* fix(proxy): infer team from DB when JWT has no team and user has one team
- When team_id is unset after JWT auth but the user row has exactly one
team, set team_id, team_object, and team_membership from DB.
- Skip when zero or multiple teams (ambiguous).
- Add parametrized unit tests in test_handle_jwt.py.
Made-with: Cursor
* fix(proxy): JWT single-team DB fallback: catch errors, tests match get_team_object
- Wrap get_team_object + get_team_membership in one try/except; log and skip on failure (stale/missing team id no longer fails auth).
- Parametrize tests: HTTP 404/500, membership error; use side_effect not return_value=None for missing team row.
Made-with: Cursor
* refactor(jwt): extract single-team fallback into _resolve_single_team_fallback helper
Made-with: Cursor
* feat(guardrails): add LLM_AS_A_JUDGE to SupportedGuardrailIntegrations
* feat(types): add EvalVerdict, StandardLoggingEvalInformation; wire eval_information into SpendLogsMetadata
* feat(guardrails): add self-contained llm_as_a_judge guardrail hook
* fix(a2a): filter agent-only litellm_params from acompletion kwargs; pass agent_id into body
* feat(ui): add LLMJudgeFields criteria builder component
* feat(ui): wire LLM-as-a-Judge into add guardrail form
* feat(ui): update EvalViewer — title 'LLM Judge Results', weighted score column, summary row
* fix(ui): wire EvalViewer into LogDetailContent to show LLM judge results on logs page
* fix(guardrails-ui): route llm_as_a_judge to criteria builder step; rename to LiteLLM LLM as a Judge; add litellm logo
* fix(guardrail-viewer): stack lifecycle + eval details vertically to avoid badge overflow in narrow drawer
* fix(guardrail-create): surface config validation errors on create instead of silently orphaning guardrail in DB
* fix(guardrail-registry): hardcode llm_as_a_judge in initializer registry so it loads regardless of package install path
* fix(llm-as-a-judge): fix P1 code quality issues - validate weights/on_failure, guard pre_call, handle multimodal, move imports to module level, fix spurious finally logging
* fix(guardrail_endpoints): use correct PK field in rollback delete and log rollback failure
* fix(llm_as_a_judge): support Pydantic object in _get_litellm_param fallback chain
* fix(LLMJudgeFields): replace @tremor/react Button with antd Button
* fix(llm_as_a_judge): remove dead registry dicts, fix KeyError in prompt builder, set correct status on judge failure
* test(llm_as_a_judge): add unit tests for guardrail hook
* fix(llm_as_a_judge): remove @log_guardrail_information decorator to fix duplicate guardrail_information entries
The decorator and the manual finally block both called add_standard_logging_guardrail_information_to_request_data, producing two entries per request. The decorator also misclassified HTTPException(422) blocks as guardrail_failed_to_respond (it checks for 400). The finally block correctly tracks status throughout, so removing the decorator is sufficient.
* fix(test_gcs_pub_sub): ignore metadata.eval_information in comparison
* fix(test_spend_management): ignore metadata.eval_information in payload comparison
* fix(types/guardrails): add input_type and messages to ApplyGuardrailRequest
* fix(guardrail_endpoints): pass input_type and messages through apply_guardrail endpoint
* fix(guardrail_endpoints): auto-detect post_call guardrails and use input_type=response
* fix(a2a_endpoints): merge agent litellm_params guardrails into data before post_call hooks
* fix(llm_as_a_judge): use float sum with tolerance for weight validation
* fix(guardrail_registry): split long import line for black formatting
* fix(llm_as_a_judge): guard guardrail_name Optional for mypy
* fix(llm_as_a_judge): set guardrail_status=guardrail_intervened when score fails, regardless of on_failure mode
* fix(a2a_endpoints): use try/finally so deferred spend log fires even when guardrail blocks with 422
* fix(litellm_logging): declare _defer_async_logging and _enqueue_deferred_logging on Logging class for mypy
* fix(logging_worker): restore queue.join() in flush() to wait for in-flight callbacks
* fix(vertex passthrough): log :embedContent and :batchEmbedContents responses
* test(vertex passthrough): add unit tests for :embedContent and :batchEmbedContents logging
* fix(vertex passthrough): extract input text from request body for embedContent token counting
* fix(vertex passthrough): add embedContent and batchEmbedContents to TRACKED_VERTEX_ROUTES
* fix(vertex passthrough): detect Google AI Studio URLs in embedContent handler
* test(vertex passthrough): add unit test for Google AI Studio URL embedContent provider detection
* style: black format vertex_passthrough_logging_handler
create_model does not inherit the base class docstring, so once an
extension registered a field the effective class had no description.
The UI renders schema.description as a header paragraph — losing it
broke the 'Configuration for UI-specific flags' text. Pass __doc__
through explicitly and add a regression test.
Extract the admin team-header attachment into a helper so
auth_builder stays under the 50-statement lint threshold; apply
black formatting to the two files flagged on the prior commit.
No behavior change.
Scope the header-driven team fetch to LLM API routes so admin
management routes keep the pre-existing bypass behavior (no
phantom teams, no 404s on mgmt calls). Team context is threaded
onto UserAPIKeyAuth so spend logs, rate limits, and team_models
attribution are correctly applied when admins act on behalf of
a team via x-litellm-team-id.
* fix(proxy): honor object_permission for managed vector store access
* perf(proxy): preload team object_permission on UserAPIKeyAuth
Populate team_object_permission during virtual-key and JWT auth when the
team is loaded, so can_user_access_vector_store uses it in memory first
and only falls back to get_object_permission by id when missing.
Made-with: Cursor
* fix(team_endpoints): auto-add SSO team members to org for proxy admins
* test: proxy_admin vs team_admin security boundary for team→org move
* screenshots: before/after for team-org SSO fix
* fix(team_endpoints): restore staging security features dropped in SSO commit
Co-Authored-By: Ishaan Jaff <ishaan@berri.ai>
* style: black formatting for team_endpoints
MCP server CRUD endpoints (/v1/mcp/server*) were bundled with MCP
tool-call / passthrough endpoints under llm_api_routes, so setting
DISABLE_LLM_API_ENDPOINTS=true on admin-only nodes also blocked the
Admin UI from listing, adding, or attaching MCP servers.
Separate mcp_inference_routes (data-plane, gated by
DISABLE_LLM_API_ENDPOINTS) from mcp_management_routes (control-plane,
gated by DISABLE_ADMIN_ENDPOINTS). Keep mcp_routes as a union for
backward compat with allowed_routes=["mcp_routes"] virtual key configs.
Upgrade is_management_route to pattern-aware matching so
/v1/mcp/server/{path:path} resolves for concrete IDs.
Temporary MCP OAuth sessions were kept in process-local memory, so on
multi-instance/LB proxy deployments a session created on instance A could
not be found when the follow-up /server/oauth/{server_id}/... request
landed on instance B.
Persist temporary session records to Redis (encrypted with the existing
proxy encryption helpers) as a best-effort L2 cache alongside the current
in-memory L1. Convert get_cached_temporary_mcp_server to async and await
it from the authorize/token/register OAuth endpoints.
Made-with: Cursor
Vertex multi-region endpoints (e.g. us, eu) use the rep host pattern, not
{geo}-aiplatform.googleapis.com. Regional IDs still contain a hyphen.
common_utils.get_vertex_base_url centralizes the rule for SDK/API URL building.
Proxy pass-through duplicates the same branching in a local get_vertex_base_url
(with trailing slashes) to avoid importing from common_utils there; live
WebSocket passthrough uses the same multi-region host logic for wss://.
Tests cover us/eu for the common_utils helper.
Made-with: Cursor
Sibling tests were mutating litellm.proxy.proxy_server.master_key and
prisma_client with raw setattr. Values leaked across tests in the same
xdist worker, flipping the auth short-circuit in user_api_key_auth and
causing unrelated tests (e.g. test_ui_view_session_spend_logs_pagination)
to return 401 instead of 200.
Replace raw setattr with monkeypatch in the two offending files and add
an autouse conftest fixture that snapshots/restores the known-leaky
module globals for every proxy test.
Two fixes to proxy-db CI:
1. test_realtime_webrtc_endpoints.py's `proxy_app` fixture mutated the
module-global `proxy_server.master_key` without restoring it, leaking
state into any test that shared the same xdist worker. Under
--dist=loadscope with 2 workers (GHA proxy-endpoints), this caused the
google_endpoints tests to fail with "No api key passed in." because
user_api_key_auth saw a set master_key and a missing API key on the
test request. The fixture now saves and restores the original value.
2. Address the Greptile note that the semantic shard design has no
catch-all, so a new test file added to tests/proxy_unit_tests/ without
a matrix entry would silently skip CI. Adds an assert-shard-coverage
job that enumerates test_*.py files and fails the workflow if any are
not referenced by a matrix entry, with a clear message telling the
author which semantic shard to place it in. All proxy-db shards now
depend on this guard.
The mocked async_increment_cache_pipeline is invoked from Router's
deployment_callback_on_success, registered as an async success callback.
Those callbacks are enqueued to GLOBAL_LOGGING_WORKER and run on a
background task, so the mock may not have been called yet when the test
asserts on it. Flush the worker before asserting.
Two independent deflakes:
1. test_ui_view_spend_logs_unauthorized (unit) was returning 400 instead
of 401/403 when earlier tests in the file left proxy-auth globals
(prisma_client, master_key, user_custom_auth, general_settings,
user_api_key_cache) in a state that let invalid tokens pass auth and
fall through to the endpoint's own start_date/end_date validation.
Add an autouse fixture that pins those globals to their import-time
defaults for every test in the file. Harden the assertion to include
response body so future flakes are diagnosable.
2. test_basic_spend_accuracy (CI job proxy_spend_accuracy_tests) depends
on the Redis transaction buffer flushing spend to Postgres. The buffer
uses a single global pod-lock key (cronjob_lock:db_spend_update_job)
and a single global buffer list key. Pointing the proxy at the shared
remote Redis means concurrent CI pipelines contend for the same lock
and can drain each other's buffer into the wrong database. Add a
start_redis reusable command that boots a per-job redis:7-alpine
container (digest-pinned), and switch proxy_spend_accuracy_tests to
REDIS_HOST=host.docker.internal:6379 so lock and buffer state are
isolated per CI run.
- Add gpt-5.5 to GPT5_MODELS parametrized list so both OpenAIGPT5Config
and AzureOpenAIGPT5Config routing tests cover the new model.
- Add test_generic_cost_per_token_gpt55 verifying the new entry's
cost-map values ($5/$0.50/$30 per 1M) and that generic_cost_per_token
returns the expected prompt/completion costs.
* feat: add gpt-5.5 to model cost map
Add gpt-5.5 entry with pricing from OpenAI flagship page:
input $5/1M, cached input $0.50/1M, output $30/1M, 272K context.
* test: add gpt-5.5 coverage for model cost map and gpt-5 routing
- Add gpt-5.5 to GPT5_MODELS parametrized list so both OpenAIGPT5Config
and AzureOpenAIGPT5Config routing tests cover the new model.
- Add test_generic_cost_per_token_gpt55 verifying the new entry's
cost-map values ($5/$0.50/$30 per 1M) and that generic_cost_per_token
returns the expected prompt/completion costs.
The periodic budget-window reset job filtered keys/teams with
`where={"budget_limits": {"not": None}}`. The prisma-client-python
library does not support null-filtering on `Json?` columns (no
DbNull/JsonNull sentinel — upstream issue #714). The client drops the
`None` value during serialization and the engine rejects the query with
`MissingRequiredValueError: where.budget_limits.not: A value is
required but not set`, so neither the key nor team reset path runs.
Switch those two `find_many` calls to `query_raw` with
`WHERE budget_limits IS NOT NULL`, selecting only the PK and the
`budget_limits` column. Writes still go through the ORM. Add unit tests
covering the expired/unexpired paths for keys and teams, string-encoded
JSON payloads, empty payloads, error isolation between the two paths,
and a regression guard asserting the query still uses `IS NOT NULL`.
Align the Ruby, Node.js, and npm install path with the rest of the
config. Three separate upstream installers were being invoked via
\`curl ... | bash\` or unlocked \`npm install\`:
- RVM's \`get.rvm.io/stable\` installer (mutable upstream script).
Replace with a shallow git clone of the rvm/rvm repo at tag 1.29.12
and verify HEAD matches the published commit SHA before running the
local \`./install\` script. Same pattern already used for the
helm-unittest plugin in .github/workflows/helm_unit_test.yml.
- NodeSource's \`deb.nodesource.com/setup_18.x\` piped into sudo bash.
Replace with a direct download of the Node.js 18.20.8 linux-x64
tarball from nodejs.org, verified against the published
SHASUMS256.txt digest before extraction.
- \`npm install @google-cloud/vertexai @google/generative-ai\` and
\`--save-dev jest\` resolved fresh from the npm registry on every
run. Add \`tests/pass_through_tests/package.json\` with pinned
direct-dep versions and commit the generated package-lock.json, then
switch CI to \`npm ci\` (exact lockfile install, fails on drift).
Also scopes the Ruby+JS test runners to \`tests/pass_through_tests/\`
so they pick up the committed package.json rather than writing
node_modules at repo root.
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