* style(ui/): distinguish agent calls from llm calls on ui
* feat: initial grouping working
* feat: set stable contextid for a2a calls - allows for easily passing to downstream llm/mcp calls
* feat(a2a_endpoints.py): fix tracing to avoid recreating logging objects for the same call
allows stable trace id usage
* fix(guardrail_endpoints): handle string ui_type values in _build_field_dict
_build_field_dict unconditionally called .value on ui_type, which crashes
for guardrail configs that use plain strings (e.g. BlockCodeExecutionGuardrailConfigModel
uses "multiselect" and "percentage"). Now checks with hasattr before calling .value.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: propagate trace/session id from headers in MCP server calls
Cherry-picked mcp_server/server.py fixes from 6feb9bab: adds
get_chain_id_from_headers to extract x-litellm-trace-id /
x-litellm-session-id from raw headers, and uses it in call_tool
and list_tools to keep spend logs and tracing consistent with A2A.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
- Change status codes from 400 to 500 for team metadata misconfig errors
(callers can't fix admin-set config, 400 is misleading)
- Add anchor value validation to batch endpoint (matching files endpoint)
- Coerce seconds to int to handle string values from metadata
- Add error-path tests: missing keys, invalid anchor, status code assertions
- Add happy-path test: team injects expiry when caller sends nothing
The route-level auth check was blocking internal_user role (team admins)
from reaching /key/{key}/reset_spend because KEY_RESET_SPEND was missing
from key_management_routes. Added it so team admins pass the route check
and the endpoint's existing _check_proxy_or_team_admin_for_key enforces
actual authorization.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The _resolve_model_for_cost_lookup function was only checking
litellm_params.model when resolving model names from the router.
For Azure custom deployment names (e.g. azure/openai/gpt-5.3-codex),
this deployment name doesn't exist in the model cost map, so cost
returned /bin/zsh.
Now checks model_info.base_model and litellm_params.base_model first,
falling back to litellm_params.model only if no base_model is set.
This matches how the router resolves base_model everywhere else.
Address Greptile review: test_resolve_jwks_url_resolves_oidc_discovery_document
also used the inconsistent patch.object pattern.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Vertex AI / Gemini uses Pydantic's model_json_schema() which omits
additionalProperties: False (Gemini rejects it). The test expected
the same schema for all providers.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The patch.object with new_callable=AsyncMock can behave inconsistently
across Python versions, causing mock_response.status_code to return a
MagicMock instead of the assigned value. Direct assignment is simpler
and more reliable.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The CompletionTokensDetailsWrapper type now includes video_tokens field,
but this test's expected dict was not updated to include it.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The Gemini API requires role="user" on function_response content blocks
(added in commit 273cf12afa), but these tests were never updated to match.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Two independent fixes for pre-existing test failures on main:
1. Anthropic streaming: The sync __next__ method used a simple
holding_chunk pattern that lost chunks when multiple events needed
to be returned. Refactored to use the same chunk_queue approach as
the async __anext__ method. Also fixed tests that used ModelResponse
(which defaults finish_reason to 'stop') instead of ModelResponseStream.
2. Azure GPT-5.1 logprobs: The base OpenAI class includes logprobs for
gpt-5.1+ models, but Azure hasn't verified support for gpt-5.1.
Added explicit removal of logprobs/top_logprobs for gpt-5.1 (non-5.2)
models in the Azure config.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Only release distributed lock in finally if it was actually acquired;
prevents spurious Redis release_lock calls on early returns
- Treat bare integer maximum_spend_logs_retention_period as days (e.g. 3 → "3d")
instead of silently failing with a ValueError
- Elevate "Skipping cleanup" log from info to error so misconfigured
retention settings are visible without verbose logging
- Add tests for all three fixes
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add created_at field to MCPServer type (was missing)
- Map created_at from LiteLLM_MCPServerTable in build_mcp_server_from_table()
- Use server.created_at and server.updated_at instead of datetime.now() in _build_mcp_server_table() and health check table builder
- Add regression tests to verify timestamps are preserved through round-trip conversions
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Replaces the skip_route_check approach from PR #22662 with a configurable
opt-in flag. By default, common_checks() is not run for custom auth flows,
preserving backwards compatibility with pre-#22164 behavior.
Users who want budget/team/route enforcement on custom auth can enable it:
general_settings:
custom_auth_run_common_checks: true
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Custom user-added routes (e.g. /ldap/ngs/ready) used with Depends(user_api_key_auth) were being rejected as admin-only after _run_post_custom_auth_checks was introduced in commit 14badde13c.
The route authorization check in common_checks is designed for LiteLLM's own management routes. Custom auth flows that add their own routes should be trusted since the custom auth function already validated the request. Budget and expiry checks still run.
Add skip_route_check parameter to common_checks() and pass skip_route_check=True from _run_post_custom_auth_checks() to skip route authorization while preserving budget/team/model checks.
Regression test added: test_common_checks_skip_route_check_for_custom_auth
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
* feat(guardrails): team-based guardrail registration and approval workflow
Add team-based guardrail submission system where teams can register
Generic Guardrail API guardrails for admin review. Includes:
- POST /guardrails/register endpoint for team-scoped submissions
- Admin review endpoints (list/get/approve/reject submissions)
- Team Guardrails tab in the UI dashboard
- extra_headers support for forwarding client headers to guardrail APIs
- Prisma schema migration for status, submitted_at, reviewed_at fields
- Documentation for team-based guardrails and static/dynamic headers
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(guardrails): address review feedback - SSRF, silent failure, redundant query
- Validate api_base URL scheme (http/https only) and hostname in
register_guardrail to prevent SSRF via team submissions
- Return warning field in approve response when in-memory initialization
fails so admins know the guardrail won't work until next sync cycle
- Eliminate redundant DB query in list_guardrail_submissions by fetching
all team guardrails once and deriving both filtered list and summary
counts from the single result set
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(guardrails): add pending_review status guard to reject endpoint
Prevent rejecting already-active or already-rejected guardrails, which
would create a DB/memory inconsistency (active in memory but rejected
in DB). Now mirrors the approve endpoint's status check.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
