From 4a70d80aef0c600e4c493a77ab0a69d001d3d3bc Mon Sep 17 00:00:00 2001 From: Kerry Lu Date: Wed, 28 Oct 2026 15:23:52 -0700 Subject: [PATCH 01/10] fix(aiohttp_transport): keep the owned session open while a response stream is still being read (LIT-10237) (#48920) * fix(aiohttp_transport): keep the owned session open while a response stream is still being read (LIT-10237) * test(aiohttp_transport): annotate the stream regression test locals with Final and drop its docstring --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../llms/custom_httpx/aiohttp_transport.py | 23 +++++++- .../custom_httpx/test_aiohttp_transport.py | 55 +++++++++++++++++++ 2 files changed, 77 insertions(+), 1 deletion(-) diff --git a/litellm/llms/custom_httpx/aiohttp_transport.py b/litellm/llms/custom_httpx/aiohttp_transport.py index 0e4d97fd770..9297e76624d 100644 --- a/litellm/llms/custom_httpx/aiohttp_transport.py +++ b/litellm/llms/custom_httpx/aiohttp_transport.py @@ -6,6 +6,7 @@ import ssl import sys import typing import urllib.request +import weakref from collections.abc import Callable, Generator from typing import ClassVar, Final @@ -109,6 +110,24 @@ def map_aiohttp_exceptions() -> Generator[None, None, None]: raise mapped_exc(message) from exc +def _release_transport_anchor(_transport: object) -> None: + """Release a transport anchored to a response stream. See ``_anchor_transport_to``.""" + + +def _anchor_transport_to(stream: "AiohttpResponseStream", transport: object) -> None: + """Keep the transport alive for as long as the stream can still read. + + The transport finalizer closes the session it owns, and nothing on the path from a + live response back to that session references the transport, so a client dropped + mid-stream would close the session under the body. ``weakref.finalize`` holds the + transport in its own registry rather than on the stream, which keeps the transport + out of the response's reference cycle (an exception carrying the response, for one) + so it is finalized by refcount once the anchor drops and can still schedule an async + close, instead of being collected in the same cyclic pass as the session it closes. + """ + weakref.finalize(stream, _release_transport_anchor, transport) + + class AiohttpResponseStream(httpx.AsyncByteStream): CHUNK_SIZE = 1024 * 16 @@ -463,10 +482,12 @@ class LiteLLMAiohttpTransport(AiohttpTransport): # Re-raise if it's a different RuntimeError raise + stream: Final = AiohttpResponseStream(response) + _anchor_transport_to(stream, self) return httpx.Response( status_code=response.status, headers=response.headers, - stream=AiohttpResponseStream(response), + stream=stream, request=request, ) diff --git a/tests/unit/llms/custom_httpx/test_aiohttp_transport.py b/tests/unit/llms/custom_httpx/test_aiohttp_transport.py index c7d5518ef5b..aed808223bd 100644 --- a/tests/unit/llms/custom_httpx/test_aiohttp_transport.py +++ b/tests/unit/llms/custom_httpx/test_aiohttp_transport.py @@ -5,6 +5,7 @@ import socket import sys import struct import threading +import weakref from typing import Final import aiohttp @@ -1383,3 +1384,57 @@ def test_a_transport_collected_while_its_loop_runs_elsewhere_closes_its_session_ loop.call_soon_threadsafe(loop.stop) thread.join(timeout=10) loop.close() + + +@pytest.mark.asyncio +async def test_a_stream_keeps_reading_after_the_client_that_opened_it_is_collected(): + from aiohttp import web + + release: Final = asyncio.Event() + body: Final = tuple(f"chunk{i}\n".encode() for i in range(4)) + + async def handler(request: web.Request) -> web.StreamResponse: + response: Final = web.StreamResponse() + await response.prepare(request) + await response.write(body[0]) + await release.wait() + for chunk in body[1:]: + await response.write(chunk) + await response.write_eof() + return response + + app: Final = web.Application() + app.router.add_get("/stream", handler) + runner: Final = web.AppRunner(app) + await runner.setup() + sock: Final = socket.socket() + sock.bind(("127.0.0.1", 0)) + port: Final[int] = sock.getsockname()[1] + await web.SockSite(runner, sock).start() + + transport: Final = LiteLLMAiohttpTransport(client=aiohttp.ClientSession) + client: Final = httpx.AsyncClient(transport=transport) + transport_ref: Final = weakref.ref(transport) + try: + response: Final = await client.send(client.build_request("GET", f"http://127.0.0.1:{port}/stream"), stream=True) + session: Final = transport.client + assert isinstance(session, aiohttp.ClientSession) + chunks: Final = response.aiter_bytes() + first: Final = await chunks.__anext__() + + del client, transport + gc.collect() + await asyncio.gather(*LiteLLMAiohttpTransport._background_close_tasks) + release.set() + + rest: Final = [chunk async for chunk in chunks] + assert first + b"".join(rest) == b"".join(body), (first, rest) + assert not session.closed, "the session was closed under a stream that was still being read" + + del response, chunks + gc.collect() + await asyncio.gather(*LiteLLMAiohttpTransport._background_close_tasks) + assert transport_ref() is None, "the finished stream kept the transport alive" + assert session.closed, "the owned session stayed open after its last stream finished" + finally: + await runner.cleanup() From 2791822f921fab9469b86ed37d8a2deadad0fc58 Mon Sep 17 00:00:00 2001 From: Kerry Lu Date: Wed, 28 Oct 2026 15:28:35 -0700 Subject: [PATCH 02/10] ci(spend-logs-guard): run only on pull_request_target, re-run by hand after approving (#48941) Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .github/workflows/spend-logs-guard.yml | 4 ---- ci_cd/spend_logs_guard.py | 4 ++-- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/.github/workflows/spend-logs-guard.yml b/.github/workflows/spend-logs-guard.yml index 354a1b7c947..29e9f236202 100644 --- a/.github/workflows/spend-logs-guard.yml +++ b/.github/workflows/spend-logs-guard.yml @@ -4,10 +4,6 @@ on: # zizmor: ignore[dangerous-triggers] runs the base branch's code only; the P pull_request_target: branches: - main - pull_request_review: - types: - - submitted - - dismissed permissions: contents: read diff --git a/ci_cd/spend_logs_guard.py b/ci_cd/spend_logs_guard.py index fac9d4ba5d2..a4d9a2e0a0d 100644 --- a/ci_cd/spend_logs_guard.py +++ b/ci_cd/spend_logs_guard.py @@ -6,7 +6,7 @@ so a path rule would put every migration on the owner. This gate reads the diff added line in the watched files mentions the table it passes at once, otherwise it passes only once the owner's latest review on the pull request is an approval that still covers every spend-log line in the head (approvals survive pushes, so a later commit may not add spend-log lines the owner never -saw). The workflow re-runs on every review. +saw). Reviews do not trigger the workflow, so the check is re-run by hand after approving. """ from __future__ import annotations @@ -153,7 +153,7 @@ def main(argv: Sequence[str]) -> int: else f"LiteLLM_SpendLogs lines changed after @{args.approver} approved {approval.commit_id}, " f"a new approving review is needed:\n" ) - sys.stdout.write(f"{reason}{listed}The check re-runs when a review is submitted.\n") + sys.stdout.write(f"{reason}{listed}After approving, re-run this job.\n") return 1 From 84c4c5aa5c530610863afe104b32dc50ebca37da Mon Sep 17 00:00:00 2001 From: Kerry Lu Date: Wed, 28 Oct 2026 15:32:27 -0700 Subject: [PATCH 03/10] fix(router): cool down failing deployments when fallbacks use string targets (LIT-10238) (#48913) Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/router_utils/cooldown_handlers.py | 32 ++++++++++++++----- .../sdk/test_router_cooldown_fallback_sdk.py | 28 ++++++++++++++++ .../router_utils/test_cooldown_handlers.py | 32 +++++++++++++++++++ 3 files changed, 84 insertions(+), 8 deletions(-) diff --git a/litellm/router_utils/cooldown_handlers.py b/litellm/router_utils/cooldown_handlers.py index 128bca6cca0..a1b1e327802 100644 --- a/litellm/router_utils/cooldown_handlers.py +++ b/litellm/router_utils/cooldown_handlers.py @@ -13,7 +13,7 @@ from datetime import datetime from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final -from pydantic import TypeAdapter +from pydantic import TypeAdapter, ValidationError import litellm from litellm._internal_context import service_target @@ -417,17 +417,35 @@ def _should_run_cooldown_logic( return True -_FALLBACK_ENTRIES_ADAPTER: Final = TypeAdapter(tuple[Mapping[str, list[str | Mapping[str, object]]] | str, ...]) +_FALLBACK_ENTRIES_ADAPTER: Final = TypeAdapter(tuple[object, ...]) +_FALLBACK_ENTRY_ADAPTER: Final = TypeAdapter(Mapping[str, list[str | Mapping[str, object]] | str]) def _fallback_target_name(target: str | Mapping[str, object]) -> str: return target if isinstance(target, str) else str(target.get("model", "")) +def _fallback_target_names( + targets: Sequence[str | Mapping[str, object]] | str, +) -> list[str]: # mutable-ok: mirrors get_fallback_model_group's fallbacks shape + return [targets] if isinstance(targets, str) else [_fallback_target_name(target) for target in targets] + + def _fallback_chain_names( - entry: Mapping[str, Sequence[str | Mapping[str, object]]], -) -> Mapping[str, list[str]]: # mutable-ok: mirrors get_fallback_model_group's fallbacks shape - return {key: [_fallback_target_name(target) for target in targets] for key, targets in entry.items()} + entry: object, +) -> Mapping[str, list[str]] | None: # mutable-ok: mirrors get_fallback_model_group's fallbacks shape + try: + validated: Final = _FALLBACK_ENTRY_ADAPTER.validate_python(entry) + except ValidationError: + return None + return {key: _fallback_target_names(targets) for key, targets in validated.items()} + + +def _fallback_entries(configured: object) -> tuple[object, ...]: + try: + return _FALLBACK_ENTRIES_ADAPTER.validate_python(configured) + except ValidationError: + return () def _has_fallback_group(litellm_router_instance: LitellmRouter, requested_model_group: str | None) -> bool: @@ -437,9 +455,7 @@ def _has_fallback_group(litellm_router_instance: LitellmRouter, requested_model_ if requested_model_group is None or not configured: return False chains: Final = tuple( - _fallback_chain_names(entry) - for entry in _FALLBACK_ENTRIES_ADAPTER.validate_python(configured) - if isinstance(entry, Mapping) + chain for chain in map(_fallback_chain_names, _fallback_entries(configured)) if chain is not None ) fallback_group, _ = get_fallback_model_group(fallbacks=chains, model_group=requested_model_group) return bool(fallback_group) diff --git a/tests/integration/sdk/test_router_cooldown_fallback_sdk.py b/tests/integration/sdk/test_router_cooldown_fallback_sdk.py index 747adeee41d..e7508a2670e 100644 --- a/tests/integration/sdk/test_router_cooldown_fallback_sdk.py +++ b/tests/integration/sdk/test_router_cooldown_fallback_sdk.py @@ -12,6 +12,7 @@ from pydantic import JsonValue, TypeAdapter import litellm from litellm import Router +from litellm.router_utils.cooldown_handlers import async_get_cooldown_deployments from litellm.types.router import DeploymentTypedDict _MODEL: Final = "gpt-5.4" @@ -118,3 +119,30 @@ async def test_cooldown_skips_only_the_failed_duplicate_model_deployment() -> No "/primary/chat/completions", "/backup/chat/completions", ) + + +@pytest.mark.parametrize( + "router_kwargs", + [{"fallbacks": [{"primary": "backup"}]}, {"default_fallbacks": "backup"}], + ids=["string_fallback_target", "string_default_fallbacks"], +) +@pytest.mark.asyncio +async def test_string_valued_fallbacks_still_cool_down_the_failing_primary(router_kwargs: dict[str, object]) -> None: + with wire_server(_peer) as wire: + router: Final = Router( + model_list=[ + _deployment("primary", f"{wire.url}/primary", "primary-deployment"), + _deployment("backup", f"{wire.url}/backup", "backup-deployment"), + ], + allowed_fails=0, + num_retries=0, + **router_kwargs, + ) + with pytest.raises(litellm.AuthenticationError): + await router.acompletion( + model="primary", + messages=[{"role": "user", "content": f"cooldown {uuid.uuid4().hex}"}], + ) + cooled: Final = await async_get_cooldown_deployments(litellm_router_instance=router, parent_otel_span=None) + + assert tuple(cooled) == ("primary-deployment",) diff --git a/tests/unit/router_utils/test_cooldown_handlers.py b/tests/unit/router_utils/test_cooldown_handlers.py index 0d39016ea79..24459a5a250 100644 --- a/tests/unit/router_utils/test_cooldown_handlers.py +++ b/tests/unit/router_utils/test_cooldown_handlers.py @@ -25,6 +25,7 @@ from litellm.router_utils.cooldown_callbacks import router_cooldown_event_callba from litellm.router_utils.cooldown_handlers import ( _get_deployment_cooldown_policy, _has_explicit_allowed_fails_policy_for_exception, + _has_fallback_group, _increment_allowed_fails, _is_cooldown_required, _resolve_allowed_fails_from_policy, @@ -3149,6 +3150,8 @@ BENCHED: Final = (litellm.Timeout, litellm.Timeout, RouterRateLimitError, Router {}, BENCHED, ), + ({"allowed_fails": 1, "fallbacks": [{"test-model": "backup-model"}]}, {}, BENCHED), + ({"allowed_fails": 1, "default_fallbacks": "backup-model"}, {}, BENCHED), ], ids=[ "allowed_fails", @@ -3157,6 +3160,8 @@ BENCHED: Final = (litellm.Timeout, litellm.Timeout, RouterRateLimitError, Router "policy_names_timeout", "allowed_fails_with_a_fallback_group", "allowed_fails_with_a_dict_fallback_target", + "allowed_fails_with_a_string_fallback_target", + "allowed_fails_with_a_string_default_fallbacks", ], ) @pytest.mark.asyncio @@ -3180,6 +3185,33 @@ async def test_router_allowed_fails_benches_a_lone_deployment_only_when_the_poli assert len(route.calls) == outcomes.count(litellm.Timeout) +@pytest.mark.parametrize( + ("fallbacks", "expected"), + [ + ([{"test-model": "backup-model"}], True), + ([{"*": "backup-model"}], True), + ([{"test-model": ["backup-model"]}], True), + ([{"test-model": 5}, {"*": "backup-model"}], True), + ([{"test-model": 5}], False), + ([{"other-model": ["backup-model"]}], False), + ], + ids=[ + "string_target", + "string_catch_all_from_default_fallbacks", + "list_target", + "unparseable_entry_does_not_hide_the_catch_all", + "unparseable_entry_alone", + "another_groups_chain", + ], +) +def test_has_fallback_group_reads_string_targets_and_skips_unparseable_entries( + fallbacks: Sequence[Mapping[str, object]], expected: bool +) -> None: + router: Final = Router(model_list=[TIMED_OUT_DEPLOYMENT], fallbacks=list(fallbacks)) + + assert _has_fallback_group(router, "test-model") is expected + + async def _group_call_outcome(router: Router) -> str: try: response: Final = await router.acompletion( From e157c5e520acbd83ed75bb26ec3633c4b2cc09b1 Mon Sep 17 00:00:00 2001 From: Kerry Lu Date: Wed, 28 Oct 2026 15:34:15 -0700 Subject: [PATCH 04/10] fix(migration_data_checks): size btree entries by the bytes Postgres stores (LIT-10244) (#48911) * fix(migration_data_checks): size btree entries by the bytes Postgres stores (LIT-10244) * test(migration_data_checks): flag exactly the compressed keys Postgres rejects at the entry limit (LIT-10244) --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../migration_data_checks.py | 11 +++- .../migrations/test_request_log_indexes.py | 64 +++++++++++++++++++ .../test_migration_data_checks.py | 15 +++++ 3 files changed, 87 insertions(+), 3 deletions(-) diff --git a/litellm-proxy-extras/litellm_proxy_extras/migration_data_checks.py b/litellm-proxy-extras/litellm_proxy_extras/migration_data_checks.py index 7b01e64dd73..e22639daaef 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/migration_data_checks.py +++ b/litellm-proxy-extras/litellm_proxy_extras/migration_data_checks.py @@ -343,11 +343,16 @@ def btree_max_entry_bytes(block_size: int) -> int: def _value_bytes(column: ColumnType, identifier: "sql.Identifier") -> "sql.Composed": + """The bytes a value takes in the index entry: its length, or its stored size when + Postgres compressed it, since `index_form_tuple` keeps the compressed bytes.""" from psycopg import sql - if column.type_name in _OCTET_LENGTH_TYPES: - return sql.SQL("octet_length({})").format(identifier) - return sql.SQL("octet_length({}::text)").format(identifier) + length: Final = ( + sql.SQL("octet_length({})").format(identifier) + if column.type_name in _OCTET_LENGTH_TYPES + else sql.SQL("octet_length({}::text)").format(identifier) + ) + return sql.SQL("least({}, pg_column_size({}))").format(length, identifier) def _aligned(offset: "sql.Composable", align: str) -> "sql.Composed": diff --git a/tests/integration/database/migrations/test_request_log_indexes.py b/tests/integration/database/migrations/test_request_log_indexes.py index 1de2090b487..f558c355c84 100644 --- a/tests/integration/database/migrations/test_request_log_indexes.py +++ b/tests/integration/database/migrations/test_request_log_indexes.py @@ -1,3 +1,4 @@ +import hashlib import os import queue import secrets @@ -973,6 +974,7 @@ def test_the_migration_job_refuses_before_the_first_migration_when_spend_log_key _insert_spend_log_with_key(conn, "legacy-1", _legacy_bearer_token()) _insert_spend_log_with_key(conn, "legacy-2", _legacy_bearer_token()) _insert_spend_log_with_key(conn, "hashed-1", "a" * 64) + _insert_spend_log_with_key(conn, "repetitive-1", "z" * 3000) ledger_before: Final = _ledger(scratch_database) with pytest.raises(RuntimeError) as refused: @@ -1109,6 +1111,68 @@ def test_the_entry_size_check_draws_the_line_exactly_where_postgres_does( assert finding.detail == f"with an index entry over 2704 bytes, largest 2712 bytes ({described_as})" +@requires_db +def test_a_value_postgres_compresses_under_the_limit_is_not_counted_while_random_text_of_that_length_is( + scratch_database: str, +) -> None: + """Postgres compresses a long value before it checks the entry size, so 3000 repeated + bytes index fine while 3000 random hex bytes do not. The check must draw the same line.""" + create_index: Final = sql.SQL('CREATE INDEX "compress_probe_idx" ON "compress_probe" ("k")') + with psycopg.connect(scratch_database, autocommit=True) as conn: + conn.execute('CREATE TABLE "compress_probe" ("k" TEXT)') + conn.execute('INSERT INTO "compress_probe" ("k") VALUES (%s), (%s)', ("a" * 3000, secrets.token_hex(1500))) + findings: Final = migration_data_checks.find_blockers( + conn, "public", migration_data_checks.checks_for_statement(create_index.as_string(conn), "probe") + ) + with pytest.raises(psycopg.errors.ProgramLimitExceeded, match="index row size 3016 exceeds"): + conn.execute(create_index) + conn.execute('DELETE FROM "compress_probe" WHERE "k" <> %s', ("a" * 3000,)) + conn.execute(create_index) + stored: Final = conn.execute('SELECT octet_length("k"), pg_column_size("k") FROM "compress_probe"').fetchone() + + assert stored is not None and stored[0] == 3000 and stored[1] < 2704, stored + (finding,) = findings + assert isinstance(finding, migration_data_checks.BlockedChange) + assert finding.rows == 1, "only the random key is too long for the index once Postgres compresses the other" + assert finding.detail == "with an index entry over 2704 bytes, largest 3016 bytes (k up to 3000 bytes)" + + +def _postgres_rejects_an_index_on(conn: "psycopg.Connection[tuple[object, ...]]", key: str) -> bool: + conn.execute('DROP TABLE IF EXISTS "one_key"') + conn.execute('CREATE TABLE "one_key" ("k" TEXT)') + conn.execute('INSERT INTO "one_key" ("k") VALUES (%s)', (key,)) + try: + conn.execute('CREATE INDEX "one_key_idx" ON "one_key" ("k")') + except psycopg.errors.ProgramLimitExceeded: + return True + return False + + +@requires_db +def test_the_check_flags_exactly_the_compressed_keys_postgres_rejects_at_the_entry_limit(scratch_database: str) -> None: + """Keys that compress to a stored size just under and just over the entry limit go through the + check and through Postgres one by one. The check must flag a key exactly when Postgres rejects it.""" + noise: Final = "".join(hashlib.sha256(str(i).encode()).hexdigest() for i in range(40)) + keys: Final = tuple(noise[:n] + "a" * 1500 for n in range(2400, 2500)) + create_index: Final = sql.SQL('CREATE INDEX "stored_probe_idx" ON "stored_probe" ("k")') + with psycopg.connect(scratch_database, autocommit=True) as conn: + conn.execute('CREATE TABLE "stored_probe" ("k" TEXT)') + conn.execute('INSERT INTO "stored_probe" ("k") SELECT unnest(%s::text[])', (list(keys),)) + compressed: Final = conn.execute( + 'SELECT count(*) FROM "stored_probe" WHERE pg_column_size("k") < octet_length("k") AND octet_length("k") > 2704' + ).fetchone() + findings: Final = migration_data_checks.find_blockers( + conn, "public", migration_data_checks.checks_for_statement(create_index.as_string(conn), "probe") + ) + rejected: Final = tuple(key for key in keys if _postgres_rejects_an_index_on(conn, key)) + + assert compressed == (len(keys),), "every probe key must be longer than the limit yet stored compressed" + assert 0 < len(rejected) < len(keys), f"the probe must straddle the limit, Postgres rejected {len(rejected)}" + (finding,) = findings + assert isinstance(finding, migration_data_checks.BlockedChange) + assert finding.rows == len(rejected), f"the check must flag the {len(rejected)} keys Postgres rejects and no other" + + @requires_db def test_a_scan_that_cannot_finish_in_time_is_reported_as_unverified_rather_than_passed(scratch_database: str) -> None: with psycopg.connect(scratch_database, autocommit=True) as conn: diff --git a/tests/unit/litellm_proxy_extras/test_migration_data_checks.py b/tests/unit/litellm_proxy_extras/test_migration_data_checks.py index f3b787beda1..d4490927e29 100644 --- a/tests/unit/litellm_proxy_extras/test_migration_data_checks.py +++ b/tests/unit/litellm_proxy_extras/test_migration_data_checks.py @@ -7,7 +7,9 @@ from litellm_proxy_extras.migration_data_checks import ( MIGRATION_DATA_CHECK_TIMEOUT_ENV_VAR, BlockedChange, Check, + ColumnType, CouldNotVerify, + _count_query, btree_max_entry_bytes, checks_for_index, checks_for_migration, @@ -113,6 +115,19 @@ def test_the_btree_entry_limit_on_the_default_page_is_the_number_in_postgres_err assert btree_max_entry_bytes(8192) == 2704 +def test_the_entry_size_query_sizes_a_text_column_by_its_stored_bytes_when_postgres_compressed_it() -> None: + """Postgres compresses a long value before it checks the entry size, so a repetitive + 3000-byte key indexes fine. The query has to size it as stored, never by its length alone.""" + (check,) = checks_for_index( + "LiteLLM_SpendLogs", "LiteLLM_SpendLogs_api_key_startTime_idx", ("api_key", "startTime") + ) + types: Final = (ColumnType("text", -1, "i", -1), ColumnType("timestamp", 8, "d", 3)) + query: Final = _count_query(check, "public", types, 2704).as_string(None) + stored: Final = 'least(octet_length("api_key"), pg_column_size("api_key"))' + assert stored in query + assert 'octet_length("api_key")' not in query.replace(stored, ""), query + + def test_the_report_names_the_rows_the_statement_and_the_fix_and_says_nothing_was_applied() -> None: (check,) = checks_for_index( "LiteLLM_SpendLogs", "LiteLLM_SpendLogs_api_key_startTime_idx", ("api_key", "startTime") From 0b57b9976a609ab74ba5c5cf21f75079527527ff Mon Sep 17 00:00:00 2001 From: mrinal-berri Date: Wed, 28 Oct 2026 15:35:08 -0700 Subject: [PATCH 05/10] feat(daily-activity): per-guardrail spend breakdown in user, team and organization daily activity (#48702) * feat(daily-activity): read guardrail spend per key from the daily guardrail usage table Adds DailyActivityRepository.guardrail_spend, which sums LiteLLM_DailyGuardrailUsageUnits.cost by date, guardrail and key. A guardrail row counts only when its key has a spend row on that day under the same scope filters as the rest of the daily activity response, so user, key and date filters apply to guardrail cost too * feat(daily-activity): add a per-guardrail spend breakdown to /user/daily/activity/aggregated Each day now has breakdown.guardrails[] with metrics.spend and an api_key_breakdown carrying each key's spend and metadata. Guardrail entries only report spend, since that is the one metric stored per key. The breakdown is on the user endpoint only, is empty when a model filter is set because guardrail cost is not stored per model, and lists only keys within api_key_limit while the guardrail total keeps every key. spend and budgets are unchanged Resolves LIT-9785 * feat(daily-activity): add the guardrail breakdown to team and organization activity, with guardrail names /team/daily/activity/aggregated and /organization/daily/activity/aggregated now return breakdown.guardrails the same way the user endpoint does, since each key belongs to one team and one organization. Each guardrail entry also carries metadata.guardrail_name, read from LiteLLM_GuardrailsTable for guardrails created through the UI or API and falling back to the breakdown key for config.yaml guardrails, whose key is already their name * fix(daily-activity): keep daily activity up when the guardrail breakdown query fails, and treat an empty model filter as none A database error from the guardrail spend query now logs a warning and returns the response without guardrails, where it used to fail the whole aggregated response with a 500. An empty model= no longer drops the guardrail breakdown, matching how the rest of the endpoint already ignores it. The daily activity golden files and fixtures gain the empty guardrails key every breakdown now carries * refactor(daily-activity): fold guardrail breakdown in a worker thread and drop docstrings Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(daily-activity): report untracked guardrail units next to spend Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/proxy/_lazy_openapi_snapshot.json | 75 ++++++++ .../common_daily_activity.py | 68 ++++++- .../daily_activity_routes.py | 1 + .../daily_activity_scopes.py | 4 + .../repositories/daily_activity_repository.py | 6 + litellm/repositories/daily_activity_sql.py | 19 ++ .../common_daily_activity.py | 29 +++ litellm/types/repositories/daily_activity.py | 10 + .../spend/fixtures/daily_activity_team.json | 2 +- .../spend/fixtures/daily_activity_user.json | 2 +- .../daily_activity_team_aggregated.json | 2 +- .../golden/daily_activity_team_paginated.json | 2 +- .../daily_activity_user_aggregated.json | 2 +- .../golden/daily_activity_user_paginated.json | 2 +- ...st_daily_activity_aggregated_breakdowns.py | 180 ++++++++++++++++++ .../test_daily_activity_routes.py | 1 + ui/litellm-dashboard/src/lib/http/schema.d.ts | 36 ++++ 17 files changed, 432 insertions(+), 9 deletions(-) diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index b10b5ae98b5..39adb99a0d0 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -3487,6 +3487,13 @@ "title": "Entities", "type": "object" }, + "guardrails": { + "additionalProperties": { + "$ref": "#/components/schemas/GuardrailMetric" + }, + "title": "Guardrails", + "type": "object" + }, "mcp_servers": { "additionalProperties": { "$ref": "#/components/schemas/MetricWithMetadata" @@ -3802,6 +3809,74 @@ "title": "ExportType", "type": "string" }, + "GuardrailKeyMetric": { + "properties": { + "metadata": { + "$ref": "#/components/schemas/KeyMetadata" + }, + "metrics": { + "$ref": "#/components/schemas/GuardrailSpendMetrics" + } + }, + "required": [ + "metrics", + "metadata" + ], + "title": "GuardrailKeyMetric", + "type": "object" + }, + "GuardrailMetadata": { + "properties": { + "guardrail_name": { + "title": "Guardrail Name", + "type": "string" + } + }, + "required": [ + "guardrail_name" + ], + "title": "GuardrailMetadata", + "type": "object" + }, + "GuardrailMetric": { + "properties": { + "api_key_breakdown": { + "additionalProperties": { + "$ref": "#/components/schemas/GuardrailKeyMetric" + }, + "title": "Api Key Breakdown", + "type": "object" + }, + "metadata": { + "$ref": "#/components/schemas/GuardrailMetadata" + }, + "metrics": { + "$ref": "#/components/schemas/GuardrailSpendMetrics" + } + }, + "required": [ + "metrics", + "metadata" + ], + "title": "GuardrailMetric", + "type": "object" + }, + "GuardrailSpendMetrics": { + "properties": { + "spend": { + "default": 0.0, + "title": "Spend", + "type": "number" + }, + "untracked_units": { + "default": 0, + "title": "Untracked Units", + "type": "integer" + } + }, + "title": "GuardrailSpendMetrics", + "type": "object" + }, "HTTPAuthSecurityScheme": { "description": "Defines a security scheme using HTTP authentication.", "properties": { diff --git a/litellm/proxy/management_endpoints/common_daily_activity.py b/litellm/proxy/management_endpoints/common_daily_activity.py index f948a49441a..66f386b792d 100644 --- a/litellm/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/proxy/management_endpoints/common_daily_activity.py @@ -3,6 +3,7 @@ from collections.abc import Awaitable, Callable, Mapping, Sequence from collections.abc import Set as AbstractSet from dataclasses import dataclass, replace from datetime import date, datetime, timedelta +from itertools import groupby from types import MappingProxyType from typing import Final, Literal, NoReturn, Protocol @@ -28,6 +29,10 @@ from litellm.types.proxy.management_endpoints.common_daily_activity import ( DailySpendData, DailySpendMetadata, GroupedData, + GuardrailKeyMetric, + GuardrailMetadata, + GuardrailMetric, + GuardrailSpendMetrics, KeyMetadata, KeyMetricWithMetadata, MetricWithMetadata, @@ -39,6 +44,7 @@ from litellm.types.repositories.daily_activity import ( DailyActivityTable, EntityRollupRow, GroupingSetsRow, + GuardrailSpendRow, KeyMetadataRow, RollupMetricsRow, SpendLogsWindow, @@ -1013,17 +1019,68 @@ def _fold_entity_rollups_sync( ) +def _guardrail_metric(day: DailySpendData, rows: Sequence[GuardrailSpendRow]) -> GuardrailMetric: + return GuardrailMetric( + metrics=GuardrailSpendMetrics( + spend=sum(row.spend for row in rows), + untracked_units=sum(row.untracked_units for row in rows), + ), + metadata=GuardrailMetadata(guardrail_name=rows[0].guardrail_name), + api_key_breakdown={ + row.api_key: GuardrailKeyMetric( + metrics=GuardrailSpendMetrics(spend=row.spend, untracked_units=row.untracked_units), + metadata=day.breakdown.api_keys[row.api_key].metadata, + ) + for row in rows + if row.api_key in day.breakdown.api_keys + }, + ) + + +def _day_with_guardrails(day: DailySpendData, rows: Sequence[GuardrailSpendRow]) -> DailySpendData: + by_guardrail: Final = groupby(sorted(rows, key=lambda row: row.guardrail_id), key=lambda row: row.guardrail_id) + guardrails: Final = {guardrail_id: _guardrail_metric(day, tuple(group)) for guardrail_id, group in by_guardrail} + return day.model_copy(update={"breakdown": day.breakdown.model_copy(update={"guardrails": guardrails})}) + + +def _with_guardrail_breakdown( + results: Sequence[DailySpendData], rows: Sequence[GuardrailSpendRow] +) -> tuple[DailySpendData, ...]: + rows_by_date: Final = MappingProxyType( + {day: tuple(group) for day, group in groupby(sorted(rows, key=lambda row: row.date), key=lambda row: row.date)} + ) + return tuple(_day_with_guardrails(day, rows_by_date.get(day.date.strftime("%Y-%m-%d"), ())) for day in results) + + +async def _guardrail_spend_or_empty( + repository: DailyActivityRepository, scope: DailyActivityScope +) -> tuple[GuardrailSpendRow, ...]: + from prisma.errors import PrismaError + + try: + return await repository.guardrail_spend(scope) + except PrismaError as exc: + verbose_proxy_logger.warning("Returning daily activity without its guardrail breakdown: %s", exc) + return () + + async def get_daily_activity_aggregated( repository: DailyActivityRepository, scope: DailyActivityScope, *, entity_metadata_field: Mapping[str, dict[str, object]] | None = None, include_entity_breakdown: bool = False, + include_guardrail_breakdown: bool = False, api_key_limit: int = constants.USAGE_TOP_API_KEYS_DEFAULT, ) -> SpendAnalyticsPaginatedResponse: try: - aggregated_rows: Final = await repository.aggregated( - scope, include_entity_breakdown=include_entity_breakdown, api_key_limit=api_key_limit + aggregated_rows, guardrail_rows = await asyncio.gather( + repository.aggregated( + scope, include_entity_breakdown=include_entity_breakdown, api_key_limit=api_key_limit + ), + _guardrail_spend_or_empty(repository, scope) + if include_guardrail_breakdown and not scope.model + else asyncio.sleep(0, result=()), ) records: Final = aggregated_rows.grouping_rows aggregated: Final = await _aggregate_grouping_sets_records( @@ -1058,8 +1115,13 @@ async def get_daily_activity_aggregated( api_key_metadata=entity_key_metadata, entity_metadata_field=entity_metadata_field, ) + results: Final = ( + list(await asyncio.to_thread(_with_guardrail_breakdown, aggregated["results"], guardrail_rows)) + if guardrail_rows + else aggregated["results"] + ) return SpendAnalyticsPaginatedResponse( - results=aggregated["results"], + results=results, metadata=DailySpendMetadata( total_spend=aggregated["totals"].spend, total_flat_cost=aggregated["totals"].flat_cost, diff --git a/litellm/proxy/management_endpoints/daily_activity_routes.py b/litellm/proxy/management_endpoints/daily_activity_routes.py index 842873129e4..79e515944ce 100644 --- a/litellm/proxy/management_endpoints/daily_activity_routes.py +++ b/litellm/proxy/management_endpoints/daily_activity_routes.py @@ -300,6 +300,7 @@ def _register_aggregated_route(router: APIRouter, resolver: EntityScopeResolver, resolved.scope, entity_metadata_field=resolved.entity_metadata, include_entity_breakdown=resolver.include_entity_breakdown, + include_guardrail_breakdown=resolver.include_guardrail_breakdown, api_key_limit=api_key_limit, ) if resolver.entity != "team": diff --git a/litellm/proxy/management_endpoints/daily_activity_scopes.py b/litellm/proxy/management_endpoints/daily_activity_scopes.py index bc373388a4e..77246f5dda6 100644 --- a/litellm/proxy/management_endpoints/daily_activity_scopes.py +++ b/litellm/proxy/management_endpoints/daily_activity_scopes.py @@ -56,6 +56,7 @@ class EntityScopeResolver: resolve: EntityScopeResolve include_entity_breakdown: bool operation_names: OperationNames + include_guardrail_breakdown: bool = False def _query_ids(value: str | None) -> tuple[str, ...] | None: @@ -364,6 +365,7 @@ USER_RESOLVER = EntityScopeResolver( query=_user_query, resolve=_resolve_user, include_entity_breakdown=False, + include_guardrail_breakdown=True, operation_names=MappingProxyType( { "aggregated": "get_user_daily_activity_aggregated", @@ -385,6 +387,7 @@ TEAM_RESOLVER = EntityScopeResolver( query=_team_query, resolve=_resolve_team, include_entity_breakdown=True, + include_guardrail_breakdown=True, operation_names=MappingProxyType( { "aggregated": "get_team_daily_activity_aggregated", @@ -423,6 +426,7 @@ ORGANIZATION_RESOLVER = EntityScopeResolver( query=_organization_query, resolve=_resolve_organization, include_entity_breakdown=True, + include_guardrail_breakdown=True, operation_names=MappingProxyType( { "aggregated": "get_organization_daily_activity_aggregated", diff --git a/litellm/repositories/daily_activity_repository.py b/litellm/repositories/daily_activity_repository.py index 10c603fe56f..4ca23e4e89e 100644 --- a/litellm/repositories/daily_activity_repository.py +++ b/litellm/repositories/daily_activity_repository.py @@ -19,6 +19,7 @@ from litellm.repositories.daily_activity_sql import ( build_cache_leakage_keys_sql, build_entity_rollup_sql, build_export_sql, + build_guardrail_spend_sql, build_key_page_sql, build_key_search_sql, build_model_top_keys_sql, @@ -36,6 +37,7 @@ from litellm.types.repositories.daily_activity import ( ExportRow, ExportType, GroupingSetsRow, + GuardrailSpendRow, KeyMetadataRow, KeyPage, KeySpendRow, @@ -100,6 +102,7 @@ class DailyActivityDatabase(Protocol): _GROUPING_ADAPTER: Final = TypeAdapter(tuple[GroupingSetsRow, ...]) _ENTITY_ADAPTER: Final = TypeAdapter(tuple[EntityRollupRow, ...]) +_GUARDRAIL_SPEND_ADAPTER: Final = TypeAdapter(tuple[GuardrailSpendRow, ...]) _KEY_SPEND_ADAPTER: Final = TypeAdapter(tuple[KeySpendRow, ...]) _KEY_PAGE_TOTAL_ADAPTER: Final[TypeAdapter[int]] = TypeAdapter(int) _USER_SPEND_ADAPTER: Final = TypeAdapter(tuple[UserSpendRow, ...]) @@ -191,6 +194,9 @@ class DailyActivityRepository: distinct_api_keys=distinct_api_keys, ) + async def guardrail_spend(self, scope: DailyActivityScope) -> tuple[GuardrailSpendRow, ...]: + return _GUARDRAIL_SPEND_ADAPTER.validate_python(await self._query(build_guardrail_spend_sql(scope))) + async def search_keys(self, scope: DailyActivityScope, *, search: str, limit: int) -> tuple[str, ...]: if not 1 <= limit <= constants.USAGE_KEY_SEARCH_MAX: raise ValueError(f"limit must be between 1 and {constants.USAGE_KEY_SEARCH_MAX}") diff --git a/litellm/repositories/daily_activity_sql.py b/litellm/repositories/daily_activity_sql.py index 3d27e7d937e..7ec9fa67a67 100644 --- a/litellm/repositories/daily_activity_sql.py +++ b/litellm/repositories/daily_activity_sql.py @@ -261,6 +261,25 @@ def build_entity_rollup_sql(scope: DailyActivityScope, *, api_key_limit: int) -> return SqlQuery(sql=sql, params=(*where_params, PTU_SENTINEL_API_KEY, api_key_limit)) +def build_guardrail_spend_sql(scope: DailyActivityScope) -> SqlQuery: + pg_table: Final = PRISMA_TO_PG_TABLE[scope.table] + where_clause, where_params = build_where_clause(scope) + sql: Final = f""" + SELECT g.date, g.guardrail_id, COALESCE(t.guardrail_name, g.guardrail_id) AS guardrail_name, g.api_key, + COALESCE(SUM(g.cost), 0)::float AS spend, + COALESCE(SUM(CASE WHEN g.cost IS NULL THEN g.units ELSE g.untracked_units END), 0)::bigint AS untracked_units + FROM "LiteLLM_DailyGuardrailUsageUnits" g + LEFT JOIN "LiteLLM_GuardrailsTable" t ON t.guardrail_id = g.guardrail_id + WHERE g.date >= $1 AND g.date <= $2 + AND EXISTS ( + SELECT 1 FROM "{pg_table}" + WHERE {where_clause} AND "{pg_table}".date = g.date AND "{pg_table}".api_key = g.api_key + ) + GROUP BY g.date, g.guardrail_id, t.guardrail_name, g.api_key + """ + return SqlQuery(sql=sql, params=where_params) + + def _key_spend_select() -> str: return """ COALESCE(SUM(spend), 0)::float AS spend, diff --git a/litellm/types/proxy/management_endpoints/common_daily_activity.py b/litellm/types/proxy/management_endpoints/common_daily_activity.py index 213c911cfdc..3f1a7980b27 100644 --- a/litellm/types/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/types/proxy/management_endpoints/common_daily_activity.py @@ -65,6 +65,34 @@ class MetricWithMetadata(MetricBase): api_key_breakdown: dict[str, KeyMetricWithMetadata] = Field(default_factory=dict) # api_key -> {metrics, metadata} +class GuardrailSpendMetrics(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + spend: float = 0.0 + untracked_units: int = 0 + + +class GuardrailKeyMetric(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + metrics: GuardrailSpendMetrics + metadata: KeyMetadata + + +class GuardrailMetadata(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + guardrail_name: str + + +class GuardrailMetric(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + metrics: GuardrailSpendMetrics + metadata: GuardrailMetadata + api_key_breakdown: Mapping[str, GuardrailKeyMetric] = Field(default_factory=dict) + + class BreakdownMetrics(LiteLLMBaseModel): """Breakdown of spend by different dimensions""" @@ -75,6 +103,7 @@ class BreakdownMetrics(LiteLLMBaseModel): endpoints: dict[str, MetricWithMetadata] = Field(default_factory=dict) # endpoint -> {metrics, metadata} api_keys: dict[str, KeyMetricWithMetadata] = Field(default_factory=dict) # api_key -> {metrics, metadata} entities: dict[str, MetricWithMetadata] = Field(default_factory=dict) # entity -> {metrics, metadata} + guardrails: Mapping[str, GuardrailMetric] = Field(default_factory=dict) # guardrail_id -> spend class DailySpendData(LiteLLMBaseModel): diff --git a/litellm/types/repositories/daily_activity.py b/litellm/types/repositories/daily_activity.py index 4111b83a891..b013ce43113 100644 --- a/litellm/types/repositories/daily_activity.py +++ b/litellm/types/repositories/daily_activity.py @@ -168,6 +168,16 @@ class EntityRollupRow(RollupMetricsRow): distinct_api_keys: int | None +@dataclass(frozen=True, slots=True) +class GuardrailSpendRow: + date: str + guardrail_id: str + guardrail_name: str + api_key: str + spend: float + untracked_units: int + + @dataclass(frozen=True, slots=True) class AggregatedRows: grouping_rows: tuple[GroupingSetsRow, ...] diff --git a/tests/integration/spend/fixtures/daily_activity_team.json b/tests/integration/spend/fixtures/daily_activity_team.json index 62377c07432..8f4956dd7fe 100644 --- a/tests/integration/spend/fixtures/daily_activity_team.json +++ b/tests/integration/spend/fixtures/daily_activity_team.json @@ -1 +1 @@ -{"results":[{"date":"2026-06-01","metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"breakdown":{"mcp_servers":{},"models":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"model_groups":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"providers":{"provider-a":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"endpoints":{"/v1/chat/completions":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"api_keys":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}},"entities":{"team-1":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{"team_alias":"Usage Team"},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}}}}}],"metadata":{"total_spend":1273.0,"total_flat_cost":0.0,"total_ptu_hours":0.0,"total_prompt_tokens":1014,"total_completion_tokens":10,"total_tokens":1024,"total_api_requests":5,"total_successful_requests":5,"total_failed_requests":0,"total_cache_read_input_tokens":6,"total_cache_creation_input_tokens":0,"total_compression_saved_tokens":0,"total_compression_savings_spend":0.0,"total_prompt_caching_savings_spend":0.0,"total_gateway_injected_caching_savings_spend":0.0,"total_autorouter_savings_spend":0.0,"total_response_time_ms":0,"total_timed_requests":0,"page":1,"total_pages":1,"has_more":false,"api_key_limit":100,"total_api_keys":5,"entity_total_api_keys":{"team-1":5}}} +{"results":[{"date":"2026-06-01","metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"breakdown":{"mcp_servers":{},"models":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"model_groups":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"providers":{"provider-a":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"endpoints":{"/v1/chat/completions":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"api_keys":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}},"entities":{"team-1":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{"team_alias":"Usage Team"},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}}},"guardrails":{}}}],"metadata":{"total_spend":1273.0,"total_flat_cost":0.0,"total_ptu_hours":0.0,"total_prompt_tokens":1014,"total_completion_tokens":10,"total_tokens":1024,"total_api_requests":5,"total_successful_requests":5,"total_failed_requests":0,"total_cache_read_input_tokens":6,"total_cache_creation_input_tokens":0,"total_compression_saved_tokens":0,"total_compression_savings_spend":0.0,"total_prompt_caching_savings_spend":0.0,"total_gateway_injected_caching_savings_spend":0.0,"total_autorouter_savings_spend":0.0,"total_response_time_ms":0,"total_timed_requests":0,"page":1,"total_pages":1,"has_more":false,"api_key_limit":100,"total_api_keys":5,"entity_total_api_keys":{"team-1":5}}} diff --git a/tests/integration/spend/fixtures/daily_activity_user.json b/tests/integration/spend/fixtures/daily_activity_user.json index c4302ee7045..ae05e661071 100644 --- a/tests/integration/spend/fixtures/daily_activity_user.json +++ b/tests/integration/spend/fixtures/daily_activity_user.json @@ -1 +1 @@ -{"results":[{"date":"2026-06-01","metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"breakdown":{"mcp_servers":{},"models":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"model_groups":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"providers":{"provider-a":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"endpoints":{"/v1/chat/completions":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"api_keys":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}},"entities":{"user-1":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}}}}}],"metadata":{"total_spend":1273.0,"total_flat_cost":0.0,"total_ptu_hours":0.0,"total_prompt_tokens":1014,"total_completion_tokens":10,"total_tokens":1024,"total_api_requests":5,"total_successful_requests":5,"total_failed_requests":0,"total_cache_read_input_tokens":6,"total_cache_creation_input_tokens":0,"total_compression_saved_tokens":0,"total_compression_savings_spend":0.0,"total_prompt_caching_savings_spend":0.0,"total_gateway_injected_caching_savings_spend":0.0,"total_autorouter_savings_spend":0.0,"total_response_time_ms":0,"total_timed_requests":0,"page":1,"total_pages":1,"has_more":false,"api_key_limit":100,"total_api_keys":5,"entity_total_api_keys":{"user-1":5}}} +{"results":[{"date":"2026-06-01","metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"breakdown":{"mcp_servers":{},"models":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"model_groups":{"model-ptu":{"metrics":{"spend":1000.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":0,"completion_tokens":0,"cache_read_input_tokens":0,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":0,"successful_requests":0,"failed_requests":0,"api_requests":0,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{}},"model-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}},"model-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}},"model-popular":{"metrics":{"spend":270.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":9,"completion_tokens":6,"cache_read_input_tokens":3,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":15,"successful_requests":3,"failed_requests":0,"api_requests":3,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"providers":{"provider-a":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"endpoints":{"/v1/chat/completions":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}}}}},"api_keys":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}},"entities":{"user-1":{"metrics":{"spend":1273.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1014,"completion_tokens":10,"cache_read_input_tokens":6,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1024,"successful_requests":5,"failed_requests":0,"api_requests":5,"total_response_time_ms":0,"timed_requests":0},"metadata":{},"api_key_breakdown":{"key-a":{"metrics":{"spend":100.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":2,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":4,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-a","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-b":{"metrics":{"spend":90.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":3,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":5,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-b","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-c":{"metrics":{"spend":80.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":4,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":6,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-c","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-cache":{"metrics":{"spend":2.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":1000,"completion_tokens":2,"cache_read_input_tokens":1,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":1002,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"alias-cache","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":true}},"key-target":{"metrics":{"spend":1.0,"flat_cost":0.0,"ptu_hours":0.0,"prompt_tokens":5,"completion_tokens":2,"cache_read_input_tokens":2,"cache_creation_input_tokens":0,"compression_saved_tokens":0,"compression_savings_spend":0.0,"prompt_caching_savings_spend":0.0,"gateway_injected_caching_savings_spend":0.0,"autorouter_savings_spend":0.0,"total_tokens":7,"successful_requests":1,"failed_requests":0,"api_requests":1,"total_response_time_ms":0,"timed_requests":0},"metadata":{"key_alias":"deleted-target","team_id":"team-1","user_id":"user-1","user_email":"user@example.com","key_exists":false}}}}},"guardrails":{}}}],"metadata":{"total_spend":1273.0,"total_flat_cost":0.0,"total_ptu_hours":0.0,"total_prompt_tokens":1014,"total_completion_tokens":10,"total_tokens":1024,"total_api_requests":5,"total_successful_requests":5,"total_failed_requests":0,"total_cache_read_input_tokens":6,"total_cache_creation_input_tokens":0,"total_compression_saved_tokens":0,"total_compression_savings_spend":0.0,"total_prompt_caching_savings_spend":0.0,"total_gateway_injected_caching_savings_spend":0.0,"total_autorouter_savings_spend":0.0,"total_response_time_ms":0,"total_timed_requests":0,"page":1,"total_pages":1,"has_more":false,"api_key_limit":100,"total_api_keys":5,"entity_total_api_keys":{"user-1":5}}} diff --git a/tests/integration/spend/golden/daily_activity_team_aggregated.json b/tests/integration/spend/golden/daily_activity_team_aggregated.json index 2956adda17a..91a5d33391b 100644 --- a/tests/integration/spend/golden/daily_activity_team_aggregated.json +++ b/tests/integration/spend/golden/daily_activity_team_aggregated.json @@ -26,7 +26,7 @@ }, "results": [ { - "breakdown": { + "breakdown": {"guardrails": {}, "api_keys": { "key-a": { "metadata": { diff --git a/tests/integration/spend/golden/daily_activity_team_paginated.json b/tests/integration/spend/golden/daily_activity_team_paginated.json index ca7239f8fa9..4d91b0da209 100644 --- a/tests/integration/spend/golden/daily_activity_team_paginated.json +++ b/tests/integration/spend/golden/daily_activity_team_paginated.json @@ -26,7 +26,7 @@ }, "results": [ { - "breakdown": { + "breakdown": {"guardrails": {}, "api_keys": { "key-a": { "metadata": { diff --git a/tests/integration/spend/golden/daily_activity_user_aggregated.json b/tests/integration/spend/golden/daily_activity_user_aggregated.json index 261ac22b2cb..185d333965a 100644 --- a/tests/integration/spend/golden/daily_activity_user_aggregated.json +++ b/tests/integration/spend/golden/daily_activity_user_aggregated.json @@ -26,7 +26,7 @@ }, "results": [ { - "breakdown": { + "breakdown": {"guardrails": {}, "api_keys": { "key-a": { "metadata": { diff --git a/tests/integration/spend/golden/daily_activity_user_paginated.json b/tests/integration/spend/golden/daily_activity_user_paginated.json index f1fb7ba50a4..00389289ebe 100644 --- a/tests/integration/spend/golden/daily_activity_user_paginated.json +++ b/tests/integration/spend/golden/daily_activity_user_paginated.json @@ -26,7 +26,7 @@ }, "results": [ { - "breakdown": { + "breakdown": {"guardrails": {}, "api_keys": { "key-a": { "metadata": { diff --git a/tests/integration/spend/test_daily_activity_aggregated_breakdowns.py b/tests/integration/spend/test_daily_activity_aggregated_breakdowns.py index 33baf9d0e2e..1c315a6e694 100644 --- a/tests/integration/spend/test_daily_activity_aggregated_breakdowns.py +++ b/tests/integration/spend/test_daily_activity_aggregated_breakdowns.py @@ -243,3 +243,183 @@ async def test_get_daily_activity_aggregated_model_group_rollups_fall_back_to_mo assert object_value(object_value(models["gpt-5"])["metrics"])["spend"] == 10.0 finally: _clean(day) + + +def _seed_guardrail_units(day: str, rows: Sequence[tuple[str, str, str, float | None, int, int]]) -> None: + for guardrail_id, api_key, usage_unit, cost, units, untracked_units in rows: + write_rows( + 'INSERT INTO "LiteLLM_DailyGuardrailUsageUnits" (guardrail_id, date, team_id, api_key, usage_unit,' + " units, cost, untracked_units, updated_at) VALUES (%s, %s, '', %s, %s, %s, %s, %s, now())", + ( + guardrail_id, + day, + api_key, + usage_unit, + str(units), + None if cost is None else str(cost), + str(untracked_units), + ), + ) + + +def _guardrail_spend(breakdown: dict[str, JsonValue]) -> dict[str, tuple[float, dict[str, float]]]: + return { + guardrail_id: ( + float(object_value(object_value(entry)["metrics"])["spend"]), + { + api_key: float(object_value(object_value(key_entry)["metrics"])["spend"]) + for api_key, key_entry in object_value(object_value(entry)["api_key_breakdown"]).items() + }, + ) + for guardrail_id, entry in object_value(breakdown["guardrails"]).items() + } + + +def _day_breakdown(gateway: Gateway, day: str, **params: str) -> dict[str, JsonValue]: + results: Final = _RESULTS.validate_python(_activity(gateway, day, **params)["results"]) + assert len(results) == 1 + return object_value(object_value(results[0])["breakdown"]) + + +@pytest.mark.asyncio +async def test_get_daily_activity_aggregated_breaks_down_guardrail_spend(gateway: Gateway) -> None: + day: Final = _unique_day() + _seed( + day, + [ + (_row_id(), "user-a", day, "key-a", "gpt-5", "", "bedrock", None, "/v1/chat/completions", 10, 1.0, 1, 1), + (_row_id(), "user-b", day, "key-b", "gpt-5", "", "bedrock", None, "/v1/chat/completions", 10, 2.0, 1, 1), + ], + ) + _seed_guardrail_units( + day, + [ + ("pii-filter", "key-a", "contentPolicyUnits", 0.10, 5, 2), + ("pii-filter", "key-a", "sensitiveInformationPolicyUnits", 0.05, 1, 0), + ("pii-filter", "key-b", "contentPolicyUnits", 0.20, 1, 0), + ("pii-filter", "key-b", "legacyUnits", None, 7, 0), + ("topic-filter", "key-a", "topicPolicyUnits", 0.01, 1, 0), + ("topic-filter", "key-b", "topicPolicyUnits", None, 1, 0), + ("pii-filter", "orphan-key", "contentPolicyUnits", 9.0, 1, 0), + ], + ) + try: + everyone: Final = _day_breakdown(gateway, day) + assert _guardrail_spend(everyone) == { + "pii-filter": (pytest.approx(0.35), {"key-a": pytest.approx(0.15), "key-b": pytest.approx(0.20)}), + "topic-filter": (pytest.approx(0.01), {"key-a": pytest.approx(0.01), "key-b": 0.0}), + } + api_keys: Final = object_value(everyone["api_keys"]) + pii_filter: Final = object_value(object_value(everyone["guardrails"])["pii-filter"]) + assert object_value(pii_filter["metrics"]) == {"spend": pytest.approx(0.35), "untracked_units": 9} + pii_api_keys: Final = object_value(pii_filter["api_key_breakdown"]) + assert object_value(object_value(pii_api_keys["key-a"])["metrics"]) == { + "spend": pytest.approx(0.15), + "untracked_units": 2, + } + assert object_value(object_value(pii_api_keys["key-b"])["metrics"]) == { + "spend": pytest.approx(0.20), + "untracked_units": 7, + } + + assert object_value(everyone["guardrails"])["topic-filter"] == { + "metrics": {"spend": pytest.approx(0.01), "untracked_units": 1}, + "metadata": {"guardrail_name": "topic-filter"}, + "api_key_breakdown": { + "key-a": { + "metrics": {"spend": pytest.approx(0.01), "untracked_units": 0}, + "metadata": object_value(api_keys["key-a"])["metadata"], + }, + "key-b": { + "metrics": {"spend": 0.0, "untracked_units": 1}, + "metadata": object_value(api_keys["key-b"])["metadata"], + }, + }, + } + assert object_value(object_value(object_value(everyone["models"])["gpt-5"])["metrics"])["spend"] == 3.0 + + assert _guardrail_spend(_day_breakdown(gateway, day, user_id="user-a")) == { + "pii-filter": (pytest.approx(0.15), {"key-a": pytest.approx(0.15)}), + "topic-filter": (pytest.approx(0.01), {"key-a": pytest.approx(0.01)}), + } + assert _guardrail_spend(_day_breakdown(gateway, day, api_key_limit="1")) == { + "pii-filter": (pytest.approx(0.35), {"key-b": pytest.approx(0.20)}), + "topic-filter": (pytest.approx(0.01), {"key-b": 0.0}), + } + limited_pii_filter: Final = object_value( + object_value(_day_breakdown(gateway, day, api_key_limit="1")["guardrails"])["pii-filter"] + ) + assert object_value(limited_pii_filter["metrics"])["untracked_units"] == 9 + assert set(object_value(limited_pii_filter["api_key_breakdown"])) == {"key-b"} + assert _guardrail_spend(_day_breakdown(gateway, day, model="gpt-5")) == {} + assert _guardrail_spend(_day_breakdown(gateway, day, model="")) == _guardrail_spend(everyone) + finally: + _clean(day) + write_rows('DELETE FROM "LiteLLM_DailyGuardrailUsageUnits" WHERE date = %s', (day,)) + + +def _entity_breakdown(gateway: Gateway, url: str, day: str, **params: str) -> dict[str, JsonValue]: + response: Final = gateway.request("GET", url, params={"start_date": day, "end_date": day, **params}) + assert response.status_code == 200, response.text + results: Final = _RESULTS.validate_python(object_value(response.json())["results"]) + assert len(results) == 1 + return object_value(object_value(results[0])["breakdown"]) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("url", "table", "entity_column", "filter_param"), + [ + ("/team/daily/activity/aggregated", "LiteLLM_DailyTeamSpend", "team_id", "team_ids"), + ( + "/organization/daily/activity/aggregated", + "LiteLLM_DailyOrganizationSpend", + "organization_id", + "organization_ids", + ), + ], +) +async def test_team_and_organization_activity_break_down_guardrail_spend_by_name( + gateway: Gateway, url: str, table: str, entity_column: str, filter_param: str +) -> None: + day: Final = _unique_day() + db_guardrail_id: Final = str(uuid.uuid4()) + db_guardrail_name: Final = f"pii-filter-{db_guardrail_id[:8]}" + for entity_id, api_key, spend in (("entity-a", "key-a", 1.0), ("entity-b", "key-b", 2.0)): + write_rows( + f'INSERT INTO "{table}" (id, {entity_column}, date, api_key, model, spend, api_requests,' + " successful_requests, updated_at) VALUES (%s, %s, %s, %s, 'gpt-5', %s, 1, 1, now())", + (_row_id(), entity_id, day, api_key, str(spend)), + ) + write_rows( + 'INSERT INTO "LiteLLM_GuardrailsTable" (guardrail_id, guardrail_name, litellm_params, updated_at)' + " VALUES (%s, %s, '{}', now())", + (db_guardrail_id, db_guardrail_name), + ) + _seed_guardrail_units( + day, + [ + (db_guardrail_id, "key-a", "contentPolicyUnits", 0.10, 1, 0), + (db_guardrail_id, "key-b", "contentPolicyUnits", 0.20, 1, 0), + ("config-topic-filter", "key-a", "topicPolicyUnits", 0.05, 1, 0), + (db_guardrail_id, "orphan-key", "contentPolicyUnits", 9.0, 1, 0), + ], + ) + try: + everyone: Final = _entity_breakdown(gateway, url, day) + assert _guardrail_spend(everyone) == { + db_guardrail_id: (pytest.approx(0.30), {"key-a": pytest.approx(0.10), "key-b": pytest.approx(0.20)}), + "config-topic-filter": (pytest.approx(0.05), {"key-a": pytest.approx(0.05)}), + } + guardrails: Final = object_value(everyone["guardrails"]) + assert object_value(guardrails[db_guardrail_id])["metadata"] == {"guardrail_name": db_guardrail_name} + assert object_value(guardrails["config-topic-filter"])["metadata"] == {"guardrail_name": "config-topic-filter"} + + assert _guardrail_spend(_entity_breakdown(gateway, url, day, **{filter_param: "entity-a"})) == { + db_guardrail_id: (pytest.approx(0.10), {"key-a": pytest.approx(0.10)}), + "config-topic-filter": (pytest.approx(0.05), {"key-a": pytest.approx(0.05)}), + } + finally: + write_rows(f'DELETE FROM "{table}" WHERE date = %s', (day,)) + write_rows('DELETE FROM "LiteLLM_DailyGuardrailUsageUnits" WHERE date = %s', (day,)) + write_rows('DELETE FROM "LiteLLM_GuardrailsTable" WHERE guardrail_id = %s', (db_guardrail_id,)) diff --git a/tests/unit/proxy/management_endpoints/test_daily_activity_routes.py b/tests/unit/proxy/management_endpoints/test_daily_activity_routes.py index 8fbead8c01c..2a273034a97 100644 --- a/tests/unit/proxy/management_endpoints/test_daily_activity_routes.py +++ b/tests/unit/proxy/management_endpoints/test_daily_activity_routes.py @@ -248,6 +248,7 @@ class _FakeRepository: def __init__(self, rows: tuple[_Activity, ...]) -> None: self._rows: Final = rows self.aggregated = AsyncMock(side_effect=self._aggregated) + self.guardrail_spend = AsyncMock(return_value=()) self.key_page = AsyncMock(side_effect=self._key_page) self.key_page_call: tuple[DailyActivityScope, int, int] | None = None self.search_keys = AsyncMock(side_effect=self._search_keys) diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index 70406105193..72cc8cdc94e 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -27721,6 +27721,10 @@ export interface components { entities?: { [key: string]: components["schemas"]["MetricWithMetadata"]; }; + /** Guardrails */ + guardrails?: { + [key: string]: components["schemas"]["GuardrailMetric"]; + }; /** Mcp Servers */ mcp_servers?: { [key: string]: components["schemas"]["MetricWithMetadata"]; @@ -33236,6 +33240,38 @@ export interface components { /** Updated At */ updated_at?: string | null; }; + /** GuardrailKeyMetric */ + GuardrailKeyMetric: { + metadata: components["schemas"]["KeyMetadata"]; + metrics: components["schemas"]["GuardrailSpendMetrics"]; + }; + /** GuardrailMetadata */ + GuardrailMetadata: { + /** Guardrail Name */ + guardrail_name: string; + }; + /** GuardrailMetric */ + GuardrailMetric: { + /** Api Key Breakdown */ + api_key_breakdown?: { + [key: string]: components["schemas"]["GuardrailKeyMetric"]; + }; + metadata: components["schemas"]["GuardrailMetadata"]; + metrics: components["schemas"]["GuardrailSpendMetrics"]; + }; + /** GuardrailSpendMetrics */ + GuardrailSpendMetrics: { + /** + * Spend + * @default 0 + */ + spend: number; + /** + * Untracked Units + * @default 0 + */ + untracked_units: number; + }; /** GuardrailSubmissionItem */ GuardrailSubmissionItem: { /** Created At */ From cf1006a3687de717f247e846cefedf823f2d8203 Mon Sep 17 00:00:00 2001 From: mrinal-berri Date: Wed, 28 Oct 2026 15:35:33 -0700 Subject: [PATCH 06/10] feat(ui): search and multi-select tools in the MCP toolset editor (#48601) * feat(ui): add per-server MCP tool catalog query hook One query per server keyed by server_id, so the toolset editor can load tools for many servers in parallel and a failing server surfaces as an error on its own row instead of an empty list. (LIT-10012) * feat(ui): add toolset tool search and bulk selection helpers Pure functions for the toolset editor: filter a server's tools by a search query, select/deselect many tools without duplicates or dropping other selections, and compute tri-state selection. (LIT-10012) * feat(ui): search tools and bulk select in the toolset editor The toolset editor search now matches tool names and descriptions as well as server names. Typing fetches every server's tools in parallel through the per-server query hook, auto-expands matching servers and hides servers that loaded with no match. Tool rows become checkboxes, each server header gets a tri-state select-all over its visible tools, and a bar offers select/deselect all matching tools. Bulk actions only touch visible tools, so selections on other servers are kept on save. (LIT-10012) * feat(ui): clear all and flag unconfirmed tools in the toolset panel Adds a Clear all action to the Your Toolset panel and labels selected tools whose server is gone, unreachable, or no longer lists the tool. Those tools stay selected and are still saved, so an outage never silently drops part of a toolset. (LIT-10012) * test(ui): cover toolset editor tool search and bulk selection Integration tests that drive the real toolset modal against stubbed networking and assert the saved tools payload: cross-server search by tool name and description, select/deselect all matching, server select-all, single-row toggles, Clear all, and that tools on unreachable or deleted servers survive a save. (LIT-10012) * fix(ui): pointer cursor on the toolset server select-all checkbox Base UI renders the checkbox as a span, which the global button cursor rule does not cover, so the server header select-all showed the default arrow. Use a pointer, and not-allowed while it is disabled. (LIT-10012) * fix(ui): stop toolset editor background fan-out and keep tools on failed refetch The toolset modal stays mounted when closed, so a finished search kept every server's tool query enabled and refocusing the window refetched all of them once stale. Fetch only while the editor is open, require both the live and debounced search before fanning out, and disable refetch on window focus for these queries. A failed refetch now keeps the tools that already loaded instead of flagging the server unreachable, and tools without a name are dropped. Trim comments that restated the code. (LIT-10012) * fix(ui): clear toolset search on close and only keep non-empty tool lists on failed refetch Reopening the editor after a search rendered once with the old query, which fetched every stale server; clear the search whenever the editor closes. A failed refetch now keeps the previous list only when it has tools, so a server that loaded none and then fails reports the error. (LIT-10012) * fix(ui): reset toolset editor state on close and avoid mutating selection sets Closing the editor now also clears expanded servers, so reopening it cannot refetch them for one render. Build the selection and expanded-server sets without in-place mutation, drop a comment that restated the code, and use screen queries in the new tests to stay within the prefer-screen-queries lint budget. (LIT-10012) --- ui/litellm-dashboard/eslint-suppressions.json | 3 - .../mcpServers/useMCPServerTools.test.ts | 118 ++++ .../hooks/mcpServers/useMCPServerTools.ts | 70 +++ .../MCPToolsetsTab.integration.test.tsx | 219 +++++++- .../_components/MCPToolsetsTab.tsx | 503 ++++++++++++------ .../_components/toolsetSelection.test.ts | 90 ++++ .../_components/toolsetSelection.ts | 63 +++ 7 files changed, 890 insertions(+), 176 deletions(-) create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.test.ts create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.ts create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/toolsetSelection.test.ts create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/toolsetSelection.ts diff --git a/ui/litellm-dashboard/eslint-suppressions.json b/ui/litellm-dashboard/eslint-suppressions.json index e67c1105d86..9fce93782b2 100644 --- a/ui/litellm-dashboard/eslint-suppressions.json +++ b/ui/litellm-dashboard/eslint-suppressions.json @@ -498,9 +498,6 @@ } }, "src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.tsx": { - "no-nested-ternary": { - "count": 1 - }, "react-hooks/set-state-in-effect": { "count": 1 } diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.test.ts new file mode 100644 index 00000000000..3ef8e88b2c9 --- /dev/null +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.test.ts @@ -0,0 +1,118 @@ +/* @vitest-environment jsdom */ +import React from "react"; +import { act, renderHook, waitFor } from "@testing-library/react"; +import { describe, it, expect, vi, beforeEach } from "vitest"; +import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; +import { mcpServerToolKeys, useMCPServerTools } from "./useMCPServerTools"; +import * as networking from "@/components/networking"; + +vi.mock("@/components/networking", () => ({ + listMCPTools: vi.fn(), +})); + +vi.mock("@/app/(dashboard)/hooks/useAuthorized", () => ({ + default: vi.fn(() => ({ accessToken: "test-token-123" })), +})); + +const wrapper = ({ children }: { children: React.ReactNode }) => { + const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false, gcTime: 0 } } }); + return React.createElement(QueryClientProvider, { client: queryClient }, children); +}; + +const toolsFor = (serverId: string) => ({ + tools: [{ name: `${serverId}_tool`, description: `from ${serverId}` }], + error: null, +}); + +describe("useMCPServerTools", () => { + beforeEach(() => { + vi.clearAllMocks(); + }); + + it("fetches only the enabled servers and leaves the rest idle", async () => { + vi.mocked(networking.listMCPTools).mockImplementation(async (_token, serverId) => toolsFor(serverId)); + + const { result } = renderHook(() => useMCPServerTools(["a", "b"], new Set(["a"])), { wrapper }); + + await waitFor(() => expect(result.current.get("a")?.tools).toEqual([{ name: "a_tool", description: "from a" }])); + expect(result.current.get("b")).toEqual({ tools: [], status: "idle" }); + expect(networking.listMCPTools).toHaveBeenCalledTimes(1); + expect(networking.listMCPTools).toHaveBeenCalledWith("test-token-123", "a"); + }); + + it("isolates a failing server from the others", async () => { + vi.mocked(networking.listMCPTools).mockImplementation(async (_token, serverId) => + serverId === "bad" ? { tools: [], error: "http_500", message: "upstream down" } : toolsFor(serverId), + ); + + const { result } = renderHook(() => useMCPServerTools(["good", "bad"], new Set(["good", "bad"])), { wrapper }); + + await waitFor(() => expect(result.current.get("bad")).toEqual({ tools: [], status: "error" })); + expect(result.current.get("good")).toEqual({ + tools: [{ name: "good_tool", description: "from good" }], + status: "success", + }); + }); + + it("reports a server that is being fetched as loading", () => { + vi.mocked(networking.listMCPTools).mockReturnValue(new Promise(() => {})); + + const { result } = renderHook(() => useMCPServerTools(["a"], new Set(["a"])), { wrapper }); + + expect(result.current.get("a")).toEqual({ tools: [], status: "loading" }); + }); + + it("normalizes a bare array response, tools without descriptions, and drops tools without a name", async () => { + vi.mocked(networking.listMCPTools).mockResolvedValue([ + { tool_name: "legacy" }, + "plain", + { description: "nameless" }, + ]); + + const { result } = renderHook(() => useMCPServerTools(["a"], new Set(["a"])), { wrapper }); + + await waitFor(() => + expect(result.current.get("a")?.tools).toEqual([ + { name: "legacy", description: "" }, + { name: "plain", description: "" }, + ]), + ); + }); + + it("reports an error when a refetch fails for a server that had loaded no tools", async () => { + const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false } } }); + const sharedWrapper = ({ children }: { children: React.ReactNode }) => + React.createElement(QueryClientProvider, { client: queryClient }, children); + vi.mocked(networking.listMCPTools) + .mockResolvedValueOnce({ tools: [], error: null }) + .mockResolvedValueOnce({ tools: [], error: "http_502", message: "upstream down" }); + + const { result } = renderHook(() => useMCPServerTools(["a"], new Set(["a"])), { wrapper: sharedWrapper }); + await waitFor(() => expect(result.current.get("a")?.status).toBe("success")); + + await act(() => queryClient.refetchQueries({ queryKey: mcpServerToolKeys.detail("a") })); + + await waitFor(() => expect(result.current.get("a")).toEqual({ tools: [], status: "error" })); + }); + + it("keeps showing the loaded tools when a later refetch fails", async () => { + const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false } } }); + const sharedWrapper = ({ children }: { children: React.ReactNode }) => + React.createElement(QueryClientProvider, { client: queryClient }, children); + vi.mocked(networking.listMCPTools) + .mockResolvedValueOnce(toolsFor("a")) + .mockResolvedValueOnce({ tools: [], error: "http_502", message: "upstream down" }); + + const { result } = renderHook(() => useMCPServerTools(["a"], new Set(["a"])), { wrapper: sharedWrapper }); + await waitFor(() => expect(result.current.get("a")?.status).toBe("success")); + + await act(() => queryClient.refetchQueries({ queryKey: mcpServerToolKeys.detail("a") })); + + await waitFor(() => expect(queryClient.getQueryState(mcpServerToolKeys.detail("a"))?.status).toBe("error")); + expect(networking.listMCPTools).toHaveBeenCalledTimes(2); + expect(result.current.get("a")).toEqual({ + tools: [{ name: "a_tool", description: "from a" }], + status: "success", + }); + }); +}); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.ts new file mode 100644 index 00000000000..bc4a6696a6e --- /dev/null +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerTools.ts @@ -0,0 +1,70 @@ +import { useQueries, type QueryObserverResult } from "@tanstack/react-query"; +import { createQueryKeys } from "../common/queryKeysFactory"; +import { listMCPTools } from "@/components/networking"; +import useAuthorized from "../useAuthorized"; + +export const mcpServerToolKeys = createQueryKeys("mcpServerTools"); + +export interface MCPServerToolEntry { + name: string; + description: string; +} + +export type MCPServerToolsStatus = "idle" | "loading" | "error" | "success"; + +export interface MCPServerToolsState { + tools: MCPServerToolEntry[]; + status: MCPServerToolsStatus; +} + +type RawTool = string | { name?: string; tool_name?: string; description?: string }; + +const toEntry = (tool: RawTool): MCPServerToolEntry => + typeof tool === "string" + ? { name: tool, description: "" } + : { name: tool.name ?? tool.tool_name ?? "", description: tool.description ?? "" }; + +// listMCPTools never throws: it reports failures as `{ tools: [], error }`. +// Throw here so a broken server surfaces as a query error instead of an empty tool list. +export const fetchServerTools = async (accessToken: string, serverId: string): Promise => { + const result = await listMCPTools(accessToken, serverId); + if (!Array.isArray(result) && result?.error) { + throw new Error(result.message || result.error); + } + const toolList: RawTool[] = Array.isArray(result) ? result : result?.tools ?? []; + return toolList.map(toEntry).filter((tool) => tool.name !== ""); +}; + +const toStatus = ({ + status, + fetchStatus, + data, +}: Pick, "status" | "fetchStatus" | "data">): MCPServerToolsStatus => { + if (status === "error" && data !== undefined && data.length > 0) return "success"; + if (status !== "pending") return status; + return fetchStatus === "idle" ? "idle" : "loading"; +}; + +export const useMCPServerTools = ( + serverIds: readonly string[], + enabledServerIds: ReadonlySet, +): ReadonlyMap => { + const { accessToken } = useAuthorized(); + return useQueries({ + queries: serverIds.map((serverId) => ({ + queryKey: mcpServerToolKeys.detail(serverId), + queryFn: () => fetchServerTools(accessToken!, serverId), + enabled: !!accessToken && enabledServerIds.has(serverId), + staleTime: 5 * 60 * 1000, + retry: false, + refetchOnWindowFocus: false, + })), + combine: (results) => + new Map( + results.map((result, idx): [string, MCPServerToolsState] => [ + serverIds[idx], + { tools: result.data ?? [], status: toStatus(result) }, + ]), + ), + }); +}; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.integration.test.tsx index 81462c6bf9b..ba9f2bfa839 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.integration.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.integration.test.tsx @@ -1,5 +1,5 @@ import React from "react"; -import { fireEvent, render, screen, waitFor, within } from "@testing-library/react"; +import { act, fireEvent, render, screen, waitFor, within } from "@testing-library/react"; import userEvent, { PointerEventsCheckLevel } from "@testing-library/user-event"; import { describe, it, expect, vi, beforeEach } from "vitest"; import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; @@ -7,6 +7,7 @@ import { MCPToolsetsTab } from "./MCPToolsetsTab"; import * as networking from "@/components/networking"; import { useMCPToolsets } from "@/app/(dashboard)/hooks/mcpServers/useMCPToolsets"; import { useMCPServers } from "@/app/(dashboard)/hooks/mcpServers/useMCPServers"; +import { mcpServerToolKeys } from "@/app/(dashboard)/hooks/mcpServers/useMCPServerTools"; import { MCPToolset } from "@/components/mcp_tools/types"; vi.mock("@/components/networking", () => ({ @@ -20,6 +21,7 @@ vi.mock("@/components/networking", () => ({ vi.mock("@/app/(dashboard)/hooks/mcpServers/useMCPToolsets", () => ({ useMCPToolsets: vi.fn() })); vi.mock("@/app/(dashboard)/hooks/mcpServers/useMCPServers", () => ({ useMCPServers: vi.fn() })); +vi.mock("@/app/(dashboard)/hooks/useAuthorized", () => ({ default: () => ({ accessToken: "sk-test" }) })); const setup = () => userEvent.setup({ pointerEventsCheck: PointerEventsCheckLevel.Never }); @@ -197,6 +199,221 @@ describe("MCPToolsetsTab create/edit toolset form", () => { }); }); +describe("MCPToolsetsTab tool search and bulk selection", () => { + const servers = [ + { server_id: "gh", alias: "github", server_name: "GitHub" }, + { server_id: "lin", alias: "linear", server_name: "Linear" }, + { server_id: "broken", alias: "flaky", server_name: "Flaky" }, + ]; + const catalogs: Record = { + gh: [ + { name: "create_issue", description: "Open a GitHub issue" }, + { name: "list_pulls", description: "List pull requests" }, + ], + lin: [ + { name: "create_ticket", description: "Create a Linear issue" }, + { name: "list_projects", description: "List projects" }, + ], + }; + + const renderWithServers = (toolsets: MCPToolset[] = []) => { + vi.mocked(useMCPToolsets).mockReturnValue({ + data: toolsets, + isLoading: false, + } as unknown as ReturnType); + vi.mocked(useMCPServers).mockReturnValue({ data: servers, isSuccess: true } as unknown as ReturnType< + typeof useMCPServers + >); + const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false, gcTime: 0 } } }); + render( + + + , + ); + return queryClient; + }; + + const editToolset = (tools: MCPToolset["tools"]) => + ({ toolset_id: "ts-1", toolset_name: "triage", description: "", tools }) as MCPToolset; + + const expectedUpdate = (tools: MCPToolset["tools"]) => ({ + toolset_id: "ts-1", + toolset_name: "triage", + description: "", + tools, + }); + + beforeEach(() => { + vi.clearAllMocks(); + vi.mocked(networking.listMCPTools).mockImplementation(async (_token, serverId) => + serverId in catalogs + ? { tools: catalogs[serverId], error: null } + : { tools: [], error: "http_502", message: "upstream down" }, + ); + vi.mocked(networking.createMCPToolset).mockResolvedValue( + {} as Awaited>, + ); + vi.mocked(networking.updateMCPToolset).mockResolvedValue( + {} as Awaited>, + ); + }); + + it("searches tool names and descriptions across collapsed servers and selects every match", async () => { + const user = setup(); + renderWithServers(); + + await openCreate(user); + fireEvent.change(screen.getByPlaceholderText("e.g. github-linear-tools"), { target: { value: "issues" } }); + await user.type(screen.getByRole("textbox", { name: "Search tools or servers" }), "issue"); + + expect(await screen.findByRole("checkbox", { name: /^create_ticket/ })).toBeInTheDocument(); + expect(screen.getByRole("checkbox", { name: /^create_issue/ })).toBeInTheDocument(); + expect(screen.queryByRole("checkbox", { name: /^list_pulls/ })).not.toBeInTheDocument(); + expect(await screen.findByText("2 matching tools")).toBeInTheDocument(); + + await user.click(screen.getByRole("button", { name: "Select all matching" })); + await user.click(screen.getByRole("button", { name: "Create Toolset" })); + + await waitFor(() => { + expect(networking.createMCPToolset).toHaveBeenCalledWith("sk-test", { + toolset_name: "issues", + description: "", + tools: [ + { server_id: "gh", tool_name: "create_issue" }, + { server_id: "lin", tool_name: "create_ticket" }, + ], + }); + }); + }); + + it("deselecting all matches keeps selected tools the search hides", async () => { + const user = setup(); + renderWithServers([ + editToolset([ + { server_id: "gh", tool_name: "list_pulls" }, + { server_id: "gh", tool_name: "create_issue" }, + { server_id: "lin", tool_name: "create_ticket" }, + ]), + ]); + + await openEditFor(user); + await user.type(screen.getByRole("textbox", { name: "Search tools or servers" }), "create"); + expect(await screen.findByRole("checkbox", { name: /^create_ticket/ })).toBeChecked(); + + await user.click(screen.getByRole("button", { name: "Deselect all matching" })); + await user.click(screen.getByRole("button", { name: "Save Changes" })); + + await waitFor(() => { + expect(networking.updateMCPToolset).toHaveBeenCalledWith( + "sk-test", + expectedUpdate([{ server_id: "gh", tool_name: "list_pulls" }]), + ); + }); + }); + + it("selects all of one server's tools from its header and toggles single rows, fetching only that server", async () => { + const user = setup(); + renderWithServers(); + + await openCreate(user); + fireEvent.change(screen.getByPlaceholderText("e.g. github-linear-tools"), { target: { value: "gh-only" } }); + await user.click(screen.getByRole("button", { name: /^github/ })); + expect(await screen.findByRole("checkbox", { name: /^list_pulls/ })).toBeInTheDocument(); + + await user.click(screen.getByRole("checkbox", { name: "Select all tools on github" })); + expect(screen.getByRole("checkbox", { name: /^list_pulls/ })).toBeChecked(); + // Clicking anywhere on a tool row toggles it exactly once. + await user.click(screen.getByText("List pull requests")); + expect(screen.getByRole("checkbox", { name: /^list_pulls/ })).not.toBeChecked(); + await user.click(screen.getByRole("button", { name: "Create Toolset" })); + + await waitFor(() => { + expect(networking.createMCPToolset).toHaveBeenCalledWith("sk-test", { + toolset_name: "gh-only", + description: "", + tools: [{ server_id: "gh", tool_name: "create_issue" }], + }); + }); + expect(networking.listMCPTools).toHaveBeenCalledTimes(1); + }); + + it("keeps and flags tools whose server is unreachable or gone when saving", async () => { + const user = setup(); + const tools = [ + { server_id: "broken", tool_name: "flaky_tool" }, + { server_id: "deleted", tool_name: "old_tool" }, + { server_id: "gh", tool_name: "create_issue" }, + ]; + renderWithServers([editToolset(tools)]); + + await openEditFor(user); + await user.type(screen.getByRole("textbox", { name: "Search tools or servers" }), "create"); + + expect(await screen.findByText("Couldn't load tools for this server.")).toBeInTheDocument(); + expect(await screen.findByText("server unreachable")).toBeInTheDocument(); + expect(screen.getByText("server not found")).toBeInTheDocument(); + + await user.click(screen.getByRole("button", { name: "Save Changes" })); + + await waitFor(() => { + expect(networking.updateMCPToolset).toHaveBeenCalledWith("sk-test", expectedUpdate(tools)); + }); + }); + + it("stops fetching server tools once the editor is closed after a search", async () => { + const user = setup(); + const queryClient = renderWithServers(); + + await openCreate(user); + await user.type(screen.getByRole("textbox", { name: "Search tools or servers" }), "issue"); + expect(await screen.findByRole("checkbox", { name: /^create_ticket/ })).toBeInTheDocument(); + await user.click(screen.getByRole("button", { name: "Cancel" })); + await waitFor(() => expect(screen.queryByRole("dialog")).not.toBeInTheDocument()); + const callsWhileOpen = vi.mocked(networking.listMCPTools).mock.calls.length; + + await act(() => queryClient.invalidateQueries({ queryKey: mcpServerToolKeys.all })); + await new Promise((resolve) => setTimeout(resolve, 50)); + expect(networking.listMCPTools).toHaveBeenCalledTimes(callsWhileOpen); + + await openCreate(user); + expect(screen.getByRole("textbox", { name: "Search tools or servers" })).toHaveValue(""); + await new Promise((resolve) => setTimeout(resolve, 50)); + expect(networking.listMCPTools).toHaveBeenCalledTimes(callsWhileOpen); + }); + + it("does not refetch a previously expanded server when the editor is reopened", async () => { + const user = setup(); + const queryClient = renderWithServers(); + + await openCreate(user); + await user.click(screen.getByRole("button", { name: /^github/ })); + expect(await screen.findByRole("checkbox", { name: /^list_pulls/ })).toBeInTheDocument(); + await user.click(screen.getByRole("button", { name: "Cancel" })); + await waitFor(() => expect(screen.queryByRole("dialog")).not.toBeInTheDocument()); + await act(() => queryClient.invalidateQueries({ queryKey: mcpServerToolKeys.all })); + + await openCreate(user); + await new Promise((resolve) => setTimeout(resolve, 50)); + + expect(networking.listMCPTools).toHaveBeenCalledTimes(1); + expect(screen.queryByRole("checkbox", { name: /^list_pulls/ })).not.toBeInTheDocument(); + }); + + it("clears the whole toolset with Clear all", async () => { + const user = setup(); + renderWithServers([editToolset([{ server_id: "gh", tool_name: "create_issue" }])]); + + await openEditFor(user); + await user.click(screen.getByRole("button", { name: "Clear all" })); + expect(screen.getByText("No tools added yet")).toBeInTheDocument(); + await user.click(screen.getByRole("button", { name: "Save Changes" })); + + await waitFor(() => { + expect(networking.updateMCPToolset).toHaveBeenCalledWith("sk-test", expectedUpdate([])); + }); + }); +}); + describe("MCPToolsetsTab usage guide", () => { it("shows the toolset URL on the gateway host", () => { renderTab(); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.tsx b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.tsx index ff0e8f7b6a9..dc1477b79d3 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/MCPToolsetsTab.tsx @@ -1,28 +1,39 @@ -import React, { useState, useCallback } from "react"; +import React, { useState } from "react"; import { z } from "zod"; import { SortingState } from "@tanstack/react-table"; import { Inbox, Plus, X } from "lucide-react"; import { useMCPToolsets } from "@/app/(dashboard)/hooks/mcpServers/useMCPToolsets"; import { useMCPServers } from "@/app/(dashboard)/hooks/mcpServers/useMCPServers"; import { useQueryClient } from "@tanstack/react-query"; -import { DataTable } from "@/components/shared/DataTable"; +import { useDebouncedValue } from "@tanstack/react-pacer/debouncer"; import { - createMCPToolset, - updateMCPToolset, - deleteMCPToolset, - listMCPTools, - getGatewayBaseUrl, -} from "@/components/networking"; -import { MCPToolset, MCPToolsetTool } from "@/components/mcp_tools/types"; + useMCPServerTools, + type MCPServerToolEntry, + type MCPServerToolsState, +} from "@/app/(dashboard)/hooks/mcpServers/useMCPServerTools"; +import { DataTable } from "@/components/shared/DataTable"; +import { createMCPToolset, updateMCPToolset, deleteMCPToolset, getGatewayBaseUrl } from "@/components/networking"; +import { MCPServer, MCPToolset, MCPToolsetTool } from "@/components/mcp_tools/types"; import { FieldGroup } from "@/components/ui/field"; import { FormField } from "@/components/shared/form/FormField"; import { Button } from "@/components/ui/button"; +import { Checkbox } from "@/components/ui/checkbox"; import { Input } from "@/components/ui/input"; import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group"; import { UiLoadingSpinner } from "@/components/ui/ui-loading-spinner"; import { useZodForm } from "@/lib/forms/useZodForm"; import { toast } from "@/lib/toast"; import { displayToolName, getMCPToolsetTableColumns } from "./MCPToolsetTableColumns"; +import { + deselectTools, + filterServerTools, + isToolSelected, + matchesServerName, + selectTools, + selectionState, + toggleTool, + type SelectionState, +} from "./toolsetSelection"; import { Dialog, DialogContent, DialogFooter, DialogHeader, DialogTitle } from "@/components/ui/dialog"; interface MCPToolsetsTabProps { @@ -37,110 +48,191 @@ const toolsetSchema = z.object({ type ToolsetFormValues = z.infer; -interface MCPToolListProps { +const SEARCH_DEBOUNCE_WAIT_MS = 300; + +const IDLE_SERVER_TOOLS: MCPServerToolsState = { tools: [], status: "idle" }; + +const NO_SERVERS: ReadonlySet = new Set(); + +// The modal stays mounted while closed, so fetch only while it is open; otherwise a finished +// search keeps every server's query live and refetches all of them in the background. +const serversToFetch = ( + open: boolean, + searching: boolean, + serverIds: readonly string[], + expandedServerIds: ReadonlySet, +): ReadonlySet => { + if (!open) return NO_SERVERS; + return searching ? new Set(serverIds) : expandedServerIds; +}; + +const checkboxStateProps = (state: SelectionState) => ({ + checked: state === "all", + indeterminate: state === "some", +}); + +interface ServerView { + server: MCPServer; + serverName: string; + state: MCPServerToolsState; + visibleTools: readonly MCPServerToolEntry[]; +} + +const isPending = (state: MCPServerToolsState) => state.status === "idle" || state.status === "loading"; + +// While searching, a server stays listed until its tools load and turn out not to match. +const isHiddenBySearch = ( + search: string, + serverNames: readonly string[], + state: MCPServerToolsState, + visibleTools: readonly MCPServerToolEntry[], +) => { + if (!search.trim() || state.status !== "success") return false; + return visibleTools.length === 0 && !matchesServerName(search, serverNames); +}; + +const buildServerViews = ( + servers: readonly MCPServer[], + toolsByServer: ReadonlyMap, + search: string, +): ServerView[] => + servers.flatMap((server) => { + const state = toolsByServer.get(server.server_id) ?? IDLE_SERVER_TOOLS; + const names = [server.alias ?? "", server.server_name ?? ""]; + const visibleTools = filterServerTools(search, names, state.tools); + if (isHiddenBySearch(search, names, state, visibleTools)) return []; + return [{ server, serverName: server.alias || server.server_name || server.server_id, state, visibleTools }]; + }); + +const summarizeSearch = (serverViews: readonly ServerView[]) => ({ + matchingTools: serverViews.flatMap(({ server, visibleTools }) => + visibleTools.map((tool) => ({ server_id: server.server_id, tool_name: tool.name })), + ), + pendingServerCount: serverViews.filter(({ state }) => isPending(state)).length, +}); + +// Why a selected tool cannot be confirmed against its server. The tool stays selected and is +// still saved; the note only keeps it from looking lost. +const selectedToolIssue = ( + tool: MCPToolsetTool, + serverNameById: ReadonlyMap, + toolsByServer: ReadonlyMap, +): string | undefined => { + if (!serverNameById.has(tool.server_id)) return "server not found"; + const state = toolsByServer.get(tool.server_id); + if (state?.status === "error") return "server unreachable"; + if (state?.status === "success" && !state.tools.some((t) => t.name === tool.tool_name)) return "tool not found"; + return undefined; +}; + +interface ServerToolGroupProps { serverId: string; serverName: string; - accessToken: string | null; + state: MCPServerToolsState; + visibleTools: readonly MCPServerToolEntry[]; + expanded: boolean; + searchActive: boolean; selectedTools: MCPToolsetTool[]; - onToggle: (tool: MCPToolsetTool) => void; + onToggleExpanded: () => void; + onToggleTool: (tool: MCPToolsetTool) => void; + onSetToolsSelected: (tools: MCPToolsetTool[], selected: boolean) => void; } -interface ToolEntry { - name: string; - description?: string; -} +function ServerToolGroup({ + serverId, + serverName, + state, + visibleTools, + expanded, + searchActive, + selectedTools, + onToggleExpanded, + onToggleTool, + onSetToolsSelected, +}: ServerToolGroupProps) { + const selectedCount = selectedTools.filter((t) => t.server_id === serverId).length; + const visibleRefs = visibleTools.map((tool) => ({ server_id: serverId, tool_name: tool.name })); + const groupState = selectionState(selectedTools, visibleRefs); -function MCPToolList({ serverId, serverName, accessToken, selectedTools, onToggle }: MCPToolListProps) { - const [tools, setTools] = useState([]); - const [loading, setLoading] = useState(false); - const [expanded, setExpanded] = useState(false); - - const selectedSet = new Set(selectedTools.filter((t) => t.server_id === serverId).map((t) => t.tool_name)); - - const fetchTools = useCallback(async () => { - if (!accessToken || tools.length > 0) return; - setLoading(true); - try { - const result = await listMCPTools(accessToken, serverId); - const toolList = Array.isArray(result) ? result : result?.tools ?? []; - setTools(toolList.map((t: any) => ({ name: t.name ?? t.tool_name ?? t, description: t.description ?? "" }))); - } catch { - setTools([]); - } finally { - setLoading(false); + const renderBody = () => { + if (isPending(state)) { + return ( +
+ +
+ ); } - }, [accessToken, serverId, tools.length]); - - const handleToggle = () => { - if (!expanded) fetchTools(); - setExpanded(!expanded); + if (state.status === "error") { + return

Couldn't load tools for this server.

; + } + if (visibleTools.length === 0) { + return ( +

+ {searchActive ? "No matching tools on this server." : "No tools found for this server."} +

+ ); + } + return ( +
+ {visibleRefs.map((ref, idx) => { + const tool = visibleTools[idx]; + const selected = isToolSelected(selectedTools, ref); + return ( + + ); + })} +
+ ); }; return (
- - {expanded && ( -
- {loading ? ( -
- -
- ) : tools.length === 0 ? ( -

No tools found for this server.

- ) : ( -
- {tools.map((tool) => { - const selected = selectedSet.has(tool.name); - return ( - - ); - })} -
- )} -
- )} +
+ onSetToolsSelected(visibleRefs, checked)} + /> + +
+ {expanded &&
{renderBody()}
}
); } @@ -149,21 +241,29 @@ interface CreateToolsetModalProps { open: boolean; onClose: () => void; onSave: (name: string, description: string | undefined, tools: MCPToolsetTool[]) => Promise; - accessToken: string | null; initialToolset?: MCPToolset; } -function CreateToolsetModal({ open, onClose, onSave, accessToken, initialToolset }: CreateToolsetModalProps) { - const form = useZodForm(toolsetSchema, { - defaultValues: { - toolset_name: initialToolset?.toolset_name || "", - description: initialToolset?.description || "", - }, - }); +const toolsetFormDefaults = (toolset?: MCPToolset): ToolsetFormValues => ({ + toolset_name: toolset?.toolset_name || "", + description: toolset?.description || "", +}); + +function CreateToolsetModal({ open, onClose, onSave, initialToolset }: CreateToolsetModalProps) { + const form = useZodForm(toolsetSchema, { defaultValues: toolsetFormDefaults(initialToolset) }); const [selectedTools, setSelectedTools] = useState(initialToolset?.tools || []); const [saving, setSaving] = useState(false); - const [serverSearch, setServerSearch] = useState(""); - const { data: mcpServers = [] } = useMCPServers(); + const [search, setSearch] = useState(""); + const [debouncedSearch] = useDebouncedValue(search, { wait: SEARCH_DEBOUNCE_WAIT_MS }); + const [expandedServerIds, setExpandedServerIds] = useState>(() => new Set()); + const { data: mcpServers = [], isSuccess: serversLoaded } = useMCPServers(); + const serverIds = React.useMemo(() => mcpServers.map((s) => s.server_id), [mcpServers]); + const searching = search.trim() !== "" && debouncedSearch.trim() !== ""; + const fetchServerIds = React.useMemo( + () => serversToFetch(open, searching, serverIds, expandedServerIds), + [open, searching, serverIds, expandedServerIds], + ); + const toolsByServer = useMCPServerTools(serverIds, fetchServerIds); const serverPrefixById = React.useMemo( () => new Map(mcpServers.map((s) => [s.server_id, s.alias || s.server_name || s.server_id])), [mcpServers], @@ -171,41 +271,54 @@ function CreateToolsetModal({ open, onClose, onSave, accessToken, initialToolset React.useEffect(() => { if (open) { - form.reset({ - toolset_name: initialToolset?.toolset_name || "", - description: initialToolset?.description || "", - }); + form.reset(toolsetFormDefaults(initialToolset)); setSelectedTools(initialToolset?.tools || []); - setServerSearch(""); + setSearch(""); + setExpandedServerIds(new Set()); } }, [open, initialToolset, form]); const handleToggleTool = (tool: MCPToolsetTool) => { - setSelectedTools((prev) => { - const exists = prev.some((t) => t.server_id === tool.server_id && t.tool_name === tool.tool_name); - return exists - ? prev.filter((t) => !(t.server_id === tool.server_id && t.tool_name === tool.tool_name)) - : [...prev, tool]; - }); + setSelectedTools((prev) => toggleTool(prev, tool)); + }; + + const handleSetToolsSelected = (tools: MCPToolsetTool[], selected: boolean) => { + setSelectedTools((prev) => (selected ? selectTools(prev, tools) : deselectTools(prev, tools))); + }; + + const handleToggleExpanded = (serverId: string) => { + setExpandedServerIds((prev) => + prev.has(serverId) ? new Set([...prev].filter((id) => id !== serverId)) : new Set([...prev, serverId]), + ); + }; + + // The create modal stays mounted, so state left from the last session would fetch servers + // on the first render after reopening, before the open effect resets it. + const handleClose = () => { + setSearch(""); + setExpandedServerIds(new Set()); + onClose(); }; const handleSubmit = async (values: ToolsetFormValues) => { setSaving(true); try { await onSave(values.toolset_name, values.description, selectedTools); - onClose(); + handleClose(); } finally { setSaving(false); } }; - const filteredServers = mcpServers.filter((s) => { - const q = serverSearch.toLowerCase(); - return !q || (s.alias || "").toLowerCase().includes(q) || (s.server_name || "").toLowerCase().includes(q); - }); + const searchActive = search.trim() !== ""; + const serverViews = buildServerViews(mcpServers, toolsByServer, search); + const { matchingTools, pendingServerCount } = searchActive + ? summarizeSearch(serverViews) + : { matchingTools: [], pendingServerCount: 0 }; + const matchingState = selectionState(selectedTools, matchingTools); return ( - !open && onClose()}> + !open && handleClose()}> {initialToolset ? "Edit Toolset" : "New Toolset"} @@ -229,32 +342,65 @@ function CreateToolsetModal({ open, onClose, onSave, accessToken, initialToolset setServerSearch(e.target.value)} + placeholder="Search tools or servers..." + aria-label="Search tools or servers" + value={search} + onChange={(e) => setSearch(e.target.value)} /> - {serverSearch && ( + {search && ( - setServerSearch("")}> + setSearch("")}> )} + {searchActive && ( +
+

+ {matchingTools.length} matching {matchingTools.length === 1 ? "tool" : "tools"} + {pendingServerCount > 0 && + ` · loading ${pendingServerCount} ${pendingServerCount === 1 ? "server" : "servers"}…`} +

+
+ + +
+
+ )}
- {filteredServers.length === 0 ? ( + {serverViews.length === 0 ? (

- {mcpServers.length === 0 ? "No MCP servers configured" : "No servers match your search"} + {mcpServers.length === 0 ? "No MCP servers configured" : "No tools or servers match your search"}

) : ( - filteredServers.map((server) => ( - ( + handleToggleExpanded(server.server_id)} + onToggleTool={handleToggleTool} + onSetToolsSelected={handleSetToolsSelected} /> )) )} @@ -266,41 +412,60 @@ function CreateToolsetModal({ open, onClose, onSave, accessToken, initialToolset {/* Right panel: Your Toolset */}
-

- Your Toolset{" "} - ({selectedTools.length} tools) -

+
+

+ Your Toolset{" "} + ({selectedTools.length} tools) +

+ +
{selectedTools.length === 0 ? (

No tools added yet

) : ( - selectedTools.map((tool, idx) => ( -
- - ✕ - - - )) + + ); + }) )}
-
diff --git a/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx b/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx index 9f320049b09..ecb8dd161f3 100644 --- a/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx @@ -63,6 +63,24 @@ describe("SearchSelect", () => { expect(onValueChange).toHaveBeenLastCalledWith("team-3"); }); + it("offers the typed text as a value only when the caller accepts it", async () => { + const user = userEvent.setup(); + const onValueChange = vi.fn(); + const customValue = { hint: "Custom value", accepts: (typed: string) => typed.endsWith("*") }; + const { rerender } = render(); + const input = screen.getByRole("combobox"); + await user.click(input); + fireEvent.change(input, { target: { value: "team-*" } }); + expect(screen.queryByRole("option", { name: /team-\*/ })).not.toBeInTheDocument(); + + rerender(); + fireEvent.change(input, { target: { value: "team-4" } }); + expect(screen.queryByRole("option", { name: /team-4/ })).not.toBeInTheDocument(); + fireEvent.change(input, { target: { value: "team-*" } }); + await user.click(await screen.findByRole("option", { name: /team-\*/ })); + expect(onValueChange).toHaveBeenLastCalledWith("team-*"); + }); + it("filters the options client-side as you type", async () => { const user = userEvent.setup(); render(); diff --git a/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx b/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx index 3649114826d..e139720a2ed 100644 --- a/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx +++ b/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx @@ -1,6 +1,6 @@ "use client"; -import React from "react"; +import React, { useState } from "react"; import { Combobox, ComboboxContent, @@ -19,6 +19,11 @@ export interface SearchSelectOption { icon?: React.ReactNode; } +interface CustomValue { + hint: string; + accepts: (typed: string) => boolean; +} + interface SearchSelectProps { options: SearchSelectOption[]; value?: string | null; @@ -29,6 +34,8 @@ interface SearchSelectProps { className?: string; inputId?: string; allowClear?: boolean; + customValue?: CustomValue; + reservedValues?: readonly string[]; "aria-label"?: string; id?: string; } @@ -49,13 +56,22 @@ export function SearchSelect({ className, inputId, allowClear = true, + customValue, + reservedValues = [], "aria-label": ariaLabel, id, }: SearchSelectProps) { + const [query, setQuery] = useState(""); const selected = value == null || value === "" ? null : options.find((option) => option.value === value) ?? { label: value, value }; - const items = + const known = selected !== null && !options.some((option) => option.value === selected.value) ? [selected, ...options] : options; + const typed = query.trim(); + const isNewValue = typed !== "" && !reservedValues.includes(typed) && !known.some((option) => option.value === typed); + const items = + customValue !== undefined && isNewValue && customValue.accepts(typed) + ? [...known, { label: typed, value: typed, sublabel: customValue.hint }] + : known; return ( a.value === b.value} itemToStringLabel={(item: SearchSelectOption) => item.label} filter={matchesQuery} + onInputValueChange={setQuery} disabled={disabled} > x. - * - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) + * - model_max_budget: Optional[dict] - Model-specific max budget for user, keyed by model name, `*` pattern, or model access group. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) * - mcp_rpm_limit: Optional[dict] - Per-MCP-server rpm limit, keyed by MCP server name {"github": 100, "slack": 200}. Enforced for keys and teams only; values set on a user are stored but not enforced per user. @@ -18917,7 +18917,7 @@ export interface paths { * - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. * - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } * - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - * - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) + * - model_max_budget: Optional[dict] - Model-specific max budget for user, keyed by model name, `*` pattern, or model access group. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) * - mcp_rpm_limit: Optional[dict] - Per-MCP-server rpm limit, keyed by MCP server name {"github": 100, "slack": 200}. Enforced for keys and teams only; values set on a user are stored but not enforced per user. From 41c4c3788e0e39c972f6bf4ed71451e61cbb24f8 Mon Sep 17 00:00:00 2001 From: tessellark <349031000+tessellark@users.noreply.github.com> Date: Wed, 28 Oct 2026 15:42:51 -0700 Subject: [PATCH 09/10] test(routing): audit #46601 (#48910) * test(routing): audit #46601 Adds integration cells for the falsy budget 400, the empty and none-only declarations under drop_params, Vertex AI Claude, Databricks Claude, and the Bedrock native output retry * test(routing): expect the Anthropic default max_tokens on Bedrock Invoke chat Reads the default from litellm instead of pinning 4096, which #48502 raised to 128000 * test(routing): assert whole sent bodies in the Vertex AI and Bedrock native output cells --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../_reasoning_effort_levels_support.py | 5 + .../test_reasoning_effort_levels_wire.py | 320 +++++++++++++++++- 2 files changed, 316 insertions(+), 9 deletions(-) diff --git a/tests/integration/routing/_reasoning_effort_levels_support.py b/tests/integration/routing/_reasoning_effort_levels_support.py index 8d43695e419..d295f6e6d56 100644 --- a/tests/integration/routing/_reasoning_effort_levels_support.py +++ b/tests/integration/routing/_reasoning_effort_levels_support.py @@ -32,6 +32,7 @@ GEMINI: Final = "gemini-3-pro-preview" ZAI_GLM: Final = "glm-5" ECHOED_KEY_MODEL: Final = f"{KIMI}-echoed-key" BEDROCK_CLAUDE: Final = f"us.anthropic.{CLAUDE}" +DATABRICKS_CLAUDE: Final = f"databricks-{CLAUDE}" AZURE_API_VERSION: Final = "2025-04-01-preview" SYNTHETIC_KEY: Final = "synthetic-provider-key" _MARKER: Final = re.compile(r"marker-([0-9a-f]{32})") @@ -215,6 +216,10 @@ def backend(kind: str, wire_url: str) -> Backend: f"bedrock/invoke/{BEDROCK_CLAUDE}", MappingProxyType({"api_base": wire_url, "api_key": SYNTHETIC_KEY, "aws_region_name": "us-east-1"}), ) + case "databricks_claude": + return Backend( + f"databricks/{DATABRICKS_CLAUDE}", MappingProxyType({"api_base": wire_url, "api_key": SYNTHETIC_KEY}) + ) case _: raise AssertionError(f"unknown backend kind {kind}") diff --git a/tests/integration/routing/test_reasoning_effort_levels_wire.py b/tests/integration/routing/test_reasoning_effort_levels_wire.py index 3d88aad547c..d15867ac572 100644 --- a/tests/integration/routing/test_reasoning_effort_levels_wire.py +++ b/tests/integration/routing/test_reasoning_effort_levels_wire.py @@ -1,4 +1,5 @@ import asyncio +import json from collections.abc import Callable, Mapping from dataclasses import dataclass from types import MappingProxyType @@ -8,9 +9,11 @@ import anthropic import httpx import openai import pytest +from integration._support.anthropic_sse import message_json from integration._support.client import Gateway, eventually, list_value, object_value, string_value from integration._support.openai_wire import openai_error -from integration._support.wire import Request, wire_server +from integration._support.vertex import service_account_json +from integration._support.wire import Reply, Request, wire_server from integration.routing._reasoning_effort_levels_support import ( AZURE_API_VERSION, CLAUDE, @@ -34,6 +37,7 @@ from integration.routing._reasoning_effort_levels_support import ( marker_of, messages_request, new_marker, + path_of, prompt, provider_reply, responses_request, @@ -41,6 +45,8 @@ from integration.routing._reasoning_effort_levels_support import ( ) from pydantic import JsonValue +from litellm.constants import DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS + CHAT: Final = "/v1/chat/completions" MESSAGES: Final = "/v1/messages" RESPONSES: Final = "/v1/responses" @@ -49,6 +55,7 @@ _ADAPTIVE: Final[dict[str, JsonValue]] = {"type": "adaptive"} _STRING_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": "2048"} _XHIGH_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": 9000} _BOOL_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": True} +_FALSE_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": False} _NULL_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": None} _LIST_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": [2048]} _EMPTY_BUDGET: Final[dict[str, JsonValue]] = {"type": "enabled", "budget_tokens": ""} @@ -67,6 +74,8 @@ _KIMI_INFO: Final[Mapping[str, JsonValue]] = MappingProxyType({"reasoning_effort _CLAUDE_INFO: Final[Mapping[str, JsonValue]] = MappingProxyType({"reasoning_effort_levels": list(CLAUDE_LEVELS)}) _GPT_INFO: Final[Mapping[str, JsonValue]] = MappingProxyType({"reasoning_effort_levels": list(GPT_LEVELS)}) _UNDECLARED: Final[Mapping[str, JsonValue]] = MappingProxyType({}) +_EMPTY_DECLARATION: Final[Mapping[str, JsonValue]] = MappingProxyType({"reasoning_effort_levels": []}) +_NONE_ONLY_DECLARATION: Final[Mapping[str, JsonValue]] = MappingProxyType({"reasoning_effort_levels": ["none"]}) _ECHOED_MAP_KEY: Final[Mapping[str, JsonValue]] = MappingProxyType( {"key": "azure/chat-latest", "litellm_provider": "azure"} ) @@ -134,7 +143,7 @@ def _invoke_chat(effort: str, thinking: Mapping[str, JsonValue], betas: tuple[st "messages": [{"role": "user", "content": [{"type": "text", "text": prompt(marker)}]}], "thinking": dict(thinking), "output_config": {"effort": effort}, - "max_tokens": 4096, + "max_tokens": DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS, "anthropic_version": "bedrock-2023-05-31", "anthropic_beta": list(betas), } @@ -144,6 +153,14 @@ def _with_output_config(expected: Expected, output_config: JsonValue) -> Expecte return lambda marker: {**expected(marker), "output_config": output_config} +def _with_fields(expected: Expected, fields: Mapping[str, JsonValue]) -> Expected: + return lambda marker: {**expected(marker), **fields} + + +def _without(expected: Expected, field: str) -> Expected: + return lambda marker: {key: value for key, value in expected(marker).items() if key != field} + + def _converse_chat(effort: str, thinking: Mapping[str, JsonValue]) -> Expected: return lambda marker: { "messages": [{"role": "user", "content": [{"text": prompt(marker)}]}], @@ -320,6 +337,7 @@ _OPENAI_RESPONSES: Final = "/v1/responses" _AZURE_RESPONSES: Final = f"/openai/responses?api-version={AZURE_API_VERSION}" _UNSUPPORTED: Final = "does not support parameters" _GEMINI: Final = f"/models/{GEMINI}:generateContent" +_DATABRICKS: Final = "/chat/completions" CELLS: Final[Mapping[str, Cell]] = MappingProxyType( { @@ -1750,6 +1768,139 @@ CELLS: Final[Mapping[str, Cell]] = MappingProxyType( _anthropic_chat_without_effort(_ADAPTIVE), _ANTHROPIC, ), + "chat-anthropic-false-budget-400": Cell( + CHAT, "anthropic", _CLAUDE_INFO, {"thinking": _FALSE_BUDGET}, None, _ANTHROPIC, 400, _NON_NUMERIC_BUDGET + ), + "chat-anthropic-undeclared-null-budget-400": Cell( + CHAT, "anthropic", _UNDECLARED, {"thinking": _NULL_BUDGET}, None, _ANTHROPIC, 400, _NON_NUMERIC_BUDGET + ), + "chat-anthropic-undeclared-false-budget-drop-params-sends-adaptive-without-effort": Cell( + CHAT, + "anthropic", + _UNDECLARED, + {"thinking": _FALSE_BUDGET, "drop_params": True}, + _anthropic_chat_without_effort(_ADAPTIVE), + _ANTHROPIC, + ), + "chat-anthropic-undeclared-missing-budget-sends-low": Cell( + CHAT, + "anthropic", + _UNDECLARED, + {"thinking": _MISSING_BUDGET}, + _anthropic_chat("low", _ADAPTIVE), + _ANTHROPIC, + ), + "messages-anthropic-undeclared-false-budget-400": Cell( + MESSAGES, "anthropic", _UNDECLARED, {"thinking": _FALSE_BUDGET}, None, _ANTHROPIC, 400, _NON_NUMERIC_BUDGET + ), + "messages-anthropic-empty-string-budget-400": Cell( + MESSAGES, "anthropic", _CLAUDE_INFO, {"thinking": _EMPTY_BUDGET}, None, _ANTHROPIC, 400, _NON_NUMERIC_BUDGET + ), + "messages-anthropic-undeclared-null-budget-drop-params-sends-adaptive-without-effort": Cell( + MESSAGES, + "anthropic", + _UNDECLARED, + {"thinking": _NULL_BUDGET, "drop_params": True}, + _native_messages(None, _ADAPTIVE), + _ANTHROPIC, + ), + "responses-anthropic-false-budget-400": Cell( + RESPONSES, + "anthropic", + _CLAUDE_INFO, + {"thinking": _FALSE_BUDGET}, + None, + _ANTHROPIC, + 400, + _NON_NUMERIC_BUDGET, + ), + "chat-converse-undeclared-false-budget-400": Cell( + CHAT, + "bedrock_converse", + _UNDECLARED, + {"thinking": _FALSE_BUDGET}, + None, + _CONVERSE, + 400, + _NON_NUMERIC_BUDGET, + ), + "messages-invoke-undeclared-null-budget-400": Cell( + MESSAGES, "bedrock_invoke", _UNDECLARED, {"thinking": _NULL_BUDGET}, None, _INVOKE, 400, _NON_NUMERIC_BUDGET + ), + "chat-databricks-claude-undeclared-false-budget-400": Cell( + CHAT, + "databricks_claude", + _UNDECLARED, + {"thinking": _FALSE_BUDGET}, + None, + _DATABRICKS, + 400, + _NON_NUMERIC_BUDGET, + ), + "chat-anthropic-empty-declaration-budget-drop-params-sends-adaptive-without-effort": Cell( + CHAT, + "anthropic", + _EMPTY_DECLARATION, + {"thinking": _BUDGET, "drop_params": True}, + _anthropic_chat_without_effort(_ADAPTIVE), + _ANTHROPIC, + ), + "chat-anthropic-none-only-declaration-budget-drop-params-sends-adaptive-without-effort": Cell( + CHAT, + "anthropic", + _NONE_ONLY_DECLARATION, + {"thinking": _BUDGET, "drop_params": True}, + _anthropic_chat_without_effort(_ADAPTIVE), + _ANTHROPIC, + ), + "chat-anthropic-empty-declaration-budget-keeps-its-effort": Cell( + CHAT, + "anthropic", + _EMPTY_DECLARATION, + {"thinking": _BUDGET}, + _anthropic_chat("medium", _ADAPTIVE), + _ANTHROPIC, + ), + "chat-converse-empty-declaration-budget-drop-params-sends-adaptive-without-effort": Cell( + CHAT, + "bedrock_converse", + _EMPTY_DECLARATION, + {"thinking": _BUDGET, "drop_params": True}, + _converse_chat_without_effort(_ADAPTIVE), + _CONVERSE, + ), + "messages-anthropic-empty-declaration-budget-drop-params-sends-adaptive-without-effort": Cell( + MESSAGES, + "anthropic", + _EMPTY_DECLARATION, + {"thinking": _BUDGET, "drop_params": True}, + _native_messages(None, _ADAPTIVE), + _ANTHROPIC, + ), + "messages-anthropic-none-only-declaration-budget-drop-params-sends-adaptive-without-effort": Cell( + MESSAGES, + "anthropic", + _NONE_ONLY_DECLARATION, + {"thinking": _BUDGET, "drop_params": True}, + _native_messages(None, _ADAPTIVE), + _ANTHROPIC, + ), + "messages-anthropic-empty-declaration-budget-keeps-its-effort": Cell( + MESSAGES, + "anthropic", + _EMPTY_DECLARATION, + {"thinking": _BUDGET}, + _native_messages({"effort": "medium"}, _ADAPTIVE), + _ANTHROPIC, + ), + "messages-converse-empty-declaration-budget-drop-params-sends-adaptive-without-effort": Cell( + MESSAGES, + "bedrock_converse", + _EMPTY_DECLARATION, + {"thinking": _BUDGET, "drop_params": True}, + _converse_messages(None), + _CONVERSE, + ), } ) @@ -1815,20 +1966,65 @@ def _bedrock_native_schema(body: Mapping[str, JsonValue], *, invoke: bool) -> Js return JSON_OBJECT.validate_json(string_value(json_schema["schema"])) +_CONVERSE_NATIVE_OUTPUT: Final[dict[str, JsonValue]] = { + "textFormat": { + "type": "json_schema", + "structure": {"jsonSchema": {"name": "answer", "schema": json.dumps(_NATIVE_OUTPUT_SCHEMA)}}, + } +} +_INVOKE_NATIVE_OUTPUT: Final[dict[str, JsonValue]] = { + "effort": "high", + "format": {"type": "json_schema", "schema": _NATIVE_OUTPUT_SCHEMA}, +} +_JSON_TOOL: Final = "json_tool_call" +_CONVERSE_TOOL_SCHEMA: Final[dict[str, JsonValue]] = { + key: value for key, value in _NATIVE_OUTPUT_SCHEMA.items() if key != "additionalProperties" +} +_CONVERSE_WITH_NATIVE_OUTPUT: Final = _with_fields( + _converse_chat("high", _ADAPTIVE), {"outputConfig": _CONVERSE_NATIVE_OUTPUT} +) +_INVOKE_WITH_NATIVE_OUTPUT: Final = _with_output_config( + _invoke_chat("high", _ADAPTIVE, ("structured-outputs-2025-11-13",)), _INVOKE_NATIVE_OUTPUT +) +_CONVERSE_WITH_JSON_TOOL: Final = _with_fields( + _converse_chat("high", _ADAPTIVE), + { + "toolConfig": { + "tools": [ + { + "toolSpec": { + "name": _JSON_TOOL, + "description": _JSON_TOOL, + "inputSchema": {"json": _CONVERSE_TOOL_SCHEMA}, + } + } + ] + } + }, +) +_INVOKE_WITH_JSON_TOOL: Final = _with_fields( + _without(_invoke_chat("high", _ADAPTIVE, ()), "anthropic_beta"), + {"tools": [{"name": _JSON_TOOL, "input_schema": _NATIVE_OUTPUT_SCHEMA}]}, +) + + @pytest.mark.parametrize( - ("kind", "target", "fields"), + ("kind", "target", "fields", "expected"), [ - pytest.param("bedrock_converse", _CONVERSE, {"thinking": _BUDGET}, id="converse-budget"), + pytest.param( + "bedrock_converse", _CONVERSE, {"thinking": _BUDGET}, _CONVERSE_WITH_NATIVE_OUTPUT, id="converse-budget" + ), pytest.param( "bedrock_invoke", _INVOKE, {"thinking": _BUDGET, "output_config": {"effort": "medium"}}, + _INVOKE_WITH_NATIVE_OUTPUT, id="invoke-output-config-beside-budget", ), ], ) def test_a_deployment_opted_into_bedrock_native_output_keeps_it_beside_its_declared_level( - gateway: Gateway, kind: str, target: str, fields: Mapping[str, JsonValue] + gateway: Gateway, kind: str, target: str, fields: Mapping[str, JsonValue], expected: Expected ) -> None: marker: Final = new_marker() response_format: Final[dict[str, JsonValue]] = { @@ -1844,10 +2040,116 @@ def test_a_deployment_opted_into_bedrock_native_output_keeps_it_beside_its_decla assert response.status_code == 200, response.text[:2000] assert answer(marker) in response.text, response.text[:2000] assert [(request.method, request.target) for request in received] == [("POST", target)] - body: Final = body_of(received[0]) - assert _bedrock_native_schema(body, invoke=target == _INVOKE) == _NATIVE_OUTPUT_SCHEMA, body - assert {"toolConfig", "tools"}.isdisjoint(body), body - assert sent_effort(received[0]) == "high", body + assert body_of(received[0]) == expected(marker) + + +_NATIVE_OUTPUT_REJECTION: Final = ( + "The model returned the following errors: output_config.format: Extra inputs are not permitted" +) + + +def _rejecting_native_output(request: Request) -> Reply: + native: Final = _bedrock_native_schema(body_of(request), invoke=path_of(request).endswith("/invoke")) + if native is None: + return provider_reply(request) + return Reply(status=400, body=json.dumps({"message": _NATIVE_OUTPUT_REJECTION}).encode()) + + +@pytest.mark.parametrize( + ("kind", "target", "rejected", "retried"), + [ + pytest.param( + "bedrock_converse", _CONVERSE, _CONVERSE_WITH_NATIVE_OUTPUT, _CONVERSE_WITH_JSON_TOOL, id="converse" + ), + pytest.param("bedrock_invoke", _INVOKE, _INVOKE_WITH_NATIVE_OUTPUT, _INVOKE_WITH_JSON_TOOL, id="invoke"), + ], +) +def test_the_retry_after_bedrock_rejects_native_output_keeps_the_declared_level( + gateway: Gateway, kind: str, target: str, rejected: Expected, retried: Expected +) -> None: + marker: Final = new_marker() + response_format: Final[dict[str, JsonValue]] = { + "type": "json_schema", + "json_schema": {"name": "answer", "schema": _NATIVE_OUTPUT_SCHEMA}, + } + with wire_server(_rejecting_native_output) as wire, gateway.scenario() as scenario: + model: Final = deployment(scenario, kind, wire, _CLAUDE_INFO_WITH_NATIVE_OUTPUT) + response: Final = gateway.request( + "POST", CHAT, chat_request(model, marker, response_format=response_format, thinking=_BUDGET) + ) + received: Final = wire.drain() + assert response.status_code == 200, response.text[:2000] + assert [(request.method, request.target) for request in received] == [("POST", target), ("POST", target)] + assert [body_of(request) for request in received] == [rejected(marker), retried(marker)] + + +_VERTEX_PROJECT: Final = "scripted-project" +_VERTEX_LOCATION: Final = "us-east5" +_VERTEX_TOKEN: Final = "/_oauth/token" +_VERTEX_RAW_PREDICT: Final = ( + f"/v1/projects/{_VERTEX_PROJECT}/locations/{_VERTEX_LOCATION}/publishers/anthropic/models/{CLAUDE}:rawPredict" +) +_VERTEX_ACCESS_TOKEN: Final = json.dumps({"access_token": "scripted", "token_type": "Bearer", "expires_in": 3600}) + + +def _vertex(expected: Expected) -> Expected: + return _with_fields(_without(expected, "model"), {"anthropic_version": "vertex-2023-10-16"}) + + +def _vertex_reply(request: Request) -> Reply: + if request.target == _VERTEX_TOKEN: + return Reply(body=_VERTEX_ACCESS_TOKEN.encode()) + marker: Final = marker_of(request) + return Reply(body=message_json(f"msg_{marker}", CLAUDE, answer(marker))) + + +@pytest.mark.parametrize( + ("route", "fields", "expected", "status"), + [ + pytest.param( + CHAT, + {"reasoning_effort": "medium"}, + _vertex(_anthropic_chat("high", {"type": "adaptive", "display": "summarized"})), + 200, + id="chat-medium-to-high", + ), + pytest.param( + MESSAGES, + {"thinking": _BUDGET}, + _vertex(_native_messages({"effort": "high"}, _ADAPTIVE)), + 200, + id="messages-budget-to-high", + ), + pytest.param(CHAT, {"thinking": _FALSE_BUDGET}, None, 400, id="chat-false-budget-400"), + ], +) +def test_a_vertex_ai_claude_deployment_gets_one_of_its_declared_levels( + gateway: Gateway, route: str, fields: dict[str, JsonValue], expected: Expected | None, status: int +) -> None: + marker: Final = new_marker() + with wire_server(_vertex_reply) as wire, gateway.scenario() as scenario: + model: Final = scenario.model( + model=f"vertex_ai/{CLAUDE}", + api_base=wire.url, + api_key=None, + vertex_project=_VERTEX_PROJECT, + vertex_location=_VERTEX_LOCATION, + vertex_credentials=service_account_json(_VERTEX_PROJECT, wire.url), + model_info=dict(_CLAUDE_INFO), + ) + body: Final = ( + chat_request(model, marker, **fields) if route == CHAT else messages_request(model, marker, **fields) + ) + response: Final = gateway.request("POST", route, body) + received: Final = tuple(request for request in wire.drain() if request.target != _VERTEX_TOKEN) + assert response.status_code == status, response.text[:2000] + if expected is None: + assert _NON_NUMERIC_BUDGET in response.text, response.text[:2000] + assert received == (), [request.body[:300] for request in received] + return + assert answer(marker) in response.text, response.text[:2000] + assert [(request.method, request.target) for request in received] == [("POST", _VERTEX_RAW_PREDICT)] + assert body_of(received[0]) == expected(marker) def _single(received: tuple[Request, ...], marker: str) -> Request: From ddb8a14ee97e3abb6c251edfd3a4ba53467688db Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 28 Oct 2026 15:44:43 -0700 Subject: [PATCH 10/10] feat(skills): add a litellm-setup agent skill (#47731) * feat(skills): add a litellm-setup agent skill * fix(skills): run the quickstart for Docker with Postgres in litellm-setup Use scripts/quickstart.sh for the Docker plus Postgres path instead of a hand-rolled Postgres container, keep uv with the user's own Postgres, load .env as data instead of sourcing it, pin the uv Python range, chmod an existing .env, list bedrock_converse and vertex_ai rows in the cost map lookup, ask before editing the shell profile, and stop the health wait when the proxy exits * fix(skills): guide empty Postgres, docker sudo, and key fixes in litellm-setup Ask for a new empty database on the uv path and DIRECT_URL behind a pooler, add the baseline error to troubleshooting, and drop inherited database settings in the loader line. Check python3 and lsof, explain Docker's permission denied, give quickstart commands by the folder's path, and fix provider keys by recreating the container or deleting the quickstart model. Drop the structure-only test. * fix(skills): keep shell profiles untouched when litellm-setup installs uv The uv installer edits shell profiles unless UV_NO_MODIFY_PATH is set, so the skill now sets it and puts ~/.local/bin on PATH for later commands. It also says litellm --setup runs in a separate terminal and how to retire the shared master-key UI login * fix(skills): offer litellm --setup only on the uv path The Docker paths install no host litellm CLI, and the old wording also passed the skill's own step number on to the user * fix(skills): ask before using an env provider key, print model names config.yaml accepts, probe the port with curl * fix(skills): state the env key default in the question, chmod the wizard config, keep uv's bin dir on PATH * fix(skills): keep litellm-setup on its own .env and install when the shell has others * fix(skills): read the setup wizard's config without printing keys and hand off the exact restart command * fix(skills): hide the database-access dev skill from end-user skill installs * fix(skills): give the litellm --setup path a restart command that keeps its config * docs(skills): point litellm --setup users to the master key in litellm_config.yaml * fix(skills): hide every non-end-user skill, use Azure deployment names, keep the restart block out of the user's shell * test(skills): find non-end-user skills in-process instead of through git * docs(skills): price Azure deployments with base_model and put uv on PATH in the start block --- .agents/skills/database-access/SKILL.md | 2 + .../.agents/skills/rust-error/SKILL.md | 2 + .../.agents/skills/rust-gateway/SKILL.md | 2 + .../.agents/skills/rust-string-enums/SKILL.md | 2 + .../.agents/skills/rust-tracing/SKILL.md | 2 + skills/litellm-setup/SKILL.md | 205 ++++++++++++++++++ .../slack-gif-creator/SKILL.md | 2 + .../test-delete-skill/SKILL.md | 2 + .../test-skill-litellm/SKILL.md | 2 + tests/unit/test_repo_agent_skills.py | 68 ++++++ .../.agents/skills/url-state/SKILL.md | 2 + 11 files changed, 291 insertions(+) create mode 100644 skills/litellm-setup/SKILL.md create mode 100644 tests/unit/test_repo_agent_skills.py diff --git a/.agents/skills/database-access/SKILL.md b/.agents/skills/database-access/SKILL.md index 796dfafe4f6..13fb7b7e286 100644 --- a/.agents/skills/database-access/SKILL.md +++ b/.agents/skills/database-access/SKILL.md @@ -1,6 +1,8 @@ --- name: database-access description: Add database queries, extract existing Prisma calls into repositories, or explicitly port queries to Rust and SQLx without expanding migration scope +metadata: + internal: true --- # Database access diff --git a/litellm-rust/.agents/skills/rust-error/SKILL.md b/litellm-rust/.agents/skills/rust-error/SKILL.md index fd5d6222287..74da1ecbcf4 100644 --- a/litellm-rust/.agents/skills/rust-error/SKILL.md +++ b/litellm-rust/.agents/skills/rust-error/SKILL.md @@ -1,6 +1,8 @@ --- name: rust-error description: Define, wrap, convert, classify, report or test Rust error types in litellm-rust with thiserror. Use when adding an error type or variant, mapping one crate's error into another, turning an error into a gateway response or Python exception, deciding retry or fault from an error, or replacing call sites that build errors from strings +metadata: + internal: true --- # Rust errors diff --git a/litellm-rust/.agents/skills/rust-gateway/SKILL.md b/litellm-rust/.agents/skills/rust-gateway/SKILL.md index 66b93ee128d..4fee0b54a68 100644 --- a/litellm-rust/.agents/skills/rust-gateway/SKILL.md +++ b/litellm-rust/.agents/skills/rust-gateway/SKILL.md @@ -1,6 +1,8 @@ --- name: rust-gateway description: Add or change an HTTP route, extractor, response envelope, stream or router mount in the litellm-rust gateway crates (crates/gateway and crates/gateway-*). Use when adding an endpoint, parsing a request body, choosing an error envelope for an API surface, relaying SSE, or writing a router-level test +metadata: + internal: true --- # Rust gateway diff --git a/litellm-rust/.agents/skills/rust-string-enums/SKILL.md b/litellm-rust/.agents/skills/rust-string-enums/SKILL.md index 5fc067790a0..352f6427dd9 100644 --- a/litellm-rust/.agents/skills/rust-string-enums/SKILL.md +++ b/litellm-rust/.agents/skills/rust-string-enums/SKILL.md @@ -1,6 +1,8 @@ --- name: rust-string-enums description: Define or refactor Rust string-valued enums and their Serde adapters in litellm-rust, using Strum and serde_with while preserving parsing, wire values, and schemas +metadata: + internal: true --- # Rust string enums diff --git a/litellm-rust/.agents/skills/rust-tracing/SKILL.md b/litellm-rust/.agents/skills/rust-tracing/SKILL.md index c1c7f43c456..a8da3f3bb14 100644 --- a/litellm-rust/.agents/skills/rust-tracing/SKILL.md +++ b/litellm-rust/.agents/skills/rust-tracing/SKILL.md @@ -1,6 +1,8 @@ --- name: rust-tracing description: Add or change Rust diagnostic tracing in litellm-rust, including route spans, subscriber layers, and Python logger delivery +metadata: + internal: true --- # Rust tracing diff --git a/skills/litellm-setup/SKILL.md b/skills/litellm-setup/SKILL.md new file mode 100644 index 00000000000..7c824751d6f --- /dev/null +++ b/skills/litellm-setup/SKILL.md @@ -0,0 +1,205 @@ +--- +name: litellm-setup +description: Set up a self-hosted LiteLLM proxy, the OpenAI-compatible LLM gateway, on this machine, from install through provider keys, config.yaml, a master key, optional Postgres and Admin UI, and a verified chat completion. Use when the user asks to set up LiteLLM, install the LiteLLM proxy, self-host an LLM gateway, or put one endpoint in front of OpenAI, Anthropic, Gemini, Azure, Bedrock, Ollama, or other providers. Not for using the LiteLLM Python SDK inside an app +--- + +# Set up a LiteLLM proxy + +Take the user from nothing to a running LiteLLM proxy that has answered one chat completion. Run every command yourself unless a step says the user does it + +Never print a secret. Provider keys, the master key, the salt key, the database URL, and virtual keys live only in `.env`, and `config.yaml` reads them through `os.environ/NAME`. Check that a value is there with `grep -c '^NAME=.' .env`, never with `cat .env` or `echo "$NAME"`. Load `.env` into a shell with this line, which exports each line as it is, so a `&` or `$` in a value stays literal, and first drops any database settings the shell already had and sets `LITELLM_MODE=PRODUCTION`, which stops `litellm` from also loading a `.env` it finds above its install folder, such as `~/.env`, so only this `.env` picks the database. The steps that need it start with it: + +```bash +unset DATABASE_URL DIRECT_URL DATABASE_HOST; export LITELLM_MODE=PRODUCTION; while IFS= read -r line || [ -n "$line" ]; do case "$line" in [A-Za-z_]*=*) export "$line" ;; esac; done < .env +``` + +## 1. Ask once + +Ask everything in one message, with defaults the user can accept by saying "go": + +- Providers and models. Default is OpenAI with its newest flagship model, using the `OPENAI_API_KEY` in your environment when `[ -n "$OPENAI_API_KEY" ] && echo set` says it is there. Run that check before asking, and say in the question that the default uses that variable, naming it but never its value, since a key in your environment can belong to another account +- Whether they want virtual keys, teams, spend tracking, or the Admin UI. Those need Postgres, plain routing does not. Default is no +- uv (default) or Docker. With Postgres, Docker runs the repo's quickstart, which brings its own database, and uv needs a Postgres server they already have, with a new, empty database for LiteLLM, so someone with their own Postgres server picks uv +- Folder and port. Defaults are `./litellm-proxy` (`./litellm-gateway` for the quickstart) and 4000 + +Then follow the steps for their answers. Plain routing skips steps 3 and 6. The quickstart is steps 2, 3, 8, and 9. uv with their own Postgres skips step 3 + +In the same message, say that someone who picks uv and would rather answer prompts can run `litellm --setup` in a separate terminal window once LiteLLM is installed, not through Claude Code. Never run it yourself, since it needs a real terminal and without one prints "Setup cancelled." and writes nothing. Give them the command as `LITELLM_MODE=PRODUCTION /litellm --setup`, with `` replaced by the folder `uv tool dir --bin` prints, to run from the folder they want the config in. It writes `litellm_config.yaml` there with the provider keys and master key in plain text and offers to start the proxy, which then listens on every network interface and stops with Ctrl+C in that window. When the user is done, run this in that folder. It makes the file readable only by them, keeps it out of git (the wizard does neither), and prints only the model names. Never print that file or run `grep`, `sed`, or `cat` on it: + +```bash +chmod 600 litellm_config.yaml; grep -qx 'litellm_config.yaml' .gitignore 2>/dev/null || echo 'litellm_config.yaml' >> .gitignore +"$(uv tool dir)/litellm/bin/python" -I -c 'import yaml; print(*(m["model_name"] for m in yaml.safe_load(open("litellm_config.yaml"))["model_list"]), sep="\n")' +``` + +Then skip to step 8 and run it against their proxy, starting that shell command with this line instead of the loader line, which reads the master key without printing it: + +```bash +export LITELLM_MASTER_KEY="$("$(uv tool dir)/litellm/bin/python" -I -c 'import yaml; print(yaml.safe_load(open("litellm_config.yaml"))["general_settings"]["master_key"])')" +``` + +## 2. Check prerequisites + +```bash +uv --version; docker info --format '{{.ServerVersion}}'; docker compose version; curl --version | head -1; openssl version; command -v python3 +``` + +On native Windows, ask the user to run Claude Code inside WSL, since every command here is POSIX shell. Every path needs curl, openssl, and python3, so ask the user to install any that is missing. The uv path needs uv, which downloads a supported Python (LiteLLM supports 3.10 to 3.14) when the `--python` range in step 4 rules out the one on the machine. If uv is missing, offer to install it, and only after the user says yes run `curl -LsSf https://astral.sh/uv/install.sh | env UV_NO_MODIFY_PATH=1 sh`, which leaves their shell profile alone (https://docs.astral.sh/uv/getting-started/installation/). It puts uv in `~/.local/bin`, so start every later command that runs `uv` or `litellm` with `export PATH="$HOME/.local/bin:$PATH";`. The Docker path needs a running Docker daemon, and the quickstart also needs Docker Compose v2. If `docker info` says `permission denied`, the user's account cannot use Docker without sudo. Offer the uv path, or ask them to add themselves to the `docker` group the way https://docs.docker.com/engine/install/linux-postinstall/ shows and start a new login session before you check again + +Check the port is free with `curl -s -o /dev/null --max-time 2 http://127.0.0.1:4000; echo $?`, which prints `7` (could not connect) only when nothing listens there. Don't use `lsof` for this, since it misses ports that root or Docker hold. If it is taken, pick another port and use it everywhere below, because a proxy asked for a busy 4000 silently moves to a random port + +## 3. Postgres with Docker: run the quickstart + +The repo's quickstart starts the gateway, Postgres, and the Admin UI in Docker, listening on this machine only, and puts a `litellm-gateway` command in that folder that stops, starts, updates, or removes them. It asks nothing when it has no terminal. It writes the master key, salt key, and database password to its own `.env` and never prints them. Download it, then run it with the folder and port from step 1. It returns once the gateway is ready: + +```bash +curl -fsSL https://raw.githubusercontent.com/BerriAI/litellm/main/scripts/quickstart.sh -o quickstart.sh +LITELLM_DIR="$PWD/litellm-gateway" LITELLM_PORT=4000 sh quickstart.sh --yes +cd litellm-gateway +``` + +Models live in the database here, so add each one through the API instead of a `config.yaml`, naming it the way step 5 says. Pipe the request body in, so the provider key never shows up in output or on a command line. Unless the user agreed to the key in your environment, as step 5 says, ask them to add the line `OPENAI_API_KEY=` to this `.env` themselves. Run the loader line first: + +```bash +python3 -c 'import json, os, sys; json.dump({"model_name": "gpt-6.1-sol", "litellm_params": {"model": "openai/gpt-6.1-sol", "api_key": os.environ["OPENAI_API_KEY"]}}, sys.stdout)' \ + | curl -sS -o /dev/null -w '%{http_code}\n' http://127.0.0.1:4000/model/new \ + -H "Authorization: Bearer $LITELLM_MASTER_KEY" -H "Content-Type: application/json" -d @- +``` + +Run that in one shell command that starts with the loader line, since the master key is in `.env`. `200` means the model was added. Then go to step 8 + +## 4. Install + +uv: + +```bash +uv tool install --python '>=3.10,<3.15' 'litellm[proxy]' +export PATH="$(uv tool dir --bin):$PATH"; litellm --version +``` + +With their own Postgres, install `'litellm[proxy,extra_proxy]'` instead, with the same `--python` range, which adds the Prisma client the proxy uses for the database. Running `uv tool install` again with the new extras replaces the old install. Start every later command that runs `litellm` with `export PATH="$(uv tool dir --bin):$PATH";`, so this install runs even when the shell has no `litellm` or an older one from a venv or `pip install litellm`. `uv tool update-shell` puts it on the PATH of new shells by editing the user's shell profile, so run it only after the user says yes + +Docker: + +```bash +docker pull docker.litellm.ai/berriai/litellm:main-stable +``` + +## 5. Write `.env` and `config.yaml` + +Run every command from here on in the folder from step 1. Create `.env` readable only by the user, keep it out of git, and add a master key unless it already has one. The proxy refuses to start without one, and `sk-` is the format of every key it issues: + +```bash +mkdir -p litellm-proxy && cd litellm-proxy +touch .env && chmod 600 .env; grep -qx '.env' .gitignore 2>/dev/null || echo '.env' >> .gitignore +grep -q '^LITELLM_MASTER_KEY=.' .env || printf 'LITELLM_MASTER_KEY=sk-%s\n' "$(openssl rand -hex 32)" >> .env +``` + +Copy a provider key that is already in your environment only after the user agreed to that variable, in their step 1 answer or when you ask now, and copy it without printing it, as in `printf 'OPENAI_API_KEY=%s\n' "$OPENAI_API_KEY" >> .env`. Otherwise ask the user to add the line `OPENAI_API_KEY=` to `.env` themselves and tell you when it is there. If they paste a key into the chat anyway, write it to `.env` and never repeat it. Keep one `NAME=value` per line with no quotes, so `docker --env-file` and the loader line read the same value + +Confirm each model's current LiteLLM name in the cost map instead of trusting memory, since model names go stale fast. This prints the chat models of the provider named last (`openai`, `anthropic`, `gemini`, `azure`, `bedrock`, `vertex_ai`, and so on) the way `config.yaml` takes them, with the provider in front. It matches by prefix, so `bedrock` also lists the newer Bedrock models and `vertex_ai` lists every Vertex family. For Ollama, use a model from `ollama list` instead: + +```bash +curl -fsSL https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json | python3 -c ' +import json, sys +for name, row in json.load(sys.stdin).items(): + provider = str(row.get("litellm_provider", "")) if isinstance(row, dict) else "" + if provider.startswith(sys.argv[1]) and row.get("mode") == "chat": + prefix = "bedrock" if provider == "bedrock_converse" else "vertex_ai" if provider.startswith("vertex_ai") else provider + print(name if name.startswith(prefix + "/") else prefix + "/" + name) +' openai +``` + +In `config.yaml`, `model` is a name from that list, as in `openai/gpt-6.1-sol` or `bedrock/us.anthropic.`, and `model_name` is what clients will send. If the folder already has a `config.yaml`, show the user its `model_name` lines and ask before replacing it. This example uses the newest GPT model in the cost map when this skill was written, so replace it with what the user picked: + +```yaml +model_list: + - model_name: gpt-6.1-sol + litellm_params: + model: openai/gpt-6.1-sol + api_key: os.environ/OPENAI_API_KEY + +general_settings: + master_key: os.environ/LITELLM_MASTER_KEY +``` + +Add one entry per model. On Azure, ask the user for each deployment's name and the model it runs. Use `azure/` as `model`, since Azure routes by deployment and a name from the lookup works only when the deployment has that same name, and add `model_info:` with `base_model: azure/` to the entry, since LiteLLM prices each call by that name. Providers that need more than a key, like Azure or Bedrock, list their `litellm_params` on their page under https://docs.litellm.ai/docs/providers. Point every secret at `.env` through `os.environ/NAME` the same way + +## 6. Their own Postgres, on the uv path + +Ask the user to create a new, empty database for LiteLLM on their server (`CREATE DATABASE litellm;`) and add `DATABASE_URL=postgresql://...` for it to `.env` themselves. The proxy creates its tables there on first start and stops on a database that already holds other tables. If that URL goes through a transaction pooler such as PgBouncer, they also add `DIRECT_URL` for the same database without the pooler, which the migrations use. Then add a salt key. It encrypts the provider credentials the proxy stores in the database and falls back to the master key when unset, so set it once and never change it: + +```bash +grep -q '^LITELLM_SALT_KEY=.' .env || printf 'LITELLM_SALT_KEY=sk-%s\n' "$(openssl rand -hex 32)" >> .env +``` + +Generate the Prisma client once inside the tool's environment. A pip or uv install doesn't ship it generated (Docker images do): + +```bash +tool="$(uv tool dir)/litellm" +schema=$("$tool/bin/python" -I -c 'import importlib.util, os; print(os.path.join(importlib.util.find_spec("litellm").submodule_search_locations[0], "proxy", "schema.prisma"))') +PATH="$tool/bin:$PATH" prisma generate --schema "$schema" +``` + +## 7. Start the proxy + +Bind to `127.0.0.1` unless the user wants other machines to reach it + +uv, in one shell command that starts with the loader line, since the installed `litellm` does not read `.env` by itself: + +```bash +export PATH="$HOME/.local/bin:$PATH"; export PATH="$(uv tool dir --bin):$PATH" +nohup litellm --config config.yaml --host 127.0.0.1 --port 4000 > litellm.log 2>&1 & +echo $! > litellm.pid +``` + +Docker: + +```bash +docker run -d --name litellm --env-file .env -v "$PWD/config.yaml:/app/config.yaml:ro" -p 127.0.0.1:4000:4000 \ + docker.litellm.ai/berriai/litellm:main-stable --config /app/config.yaml --port 4000 +``` + +Wait on the health route, stopping early if the proxy exits. The first start with Postgres applies the database migrations and takes longer. Define `alive` for the path you took, `alive() { kill -0 "$(cat litellm.pid)" 2>/dev/null; }` for uv or `alive() { [ "$(docker inspect -f '{{.State.Running}}' litellm 2>/dev/null)" = true ]; }` for Docker, in the same shell command as the loop: + +```bash +for i in $(seq 1 180); do curl -fsS http://127.0.0.1:4000/health/liveliness >/dev/null 2>&1 && break; alive || break; sleep 1; done +curl -sS http://127.0.0.1:4000/health/readiness +``` + +Readiness reports `"db":"connected"` with Postgres and `"db":"Not connected"` without it. If the proxy never comes up, read the end of `litellm.log` (or `docker logs litellm`) and check the troubleshooting list + +## 8. Verify with a chat completion + +Use a `model_name` from `config.yaml` (or step 3), in one shell command that starts with the loader line: + +```bash +curl -sS http://127.0.0.1:4000/v1/chat/completions \ + -H "Authorization: Bearer $LITELLM_MASTER_KEY" -H "Content-Type: application/json" \ + -d '{"model": "gpt-6.1-sol", "messages": [{"role": "user", "content": "Say hello in five words."}]}' +``` + +Show the user the reply in `choices[0].message.content`. An error here means the setup is not done, so fix it before handing off + +## 9. Hand off + +Tell the user, without printing any secret: + +- The base URL is `http://127.0.0.1:4000`. Any OpenAI-compatible client works with it as the base URL and the master key or a virtual key as the API key +- The master key is `LITELLM_MASTER_KEY` in the folder's `.env`, or `general_settings.master_key` in `litellm_config.yaml` when they used `litellm --setup` +- To stop it, `kill "$(cat litellm.pid)"` (uv), `docker stop litellm` (Docker), `/litellm-gateway stop` (quickstart), or Ctrl+C in its window (`litellm --setup`). To start it again, `docker start litellm`, `/litellm-gateway start`, on uv the whole step 7 command as you ran it, loader line and PATH export included, wrapped in `( ... )` so their shell keeps its own settings, shown as a code block and never paraphrased, since a new shell has neither, or for `litellm --setup` `LITELLM_MODE=PRODUCTION /litellm --config litellm_config.yaml --host 127.0.0.1 --port ` in a terminal window in that folder, with `` and `` filled in, since running the wizard again writes a new config with a new master key. `update` and `uninstall` update or remove a quickstart install. Give the quickstart commands with the folder's full path, since a bare `litellm-gateway` is on PATH only when `~/.local/bin` is, and can belong to an earlier install +- With Postgres, the Admin UI is at `http://127.0.0.1:4000/ui` (user `admin`, password the master key), and `POST /key/generate` with the master key creates virtual keys with their own budgets and model lists. Without Postgres, both need step 3 or 6 first +- The Admin UI warns that the master-key login is a shared secret, which is fine while only this machine reaches the proxy. Before anyone else can reach it, invite an admin with their own password on the Internal Users page, then set `general_settings.disable_env_credential_login: true` in the proxy config +- To manage the running proxy from a coding agent (keys, teams, users, models, MCP servers), install `npx skills add BerriAI/litellm-skills -g` + +## Troubleshooting + +- `refused to start: no master key is set` means the loader line did not run in the shell command that started `litellm`, or `--env-file .env` is missing from `docker run` +- `a database URL is set but the prisma CLI is neither on PATH nor importable` means the install lacks `extra_proxy`, so rerun step 4 with it, or, on plain routing, that the command that started `litellm` did not start with the loader line +- `The Client hasn't been generated yet` or `Unable to find Prisma binaries` means the Prisma generate command in step 6 has not run +- `Incorrect API key provided` or another provider `AuthenticationError` means a provider key is wrong. Fix it in `.env` and restart, since the proxy reads the environment only at startup. On uv, stop it and rerun step 7. On Docker, `docker rm -f litellm` and rerun step 7, since `docker restart` keeps the environment the container was created with. On the quickstart the key is saved with the model, so delete the model and add it again: `GET /model/info` lists each model's `model_info.id`, and `POST /model/delete` with `{"id": ""}` deletes it +- `Cannot automatically baseline this database` means `DATABASE_URL` points at a database that already holds tables LiteLLM did not create. Point it at a new, empty database +- `LLM Provider NOT provided` means a `model` in `config.yaml` (or step 3) lacks its provider in front. Use the name as the step 5 lookup prints it +- `Invalid model name passed in model=...` means the request's `model` is not a `model_name` in `config.yaml` or step 3. `GET /v1/models` lists the ones the key can use +- `No connected db.` on a proxy without Postgres means the bearer token is not the master key +- `Conflict. The container name "/litellm" is already in use` means an earlier run left a container. `docker start litellm` reuses it, or with the user's OK `docker rm -f litellm` and rerun step 7 +- Inside Docker, `localhost` in `config.yaml` (an Ollama `api_base`, say) is the container itself. Use `host.docker.internal`, and on Linux also pass `--add-host=host.docker.internal:host-gateway` diff --git a/tests/unit/skills/test_skills_data/slack-gif-creator/SKILL.md b/tests/unit/skills/test_skills_data/slack-gif-creator/SKILL.md index 3cae971b731..d2cdfd17bde 100644 --- a/tests/unit/skills/test_skills_data/slack-gif-creator/SKILL.md +++ b/tests/unit/skills/test_skills_data/slack-gif-creator/SKILL.md @@ -1,6 +1,8 @@ --- name: slack-gif-creator description: Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack." +metadata: + internal: true --- # Slack GIF Creator diff --git a/tests/unit/skills/test_skills_data/test-delete-skill/SKILL.md b/tests/unit/skills/test_skills_data/test-delete-skill/SKILL.md index ba3fda9ab7b..ef1fd1a7b24 100644 --- a/tests/unit/skills/test_skills_data/test-delete-skill/SKILL.md +++ b/tests/unit/skills/test_skills_data/test-delete-skill/SKILL.md @@ -1,6 +1,8 @@ --- name: test-delete-skill description: A test skill created specifically for deletion testing +metadata: + internal: true --- # Test Delete Skill diff --git a/tests/unit/skills/test_skills_data/test-skill-litellm/SKILL.md b/tests/unit/skills/test_skills_data/test-skill-litellm/SKILL.md index ec83b580f0e..b3d54ccdf3c 100644 --- a/tests/unit/skills/test_skills_data/test-skill-litellm/SKILL.md +++ b/tests/unit/skills/test_skills_data/test-skill-litellm/SKILL.md @@ -1,6 +1,8 @@ --- name: test-skill-litellm description: A test skill created by LiteLLM automated tests +metadata: + internal: true --- # Test Skill diff --git a/tests/unit/test_repo_agent_skills.py b/tests/unit/test_repo_agent_skills.py new file mode 100644 index 00000000000..591241f0cf9 --- /dev/null +++ b/tests/unit/test_repo_agent_skills.py @@ -0,0 +1,68 @@ +from collections.abc import Iterator +from fnmatch import fnmatch +from pathlib import Path +from typing import Final + +import pytest +import yaml + +_REPO_ROOT: Final = Path(__file__).resolve().parents[2] +_SKILLS_DIR: Final = _REPO_ROOT / "skills" +_SKILL_DIRECTORIES: Final = tuple(sorted(skill_file.parent for skill_file in _SKILLS_DIR.glob("*/SKILL.md"))) +_FULL_DEPTH_MAX_DEPTH: Final = 5 +_FULL_DEPTH_SKIPPED_NAMES: Final = frozenset(("node_modules", ".git", "dist", "build", "__pycache__")) +_GITIGNORED_NAME_PATTERNS: Final = tuple( + line.strip().rstrip("/") + for line in (_REPO_ROOT / ".gitignore").read_text(encoding="utf-8").splitlines() + if line.strip() and not line.startswith(("#", "!")) and "/" not in line.strip().rstrip("/") +) + + +def _absent_from_a_clone_or_skipped_by_the_cli(name: str) -> bool: + return name in _FULL_DEPTH_SKIPPED_NAMES or any(fnmatch(name, pattern) for pattern in _GITIGNORED_NAME_PATTERNS) + + +def _full_depth_skill_directories(directory: Path, depth: int) -> Iterator[Path]: + if (directory / "SKILL.md").is_file(): + yield directory + if depth == _FULL_DEPTH_MAX_DEPTH: + return + for child in sorted(directory.iterdir()): + if child.is_dir() and not _absent_from_a_clone_or_skipped_by_the_cli(child.name): + yield from _full_depth_skill_directories(child, depth + 1) + + +_NON_END_USER_SKILL_DIRECTORIES: Final = tuple( + directory for directory in _full_depth_skill_directories(_REPO_ROOT, 0) if directory.parent != _SKILLS_DIR +) + + +def _frontmatter(skill_directory: Path) -> object: + opening, frontmatter, _body = (skill_directory / "SKILL.md").read_text(encoding="utf-8").split("---\n", 2) + assert opening == "", f"{skill_directory.name}/SKILL.md must open with a --- frontmatter block" + return yaml.safe_load(frontmatter) + + +@pytest.mark.parametrize("skill_directory", _SKILL_DIRECTORIES, ids=lambda path: path.name) +def test_skill_frontmatter_has_string_name_matching_its_directory_and_a_description(skill_directory: Path) -> None: + frontmatter: Final = _frontmatter(skill_directory) + assert isinstance(frontmatter, dict), frontmatter + assert frontmatter.get("name") == skill_directory.name, frontmatter + description: Final = frontmatter.get("description") + assert isinstance(description, str) and description.strip(), frontmatter + + +@pytest.mark.parametrize( + "skill_directory", + _NON_END_USER_SKILL_DIRECTORIES, + ids=lambda path: str(path.relative_to(_REPO_ROOT)), +) +def test_skill_outside_skills_folder_is_hidden_from_end_user_skill_installs(skill_directory: Path) -> None: + frontmatter: Final = _frontmatter(skill_directory) + assert isinstance(frontmatter, dict), frontmatter + metadata: Final = frontmatter.get("metadata") + assert isinstance(metadata, dict) and metadata.get("internal") is True, ( + f"{skill_directory} needs `metadata: {{internal: true}}`, or `npx skills add BerriAI/litellm` installs it " + "for end users, from a root dot-folder always and from anywhere with --full-depth (skills CLI 1.7.4, " + "checked 2026-10-28)" + ) diff --git a/ui/litellm-dashboard/.agents/skills/url-state/SKILL.md b/ui/litellm-dashboard/.agents/skills/url-state/SKILL.md index 986118d81a7..8bf8fadd19e 100644 --- a/ui/litellm-dashboard/.agents/skills/url-state/SKILL.md +++ b/ui/litellm-dashboard/.agents/skills/url-state/SKILL.md @@ -1,6 +1,8 @@ --- name: url-state description: Read or write dashboard URL query state (tabs, filters, pagination, deep links, demo flags) with nuqs instead of raw history or URLSearchParams +metadata: + internal: true --- # URL state