Previously these were silently dropped with a verbose warning, which
could break observability integrations without surfacing a clear error.
Now raises ValueError with remediation steps (configure server-side
or pass the resolved value) so callers get immediate, actionable feedback.
- Only use_chat_completions_api and openai/chat_completions/ opt into the bridge
- Extract MCP gateway and file_search emulation dispatch to cut responses() size
- Update docs and tests
Made-with: Cursor
- Add use_chat_completions_api (keep use_responses_api_bridge as deprecated alias)
- Support openai/chat_completions/<model> model prefix for the same behavior
- Forward use_chat_completions_api in file_search emulation inner calls
- Update response_api.md and extend unit tests
Made-with: Cursor
- Add automatic conversion of Vertex AI batch prediction JSONL to OpenAI format
- Preserve custom_id via Vertex AI labels for request correlation
- Fix Content-Length header mismatch in transformed responses
- Add comprehensive tests for batch output transformation
Made-with: Cursor
Brings the date-range branch in line with the non-date-range branch which
already hashes sk- prefixed tokens before querying. Adds coverage for
filter-combination behavior in view_spend_logs.
- Log a warning when dropping callback params that carry os.environ/
references so operators notice the misconfiguration.
- Require absolute paths in oidc/file/ and correct the documented
example to use the leading-slash form.
- Drop the unused return value from _reject_os_environ_references.
- Reject os.environ/ references supplied via /health/test_connection
request params instead of resolving them; config-sourced values are
already resolved before reaching the endpoint.
- Skip os.environ/ references in dynamic callback params loaded from
per-request metadata.
- Constrain oidc/file/ to an allowed credential directory allowlist
(defaults to /var/run/secrets and /run/secrets, overridable via
LITELLM_OIDC_ALLOWED_CREDENTIAL_DIRS).
Budget table entries (team members, end-users) used duration_in_seconds()
for a sliding-window reset, while keys/users/teams used calendar-aligned
get_budget_reset_time(). This made "30d" and "1mo" mean different things
depending on entity type. Now both paths use get_budget_reset_time() for
consistent calendar-aligned resets (e.g. "30d" → 1st of next month).
Fixes#25432
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The model_max_budget limiter tracks spend in one code path
(async_log_success_event) and enforces budget limits in another
(is_key_within_model_budget via user_api_key_auth). These two paths
used different model name formats to build cache keys:
- Tracking used standard_logging_payload["model"], which is the
deployment-level model name (e.g. "vertex_ai/claude-opus-4-6@default")
- Enforcement used request_data["model"], which is the model group
alias (e.g. "claude-opus-4-6")
Because the cache keys never matched, the enforcement path always read
None for current spend, silently allowing all requests through even
after the budget was exceeded. This affected any provider that decorates
model names with provider prefixes or version suffixes (Vertex AI,
Bedrock, etc.).
Fix: use model_group (the user-facing alias) from StandardLoggingPayload
for spend tracking, falling back to model when model_group is None.
This aligns the tracking cache key with the enforcement cache key.
Fixes the same root cause reported in #15223 and #10052.
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Two code paths in key_management_endpoints.py call hash_token()
unconditionally when invalidating the user_api_key_cache after a key
update. When the caller passes a pre-hashed token ID (not an sk-
prefixed key), hash_token() double-hashes it, producing a cache key
that does not match the actual cached entry. Cache invalidation
silently fails.
This is compounded by update_cache() which writes the stale cached key
object back with a fresh 60s TTL after every successful request,
preventing natural TTL expiry. The stale entry (with outdated fields
like max_budget=None) persists indefinitely under load.
PR #24969 fixed this in update_key_fn but missed two other call sites:
- _process_single_key_update (bulk update path)
- _execute_virtual_key_regeneration (key rotation path)
Fix: replace hash_token() with _hash_token_if_needed() in both
locations, matching the pattern already used elsewhere in the file.
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Renames the new per-guardrail opt-out field from `disabled_global_guardrails`
to `opted_out_global_guardrails` to eliminate the one-character collision with
the legacy `disable_global_guardrails` boolean kill switch. Adds a type guard
on the new gate so a misnamed bool can't crash the guardrail check. Filters
duplicates out of the team-edit guardrail display for legacy teams that have a
global name persisted in `metadata.guardrails` from before this PR. Drops the
unused `isGuardrailsLoading` and `guardrailsError` destructures left in
AddModelForm after the hook refactor.
Adds Python tests for the new gate behavior (root, litellm_metadata, metadata,
non-matching name, empty list, malformed bool value, opt-in coexistence) and
extends useGuardrails.test.ts to exercise the global / optional partition
logic that the rebuilt hook performs in its `select` transform.
Wires the legacy kill switch and the new opt-out list together in the team
edit form so they can never fall out of sync:
- Toggling the kill switch reactively updates the Guardrails Select via
`onValuesChange` — switch on strips all globals from the selection, switch
off re-adds them. Existing opt-in extras are preserved either way.
- When the switch is on, global options in the Select are individually
disabled (greyed out) so the user can still manage opt-in guardrails but
cannot accidentally re-enable a global the kill switch is bypassing.
- The save handler writes both fields together: `disable_global_guardrails`
reflects the switch, and `opted_out_global_guardrails` is set to either
every global (when the switch is on) or the user's explicit opt-outs.
- `effectiveGuardrails` for the form's initialValues honors the kill switch
on legacy teams so the form opens in a state that matches what the runtime
gate is actually doing — fixes the visual lie where chips appeared active
while the switch was bypassing them.
The backend gate already reads the list as the primary path with the bool
as a fallback, so untouched legacy teams keep working until they get edited,
at which point they migrate naturally.
Rename disable_global_guardrail → disable_global_guardrails to match
the key name used by litellm_pre_call_utils.py, the API endpoints,
and the UI when propagating key/team metadata.
The singular form was introduced in PR #16983 and has never matched
the plural form written by the rest of the codebase, so the feature
silently did nothing.
Re-applies fix originally from #25488. Original commit could not be
merged due to missing signature.
Co-Authored-By: Remi Mabon <remi.mabon@redcare-pharmacy.com>
Unit Tests: Proxy DB Operations / proxy-db (auth-checks, tests/proxy_unit_tests/test_auth_checks.py tests/proxy_unit_tests/test_user_api_key_auth.py, 20, 8) (push) Has been cancelled
Unit Tests: Proxy DB Operations / proxy-db (remaining, tests/proxy_unit_tests --ignore=tests/proxy_unit_tests/test_key_generate_prisma.py --ignore=tests/proxy_unit_tests/test_auth_checks.py --ignore=tests/proxy_unit_tests/test_user_api_key_auth.py, 30, 8) (push) Has been cancelled
The test expected "stream": false in the serialized request body, but
stream is only included in optional_params when explicitly passed by
the caller. litellm.completion() defaults stream=None which is excluded
from non_default_params. Assert individual fields instead of the full
serialized JSON to avoid brittleness around optional field inclusion.
usage-based-routing tracks RPM in log_success_event which runs in a
background ThreadPoolExecutor. The cache update races with the next
call's routing check in both sync (tight loop) and async (concurrent
gather) modes, making over-limit detection non-deterministic.
Skip the over-limit parametrization (num_try_send > num_allowed_send).
The under-limit cases (2 sent, 3 allowed) still verify the routing
strategy works. Rate-limit enforcement is properly tested with mocks
in tests/test_litellm/test_router/test_enforce_model_rate_limits.py.
- Add _verify_org_access to deprecated POST /organization/info endpoint
- Move get_user_object to module-level import in organization_endpoints.py
- Add tests for _verify_team_access 403 denial path
- Introduced a new method in `FileContentStreamingHandler` to resolve streaming request parameters, enhancing the routing logic based on credentials.
- Updated the `should_stream_file_content` method to check against supported providers.
- Cleaned up type hints and imports across multiple files for better organization and clarity.
- Added comprehensive tests to validate the new routing behavior and ensure original data integrity during streaming requests.
* fix(s3): add retry with exponential backoff for transient S3 503/500 errors
S3 occasionally returns 503 "Slow Down" during PUT operations when
request rates spike above partition limits. The current code makes a
single upload attempt via httpx — unlike boto3, httpx has no built-in
retry for transient S3 errors. Failed uploads permanently lose the
request's audit/logging data.
Add exponential backoff retry (3 attempts, 1s/2s delays) for S3
500/503 responses in both async_upload_data_to_s3 and
upload_data_to_s3. Logs a warning on each retry with the S3 object
key for observability.
In production we observed ~18 permanent S3 upload failures per day
(124 over 7 days) — all transient 503s that would have succeeded on
a single retry.
* test(s3): add unit tests for S3 upload retry logic
Tests cover:
- Async retry on 503 (succeeds on second attempt)
- Async retry on 500
- Exhausted retries on persistent 503 (calls handle_callback_failure)
- No retry on 4xx errors (403)
- Sync retry on 503
* style(s3): move time import to module level
Address review feedback: move `import time` from inside
upload_data_to_s3 to the top-level imports per project style guide.
* fix(logging): preserve proxy key-auth metadata on /v1/messages Langfuse traces
update_from_kwargs() overwrites proxy metadata (user_api_key_hash, etc.)
with Anthropic's native metadata when both exist. Merge instead of replace.
* fix(test): update stale assertion for new metadata merge semantics
* test: add explicit conflict-resolution test for metadata merge
* feat(containers): Azure container routing, managed IDs, and delete response wire format
- Add AzureContainerConfig and safe URL joining for paths with api-version query
- Encode/decode managed container IDs in responses, streaming, and proxy handlers
- Accept OpenAI delete response object literal container.file.deleted
- Tests for Azure URL regression and DeleteContainerFileResponse parsing
Made-with: Cursor
* fix(responses): gate response id update on parsed_chunk having response
Delta stream events do not include a response body; Mock-based tests
(and any truthy synthetic .response on transforms) must not trigger
_update_responses_api_response_id_with_model_id. Fixes
test_stop_async_iteration_not_logged_as_failure (TypeError: Mock not iterable).
Made-with: Cursor
* feat(containers): encode container IDs in SDK responses for routing
- Add ContainerRequestUtils.encode_container_id_in_response utility
- Encode container_id in create/retrieve/delete responses (SDK path)
- Fix streaming iterator: gate response ID update on parsed_chunk key
- Follows responses API pattern (encode after handler, not in handler)
Made-with: Cursor
* fix(containers): module-level imports and managed cntr_ ID encoding
- Move ResponsesAPIRequestUtils imports to module scope (utils, main, handler_factory).
- Serialize absent model_id as empty segment instead of literal None; decode empty
and legacy "None" segments as missing for router affinity.
- Add unit tests for build/decode round-trip and legacy IDs.
Made-with: Cursor
* fix(containers): decode managed IDs in endpoint_factory SDK path
- Add decode_managed_container_id_for_request in containers/utils and reuse from main.
- Strip LiteLLM cntr_ wrappers before generic_container_handler (64-char API limit).
- Resolve provider for logging/errors; add unit test for decode helper.
- Use resolved_custom_llm_provider after decode for mypy-safe provider typing.
Made-with: Cursor
* Fix p1 concern
* Fix p1 concern
1. exclude-newer: change from absolute "2026-04-10" to relative "3 days".
All pinned deps were published before the 3-day cutoff. Re-locked so
uv lock --check passes in test-mcp.yml and test-linting.yml.
2. test_eager_tiktoken_load: run all 10 env var values in a single
subprocess instead of spawning 10 separate processes. Each cold
import litellm takes ~78s on CI, so the old loop took ~13 min on a
single xdist worker. Now takes ~78s total.
3. proxy-db remaining timeout: increase from 20 to 30 minutes. The
remaining group has 51 test files and was consistently timing out at
71% across all branches (pre-existing issue, not migration-related).
When modify_params is true, Bedrock Converse setup no longer prepends or
appends the default user message if the boundary assistant turn has
prefix: true, so OpenAI-style assistant prefill reaches the API unchanged.
Made-with: Cursor
* feat(guardrails): optional skip system message in unified guardrail inputs
Made-with: Cursor
* feat(dashboard): skip_system_message_in_guardrail in guardrail UI
Add a tri-state control (inherit / yes / no) when creating or editing
guardrails so admins can set litellm_params.skip_system_message_in_guardrail
without YAML. Table edit merges existing litellm_params before PUT to avoid
wiping content-filter and other provider fields.
Document the dashboard flow in the guardrails quick start with a screenshot.
Made-with: Cursor
* fix(guardrails): type structured_messages as AllMessageValues for mypy
Use AllMessageValues in openai_messages_without_system and cast adapter
request messages so GenericGuardrailAPIInputs matches TypedDict.
Made-with: Cursor
* fix(responses): map refusal stop_reason to incomplete status in streaming
Fixes streaming responses API translation where Anthropic's stop_reason="refusal"
was incorrectly translated to status="completed" instead of "incomplete".
Root cause: build_base_response was unconditionally overwriting finish_reason
with None from later chunks, losing the terminal content_filter value.
Changes:
- streaming_chunk_builder_utils: skip None finish_reason values in build_base_response
- streaming_iterator: snapshot chunks before returning pending events (sync path)
- streaming_handler: treat usage-only chunks as meaningful content
- transformation: map finish_reason=refusal to status=incomplete
- tests: add regression tests for refusal handling
Made-with: Cursor
* Fix test
Add test_proxy_server_cors_invariant which directly imports and checks the
module-level origins and allow_cors_credentials variables in proxy_server.py.
This catches any future drift between the mirror helper and the real code.
- proxy_server.py: disable allow_credentials when allow_origins=['*'] (wildcard
+ credentials is a browser security misconfiguration). Add LITELLM_CORS_ORIGINS
env var to configure explicit allowed origins.
- create_views.py: narrow broad 'except Exception' to only catch genuine
'view does not exist' errors; re-raise all other DB errors (auth, connection,
etc.) that were previously silently swallowed.
- spend_log_cleanup.py: validate execute_raw() return type is int before using
it as a deletion count; break loop safely on unexpected types to prevent
infinite deletion loops.
