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* feat(guardrails): add run_in_parallel opt-in for concurrent pre_call guardrails Pre-call guardrails run sequentially because each may mutate the request payload and later guardrails depend on earlier mutations. Deployments with several slow block-only pre_call guardrails (external moderation, Bedrock, LLM-judge) therefore pay the sum of their latencies. during_call guardrails run concurrently but alongside the LLM call, so a violating payload has already been sent, which is unacceptable when the request must never reach the model. This adds a per-guardrail run_in_parallel flag (default off). Guardrails that opt in are pulled out of the sequential loop and run concurrently via asyncio.gather after every sequential (payload-mutating) guardrail has run, so they observe the mutated payload and still form a hard barrier before the LLM call; the first to raise blocks the request. Their returned data is discarded since they are declared block-only. The flag is wired from LitellmParams onto the guardrail instance at the same generic choke point in initialize_guardrail that already sets skip_system_message_in_guardrail, so no per-provider initializer needs to change. * feat(guardrails): extend run_in_parallel opt-in to post_call guardrails post_call_success_hook ran guardrails sequentially for the same reason pre_call did: response-modifying guardrails thread the response forward. But block-only output scanners (which read the response and reject on violation without changing it) serialize for no benefit and add latency. This reuses the existing run_in_parallel flag for the post_call hook. Opted-in post_call guardrails are pulled out of the sequential loop and run concurrently via asyncio.gather after the sequential (response-modifying) guardrails and before the non-guardrail CustomLogger callbacks, so they inspect the final response and still block it from reaching the client if any raises. Their returned response is discarded since they are block-only. The apply_guardrail path sets data["guardrail_to_apply"] immediately before awaiting, and unified_guardrail pops it before its first suspension point, so concurrent guardrails never race on that key under asyncio's cooperative scheduling. * fix(guardrails): await all parallel guardrails and prioritize blocks over reroutes Addresses review feedback on the run_in_parallel opt-in. asyncio.gather propagated the first exception without cancelling or awaiting the siblings, so a block at t=0 left the other guardrails running as unobserved background tasks (wasted external calls plus event-loop warnings), and a fast SensitiveDataRouteException/ModifyResponseException could return a reroute or passthrough before a slower block finished, letting crafted input bypass the block. Both the pre_call and post_call parallel batches now gather with return_exceptions=True so every guardrail runs to completion, then raise any blocking exception ahead of a flow-changing one. The registry choke point wrote bool(None)==False onto every instance when the config omitted run_in_parallel, silently disabling a constructor-set default; it now only writes when the config provides an explicit value. * fix(guardrails): record lifecycle logs for every concurrently-run guardrail The log_guardrail_information decorator skipped its auto-record when it saw that the count of standard_logging_guardrail_information entries in the shared request_data had grown during the wrapped call, taking that as proof the wrapped function had recorded its own richer entry. That heuristic breaks the moment guardrails run concurrently (parallel pre_call/post_call, during_call): a sibling guardrail's append inflates the shared count, so a guardrail that did not self-record wrongly concludes it already did and drops its own entry. The result is that enabling run_in_parallel silently loses per-guardrail lifecycle logs, so the Admin UI Request Lifecycle timeline and downstream loggers (Datadog, Langfuse, OTEL, spend logs) show only one of the concurrent guardrails. Replace the shared-count heuristic with a ContextVar flag set when a guardrail records its own entry. asyncio copies the context into each gathered task, so the flag is isolated per concurrent guardrail while still catching the self-record-then-skip-auto-record case within a single invocation. * test(guardrails): declare run_in_parallel on post_call guardrail mocks The post_call partition reads run_in_parallel on every CustomGuardrail callback. A MagicMock(spec=CustomGuardrail) has no run_in_parallel (it is set in __init__, not on the class) so the attribute access raised, and even a class-level default would return a truthy child mock that wrongly routes the double into the parallel batch. Declare the flag False on the shared mock factories so these pre-existing hook tests exercise the sequential path they assert on. * fix(guardrails): harden run_in_parallel reads and address review feedback Read run_in_parallel via getattr(..., False) in the pre_call and post_call partitions so a third-party CustomGuardrail subclass that overrides __init__ without chaining super().__init__() no longer raises AttributeError on a path that previously worked. Drop the redundant in-function GuardrailEventHooks import in _run_parallel_post_call_guardrails (already imported module-level). Remove the flaky wall-clock upper-bound assertions from the two concurrency tests; the all-start-before-any-end overlap assertion is the timing-independent signal that actually proves concurrency. |
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| .. | ||
| agent_tests | ||
| audio_tests | ||
| basic_proxy_startup_tests | ||
| batches_tests | ||
| benchmarks | ||
| code_coverage_tests | ||
| documentation_tests | ||
| e2e | ||
| enterprise | ||
| guardrails_tests | ||
| image_gen_tests | ||
| integration | ||
| litellm | ||
| litellm-proxy-extras | ||
| litellm_core_utils | ||
| litellm_utils_tests | ||
| llm_responses_api_testing | ||
| llm_translation | ||
| load_tests | ||
| local_testing | ||
| logging_callback_tests | ||
| mcp_tests | ||
| multi_instance_e2e_tests | ||
| ocr_tests | ||
| old_proxy_tests/tests | ||
| openai_endpoints_tests | ||
| otel_tests | ||
| pass_through_tests | ||
| pass_through_unit_tests | ||
| proxy_admin_ui_tests | ||
| proxy_behavior | ||
| proxy_e2e_anthropic_messages_tests | ||
| proxy_migration_tests | ||
| proxy_security_tests | ||
| proxy_unit_tests | ||
| router_unit_tests | ||
| scim_tests | ||
| search_tests | ||
| spend_tracking_tests | ||
| store_model_in_db_tests | ||
| test_litellm | ||
| unified_google_tests | ||
| vector_store_tests | ||
| windows_tests | ||
| __init__.py | ||
| _fake_openai_endpoint_server.py | ||
| _flush_vcr_cache.py | ||
| _live_test_helpers.py | ||
| _openai_record_replay_proxy.py | ||
| _vcr_conftest_common.py | ||
| _vcr_redis_persister.py | ||
| _ws_vcr.py | ||
| eval_swe_bench.py | ||
| fake_openai_endpoint.py | ||
| gettysburg.wav | ||
| large_text.py | ||
| openai_batch_completions.jsonl | ||
| pyrightconfig.json | ||
| README.MD | ||
| test_anthropic_compaction_usage.py | ||
| test_budget_management.py | ||
| test_callbacks_on_proxy.py | ||
| test_config.py | ||
| test_debug_warning.py | ||
| test_default_encoding_non_root.py | ||
| test_end_users.py | ||
| test_entrypoint.py | ||
| test_fallbacks.py | ||
| test_gpt5_azure_temperature_support.py | ||
| test_health.py | ||
| test_keys.py | ||
| test_litellm_proxy_responses_config.py | ||
| test_logging.conf | ||
| test_models.py | ||
| test_new_vector_store_endpoints.py | ||
| test_openai_endpoints.py | ||
| test_organizations.py | ||
| test_otel_thread_leak.py | ||
| test_passthrough_endpoints.py | ||
| test_presidio_latency.py | ||
| test_proxy_server_non_root.py | ||
| test_ratelimit.py | ||
| test_resource_cleanup.py | ||
| test_service_logger_otel.py | ||
| test_spend_logs.py | ||
| test_team.py | ||
| test_team_logging.py | ||
| test_team_members.py | ||
| test_users.py | ||
In total litellm runs 1000+ tests
[02/20/2025] Update:
To make it easier to contribute and map what behavior is tested,
we've started mapping the litellm directory in tests/test_litellm
This folder can only run mock tests.