider skip from the top-level model first let a caller point model at
a skip-listed provider while the file routed a rate-limited one, skipping
counter enforcement. Resolve the routing model from the file binding
first, matching the batch endpoint.

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-06-01 20:03:19 -07:00
michelligabriele
80cf50dedb
fix(v3 limiter): cap no-max_tokens TPM floor at smallest configured limit (#28805) 2026-05-30 19:36:04 -07:00
Sameer Kankute
70d2748d80
fix(proxy): map stripped batch body.model to proxy alias for auth (#29264)
* fix(proxy): map stripped batch body.model to proxy alias for auth

replace_model_in_jsonl rewrites JSONL body.model to the provider id before
upload; batch file access checks must resolve that id back to model_name
so keys granted the proxy alias are not rejected with 403.

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

* fix(proxy): surface resolved proxy alias in batch file 403 detail

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-05-29 19:58:04 -07:00
Mateo Wang
7a462a4220
fix(rate-limit): stop v3 limiter from leaking internal stash to provider body (#27913)
* fix(rate-limit): stop v3 limiter from leaking internal stash to provider body

PR #27001 (atomic TPM rate limit) introduced a reservation flow that
writes four LiteLLM-internal keys onto the request data dict:

  _litellm_rate_limit_descriptors
  _litellm_tpm_reserved_tokens
  _litellm_tpm_reserved_model
  _litellm_tpm_reserved_scopes
  _litellm_tpm_reservation_released

These keys are forwarded as request body params to the upstream provider,
which rejects them as unknown fields:

  OpenAI    -> 400 'Unknown parameter: _litellm_rate_limit_descriptors'
              (mapped by litellm to RateLimitError / 429, hiding the bug
               behind a misleading 'throttling_error' code)
  Anthropic -> 400 '_litellm_rate_limit_descriptors: Extra inputs are
               not permitted'

Net effect: every chat completion against any real provider fails the
moment a virtual key has any tpm_limit / rpm_limit set — i.e. v3-enforced
key-level TPM/RPM limits are broken end-to-end. The v3 RPM/TPM check
itself still runs (raises 429 on over-limit), but the success path
poisons the upstream body.

Reproduced on litellm_internal_staging HEAD (410ce761dc) against
gpt-4o-mini and claude-haiku-4-5 with a 1-RPM/1-TPM key — first request
fails with the provider's unknown-field error.

Fix: the stash is metadata only.

  - Add RATE_LIMIT_DESCRIPTORS_KEY constant and a _LITELLM_STASH_KEYS
    registry so we have a single source of truth for stash keys.
  - New helper _stash_value_in_metadata_channels writes to
    data['metadata'] / data['litellm_metadata'] without touching the
    top level.
  - _stash_reservation_in_data and the descriptor stash now route
    through that helper. _mark_reservation_released stops writing
    top-level.
  - _lookup_stashed_value also checks kwargs['metadata'] /
    kwargs['litellm_metadata'] (raw request_data shape) in addition to
    kwargs['litellm_params']['metadata'] (completion kwargs shape).
  - async_post_call_failure_hook now reads descriptors via the unified
    metadata lookup instead of request_data.get(top-level).
  - Defense in depth: async_pre_call_hook strips any stash key that
    somehow surfaced at the top level (stale cache, future refactor,
    test fixture) before returning.

Tests:
  - New regression test asserts no _litellm_* stash key is present at
    the top level of data after async_pre_call_hook, and that the
    metadata channel still carries the reservation + descriptors so
    success / failure reconciliation works.
  - Existing test_tpm_concurrent.py tests that asserted top-level
    presence are updated to read from data['metadata'] — the location
    is an implementation detail; the spec is that post-call callbacks
    can resolve the stash.

Verified end-to-end against OpenAI gpt-4o-mini and Anthropic
claude-haiku-4-5 via /v1/chat/completions on a low-rpm key:

  - With limits not exceeded: HTTP 200, valid completion response,
    no leaked fields in body.
  - With RPM exceeded: HTTP 429 from v3 enforcement
    ('Rate limit exceeded ... Limit type: requests').
  - With TPM exceeded: HTTP 429 from v3 enforcement
    ('Rate limit exceeded ... Limit type: tokens').

Full v3 hook test suite passes (171 tests).

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

* chore(rate-limit): use RATE_LIMIT_DESCRIPTORS_KEY constant in test, trim noisy comments

Address greptile P2: test fixture now uses the imported constant.
Drop comments that re-explain what well-named identifiers already convey.

* fix(rate-limit): reject caller-supplied stash values to prevent TPM-refund abuse

Strip _LITELLM_STASH_KEYS from data top-level and both metadata channels at
the start of async_pre_call_hook. Without this, an authenticated caller can
inject _litellm_rate_limit_descriptors plus _litellm_tpm_reserved_tokens in
body metadata, trigger a proxy-side rejection, and cause
async_post_call_failure_hook to refund TPM counters against attacker-named
scopes (e.g. another tenant's api_key).

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-14 10:53:04 -07:00
ishaan-berri
e9fb29061a
Include model name + configured TPM/RPM in priority rate-limit 429 er… (#27216)
* Include model name + configured TPM/RPM in priority rate-limit 429 errors (#27215)

* Include model name + configured TPM/RPM in priority rate-limit 429 errors

The current 429 message ('Priority-based rate limit exceeded. Priority: prod,
Rate limit type: tokens, Remaining: -664145, Model saturation: 86.3%') doesn't
tell the operator which model was hit or what the configured limit is, so they
can't tell whether the priority allocation needs tuning or the model TPM is
just too small.

Add Model, Model TPM, and Model RPM to both the priority-based 429 and the
sibling Model-capacity 429 in dynamic_rate_limiter_v3._check_rate_limits.
Pure error-message change — no behavior or schema impact.

* test: assert priority 429 includes model name + configured TPM/RPM

Adds a regression test for the new fields in the priority-based 429 detail
('Model:', 'Model TPM:', 'Model RPM:'). Verified locally that the test
fails against the unpatched dynamic_rate_limiter_v3.py and passes after
the patch.

---------

Co-authored-by: shin-watcher <ext-agent-shin@berri.ai>

* Update litellm/proxy/hooks/dynamic_rate_limiter_v3.py

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

* Update litellm/proxy/hooks/dynamic_rate_limiter_v3.py

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

---------

Co-authored-by: shin-watcher <ext-agent-shin@berri.ai>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
2026-05-05 19:05:22 -07:00
Yassin Kortam
950074eea2
fix: atomic TPM rate limit (#27001)
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
2026-05-05 16:58:07 -07:00
Yuneng Jiang
8cac6c5bff
[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.
2026-05-04 20:13:31 -07:00
Yuneng Jiang
727ab8dcc4
[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.
2026-05-04 20:05:24 -07:00
mateo-berri
ea0d92a3d8 fix: remove traceback key instead of it being "" 2026-05-01 20:49:49 -07:00
Claude
5b775d1274
feat(spend-logs): suppress traceback in SpendLogs error_information row
Some checks are pending
Unit Tests: Caching (Redis) / caching-redis (push) Waiting to run
Unit Tests: Proxy DB Operations / proxy-utils (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / assert-shard-coverage (push) Waiting to run
Unit Tests: Proxy DB Operations / auth-checks (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / budgets (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / custom-logging (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / db-and-spend (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / endpoints-and-responses (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / guardrails-hooks (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / jwt-and-keys (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / key-generation (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / logging-misc (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / proxy-runtime (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / proxy-server-core (push) Blocked by required conditions
Unit Tests: Proxy DB Operations / schema-migration (push) Blocked by required conditions
Unit Tests: Security / security (push) Waiting to run
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
2026-05-02 00:44:35 +00:00
stuxf
b80246971b
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>
2026-05-01 17:36:12 -07:00
yuneng-jiang
57dd3891fb
Merge pull request #27024 from BerriAI/litellm_yj_may1
[Infra] Merge dev branch
2026-05-01 16:36:24 -07:00
Yuneng Jiang
a12b4249bd
[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`.
2026-05-01 15:57:42 -07:00
mateo-berri
04e96a9bdc Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_clean_litellm_oss_staging_04_01_2026 2026-05-01 15:54:10 -07:00
Krrish Dholakia
eba0cdf3f5 fix(rate-limit): fail closed on unrecognized OVER_LIMIT descriptor
If atomic_check_and_increment_by_n returns overall_code=OVER_LIMIT but no
status entry matches a descriptor key the dynamic limiter dispatcher knows
how to translate into a 429 (`model_saturation_check` or `priority_model`),
the for-loop previously exited cleanly and execution fell through to the
priority-tracking increment + the data["litellm_proxy_rate_limit_response"]
write — silently admitting an over-limit request.

This is the fail-open path a future contributor would hit by wiring a new
descriptor type into enforced_descriptors without updating the dispatcher.
Refuse the request with a generic 429 carrying the offending descriptor
metadata so the operator can see what slipped past, and emit an error log
to surface the wiring gap.

Adds a regression test (test_dynamic_rate_limiter_v3_fails_closed_on_unknown_descriptor)
that drives the limiter with a synthetic OVER_LIMIT response carrying an
unrecognized descriptor_key and asserts a 429 is raised.

Tests: 65 passed (1 skipped), 0 regressions.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 12:19:43 -07:00
Krrish Dholakia
6496e58417 review: address atomic limiter review feedback
- Lua script now reads time via redis.call('TIME') instead of a client-supplied
  timestamp. Prevents window-reset divergence across replicas with skewed
  wall-clocks, which could otherwise reopen the cross-replica TOCTOU window.
- Per-descriptor window_size is now plumbed through both the Lua ARGV layout
  and the in-memory fallback. Previously the in-memory path used the global
  self.window_size while Lua honored the per-descriptor override, so a
  descriptor with a custom window would be enforced inconsistently between
  Redis-available and Redis-unavailable code paths.
- Lua-failure fallback path now logs at error severity and explicitly
  documents the in-memory ↔ Redis state divergence risk so operators can
  alert on it. Prior `warning` log understated the impact.
- Coarse-granularity lock is now documented inline with the conditions under
  which a per-descriptor sharded lock would be worth introducing.
- New regression test: zero-token batch consumes RPM only and is properly
  capped by the RPM ceiling (validates the asymmetric quota path that arises
  from `inc_amount <= 0: continue`).

Tests: 64 passed (1 skipped), 0 regressions. Multi-instance Redis loadtest
re-verified: chat 20/80 success @ RPM=20, batches 3/20 @ TPM=200.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 12:02:04 -07:00
milan-berri
7e58c7139a
fix(proxy): include team membership budget in combined_view for RPM/TPM (#24925)
Join LiteLLM_BudgetTable as b_tm on team membership budget_id and select
team_member_tpm_limit / team_member_rpm_limit so virtual key auth populates
limits for parallel_request_limiter_v3.

Add test_team_member_rate_limits_v3_raises_429_when_over_limit mirroring
existing key-level OVER_LIMIT / HTTP 429 coverage.

Made-with: Cursor
2026-05-01 17:26:45 +05:30
user
b53adf7cff address budget reservation review edges 2026-04-30 21:21:26 -07:00
Krrish Dholakia
dd57ae6691 feat(rate-limit): atomic check-and-increment-by-N for multi-process safety
The previous fix for the TOCTOU bypass relied on a per-instance asyncio.Lock,
which closed the window only within a single proxy worker. Multi-replica
deployments still raced across processes — A and B both read counter=99,
both passed validation, both incremented to 100/100 → effective limit doubled.

Add `CHECK_AND_INCREMENT_BY_N_SCRIPT` Lua script that processes any number of
(window_key, counter_key, limit, increment, ttl) descriptors atomically with
all-or-nothing semantics: if any descriptor would exceed its limit, no counter
is modified and the script returns OVER_LIMIT with the offending descriptor's
state. When Redis isn't configured, the in-memory fallback uses the existing
asyncio.Lock for single-process atomicity.

Expose this as `_PROXY_MaxParallelRequestsHandler_v3.atomic_check_and_increment_by_n`
and rewire both call sites:

- batch_rate_limiter._check_and_increment_batch_counters: replace the
  read_only=True check + separate async_increment_tokens_with_ttl_preservation
  with a single atomic call passing the batch's (request_count, total_tokens)
  as the increment.
- dynamic_rate_limiter_v3._check_rate_limits: bundle model_saturation_check
  (always enforced) and priority_model (enforced only when saturated) into
  one atomic call. When priority is unenforced, increment its counter via
  the existing should_rate_limit(read_only=False) path for tracking only.

Update structural regression tests to assert the new atomic path is used
rather than the legacy two-phase pattern.

Tests: 4/4 TOCTOU tests pass, 59 existing rate-limiter tests pass, no
regressions.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 18:54:36 -07:00
Krrish Dholakia
dbe5c3b0b2 fix: close TOCTOU window in batch + dynamic rate limiters
The batch rate limiter (`_check_and_increment_batch_counters`) and the
dynamic rate limiter (`_check_rate_limits`) implemented rate limiting in
two disjoint awaits: a `should_rate_limit(read_only=True)` check followed
by a separate increment. Concurrent requests could all observe the same
pre-increment state, all pass enforcement, and all then increment —
multiplying the effective quota by the concurrency level.

Demonstrated bypass (see new test):
- Batch: 5 concurrent batches of 40 tokens each against TPM=100 consumed
  200 tokens (100% over).
- Dynamic: 5 concurrent priority="high" requests against RPM=2 all
  passed Phase 1 + Phase 3.

Wrap both critical sections in a per-instance asyncio.Lock so the read
and increment execute atomically within a process. Multi-replica
deployments still rely on Redis Lua atomicity for cross-process safety;
that is a follow-up.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 18:46:09 -07:00
user
694fadd175 fix budget reservation review findings 2026-04-30 17:38:18 -07:00
user
fce86d1334 fix budget reservation greptile findings 2026-04-30 17:08:45 -07:00
user
f8d187785d finalize invalidated budget reservations 2026-04-30 16:52:09 -07:00
user
1373ae1021 fix budget tag spend counter reconciliation 2026-04-30 16:09:38 -07:00
user
96a283ed0f guard reservation invalidation cleanup 2026-04-30 15:00:35 -07:00
user
8311456cfc invalidate reservations after release cleanup failure 2026-04-30 14:48:55 -07:00
user
5521af096e preserve database failure during reservation cleanup 2026-04-30 14:23:57 -07:00
user
0b71282985 address budget reservation review findings 2026-04-30 14:06:42 -07:00
user
09503ebb8f harden budget reservation recovery 2026-04-29 21:06:30 -07:00
user
5a619cf879 tighten budget spend admission 2026-04-29 20:30:09 -07:00
shivam
a449fc11a6
Merge branch 'litellm_internal_staging' into litellm_project_rate_limiting 2026-04-17 19:10:06 -07:00
shivam
6fd49f1da1
fix: enforce project-level model-specific rate limits in parallel_request_limiter_v3
Project-level model rpm/tpm limits stored in project_metadata were never
checked during rate limit enforcement — only model-level limits applied.

Adds _add_project_model_rate_limit_descriptor_from_metadata() to the v3
limiter (mirrors the existing team metadata path) and calls it in
async_pre_call_hook, creating a model_per_project descriptor keyed as
"{project_id}:{model}" with the project's configured limits.

Also extends get_model_rate_limit_from_metadata's Literal to accept
"project_metadata" and adds get_project_model_rpm/tpm_limit helpers.

Fixes: LIT-2317

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-17 18:17:24 -07:00
Ishaan Jaffer
e8461b5b97
style: run black formatter on files from main merge 2026-04-17 13:02:59 -07:00
ishaan-berri
c6aa3ea452
Litellm ishaan april1 try2 (#25110)
* Litellm ishaan april1 (#25103)

* fix(proxy): enforce upperbound key params on key/update and add custom_key_update hook

The /key/update endpoint did not enforce upperbound_key_generate_params,
allowing users to bypass configured limits (tpm_limit, rpm_limit,
max_budget, duration, budget_duration) by updating an existing key
instead of generating a new one.

Extract the upperbound enforcement logic from _common_key_generation_helper()
into a standalone _enforce_upperbound_key_params() function and call it from
both the generate and update paths. For updates, None values are skipped
(not filled with defaults) since they mean "don't change this field".

Also adds a custom_key_update config option and user_custom_key_update global,
mirroring the existing custom_key_generate pattern, so custom key validation
logic can fire during key updates as well.

* fix(proxy): invoke custom_key_update hook in bulk update path

The user_custom_key_update hook was only called in update_key_fn
(single key update) but not in _process_single_key_update (bulk
update path), allowing custom validation to be bypassed via the
/key/update/bulk endpoint. Mirror the hook invocation in both paths.

* fix(proxy): pass UpdateKeyRequest to hook in bulk path, not BulkUpdateKeyRequestItem

Move the custom_key_update hook invocation to after UpdateKeyRequest
is constructed so the hook receives the same type in both single and
bulk update paths. Previously the bulk path passed
BulkUpdateKeyRequestItem (5 fields only), which would cause
AttributeError for hooks accessing fields like tpm_limit or models.

* fix(bedrock): promote cache usage to message_delta for Claude Code (#24850)

Ensure Bedrock/Anthropic-compatible streaming exposes cache usage where Claude Code reads it by promoting message_stop usage onto message_delta and preserving usage fields in fake-streamed message_delta events.

Made-with: Cursor

* fix(search): Support self-hosted Firecrawl response format in search transform (#24866)

The `transform_search_response` method only handled Firecrawl Cloud (v2)
response format where `data` is a dict with `web`/`news` keys. Self-hosted
Firecrawl (v1) returns `data` as a flat list of result objects, causing an
`AttributeError: 'list' object has no attribute 'get'`.

Detect the response format by checking if `data` is a list (self-hosted)
or dict (cloud) and handle both cases.

Cloud format:  {"data": {"web": [...], "news": [...]}}
Self-hosted:   {"success": true, "data": [{"url": "...", "title": "...", ...}]}

Co-authored-by: Synergy <synergyoclaw@gmail.com>

* feat: add environment and user tracking to prompt management (#24855)

* feat: add environment and user tracking to prompt management

- Add environment (development/staging/production) and created_by columns to LiteLLM_PromptTable
- Update unique constraint to [prompt_id, version, environment]
- All CRUD endpoints support environment filtering and user tracking
- Redesigned prompt detail page with environment tabs and version history
- UI: environment filter on list page, environment selector in editor
- 8 new tests for environment and user tracking

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: Black formatting and add environments to PromptInfoResponse TypeScript type

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: address Greptile review findings

- P1: delete_prompt scopes in-memory cleanup to environment when provided
- P2: dotprompt_content parsed directly regardless of environment flag
- P2: use distinct for environments query
- P2: fix double-fetch on initial mount in prompt_info.tsx
- fix: remove unsupported select kwarg from find_many

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: address remaining Greptile review comments

- Remove unused useCallback import (index.tsx)
- Remove unused ENV_COLORS variable (prompt_info.tsx)
- P1: in-memory fallback in get_prompt_versions now respects environment filter
- P1: reset selectedEnv when promptId changes to avoid stale state
- Cyclic imports are pre-existing pattern, not introduced by this PR

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: scope patch_prompt to environment using primary key

- Add environment query param to patch_prompt endpoint
- Look up target row by composite key (prompt_id + version + environment)
- Update by primary key (id) to target exactly one row
- Fixes Greptile finding: patch with multiple environments no longer ambiguous

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: use actual start_time for failed request spend logs (#24906)

async_post_call_failure_hook set both start_time and end_time to
datetime.now(), making all failed requests show duration=0. Use the
actual start_time from litellm_logging_obj instead, so spend logs
reflect the real request duration on timeout and other failures.

Fixes #24888

* feat(bedrock): add nova canvas image edit support (#24869)

* feat(bedrock): add nova canvas image edit support

* fix(bedrock): support PathLike inputs for nova image edit

* chore: sync schema.prisma copies from root

* fix(mypy): correct type-ignore code for delta_usage arg-type

* fix(mypy): cast status_code to str, suppress intentional str yield

* fix(lint): extract _create_content_block_chunks to fix PLR0915

* fix(lint): extract helpers to fix PLR0915 in prompt endpoints

---------

Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: redhelix <amin.lalji@gmail.com>
Co-authored-by: Synergy <synergyoclaw@gmail.com>
Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: madhu19991 <madhu@thunkai.com>
Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

* fix(test): update model armor streaming test to handle string or int error code

---------

Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: redhelix <amin.lalji@gmail.com>
Co-authored-by: Synergy <synergyoclaw@gmail.com>
Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: madhu19991 <madhu@thunkai.com>
Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
2026-04-03 14:57:44 -07:00
Harshit Jain
4f04d2648e
Merge branch 'main' into litellm_langfuse-session-trace-fix 2026-03-15 01:09:49 +05:30
michelligabriele
7c5e2e8389
fix(proxy): make async_post_call_response_headers_hook consistent across all endpoints (#22985)
* fix(proxy): make async_post_call_response_headers_hook consistent across all endpoints

The response headers hook had 5 gaps that prevented callbacks from
reliably extracting routing metadata across endpoint types:

1. Hook never fired for /audio/transcriptions (endpoint bypasses
   base_process_llm_request)
2. custom_llm_provider not accessible in hook data for any endpoint
3. custom_llm_provider not stamped in ResponsesAPIResponse._hidden_params
   (unlike chat completions)
4. model_info under inconsistent keys (metadata vs litellm_metadata)
5. request_headers always None at all call sites

This adds a litellm_call_info parameter to the hook that normalizes
routing metadata (custom_llm_provider, model_info, api_base, model_id)
regardless of endpoint type. Also stamps custom_llm_provider on
Responses API responses, adds the hook call to the transcription
handler, and passes request_headers at all call sites.

Supersedes PR #21385.

* fix(proxy): address review feedback — safer backwards compat and None guards

- Replace try/except TypeError with inspect.signature() check for
  litellm_call_info backwards compatibility. This avoids masking real
  TypeErrors inside callback implementations and prevents double
  invocation with inconsistent parameters.

- Use (data.get("key") or {}) instead of data.get("key", {}) to guard
  against keys that exist with an explicit None value, which would
  cause AttributeError on the subsequent .get() call.

* fix(proxy): cache inspect.signature result for callback compat check

Move the inspect.signature() call into a module-level helper with a
dict cache keyed by callback identity. Avoids repeated introspection
per request per callback in the hot path.

* fix(proxy): use class identity for signature cache key

Key the _CALLBACK_ACCEPTS_CALL_INFO cache by id(type(cb)) instead of
id(cb) to avoid stale entries from Python address reuse after GC.
All instances of the same callback class share the same method
signature, so class identity is both safer and more cache-efficient.
2026-03-12 08:51:00 -07:00
Krish Dholakia
cf439c269c
Agents - add max budget + tpm/rpm limiting per agent AND per agent session (#22849)
* feat: enforce x-litellm-trace-id in header, if required

* feat: update spend for agent

* refactor: update agent table to follow similar format as other entities - also add a spend column - allows us to see spend of an agent

* fix: cleanup ui

* feat: return spend on agent endpoints

* feat: scope pr

* feat(agents/): support budgets + rate limiting on agents + agent sessions

* fix: address PR review feedback

- Add missing tpm_limit, rpm_limit, session_tpm_limit, session_rpm_limit
  columns to root schema.prisma to match proxy and extras schemas
- Add backwards-compatible fallback to key metadata for max_iterations
  so existing users don't silently lose enforcement

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: qa'ed RPM limiting on agents

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-07 19:12:42 -08:00
Harshit28j
338a634762 Fix root cause: DB spend log session_id didn't match Langfuse trace_id
The proxy has two separate failure paths:
1. async_failure_handler → Langfuse callback (uses model_call_details with
   standard_logging_object containing the correct trace_id)
2. post_call_failure_hook → _ProxyDBLogger → spend log (uses request_data
   which did NOT have standard_logging_object, so session_id fell to
   random uuid4())

These two paths used different data dicts, so the DB session_id was a
random UUID unrelated to the Langfuse trace_id. Users could not search
by the Session ID from LiteLLM logs in Langfuse for failed requests.

Fix: In _ProxyDBLogger.async_post_call_failure_hook, propagate
standard_logging_object and litellm_trace_id from the litellm_logging_obj
(already present in request_data) before writing the spend log.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-02 21:31:47 +05:30
Ishaan Jaff
755ae9ed56
Litellm stability fix v2 (#22452)
* fix(test): add spend data polling + graceful skip to Gemini e2e spend tests

Same fix as test_vertex_with_spend.test.js — replace fixed 15s wait with
polling loop (6 attempts, 10s each) and graceful skip if spend data not
available. Also add jest.retryTimes(3) and increase timeout to 90s.

This is the last remaining CI failure on main (pipeline 62771).

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix(test): add graceful skip for spend data in Anthropic passthrough test

The test_anthropic_basic_completion_with_headers fails with KeyError: 0
because the /spend/logs endpoint returns an error dict (auth error) instead
of a list. When dict[0] is accessed, it throws KeyError.

Fix: Check if spend_data is actually a list with valid entries before
asserting. Skip spend assertions gracefully if data unavailable.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix(ci): resolve 4 CI test failures

1. Add CURSOR_API_BASE to environment variables reference in config_settings.md
2. Fix test_sse_mcp_handler_mock by mocking extract_mcp_auth_context and
   set_auth_context so the handler reaches sse_session_manager.handle_request
3. Change test_async_increment_tokens_with_ttl_preservation flaky decorator
   from reruns=3 to retries=3,delay=2 for better intermittent failure handling
4. Add app.dependency_overrides for user_api_key_auth in test_mock_create_audio_file
   to bypass authentication (same pattern as test_target_storage_invokes_storage_backend)

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
2026-02-28 15:29:45 -08:00
Krish Dholakia
12c4876891
Agents - assign tools (#22064)
* feat(proxy): add max_iterations limiter for agent session loops (#22058)

Adds a new proxy hook that enforces a per-session cap on the number of
LLM calls an agentic loop can make. Callers send a session_id with each
request, and the hook counts calls per session, returning 429 when the
configured max_iterations limit is exceeded.

- Uses Redis Lua script for atomic increment (multi-instance safe)
- Falls back to in-memory cache when Redis unavailable
- Follows parallel_request_limiter_v3 pattern
- Configurable via key metadata: {"max_iterations": 25}
- Session counters auto-expire via TTL (default 1hr)

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add new code execution dataset

* feat(agent_endpoints/): allow giving agents keys

* fix: ui fixes

* feat: allow assigning mcp servers to agents

* fix: eliminate duplicate DB queries in MCP agent auth and N+1 in agent listing (#22110)

- Extract _get_agent_object_permission helper so _get_allowed_mcp_servers_for_agent
  and _get_agent_tool_permissions_for_server share a single DB fetch instead of
  each independently querying the same agent row (was 1+N queries per MCP request)
- Use include={"object_permission": True} on find_many in get_all_agents_from_db
  to eagerly load permissions in one query instead of N+1
- Use include={"object_permission": True} on create/update/find_unique in all
  agent CRUD operations, removing attach_object_permission_to_dict follow-up calls

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-25 11:44:30 -08:00
yuneng-jiang
f4e23c97fd [Fix] Enrich failure spend logs with key/team metadata
Failure spend logs were missing key metadata (key alias, user ID, team ID,
team alias) in two scenarios:

1. Auth errors (401 ProxyException): auth_exception_handler creates a
   minimal UserAPIKeyAuth with only api_key and request_route set — all
   other fields are null. The failure hook now looks up the full key object
   from cache/DB using the key hash to populate the missing fields.

2. Post-auth failures (provider errors, rate limits): key fields are
   present but team_alias is always null because LiteLLM_VerificationTokenView
   SQL view does not include team_alias. The failure hook now looks up the
   team object from cache to populate team_alias.

Both lookups are non-fatal and wrapped in try/except.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-24 17:14:37 -08:00
Ishaan Jaff
c6a8034184
fix(tests): isolate flaky tests - restore global state in setup/teardown (#21791)
* fix(tests): isolate flaky files endpoint tests from global proxy state

* test(secret_managers): add mocked unit test for write/read JSON secret cycle

* fix(tests): restore litellm.callbacks in TestSpendLogsPayload setup/teardown

* fix(tests): clear app.openapi_schema in TestSwaggerChatCompletions setup/teardown

* fix(tests): add flaky marker to test_async_increment_tokens_with_ttl_preservation
2026-02-21 11:30:35 -08:00