* fix(budget): fix timezone config lookup and replace hardcoded timezone map with ZoneInfo
* fix(budget): update stale docstring on get_budget_reset_time
Intercepts at httpx transport layer so the full proxy path (auth, routing,
OpenAI SDK, response transformation) is exercised with zero-latency responses.
Activated via `litellm_settings: { network_mock: true }` in proxy config.
Adds GetBlogPosts class that fetches blog posts from GitHub with a 1-hour
in-process TTL cache, validates the response, and falls back to the bundled
blog_posts_backup.json on any network or validation failure.
* fix: feat: add litellm_system_prompt support
* feat: support new 'litellm_agent' model provider
* feat: ui/ - new agent builder ui
* fix(anthropic/chat/transformation.py): normalize max_tokens if decimal
* feat(agentbuilderview.tsx): run compliance datasets against litellm agent
* feat: new response rejection detector
* fix: multiple fixes
* feat: add mcp tools support to agent builder
create an agent with access to llm's + mcp servers
* fix: feat: add litellm_system_prompt support
* feat: support new 'litellm_agent' model provider
* feat: ui/ - new agent builder ui
* fix(anthropic/chat/transformation.py): normalize max_tokens if decimal
* feat(agentbuilderview.tsx): run compliance datasets against litellm agent
Replace Click CliRunner with standalone_mode=False to avoid
"I/O operation on closed file" errors caused by Click's stream
isolation in CI environments.
Adds per-alert-type digest mode that aggregates duplicate alerts
within a configurable time window and emits a single summary message
with count, start/end timestamps.
Configuration via general_settings.alert_type_config:
alert_type_config:
llm_requests_hanging:
digest: true
digest_interval: 86400
Digest key: (alert_type, request_model, api_base)
Default interval: 24 hours
Window type: fixed interval
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(logging): preserve pass-through endpoint response_cost in async_success_handler
Two places in the logging pipeline were overwriting response_cost that
pass-through handlers (Gemini/Vertex) had already calculated:
1. _process_hidden_params_and_response_cost fell through to
_response_cost_calculator which returns None for pass-through calls
2. async_success_handler pass-through branch unconditionally set
response_cost = None (introduced in PR #19887)
Now both places check if response_cost is already set before overwriting.
* test: add regression test for pass-through endpoint response_cost preservation
Replace patch('litellm._redis._get_redis_client_logic') with monkeypatch.setenv
in test_max_connections_url_config and test_max_connections_url_config_string_value.
The mock was unreliable in CI (REDIS_URL is set to the real Redis Cloud server),
causing the pool to silently use the real config instead of the test config.
Using monkeypatch.setenv tests the full env-var→pool chain more robustly and
matches the actual production code path.
test_vertex_passthrough_with_default_credentials and
test_view_spend_logs_with_date_range_summarized fail intermittently when a
prior xdist worker sets master_key — auth then rejects the unauthenticated
test requests before the code under test is reached.
- mock user_api_key_auth in test_vertex_passthrough_with_default_credentials
(same pattern used for test_vertex_passthrough_with_no_default_credentials
in #21810)
- wrap test_view_spend_logs_with_date_range_summarized in
app.dependency_overrides[ps.user_api_key_auth] with try/finally cleanup
(same pattern used for the other spend log tests in #21810)
- TestSpendLogsPayload: save/restore litellm.cache in setup_method/teardown_method
so tests that run after a cache-setting test don't see a non-None cache and get
a hash instead of "Cache OFF" in the cache_key field
- test_use_prisma_db_push_flag_behavior: apply clean_env pattern (strip DATABASE_URL/DIRECT_URL,
then set DATABASE_URL to test value) inside the with block instead of using @patch.dict
decorator, matching the pattern from test_skip_server_startup to avoid Click 8.3.x
StreamMixer stream lifecycle issues in CI
Tests hardcode expected api_base as https://api.anthropic.com/v1/messages but
if ANTHROPIC_BASE_URL is set in the environment the recorded api_base changes,
causing a mismatch. Clear both env vars via monkeypatch at the start of each test.
GLOBAL_LOGGING_WORKER.flush() calls queue.join() which blocks until all
items are task_done(). In CI with pytest-asyncio, each test gets a fresh
event loop so the worker reinitializes its queue - items from a previous
test never get task_done(), causing an infinite hang.
Fix: wrap flush() with asyncio.wait_for(..., timeout=10.0).
* fix(tests): add app.dependency_overrides for auth in spend logs tests
test_ui_view_spend_logs_with_status, test_ui_view_spend_logs_with_model,
test_ui_view_spend_logs_with_model_id, and test_view_spend_logs_summarize_parameter
all send Bearer sk-test without mocking user_api_key_auth. When a prior test
in the same xdist worker sets master_key, the auth check fails for sk-test
and the test fails intermittently.
Fix: use app.dependency_overrides[ps.user_api_key_auth] to bypass auth,
same pattern as other tests in the same file.
* fix(tests): mock user_api_key_auth in test_vertex_passthrough_with_no_default_credentials
vertex_proxy_route calls user_api_key_auth internally. When a prior test in the
same xdist worker sets master_key, the auth check fails for the test request
and create_pass_through_route is never called, causing assert_called_once_with to fail.
Fix: patch user_api_key_auth as an AsyncMock in the with mock.patch() block.
* check should_run_guardrail in sync logging hook path
* Add tests for CustomGuardrail logging behavior
Added tests to ensure CustomGuardrail logging behavior based on the guardrail execution state.
---------
Co-authored-by: Miguel Armenta <ma826r@att.com>
Pre-resolve CallTypes enum values into module-level frozensets to avoid
repeated .value attribute access in the elif chain. Inline the hot-path
_store_cost_breakdown_in_logging_obj as a direct dict literal. Remove
unnecessary cast(CallTypesLiteral, call_type) call. Guard
_get_additional_costs() with azure_ai-only check since no other provider
implements additional costs.
Line profile shows 20.5% reduction in completion_cost() total time
(7.14s → 5.68s across 6,006 calls). The four targeted bottlenecks
dropped from 2.82s to 0.28s combined.
