* feat(spend): store litellm_call_id on spend logs for DB-to-trace correlation
Successful spend logs keyed request_id to the provider response id while
tracing uses x-litellm-call-id, so a DB row could not be correlated with its
trace; this only worked for failures, where request_id already fell back to
the call id. Add a nullable litellm_call_id column to LiteLLM_SpendLogs,
populate it in get_logging_payload, and surface it in the spend logs read
endpoints so correlation works both directions for successful calls
Fixes LIT-3868
* chore: sync schema.prisma copies from root
* test(spend): cover cache-hit and missing-response-id paths for litellm_call_id
Lock the intended behavior surfaced in review: on a cache hit request_id gets
the uniqueness suffix while litellm_call_id stays the raw call id, and when the
provider returns no id request_id falls back to the call id so both columns
match. Both assertions fail when the populate line is reverted
* test(spend): ignore litellm_call_id in spend logs payload comparisons
get_logging_payload now always writes litellm_call_id, so the full-payload
comparisons in test_spend_management_endpoints.py saw an unexpected key and
failed. litellm_call_id is a per-request runtime uuid like request_id, which
is already ignored, so add it to ignored_keys
* test(logging): ignore litellm_call_id in gcs pubsub spend logs comparison
The gcs pubsub spend logs payload comparison flags any key present in the
actual payload but absent from the golden snapshot. get_logging_payload now
always emits litellm_call_id, a per-request runtime uuid like request_id which
is already ignored, so add it to ignored_keys
* refactor(spend): store litellm_call_id in spend log metadata, drop column
Switch DB-to-trace correlation off a dedicated column and onto the existing
metadata JSON, avoiding a schema migration entirely. litellm_call_id is now
written into spend log metadata (already selected and re-hydrated on the read
paths) instead of a new LiteLLM_SpendLogs column, so the three schema.prisma
copies and the migration are reverted and the read SELECTs go back to their
original form. Correlation is queryable via metadata->>'litellm_call_id'
Trade-off: an unindexed JSON lookup rather than an indexed column; acceptable
for this use case and removes all migration risk
* refactor(spend): thread litellm_call_id into _get_spend_logs_metadata
Set litellm_call_id beside the other computed metadata values inside
_get_spend_logs_metadata rather than mutating clean_metadata back in the
caller, matching how applied_guardrails, cost_breakdown and the rest are
threaded. No behavior change; the value still comes from kwargs with a
litellm_params fallback
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* 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
* add session id in spendLogs
* fix log proxy server request as independant field
* use trace id for SpendLogs
* add _ENTERPRISE_ResponsesSessionHandler
* use _ENTERPRISE_ResponsesSessionHandler
* working session_ids
* working session management
* working session_ids
* test_async_gcs_pub_sub_v1
* test_spend_logs_payload_e2e
* working session_ids
* test_get_standard_logging_payload_trace_id
* test_get_standard_logging_payload_trace_id
* test_gcs_pub_sub.py
* fix all linting errors
* test_spend_logs_payload_with_prompts_enabled
* _ENTERPRISE_ResponsesSessionHandler
* _ENTERPRISE_ResponsesSessionHandler
* expose session id on ui
* get spend logs by session
* add sessionSpendLogsCall
* add session handling
* session logs
* ui session details
* fix on rowExpandDetails
* ui working sessions
