diff --git a/tests/e2e/coverage_registry/llm_conversational.yaml b/tests/e2e/coverage_registry/llm_conversational.yaml index 8de8d5875b4..61f3be34a43 100644 --- a/tests/e2e/coverage_registry/llm_conversational.yaml +++ b/tests/e2e/coverage_registry/llm_conversational.yaml @@ -103,6 +103,7 @@ - {id: llm.messages.together_ai.multi_turn.nonstream.works, module: llm, tier: P1, subject_endpoint: messages, route: together_ai, capability: multi_turn, streaming: nonstream, assertions: [works], source: "llm_translation/test_together_ai_e2e.py", rationale: "Together tool result round trip over /v1/messages"} - {id: llm.chat_completions.sail.service_tier.nonstream.cost_logged, module: llm, tier: P1, subject_endpoint: chat_completions, route: sail, capability: service_tier, streaming: nonstream, assertions: [cost_logged], source: "llm_translation/test_sail_e2e.py", rationale: "service_tier flex, balanced and auto map to Sail completion windows and bill the matching price columns"} - {id: llm.chat_completions.sail.service_tier.nonstream.rejects_unknown_tier, module: llm, tier: P1, subject_endpoint: chat_completions, route: sail, capability: service_tier, streaming: nonstream, assertions: [rejects_unknown_tier], source: "llm_translation/test_sail_e2e.py", rationale: "A service_tier Sail has no completion window for is a 400 without drop_params"} +- {id: llm.chat_completions.sail.service_tier.nonstream.drops_unknown_tier_and_bills_asap, module: llm, tier: P1, subject_endpoint: chat_completions, route: sail, capability: service_tier, streaming: nonstream, assertions: [drops_unknown_tier_and_bills_asap], source: "llm_translation/test_sail_e2e.py", rationale: "An unknown service_tier under drop_params is dropped and billed at asap in both the cost header and spend log"} - {id: llm.responses.sail.service_tier.nonstream.cost_logged, module: llm, tier: P1, subject_endpoint: responses, route: sail, capability: service_tier, streaming: nonstream, assertions: [cost_logged], source: "llm_translation/test_sail_e2e.py", rationale: "A caller metadata.completion_window of flex on /v1/responses bills Sail flex rates"} - {id: llm.messages.sail.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: messages, route: sail, capability: basic, streaming: nonstream, assertions: [works], source: "llm_translation/test_sail_e2e.py", rationale: "Sail over /v1/messages"} - {id: llm.chat_completions.anthropic.basic.nonstream.cost_logged, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: basic, streaming: nonstream, assertions: [works, cost_logged], source: "llm_translation/test_conversational_matrix_e2e.py", rationale: "Anthropic over /chat/completions: cost header and spend row agree"} diff --git a/tests/e2e/llm_translation/test_completions_endpoint_e2e.py b/tests/e2e/llm_translation/test_completions_endpoint_e2e.py index 63fcee3ce36..6202dada599 100644 --- a/tests/e2e/llm_translation/test_completions_endpoint_e2e.py +++ b/tests/e2e/llm_translation/test_completions_endpoint_e2e.py @@ -2,7 +2,7 @@ The legacy text-completion endpoint (prompt-style, non-chat) is the second-busiest route in production yet was previously uncovered; the rest of the "completions" -surface is chat only. Registers an OpenAI instruct deployment at runtime (deleted +surface is chat only. Registers an OpenAI chat deployment at runtime (deleted on teardown), drives /v1/completions through the gateway with the real OpenAI SDK (LIT-4577), and asserts real generated text came back so a regression that empties the completion fails here. @@ -29,7 +29,7 @@ class TestCompletionsEndpoint: model_id = proxy.create_model( model, LiteLLMParamsBody( - model="text-completion-openai/gpt-3.5-turbo-instruct", + model="openai/gpt-5.4-nano", api_key="os.environ/OPENAI_API_KEY", ), ) @@ -40,7 +40,7 @@ class TestCompletionsEndpoint: model=model, prompt="Finish this sentence in a few words: the capital of France is", max_tokens=32, - extra_body=NO_PROXY_CACHE, + extra_body={**NO_PROXY_CACHE, "reasoning_effort": "none"}, ) assert completion.choices, f"/v1/completions returned no choices: {completion!r}" text = (completion.choices[0].text or "").strip() diff --git a/tests/e2e/llm_translation/test_sail_e2e.py b/tests/e2e/llm_translation/test_sail_e2e.py index 9c714544d6e..cf662afea90 100644 --- a/tests/e2e/llm_translation/test_sail_e2e.py +++ b/tests/e2e/llm_translation/test_sail_e2e.py @@ -13,7 +13,6 @@ from collections.abc import Mapping from dataclasses import dataclass from typing import Final, Literal -import openai import pytest from e2e_config import SLOW_PROVIDER_TIMEOUT_SECONDS, unique_marker from lifecycle import ResourceManager @@ -150,20 +149,29 @@ class TestSailChatCompletions: ) _assert_spend_row_matches(proxy, key, header_cost) - @pytest.mark.covers("llm.chat_completions.sail.service_tier.nonstream.rejects_unknown_tier") - def test_unknown_service_tier_is_rejected( - self, proxy: ProxyClient, resources: ResourceManager, sdk: SdkClients + @pytest.mark.covers("llm.chat_completions.sail.service_tier.nonstream.drops_unknown_tier_and_bills_asap") + @pytest.mark.parametrize("service_tier", ["bogus", 5]) + def test_unknown_service_tier_is_dropped_and_billed_asap( + self, proxy: ProxyClient, resources: ResourceManager, sdk: SdkClients, service_tier: str | int ) -> None: model, key = _register(proxy, resources) - with pytest.raises(openai.BadRequestError) as raised: - _ = _openai(sdk, key).chat.completions.create( - model=model, - messages=[{"role": "user", "content": PROMPT}], - max_completion_tokens=MAX_TOKENS, - extra_body={**NO_PROXY_CACHE, "service_tier": "bogus"}, - ) - assert "service_tier" in raised.value.message, f"400 does not name service_tier: {raised.value.message}" + raw: Final = _openai(sdk, key).chat.completions.with_raw_response.create( + model=model, + messages=[{"role": "user", "content": f"{PROMPT} {unique_marker()}"}], + max_completion_tokens=MAX_TOKENS, + extra_body={**NO_PROXY_CACHE, "service_tier": service_tier, "drop_params": True}, + ) + usage: Final = raw.parse().usage + assert usage is not None, "chat response carries no usage" + details: Final = usage.prompt_tokens_details + tokens: Final = _Tokens( + prompt=usage.prompt_tokens, + cached=(details.cached_tokens or 0) if details else 0, + completion=usage.completion_tokens, + ) + header_cost: Final = _assert_billed_at("base", tokens, response_header(raw.headers, "x-litellm-response-cost")) + _assert_spend_row_matches(proxy, key, header_cost) class TestSailResponses: diff --git a/tests/e2e/models.py b/tests/e2e/models.py index 4f8f6926095..8dccec8d9e1 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -949,9 +949,14 @@ class GuardrailEntityMatch(BaseModel): end: int +class GuardrailModeRecord(BaseModel): + tags: dict[str, str | list[str]] | None = None + default: str | list[str] | None = None + + class GuardrailRunRecord(BaseModel): guardrail_name: str | None = None - guardrail_mode: str | None = None + guardrail_mode: str | list[str] | GuardrailModeRecord | None = None guardrail_status: str | None = None guardrail_provider: str | None = None masked_entity_count: dict[str, int] | None = None diff --git a/tests/e2e/test_e2e_http.py b/tests/e2e/test_e2e_http.py index 7201da84924..e1c4145de8e 100644 --- a/tests/e2e/test_e2e_http.py +++ b/tests/e2e/test_e2e_http.py @@ -12,6 +12,7 @@ monkeypatches anything. from __future__ import annotations +import json from collections.abc import Callable, Iterator, Mapping, Sequence from dataclasses import dataclass from types import MappingProxyType @@ -31,6 +32,7 @@ from e2e_http import ( wire_body, without_retries, ) +from models import SpendLogs, SpendLogsPage from pydantic import BaseModel, TypeAdapter @@ -217,3 +219,55 @@ class TestClassifyEmptyBody: def test_body_that_is_not_json_is_still_a_validation_failure(self) -> None: result: Final = classify(FakeJsonResponse(status_code=200, content=b""), NoBody) assert isinstance(result, ValidationError) + + +class TestSpendLogDecoding: + @pytest.mark.parametrize("paginated", [False, True]) + @pytest.mark.parametrize( + "mode", + [ + None, + "post_call", + ["post_call"], + ["pre_call", "post_call"], + {"tags": {"audit": ["post_call"]}, "default": "pre_call"}, + ], + ) + def test_supported_guardrail_modes_preserve_neighbor_attribution_and_masked_response( + self, mode: object, paginated: bool + ) -> None: + rows: Final = [ + { + "request_id": "guarded-call", + "api_key": "scoped-key-hash", + "metadata": {"guardrail_information": [{"guardrail_mode": mode, "guardrail_status": "success"}]}, + "response": {"content": ""}, + }, + {"request_id": "health-call", "api_key": "litellm-health-check", "request_tags": ["litellm-health-check"]}, + ] + payload: Final = ( + {"data": rows, "total": 2, "page": 1, "page_size": 100, "total_pages": 1} if paginated else rows + ) + response: Final = FakeJsonResponse(status_code=200, content=json.dumps(payload).encode()) + result: Final = classify(response, SpendLogsPage) if paginated else classify(response, SpendLogs) + + assert isinstance(result, Success), result + decoded: Final = result.data.data if isinstance(result.data, SpendLogsPage) else result.data.root + assert [(row.request_id, row.api_key) for row in decoded] == [ + ("guarded-call", "scoped-key-hash"), + ("health-call", "litellm-health-check"), + ] + assert decoded[1].request_tags == ["litellm-health-check"] + assert decoded[0].response == {"content": ""} + metadata: Final = decoded[0].metadata + assert metadata is not None and metadata.guardrail_information is not None + record: Final = metadata.guardrail_information[0] + assert record.model_dump(exclude_unset=True) == {"guardrail_mode": mode, "guardrail_status": "success"} + + @pytest.mark.parametrize("mode", [5, [5], {"tags": {"audit": 5}}]) + def test_malformed_guardrail_mode_remains_a_validation_failure(self, mode: object) -> None: + payload: Final = [{"metadata": {"guardrail_information": [{"guardrail_mode": mode}]}}] + result: Final = classify(FakeJsonResponse(status_code=200, content=json.dumps(payload).encode()), SpendLogs) + + assert isinstance(result, ValidationError) + assert "guardrail_mode" in result.message diff --git a/tests/unit/llms/sail/chat/test_sail_chat_transformation.py b/tests/unit/llms/sail/chat/test_sail_chat_transformation.py index a42fb1074a0..c7b1a77343a 100644 --- a/tests/unit/llms/sail/chat/test_sail_chat_transformation.py +++ b/tests/unit/llms/sail/chat/test_sail_chat_transformation.py @@ -98,7 +98,7 @@ def test_sail_sync_chat_sends_the_tier_window( assert _window(body) == window -@pytest.mark.parametrize("service_tier", ["scale", "standard", "asap", 5, ["flex"]]) +@pytest.mark.parametrize("service_tier", ["bogus", "scale", "standard", "asap", 5, ["flex"]]) @pytest.mark.asyncio async def test_sail_chat_rejects_a_tier_with_no_window_before_sending( sail_env: None, chat_route: respx.Route, service_tier: object @@ -110,16 +110,24 @@ async def test_sail_chat_rejects_a_tier_with_no_window_before_sending( assert not chat_route.called -@pytest.mark.parametrize("service_tier", ["scale", 5]) +@pytest.mark.parametrize("service_tier", ["bogus", "scale", 5]) +@pytest.mark.parametrize(("global_drop", "request_drop"), [(False, True), (True, False)]) @pytest.mark.asyncio async def test_sail_chat_drops_an_unknown_tier_under_drop_params_and_bills_asap( - sail_env: None, chat_route: respx.Route, spend_capture: SpendCapture, service_tier: object + sail_env: None, + chat_route: respx.Route, + spend_capture: SpendCapture, + monkeypatch: pytest.MonkeyPatch, + service_tier: object, + global_drop: bool, + request_drop: bool, ) -> None: + monkeypatch.setattr(litellm, "drop_params", global_drop) await litellm.acompletion( model=MODEL, messages=MESSAGES, service_tier=service_tier, - drop_params=True, + drop_params=request_drop, litellm_call_id=spend_capture.call_id, )