openai videos models support the features to download variants.
See more details here: https://developers.openai.com/api/docs/guides/video-generation#use-image-references.
Plumb variant (e.g. "thumbnail", "spritesheet") through the full
video content download chain: avideo_content → video_content →
video_content_handler → transform_video_content_request. OpenAI
appends ?variant=<value> to the GET URL; other providers accept
the parameter in their signature but ignore it.
Concurrent requests via run_in_executor + asyncio.gather caused a race
condition where more requests slipped through the rate limiter than
expected, leading to flaky test failures (e.g. 3 successes instead of 2
with rpm_limit=2).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Google added INCOMPLETE to the Interactions API OpenAPI spec status enum.
Update both the Status3 enum in the SDK types and the test's expected
values to match.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The test used a relative path 'litellm/model_prices_and_context_window.json'
which only works when pytest runs from a specific working directory.
Use os.path based on __file__ to resolve the path reliably.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The test used a fixed side_effect list for time.time(), but the number
of calls varies by Python version, causing StopIteration on 3.12 and
AssertionError on 3.14. Replace with an infinite counter-based callable
and assert the timestamp was updated rather than checking for an exact
value.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* 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.
* 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.
