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* feat(spend): derive a default auto-router savings baseline from the hardest tier The savings driver shipped off by default: unless an operator names litellm_settings.autorouter_savings_baseline_model, every auto-routed request records $0.00 and the dashboard card never populates. Nobody discovers a knob whose feature they have never seen work, so the default has to come from somewhere the proxy already knows. The router's own tier ladder is that place. Without a router a deployment runs one model that can carry the hardest request it will see, so the derived baseline is the priciest model in the hardest configured tier, REASONING when present, otherwise the most severe tier the router actually defines. A cheap tier is a choice the router made, not a ceiling it was bounded by. An earlier draft of #35521 derived this per request and was deleted for it: ranking candidates against the request that ran meant reading the request, and every input shape it could take produced its own review finding. This derivation is ranked against one fixed reference request instead, a cache-heavy shape matching real auto-routed traffic, so it never reads the request at all. Candidates still resolve through the router's deployments, so Azure base_model and per-deployment pricing overrides rank correctly. The deciding router records the result on its routing_decision, because one model name can carry several tag-scoped routers with different tier ladders and only the deciding instance knows which of them routed the request. The spend writer's precedence is: configured baseline, then the recorded one, then off. When the setting is present the router skips deriving entirely rather than pricing candidates per decision only to be ignored. Resolution never raises; an unresolvable baseline zeroes the driver instead of failing a live request. Rows queued by a pod on the previous release carry no recorded baseline and fall back to the configured setting, exactly as today. The schema.d.ts regeneration also picks up the reminder_markers field that UI-19232 (#35874) added without regenerating, so one hunk there is inherited staleness rather than part of this change. * fix(spend): cache the derived baseline, price it by deployment, keep it out of the routing preview Three review findings on the derived baseline, addressed together because they all sit on the same value's path from derivation to consumer. Derivation walked and priced the hardest tier's whole pool inside a property read on every routing decision, unbounded by pool size. The router now caches the result per instance with a 30 second TTL, None results included, so the hot path is a clock compare and a deployment edit still lands within a window no operator watches closer than. Ranking used each deployment's effective pricing but recorded only the model name, so the spend writer priced the winning baseline at its public rate: a hardest tier whose deployment carries a negotiated rate produced materially wrong savings. The decision now also records savings_baseline_deployment_id and the writer resolves it through Router.get_deployment_model_info, exactly as the selected arm already does. The id is ignored whenever the configured setting overrides the recorded baseline, since the setting names a model, not a deployment. /auto_router/test_routing returns the routing decision verbatim to team admins while only authorizing the classifier and embedding models, so a derived baseline would resolve another team's model-group alias into its backend provider/model mapping and hand it to a caller never authorized for it. The preview's throwaway router is built with derive_savings_baseline=False; its decisions are never spend-tracked, so nothing is lost, and a source-pinning test keeps the flag on the endpoint. Also strips the explanatory comments this PR had added. * refactor(spend): pin the derived baseline per router instance instead of a TTL Creating or editing a router already rebuilds its ComplexityRouter instance, through unregister and re-add on upsert and through the registry reset on a full model_list load, so a value derived once per instance refreshes on exactly the flows that can change it. That makes the TTL a solution to a problem the rebuild lifecycle already solves, and it goes. Derivation stays deferred to first use rather than running in __init__: during a config load this router can be constructed before the deployments its tiers name, and a baseline pinned at that moment would be empty for the process lifetime. The one behavior the TTL had that the pin does not: editing a tier deployment without touching the router itself refreshed the baseline within a window. That edit path rebuilds only the edited deployment's own strategies, so the pin holds the old answer until the router is next saved or the config next loads. A stale deployment id degrades to public-rate pricing rather than failing, which is where every other unresolvable baseline already lands. |
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| .. | ||
| _experimental/mcp_server | ||
| a2a | ||
| agent_endpoints | ||
| analytics_endpoints | ||
| anthropic_endpoints | ||
| auth | ||
| batches_endpoints | ||
| client | ||
| common_utils | ||
| config_resolvers | ||
| db | ||
| discovery_endpoints | ||
| enterprise_billing | ||
| experimental/mcp_server | ||
| google_endpoints | ||
| guardrails | ||
| health_endpoints | ||
| hooks | ||
| image_endpoints | ||
| logging_endpoints | ||
| management_endpoints | ||
| management_helpers | ||
| memory | ||
| middleware | ||
| openai_files_endpoint | ||
| pass_through_endpoints | ||
| policy_engine | ||
| prompts | ||
| proxy_server | ||
| public_endpoints | ||
| rag_endpoints | ||
| realtime_endpoints | ||
| response_api_endpoints | ||
| shutdown | ||
| spend_tracking | ||
| test_configs | ||
| types_utils | ||
| ui_crud_endpoints | ||
| utils | ||
| vector_store_endpoints | ||
| video_endpoints | ||
| __init__.py | ||
| conftest.py | ||
| test_aiohttp_cleanup_closed.py | ||
| test_aiohttp_session_recovery.py | ||
| test_api_key_masking_in_errors.py | ||
| test_audio_speech_prometheus_hooks.py | ||
| test_batch_expiry.py | ||
| test_batch_metadata_none_fix.py | ||
| test_batch_retrieve_bedrock.py | ||
| test_batch_x_litellm_model_encoding.py | ||
| test_blocked_response_usage.py | ||
| test_budget_reservation.py | ||
| test_caching_routes.py | ||
| test_chat_completion_metadata.py | ||
| test_common_request_processing.py | ||
| test_component_allowlists.py | ||
| test_cors_config.py | ||
| test_custom_proxy.py | ||
| test_dynamic_mcp_route.py | ||
| test_empty_model_list.py | ||
| test_enforce_user_param.py | ||
| test_fallback_management_endpoints.py | ||
| test_fastapi_offline_routes.py | ||
| test_filter_models_by_team_access_group.py | ||
| test_health_check_functions.py | ||
| test_health_check_max_tokens.py | ||
| test_langfuse_passthrough_security.py | ||
| test_lazy_openapi_snapshot.py | ||
| test_litellm_pre_call_utils.py | ||
| test_max_budget_env_var.py | ||
| test_mcp_asgi_response.py | ||
| test_model_based_routing_files_batches.py | ||
| test_model_dump_with_preserved_fields.py | ||
| test_model_id_header_propagation.py | ||
| test_model_info_default_limits.py | ||
| test_model_level_guardrails.py | ||
| test_model_list_healthy_only.py | ||
| test_modify_response_streaming_passthrough.py | ||
| test_openapi_schema_validation.py | ||
| test_plugin_routes.py | ||
| test_pricing_field_strip.py | ||
| test_prometheus_cleanup.py | ||
| test_provider_url_destination_guard.py | ||
| test_proxy_cli.py | ||
| test_proxy_logging_hook_detection.py | ||
| test_proxy_server.py | ||
| test_proxy_types.py | ||
| test_proxy_utils.py | ||
| test_pyroscope.py | ||
| test_read_model_list.py | ||
| test_redis_auth_cache_flag.py | ||
| test_response_model_sanitization.py | ||
| test_route_a2a_models.py | ||
| test_route_llm_request.py | ||
| test_sensitive_route_auth.py | ||
| test_shared_health_check.py | ||
| test_spend_log_cleanup.py | ||
| test_swagger_chat_completions.py | ||
| test_team_member_update.py | ||
| test_team_org_move.py | ||
| test_tools_allowlist_enforcement.py | ||
| test_update_llm_router_resilience.py | ||