Commit graph

41 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
e59e34bed3
Gemini managed agents support (#28270)
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* Add support for environment variable in interactions api

* Add sdk  support for gemini create agent

* Add agents endpoint support via proxy

* Add outputs of each api

* Add routing for model and agents param

* Remove redundant condition in get_provider_agents_api_config

LlmProviders.GEMINI.value is literally the string "gemini", so the
second clause of the or was checking the exact same thing as the first.

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

* fix: forward query-param credentials to list/get/delete/versions Gemini agent endpoints

The list_gemini_agents, get_gemini_agent, delete_gemini_agent, and
list_gemini_agent_versions endpoints previously constructed a hardcoded
data dict with no mechanism to pass provider credentials.  Unlike
create_gemini_agent (POST, reads litellm_params_template from body),
these GET/DELETE endpoints gave no way for multi-tenant callers to
supply a per-request api_key or other LiteLLM params.

Fix:
- Add _merge_query_params_into_data() helper that reads query parameters
  from the request and merges them into the data dict without overwriting
  already-set keys (e.g. path params like 'name').
- Support a JSON-encoded litellm_params_template query parameter
  (matching the POST body pattern) as well as flat key=value pairs
  (e.g. api_key=AIza...).
- Apply the helper in all four affected endpoints.
- Add 13 unit tests covering the helper and each endpoint.

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

* fix: pass model=None for managed agent proxy endpoints to prevent agent name polluting data["model"]

Endpoints acreate_agent, aget_agent, adelete_agent, and alist_agent_versions
were passing model=<agent_name> to base_process_llm_request. This caused
common_processing_pre_call_logic to write the agent name into self.data["model"],
which then triggered spurious model-alias mapping, rate-limiting lookups, and
logging tied to a non-existent model deployment.

The agent name is already carried in data["name"] and is passed correctly to
the SDK functions (litellm.interactions.agents.*). There is no reason to also
set model=<agent_name>; the correct value is model=None for all five managed-agent
management routes.

Adds tests/test_litellm/proxy/google_endpoints/test_managed_agents_model_param.py
to verify all five managed-agent endpoints pass model=None.

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

* fix: address greptile P1/P2 review comments

P1 (router.py): Restore fallback/retry support for acreate_interaction
and create_interaction. Both were silently moved to _init_interactions_api_endpoints
(direct call, no fallbacks). Moved them back to _ageneric_api_call_with_fallbacks
so users with configured fallback models keep retry behaviour.

P1 security (agents_endpoints.py): Remove flat query-param credential
path (e.g. ?api_key=AIza...) from _merge_query_params_into_data.
Credentials in URL query strings appear verbatim in server access logs,
CDN edge logs, and browser history. Only the JSON-encoded
litellm_params_template query param (matching the POST body pattern) is
retained.

P2 (interactions/http_handler.py): Extract _BaseHTTPHandler with shared
_handle_error, _sync_client, and _async_client helpers. InteractionsHTTPHandler
now extends _BaseHTTPHandler. The _async_client reads the provider from
litellm_params instead of hardcoding GEMINI.

P2 (interactions/agents/http_handler.py): AgentsHTTPHandler now extends
InteractionsHTTPHandler (which inherits _BaseHTTPHandler) so all shared
HTTP infrastructure is reused rather than duplicated. Removes the
hardcoded LlmProviders.GEMINI from the async client path.

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

* fix: address CI failures from greptile review fixes

- black: format interactions/agents/main.py and utils.py
- tests: update test_gemini_agents_endpoints.py to match new
  _merge_query_params_into_data behaviour (flat credential params are
  rejected; only JSON-encoded litellm_params_template is accepted)
- ci: add test_gemini_agents_endpoints.py to endpoints-and-responses
  shard in test-unit-proxy-db.yml so assert-shard-coverage passes
- tests: add _initialize_managed_agents_endpoints and
  _init_managed_agents_api_endpoints test coverage so router_code_coverage
  passes; also fix TestRouterCreateInteractionRouting to reflect that
  acreate_interaction now correctly routes through
  _ageneric_api_call_with_fallbacks (restoring fallback support)

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

* fix: remove InteractionsHTTPHandler._handle_error override to fix type errors

AgentsHTTPHandler extends InteractionsHTTPHandler and calls
self._handle_error(provider_config=agents_api_config) where
agents_api_config is BaseAgentsAPIConfig. Python MRO resolved _handle_error
to InteractionsHTTPHandler._handle_error which expected BaseInteractionsAPIConfig,
causing 10 mypy arg-type errors in interactions/agents/http_handler.py.

Removing the redundant override lets both classes inherit _BaseHTTPHandler._handle_error
(provider_config: Any) which is structurally correct for both config types.

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

* fix: agent-only interactions and managed agents provider routing

Resolve None custom_llm_provider in agents HTTP client lookup and set
custom_llm_provider on GenericLiteLLMParams for all agent CRUD paths.

Stop mapping agent names to proxy model routing; route interactions
through _init_interactions_api_endpoints with fallbacks only when model
is set. Consolidate duplicate router elif branches for interaction APIs.

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

* Fix greptile review

* test(agents): add unit tests for managed agents SDK and HTTP handler

Adds coverage for the new `litellm.interactions.agents` surface area:
- main.py: sync/async entry points (create/list/get/delete/list_versions),
  provider config lookup, logging-obj helper, async error wrapping
- http_handler.py: every CRUD method (sync + async paths), `_is_async`
  dispatch branches, and provider error mapping through GeminiAgentsConfig
- utils.py: get_provider_agents_api_config for supported / unsupported
  providers

Brings patch coverage on these files from <25% to ~100% so codecov/patch
is satisfied.

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

* docs(gemini-agents): fix misleading credential-passing examples in GET/DELETE docstrings (#28293)

The four GET/DELETE endpoint docstrings (list_gemini_agents,
get_gemini_agent, delete_gemini_agent, list_gemini_agent_versions)
documented passing per-request credentials as flat query parameters
(e.g. ?api_key=AIza...). However, _merge_query_params_into_data only
reads the JSON-encoded litellm_params_template query parameter and
intentionally ignores flat params (URL query strings appear verbatim
in access logs, browser history, and Referer headers).

Callers following the documented curl examples would have their
credentials silently dropped and hit auth failures against Gemini.

Update the examples to use the supported JSON-encoded
litellm_params_template query parameter, matching _merge_query_params_into_data's own docstring.

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

* refactor(agents): rename provider-agnostic agent response types

Move GeminiAgent{ListResponse,DeleteResult,VersionsResponse} to
provider-neutral names (AgentListResponse, AgentDeleteResult,
AgentVersionsResponse) so the BaseAgentsAPIConfig interface no longer
references Gemini-specific type names.

* fix(gemini-agents): close veria-flagged credential-escalation gaps

Two high-severity findings from the veria-ai PR review are addressed:

1. **api_base override could leak the shared Gemini key**
   GeminiAgentsConfig.validate_environment falls back to GOOGLE_API_KEY /
   GEMINI_API_KEY when no api_key is supplied. Combined with caller-controlled
   api_base on the proxy CRUD endpoints, an authenticated user could redirect
   the outbound request to an attacker-controlled host and capture the
   operator's shared Gemini key from the x-goog-api-key header. The config
   now refuses env-fallback whenever api_base is explicitly overridden.

2. **Managed-agent CRUD exposed to ordinary LLM keys**
   The new /v1beta/agents routes live in google_routes (i.e. llm_api_routes),
   so any non-admin LLM key can reach them. Unlike /v1beta/models/...:
   generateContent these endpoints are NOT model-routed and have no
   model_list-supplied credentials, so env-fallback would let any LLM key
   list / create / delete agents inside the operator's Gemini project. Each
   endpoint now calls _enforce_caller_supplied_provider_key, which requires
   non-admin callers to supply their own Gemini api_key via
   litellm_params_template. Proxy admins keep the env-fallback convenience.

Tests cover non-admin rejection, admin allow-through, the api_base override
guard, and SDK env-fallback when api_base is not overridden.

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

* test(router): restore strict assert_called_once_with on interactions default-provider test

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-19 16:02:03 -07:00
Mateo Wang
2e5ebf826f
fix(responses): register cooldowns on failure + fail fast on stale encrypted_content (#27820) 2026-05-13 09:03:13 -07:00
Cursor Agent
40db114a23
fix(router): accept Pydantic LiteLLM_Params in encryption-boundary key lookup
Greptile flagged that the strict isinstance(dict) guard in
_encryption_boundary_key would silently return None for any non-dict input,
including a LiteLLM_Params Pydantic instance, which exposes a custom .get()
method and is intended to be used dict-style in some router paths. If such
an instance ever flowed into healthy_deployments, the guard would drop every
candidate from boundary matching and fall through to the full deployment
pool, i.e. trigger the exact invalid_encrypted_content failure this check
exists to prevent.

Loosen the guard to accept any object exposing a callable .get(): plain
dicts (the common case) and LiteLLM_Params-style Pydantic instances. The
function still returns None for non-dict-like values (None, lists, strings,
ints, bare objects).

Adds regression tests covering:
  - LiteLLM_Params Pydantic instance resolves to the same boundary tuple as
    an equivalent plain dict
  - non-dict-like values and dicts missing required fields still return None
2026-05-12 03:09:08 +00:00
mateo-berri
f3b8aad883
fix(router): pin Responses API affinity to Azure resource on model-group switch
When a Responses API follow-up switches model_name (e.g. gpt-5.3-codex ->
gpt-5.4, or to a LiteLLM-side alias of the same Azure deployment), the
router has already filtered healthy_deployments to the new group, so the
originating model_id is no longer present. The encrypted_content_affinity
check would log "decoded deployment not found" and fall back to the full
deployment pool, where simple-shuffle could land on a different Azure
resource and trip a 400 invalid_encrypted_content.

Fall back to pinning by the originating deployment's encryption boundary
(api_base + api_key) when the model_id miss is across model groups. The
encrypted_content travels with the Azure resource, not the model_name,
so any deployment on the same resource accepts it.

LIT-2531
2026-05-12 02:26:06 +00:00
mateo-berri
860f6b526e
Merge branch 'litellm_internal_staging' into litellm_access-group-routing-fix 2026-05-01 23:07:37 +00:00
shivam
e72eac9176
Fix add_model_file_id_mappings when router returns single deployment dict
When model_info.id equals model_name (common for batch models), the router
resolves via has_model_id and returns one deployment dict instead of a list.
The dict branch incorrectly iterated deployment keys (model_name,
litellm_params, model_info), producing non-string values that broke
LiteLLM_ManagedFileTable validation on managed file upload.

Normalize list vs dict by wrapping single deployments and extracting
model_info.id for each response pair.

Add regression tests including the batch model id == model_name case.

Made-with: Cursor
2026-04-30 18:04:47 -07:00
Sameer Kankute
a3da4721ca
test(router): add coverage for access-group deployment filter
Add a router utils unit test that directly exercises _filter_deployments_by_model_access_groups for access-group-only key permissions.

Made-with: Cursor
2026-04-21 15:21:35 +05:30
Ishaan Jaffer
e8461b5b97
style: run black formatter on files from main merge 2026-04-17 13:02:59 -07:00
Sameer Kankute
3a4ed48f54
fix(router): don't create litellm_metadata for non-Responses API calls in encrypted_content_affinity_check (#25347)
Using setdefault('litellm_metadata', {}) unconditionally created an empty
litellm_metadata key for chat completions and embeddings. This caused
_get_metadata_variable_name_from_kwargs to return 'litellm_metadata' instead
of 'metadata', so tag-based routing looked for tags in the wrong dict and
ignored all tag filters.

Fix: only set the encrypted_content_affinity_enabled flag when litellm_metadata
already exists (Responses API path). Chat completions and embeddings never have
this key, so nothing is created and tag routing works correctly.
2026-04-08 21:11:19 -07:00
ishaan-berri
51876292a0
Litellm ishaan april4 2 (#25150)
* feat(router): integrate allowed_fails_policy into health check failures (#24988)

* feat(router): integrate allowed_fails_policy into health check failures

Health check failures now increment the same per-deployment failure
counters used by allowed_fails_policy, so users can control how many
health check failures of each error type are required before a
deployment enters cooldown.

- ahealth_check() preserves the original exception in its return dict
- run_with_timeout() returns a litellm.Timeout on health check timeout
- _perform_health_check() propagates exceptions to unhealthy endpoints
- _write_health_state_to_router_cache() calls _set_cooldown_deployments
  for each unhealthy endpoint that has an exception
- When allowed_fails_policy is set, the binary health check filter is
  bypassed so cooldown is the sole routing exclusion mechanism
- Safety net: if all deployments are in cooldown with
  enable_health_check_routing=True, the cooldown filter is bypassed

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

* feat(router): add health_check_ignore_transient_errors flag

When enabled, health check failures with 429 (rate limit) or 408 (timeout)
status codes are skipped from the cooldown pipeline. These are transient
load issues, not broken deployments. Auth errors (401), 404, and 5xx errors
still increment counters and trigger cooldown as before.

Config (general_settings):
  health_check_ignore_transient_errors: true

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

* fix(router): also exclude 429/408 from health state cache when ignore_transient_errors set

The previous fix only skipped cooldown counter increments. The health state
cache was still marking 429/408 endpoints as is_healthy=False, causing the
binary health check filter to exclude them from routing.

Now, when health_check_ignore_transient_errors=True, 429/408 endpoints are
also excluded from the unhealthy list passed to build_deployment_health_states(),
so the binary filter treats them as unaffected (not unhealthy).

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

* docs(router): add health check driven routing guide

New standalone page covering the full health check routing feature:
allowed_fails_policy integration, health_check_ignore_transient_errors,
architecture SVG, step-by-step setup, and gotchas (TTL, AllowedFails semantics).

Replaces the inline section in health.md with a link to the new page.
Added to the Routing & Load Balancing sidebar.

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

* fix(health-check-routing): fix three CI failures

- Add "exception" to ILLEGAL_DISPLAY_PARAMS in health_check.py so the
  exception object is stripped before the health endpoint serializes
  results to JSON (fixes TypeError: 'URL' object is not iterable)
- Add allowed_fails_policy = None to FakeRouter stubs in
  test_router_health_check_routing.py (fixes AttributeError)
- Add health_check_ignore_transient_errors to config_settings.md router
  settings reference table (fixes documentation test)

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

* Fix litellm/tests/proxy_unit_tests/test_proxy_server.py

* fix(router): address greptile review comments

- Narrow cooldown safety-net bypass: only fires when allowed_fails_policy
  is set (cooldown is health-check driven). Without a policy, cooldowns
  are from real request failures and must not be bypassed.
- Restore cooldown deployments DEBUG log that was accidentally removed.
- Fix test_health TypeError: move exception extraction to a separate
  exceptions_by_model_id dict returned alongside endpoints, so exception
  objects never appear in the endpoint dicts that get JSON-serialized
  by the /health response.

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

* fix(health-check-routing): properly isolate exceptions from health response

Return exceptions_by_model_id as a separate third value from
_perform_health_check / perform_health_check so exception objects
(which contain non-JSON-serializable httpx URL types) never appear
in the endpoint dicts that get serialized by the /health response.

Callers updated: _health_endpoints.py, shared_health_check_manager.py,
proxy_server.py background loop. All use the exceptions dict only for
cooldown integration, not for display.

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

* fix(shared-health-check): fix remaining 2-value return sites and update type annotation

* fix(health-check-routing): fix P0 cooldown integration never firing

The cooldown loop was reading endpoint.get("exception") which is always
None because exceptions are now returned via exceptions_by_model_id, not
stored in endpoint dicts. Fixed to use _exceptions.get(model_id).

Also fixes the transient-error filter to use _exceptions instead of
endpoint.get("exception"), and fixes all remaining 2-value return sites
in shared_health_check_manager.py. Tests updated to pass exceptions via
exceptions_by_model_id parameter instead of endpoint dicts.

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

* fix(health-check-routing): fix P1 transient-error filter broken on cache hits

When SharedHealthCheckManager returns cached results, exceptions_by_model_id
is always {} so the transient-error filter defaulted to status 500 for all
endpoints, incorrectly marking 429/408 endpoints as unhealthy.

Fix: store integer exception_status on each unhealthy endpoint dict in
_perform_health_check. _get_endpoint_exception_status() uses the live
exception object when available (direct path) and falls back to the stored
integer (cache-hit path). The integer is JSON-serializable and survives
the shared cache round-trip.

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

* fix(health-check-routing): gate cooldown loop behind allowed_fails_policy

Without the policy, cooldown is not the routing exclusion mechanism.
Firing _set_cooldown_deployments for all enable_health_check_routing users
was a backwards-incompatible change — 401s would immediately cooldown
deployments that the binary filter would have recovered on the next cycle.

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

* revert: undo allowed_fails_policy gate on cooldown loop

Cooldown integration via health checks is intentional for all
enable_health_check_routing users, not just those with allowed_fails_policy.

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

* fix(docs+tests): fix health_check_ignore_transient_errors doc section and test coverage

- Move health_check_ignore_transient_errors from router_settings to
  general_settings in config_settings.md (code reads it from general_settings)
- Remove duplicate enable_health_check_routing / health_check_staleness_threshold
  entries that were incorrectly listed under router_settings
- Replace TestHealthCheckEndpointExceptionPropagation tests with ones that
  exercise the real _perform_health_check code path via mocked ahealth_check,
  verifying exceptions appear in exceptions_by_model_id and NOT in endpoint dicts

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

* fix(tests+docs): fix tuple unpacking and docs test failures

- Update test mocks that return (healthy, unhealthy) to return
  (healthy, unhealthy, {}) to match the new 3-value signature
- Update test unpackings of perform_shared_health_check to use
  healthy, unhealthy, _ = ...
- Add health_check_ignore_transient_errors to router_settings section
  in config_settings.md (it is a Router constructor param, so the doc
  test requires it there; it also lives in general_settings for proxy use)

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

* Fix CodeQL errors

* fix(tests): fix 2-value unpackings of _perform_health_check in test_health_check.py

* fix(tests): fix mock _perform_health_check returning 2-tuple instead of 3

* fix team routing

---------

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

* fix: add distributed lock for key rotation job (#23364)

* fix: add distributed lock for key rotation job

* fix: address Greptile review feedback on key rotation lock (#23834)

* fix: address Greptile review feedback on key rotation lock

* fix req changes greptile

* feat(proxy): Optional on_error for guardrail pipeline (API / technical failures) (#24831)

* guardrails fallback

* docs

* docs: add LITELLM_KEY_ROTATION_LOCK_TTL_SECONDS to environment variables reference

* fix(mypy): accept Union[Dict, Any] in _get_deployment_order and use typed list to fix min() type error

* fix(mypy): use Optional[str] for api_base in PydanticAI provider to match superclass signature

---------

Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Harshit Jain <48647625+Harshit28j@users.noreply.github.com>
Co-authored-by: Shivam Rawat <shivam@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
2026-04-04 23:09:42 +00:00
Yuneng Jiang
fc32f91ffd
[Fix] Rename test file so router code coverage check detects it
The router_code_coverage.py script only scans test files with "router" in the filename.
test_health_check_routing.py was invisible to this check, causing _async_filter_health_check_unhealthy_deployments
and _filter_health_check_unhealthy_deployments to appear untested.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-30 13:13:41 -07:00
Sameer Kankute
7675488640
feat(router): add health-check-driven routing behind opt-in flag
Background health checks now feed deployment health state into the
router candidate-filtering pipeline. Unhealthy deployments are excluded
proactively instead of waiting for request failures to trigger cooldown.

Gated by `enable_health_check_routing: true` in general_settings.
Off by default — zero behavior change for existing users.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 20:57:08 +05:30
Sameer Kankute
528daa8cf4 feat(router): add per-model-group deployment affinity configuration
Enable deployment_affinity, responses_api_deployment_check, and session_affinity to be configured per model group via router_settings.model_group_affinity_config, falling back to global settings for unconfigured groups.

- Add model_group_affinity_config parameter to Router and DeploymentAffinityCheck
- Add _get_effective_flags helper to resolve flags per model group
- Update async_filter_deployments and async_pre_call_deployment_hook to use per-group config
- Add 4 comprehensive tests covering per-group config, fallback, and override scenarios

This allows fine-grained control of affinity behavior across model groups, e.g., enabling stickiness only for cross-provider deployments while leaving other groups free to load-balance.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-03-19 14:44:01 +05:30
yuneng-jiang
1092c17468 Fix flaky encrypted_content_affinity tests: mock at handler level
The 4 integration tests were flaky in CI because the AsyncHTTPHandler.post
mock was bypassed when aiohttp transport is used. Mock at the higher
BaseLLMHTTPHandler.async_response_api_handler level instead, which
bypasses the HTTP layer entirely while still exercising router deployment
selection, pre-call checks, and response post-processing (item ID rewriting).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-15 15:39:25 -07:00
yuneng-jiang
67e905f0d0 Fix flaky encrypted_content_affinity tests: clear HTTP client cache, disable retries
Tests failed intermittently in CI (-n 8 workers) because cached
AsyncHTTPHandler instances from other tests bypassed the class-level
mock on AsyncHTTPHandler.post, causing real requests to OpenAI with
mock API keys. Router retries (default 2) masked the root cause.

- Add autouse fixture to flush litellm.in_memory_llm_clients_cache
  before/after each test so mocks always apply to fresh clients
- Set num_retries=0 on all Router instances to surface mock failures
  immediately instead of silently retrying

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-15 15:18:34 -07:00
Sameer Kankute
521f804350 Fix encrypted content streaming affinity issue 2026-03-03 18:37:22 +05:30
Sameer Kankute
2bc4da76ce Update the tests 2026-03-03 18:36:07 +05:30
Sameer Kankute
18bf3f2df6 Fix mock github test 2026-03-03 18:36:07 +05:30
Sameer Kankute
a88a17796b Fix logging and encrypted content extraction 2026-03-03 18:36:07 +05:30
Sameer Kankute
9f627c67d8 Add tests for encrypted_content_affinity 2026-03-03 18:36:07 +05:30
Sameer Kankute
394c49d303 Add tests for encrypted_content_affinity 2026-03-03 18:36:07 +05:30
Sameer Kankute
7cda0e4edd Fix code qa 2026-02-26 12:43:06 +05:30
Harshit Jain
456d8f5524 feat: add session_id to have better routing 2026-02-21 18:45:50 +05:30
Emerson Gomes
3dd55a7b61 Merge main into affinity_callback and address deployment affinity review feedback 2026-02-18 10:01:11 -06:00
Emerson Gomes
f7726c8950 Fix wrong keys being used for model sticky entry 2026-01-15 17:42:29 -06:00
Emerson Gomes
059e75ad88 fix(router): scope deployment affinity by model_map_key
- Key affinity by (user_api_key_hash, model_map_key) -> model_id
- Ignore OpenAI 'user' param for affinity
- Avoid double hashing user_api_key_hash
- Add unit tests + docs clarifications
2026-01-15 16:28:36 -06:00
Emerson Gomes
e23bd21a28 Add deployment affinity routing 2026-01-15 08:53:31 -06:00
Ishaan Jaff
539f629eff
[Feat] New Logging Integration - Azure Sentinel Logger (#18146)
* add AzureSentinelLogger

* logging: AzureSentinelLogger

* test_azure_sentinel_signature_and_send_batch

* docs azure sentinel

* fix AzureSentinelLogger

* test fix

* docs fix

* fix: AzureSentinelLogger

* docs sentintel

* feat: add example SLP

* docs sentinel

* docs fix

* docs fix

* docs fix

* fix code qa

* QA fix

* fix test

* TestInitializeInteractionsEndpoints
2025-12-18 02:04:49 +05:30
Cesar Garcia
7c2e2111c0
fix(router): handle tools=None in filter_web_search_deployments (#17684)
Fixes #17672

Changed `request_kwargs.get("tools", [])` to `request_kwargs.get("tools") or []`
to handle the case where tools is explicitly set to None.
2025-12-08 18:36:46 -08:00
Raghav Jhavar
72eb4c3a1c
🆕 feat: support routing to only websearch supported deployments (#17500)
* support routing to only websearch supported deployments

* add docs
2025-12-04 14:18:20 -08:00
Sameer Kankute
f804ab6de5
Add LLM provider response headers to Responses API (#16091)
* Add llm headers to responses api

* fix mock test
2025-11-01 13:25:56 -07:00
Ishaan Jaff
d89a2a0797 test 2025-09-06 16:38:43 -07:00
Ishaan Jaff
c168fff38a test_cooldown_badrequest_error 2025-09-06 16:28:00 -07:00
Ishaan Jaff
7054067238 test_cooldown_handlers.py 2025-09-06 16:13:30 -07:00
Krish Dholakia
3b52545db3
Merge pull request #13529 from BerriAI/litellm_dev_08_11_2025_p1
[Fix] Cooldowns - don't return raw Azure Exceptions to client
2025-08-18 18:54:19 -07:00
Ishaan Jaff
76f1064229
[Bug Fix] litellm incompatible with newest release of openAI v1.100.0 (#13728)
* fix imports OpenAI SDK

* ResponseText fixes

* fixes ResponseText

* fix imports

* catch AttributeError

* fix import

* use openai==1.100.1

* fix build from PIP

* fix lint test

* Print OpenAI version

* fix Install dependencies
2025-08-18 18:26:17 -07:00
Krrish Dholakia
bc9d0484e4 fix(cooldown_cache.py): mask error string to avoid leaking sensitive prompt data
Fixes https://github.com/BerriAI/litellm/issues/13329
2025-08-11 18:37:57 -07:00
Ishaan Jaff
39955129f5
fix mapped tests (#12320)
* fix - use flush llm client cache

* faster mapped tests

* test_async_multiple_response_ids_routing

* fix tests

* test_ateam_member_update_admin_requires_premium

* regular mapped tests

* Revert "Fix: Initialize JSON logging for all loggers when JSON_LOGS=True (#12206)"

This reverts commit 2c60c316ec.

* reset num workers
2025-07-04 10:04:43 -07:00
Krish Dholakia
1a7fd1d1c7
Litellm dev 06 25 2025 p2 (#12049)
* test(test_router.py): initial unit test confirming router.afile_content uses dynamic api key / api base

* fix(managed_files.py): filter deployments for only those within file id mapping

ensure call works - only route to models where the file was written

* fix(proxy_server.py): fix loading in model ids from config, if config id is int

* fix(router.py): return all model file id mappings on create_file

if multiple deployments - this ensures all the file id mappings are bubbled up

Fixes issue when trying to use loadbalanced deployments - only 1 file id mapping was being stored

* feat(router_utils/common_utils.py): filter models by team id when selecting for routing

Prevents team only models from being used by other teams

* fix(common_utils.py): additional fixes around filtering team-based models

* fix(batches_endpoints/endpoints): support list batches with target model names specified

* fix(common_utils.py): more testing for team deployment filters
2025-06-25 21:54:13 -07:00
Krish Dholakia
ef42461c1e
Litellm fix GitHub action testing (#11163)
* test: add __init__.py files

* refactor: rename test folder to avoid naming conflict

* test: update workflows

* test: update tests

* test: update imports

* test: update tests

* test: remove unused import

* ci(test-litellm.yml): add pytest retry to github workflow

* test: fix test
2025-05-26 14:41:42 -07:00