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litellm/tests/integration/providers/test_databricks_decisions_wire.py
yuneng-jiang 21ab2cb87b
test: update stale integration and guardrail e2e tests to intended behavior (#48665) 
* test(integration): update stale expectations to intended provider behavior

Each expectation moved because a merged PR changed behavior on purpose.
- chatgpt string input is wrapped as one user message (#41522)
- Gemini 2.5 tool media sits beside function_response (#48428)
- sampling knobs move to Gemini 3.5 Flash, which keeps them (#47645)
- a body base_model is stripped without allow_client_pricing_override (#47639)
- ai_decide answers without usage return usage null (#48261)
- azure_ai forwards mapped client anthropic-beta values (#48033)
- the OpenCode scripted upstream mints a fresh id per request

* test(e2e-ui): type the guardrail name before deleting it

GuardrailDeleteModal requires the exact name before Delete enables since
#45893. All three guardrail delete flows now go through one helper.

* test(observability): accept any sampled traceresponse flags and expect a 400 for a non-object body

OpenTelemetry 1.45 (#48055) sets the W3C random trace id flag on new traces,
so the gateway's traceresponse now ends in -03. The producer copies the server
span's own trace flags, so the tests now accept any two-digit flags with the
sampled bit set instead of pinning -01

#48438 made a non-object JSON body a 400 "Invalid JSON payload: expected an
object" on purpose, so the [1] body case is renamed non_object_body and
expects that 400

* test(observability): stop waiting on OpenTelemetry's export log line in the langtrace outage test

The outage test waited for "Exception while exporting Span batch" in the proxy
log, which is OpenTelemetry's wording and no longer appears with 1.45. The test
keeps asserting what the gateway guarantees, callers unaffected during the
outage, a live gateway, and every span after recovery delivered once with no
outage span duplicated

* test(guardrails): count the Responses disconnect spend rows #47611 added

Since #47611 a streamed /v1/responses disconnect writes its own spend row, so
the concurrent disconnect test saw 20 rows where it counted 10 by model group.
It now reads each row's call type and expects ten acompletion rows with the
outage verdict and ten aresponses rows with success. /v1/messages disconnects
still write no row on main, so they are left out of the count rather than
pinned as absent

The responses-httpx case of the single disconnect test no longer needs its
LIT-8603 skip and passes

* test(observability): size K4's timeout from the harness boot budget

K4 boots three two-worker proxies in a row. On CircleCI each boot takes 43 to
58 seconds, so a passing run took 179.97s against its fixed 180s cap and 6 of
30 runs hit pytest-timeout. The cap and the restart gate wait now come from
readiness_seconds and graceful_stop_seconds, like other multi-boot tests
2026-10-28 01:11:25 +00:00

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import threading
import time
import uuid
from collections.abc import Mapping, Sequence
from pathlib import Path
from typing import Final
import httpx
import pytest
from integration._support.client import Gateway, Scenario, eventually, object_value, string_value
from integration._support.database import read_rows
from integration._support.process import graceful_stop_seconds, owned_proxy_process
from integration._support.timing import assert_within_factor_of_control
from integration._support.upstream import ScenarioHandle, delete_scenario, register_scenario
from integration.cost_calculation.cost_tracking_case import JsonResponse
from pydantic import JsonValue
pytestmark: Final = pytest.mark.shares_worker_state
_MODEL: Final = "ai_decide"
_ROUTE: Final = "/api/2.0/ai-functions/ai-decide"
_ENDPOINT: Final = "databricks-openjev-qwen35-4b"
_API_KEY: Final = "synthetic-databricks-key"
_ENV_KEY: Final = "synthetic-databricks-env-key"
_ENV_TOKEN: Final = "synthetic-databricks-env-token"
_STATE: Final[dict[str, JsonValue]] = {"ticket": "The export job hangs at 99%", "component": "billing"}
_TIER_CRITERIA: Final[dict[str, JsonValue]] = {"SIMPLE": "a lookup", "MEDIUM": "some work", "COMPLEX": "deep work"}
_QUESTIONS: Final[dict[str, JsonValue]] = {"tier": {"type": "choice", "criteria": _TIER_CRITERIA}}
_OPENAI_INPUT: Final = "The export job hangs at 99% in billing"
_OPENAI_TIER_QUESTION: Final[dict[str, JsonValue]] = {
"type": "choice",
"name": "tier",
"instructions": "Which tier?",
"choices": [{"value": name, "description": description} for name, description in _TIER_CRITERIA.items()],
}
_ANSWERS: Final[dict[str, JsonValue]] = {
"tier": {
"type": "choice",
"choice": "COMPLEX",
"confidence": 0.91,
"probabilities": {"SIMPLE": 0.03, "MEDIUM": 0.06, "COMPLEX": 0.91},
}
}
_USAGE: Final[dict[str, JsonValue]] = {"input_tokens": 367, "output_tokens": 3}
_ANSWER_BODY: Final[dict[str, JsonValue]] = {"model": _ENDPOINT, "answers": _ANSWERS, "usage": _USAGE}
_METADATA: Final[dict[str, JsonValue]] = {"version": "1.0"}
_AI_DECIDE_BODY: Final[dict[str, JsonValue]] = {"response": {"answers": _ANSWERS}, "metadata": _METADATA}
_SYSTEM_ONE_BODY: Final[dict[str, JsonValue]] = {
"model": None,
"answers": _ANSWERS,
"usage": None,
"metadata": _METADATA,
}
_MODEL_RULE: Final = (
"Databricks decisions model must be 'ai_decide' (the ai_decide AI Function) or a bare serving endpoint name "
"(letters, digits, '-', '_' and '.', with no '/', '?', '#', spaces, or a leading '.'), e.g. "
"databricks-openjev-qwen35-4b"
)
_MISSING_KEY: Final = "Missing API key for Decisions provider 'databricks'"
_NON_BARE_NAMES: Final[tuple[tuple[str, str], ...]] = (
("slash", "foo/bar"),
("space", "a b"),
("leading-dot", ".hidden"),
("question-mark", "a?b"),
("hash", "a#b"),
("route-path", "serving-endpoints/ai_decide"),
)
_DATABRICKS_ERRORS: Final[tuple[tuple[str, str, int, dict[str, JsonValue]], ...]] = (
(_MODEL, _ROUTE, 400, {"error_code": "BAD_REQUEST", "message": "Invalid input: questions must not be empty"}),
(_MODEL, _ROUTE, 403, {"error_code": "PERMISSION_DENIED", "message": "ai_decide is not enabled for this workspace"}),
(
_ENDPOINT,
f"/{_ENDPOINT}/invocations",
404,
{"error_code": "RESOURCE_DOES_NOT_EXIST", "message": f"Endpoint with name '{_ENDPOINT}' does not exist."},
),
)
_SPEND_QUERY: Final = (
'SELECT spend, status, call_type, model_group, custom_llm_provider, api_base FROM "LiteLLM_SpendLogs" '
"WHERE request_id = %s"
)
_OWNED_PROXY_BUDGET: Final = int(2 * graceful_stop_seconds() + 120)
_MEGABYTE_NAME: Final = "a" * 1_000_000 + "/"
_TENTH_MEGABYTE_NAME: Final = "a" * 100_000 + "/"
def _number(value: JsonValue) -> float:
assert isinstance(value, (int, float)) and not isinstance(value, bool), value
return float(value)
def _register(scenario: Scenario, body: dict[str, JsonValue], *, status: int = 200) -> ScenarioHandle:
handle: Final = register_scenario(
f"databricks-{uuid.uuid4().hex[:12]}", JsonResponse(content_type="application/json", body=body, status=status)
)
scenario.cleanups.callback(delete_scenario, handle)
return handle
def _decide(gateway: Gateway, model: str, *, key: str | None = None) -> httpx.Response:
return gateway.request("POST", "/v1/systemone", {"model": model, "state": _STATE, "questions": _QUESTIONS}, key=key)
def _observed(gateway: Gateway) -> tuple[dict[str, JsonValue], ...]:
with httpx.Client(base_url=gateway.upstream_url, timeout=5, trust_env=False) as upstream:
return tuple(map(object_value, upstream.get("/__observations").json()["requests"]))
def _reset_observations(gateway: Gateway) -> None:
with httpx.Client(base_url=gateway.upstream_url, timeout=5, trust_env=False) as upstream:
upstream.delete("/__observations").raise_for_status()
def _calls_to(requests: Sequence[dict[str, JsonValue]], handle: ScenarioHandle) -> list[dict[str, JsonValue]]:
return [request for request in requests if string_value(request["path"]).startswith(f"/{handle.scenario_id}/")]
def _upstream_calls(gateway: Gateway, handle: ScenarioHandle) -> list[dict[str, JsonValue]]:
return _calls_to(_observed(gateway), handle)
def _timed_decide_under_liveliness_probes(
gateway: Gateway, model: str
) -> tuple[httpx.Response, float, tuple[tuple[int, float], ...]]:
liveliness: Final[list[tuple[int, float]]] = []
stop: Final = threading.Event()
def poll() -> None:
while not stop.is_set():
started: Final = time.perf_counter()
probe: Final = gateway.client.get("/health/liveliness")
liveliness.append((probe.status_code, time.perf_counter() - started))
poller: Final = threading.Thread(target=poll)
poller.start()
try:
started: Final = time.perf_counter()
response: Final = _decide(gateway, model)
elapsed: Final = time.perf_counter() - started
finally:
stop.set()
poller.join()
return response, elapsed, tuple(liveliness)
def _spend_row(call_id: str) -> dict[str, JsonValue]:
rows: Final = eventually(lambda: read_rows(_SPEND_QUERY, (call_id,)), lambda found: len(found) == 1, seconds=70)
return rows[0]
def _wildcard_deployment(scenario: Scenario, **parameters: JsonValue) -> str:
prefix: Final = f"databricks-{uuid.uuid4().hex[:8]}"
created: Final = scenario.gateway.post(
"/model/new",
{"model_name": f"{prefix}/*", "litellm_params": {"model": "databricks/*", **parameters}, "model_info": {}},
)
scenario.cleanups.callback(scenario.delete_model, string_value(object_value(created["model_info"])["id"]))
return prefix
def _router_config(classifier: Mapping[str, JsonValue], simple: str, complex_: str) -> dict[str, JsonValue]:
return {
"classifier_type": "oss_classifier",
"opensource_classifier_config": dict(classifier),
"tiers": {"SIMPLE": simple, "MEDIUM": simple, "COMPLEX": complex_, "REASONING": complex_},
}
def _environment_classifier() -> dict[str, JsonValue]:
return {"provider": "databricks", "model": _MODEL, "timeout_ms": 20000, "circuit_breaker_enabled": False}
def _router(scenario: Scenario, classifier: Mapping[str, JsonValue]) -> str:
simple: Final = scenario.model(model="openai/simple-tier")
complex_: Final = scenario.model(model="openai/complex-tier")
name: Final = f"router-{uuid.uuid4().hex[:10]}"
created: Final = scenario.gateway.post(
"/model/new",
{
"model_name": name,
"litellm_params": {
"model": "auto_router/complexity_router",
"complexity_router_config": _router_config(classifier, simple, complex_),
},
"model_info": {},
},
)
scenario.cleanups.callback(scenario.delete_model, string_value(object_value(created["model_info"])["id"]))
return name
def _chat(gateway: Gateway, model: str, *, key: str | None = None) -> httpx.Response:
return gateway.request(
"POST",
"/v1/chat/completions",
{"model": model, "messages": [{"role": "user", "content": f"design a distributed cache {uuid.uuid4().hex}"}]},
key=key,
)
def _assert_classified_by_the_complex_tier(response: httpx.Response, router: str) -> None:
assert response.status_code == 200, response.text
assert response.json()["choices"][0]["message"]["content"], response.text
assert (
response.headers["x-litellm-model-group"],
response.headers["x-litellm-model-name"],
response.headers["x-litellm-complexity-router-tier"],
response.headers["x-litellm-complexity-router-cause"],
) == (router, "openai/complex-tier", "COMPLEX", "jev_classifier"), dict(response.headers)
assert "x-litellm-classifier-cost" not in response.headers, dict(response.headers)
def _assert_classifier_call(
call: Mapping[str, JsonValue], *, path: str, authorization: str, prompt_marker: str
) -> None:
assert call["path"] == path, call
assert call["authorization"] == authorization, call
body: Final = object_value(call["body"])
assert "model" not in body, body
assert prompt_marker in string_value(body["state"]), body
assert sorted(object_value(object_value(body["questions"])["tier"])) == ["criteria", "instructions", "type"], body
def _assert_refused_before_any_upstream_call(gateway: Gateway, model: str, message: str) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _AI_DECIDE_BODY)
deployment: Final = scenario.model(model=model, api_base=handle.api_base(), api_key=_API_KEY)
response: Final = _decide(gateway, deployment)
assert response.status_code == 400, response.text
assert message in response.text, response.text
assert _upstream_calls(gateway, handle) == []
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (row["status"], row["call_type"], _number(row["spend"])) == ("failure", "asystemone", 0.0), row
@pytest.mark.parametrize("name", [name for _, name in _NON_BARE_NAMES], ids=[label for label, _ in _NON_BARE_NAMES])
def test_a_deployment_naming_a_non_bare_endpoint_is_refused_before_any_upstream_call(
gateway: Gateway, name: str
) -> None:
_assert_refused_before_any_upstream_call(gateway, f"databricks/{name}", _MODEL_RULE)
def test_a_deployment_naming_no_model_is_refused_before_any_upstream_call(gateway: Gateway) -> None:
_assert_refused_before_any_upstream_call(gateway, "databricks/", "A model name is required for the Decisions API")
def test_an_openai_format_request_at_v1_decisions_reaches_the_serving_endpoint_as_system_one(gateway: Gateway) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _ANSWER_BODY)
deployment: Final = scenario.model(
model=f"databricks/{_ENDPOINT}", api_base=handle.api_base(), api_key=_API_KEY
)
response: Final = gateway.request(
"POST",
"/v1/decisions",
{
"model": deployment,
"input": _OPENAI_INPUT,
"questions": [_OPENAI_TIER_QUESTION],
},
)
assert response.status_code == 200, response.text
assert response.json() == {
"model": _ENDPOINT,
"answers": [
{
"type": "choice",
"name": "tier",
"choice": "COMPLEX",
"probabilities": [
{"value": "SIMPLE", "probability": 0.03},
{"value": "MEDIUM", "probability": 0.06},
{"value": "COMPLEX", "probability": 0.91},
],
"confidence": 0.91,
}
],
"usage": {
"input_tokens": 367,
"input_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0},
"output_tokens": 3,
"output_tokens_details": {"reasoning_tokens": 0},
"total_tokens": 370,
},
}, response.text
assert response.headers["x-litellm-model-name"] == f"databricks/{_ENDPOINT}", dict(response.headers)
(call,) = _upstream_calls(gateway, handle)
assert call["path"] == f"/{handle.scenario_id}/{_ENDPOINT}/invocations", call
assert call["authorization"] == f"Bearer {_API_KEY}", call
assert call["body"] == {
"model": _ENDPOINT,
"state": _OPENAI_INPUT,
"questions": {"tier": {"type": "choice", "instructions": "Which tier?", "criteria": _TIER_CRITERIA}},
}, call
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (
row["status"],
row["call_type"],
row["custom_llm_provider"],
row["model_group"],
row["api_base"],
_number(row["spend"]),
) == ("success", "adecisions", "databricks", deployment, f"{handle.api_base()}/{_ENDPOINT}/invocations", 0.0), (
row
)
def test_an_openai_format_request_at_v1_decisions_reaches_the_ai_decide_route_without_a_model_field(
gateway: Gateway,
) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _AI_DECIDE_BODY)
deployment: Final = scenario.model(model=f"databricks/{_MODEL}", api_base=handle.api_base(), api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/decisions",
{
"model": deployment,
"input": _OPENAI_INPUT,
"questions": [_OPENAI_TIER_QUESTION],
},
)
assert response.status_code == 200, response.text
assert response.json() == {
"model": f"databricks/{_MODEL}",
"answers": [
{
"type": "choice",
"name": "tier",
"choice": "COMPLEX",
"probabilities": [
{"value": "SIMPLE", "probability": 0.03},
{"value": "MEDIUM", "probability": 0.06},
{"value": "COMPLEX", "probability": 0.91},
],
"confidence": 0.91,
}
],
"usage": {
"input_tokens": 0,
"input_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0},
"output_tokens": 0,
"output_tokens_details": {"reasoning_tokens": 0},
"total_tokens": 0,
},
}, response.text
assert response.headers["x-litellm-model-name"] == f"databricks/{_MODEL}", dict(response.headers)
(call,) = _upstream_calls(gateway, handle)
assert call["path"] == f"/{handle.scenario_id}{_ROUTE}", call
assert call["authorization"] == f"Bearer {_API_KEY}", call
assert call["body"] == {
"state": _OPENAI_INPUT,
"questions": {"tier": {"type": "choice", "instructions": "Which tier?", "criteria": _TIER_CRITERIA}},
}, call
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (
row["status"],
row["call_type"],
row["custom_llm_provider"],
row["model_group"],
row["api_base"],
_number(row["spend"]),
) == ("success", "adecisions", "databricks", deployment, f"{handle.api_base()}{_ROUTE}", 0.0), row
def test_a_noul_probability_reaches_the_caller_as_the_system_one_noul_answer(gateway: Gateway) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(
scenario, {"response": {"answers": {"defect": {"type": "noul", "probability": 0.8}}}, "metadata": _METADATA}
)
deployment: Final = scenario.model(model=f"databricks/{_MODEL}", api_base=handle.api_base(), api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/systemone",
{"model": deployment, "state": _STATE, "questions": {"defect": {"type": "noul", "instructions": "Bug?"}}},
)
assert response.status_code == 200, response.text
assert response.json()["answers"] == {"defect": {"type": "noul", "noul": 0.8}}, response.text
(call,) = _upstream_calls(gateway, handle)
assert call["body"] == {"state": _STATE, "questions": {"defect": {"type": "noul", "instructions": "Bug?"}}}
def test_a_wildcard_deployment_sends_each_request_to_the_named_endpoint_and_bills_each_once(gateway: Gateway) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _ANSWER_BODY)
prefix: Final = _wildcard_deployment(scenario, api_base=handle.api_base(), api_key=_API_KEY)
model: Final = f"{prefix}/{_ENDPOINT}"
responses: Final = tuple(_decide(gateway, model) for _ in range(2))
for response in responses:
assert response.status_code == 200, response.text
assert response.json() == _ANSWER_BODY, response.text
assert response.headers["x-litellm-model-group"] == model, dict(response.headers)
assert response.headers["x-litellm-model-name"] == f"databricks/{_ENDPOINT}", dict(response.headers)
call_ids: Final = tuple(response.headers["x-litellm-call-id"] for response in responses)
assert len(set(call_ids)) == 2, call_ids
calls: Final = _upstream_calls(gateway, handle)
assert len(calls) == 2, calls
for call in calls:
assert call["path"] == f"/{handle.scenario_id}/{_ENDPOINT}/invocations", call
assert call["authorization"] == f"Bearer {_API_KEY}", call
assert call["body"] == {"model": _ENDPOINT, "state": _STATE, "questions": _QUESTIONS}, call
for call_id in call_ids:
row: Final = _spend_row(call_id)
assert (
row["status"],
row["call_type"],
row["custom_llm_provider"],
row["model_group"],
row["api_base"],
_number(row["spend"]),
) == ("success", "asystemone", "databricks", model, f"{handle.api_base()}/{_ENDPOINT}/invocations", 0.0), (
row
)
def test_a_wildcard_deployment_sends_each_ai_decide_request_to_the_route_and_logs_each_once(gateway: Gateway) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _AI_DECIDE_BODY)
prefix: Final = _wildcard_deployment(scenario, api_base=handle.api_base(), api_key=_API_KEY)
model: Final = f"{prefix}/{_MODEL}"
responses: Final = tuple(_decide(gateway, model) for _ in range(2))
for response in responses:
assert response.status_code == 200, response.text
assert response.json() == _SYSTEM_ONE_BODY, response.text
assert response.headers["x-litellm-model-group"] == model, dict(response.headers)
assert response.headers["x-litellm-model-name"] == f"databricks/{_MODEL}", dict(response.headers)
call_ids: Final = tuple(response.headers["x-litellm-call-id"] for response in responses)
assert len(set(call_ids)) == 2, call_ids
calls: Final = _upstream_calls(gateway, handle)
assert len(calls) == 2, calls
for call in calls:
assert call["path"] == f"/{handle.scenario_id}{_ROUTE}", call
assert call["authorization"] == f"Bearer {_API_KEY}", call
assert call["body"] == {"state": _STATE, "questions": _QUESTIONS}, call
for call_id in call_ids:
row: Final = _spend_row(call_id)
assert (
row["status"],
row["call_type"],
row["custom_llm_provider"],
row["model_group"],
row["api_base"],
_number(row["spend"]),
) == ("success", "asystemone", "databricks", model, f"{handle.api_base()}{_ROUTE}", 0.0), row
@pytest.mark.parametrize("model", (5, ["a"]), ids=("int", "list"))
def test_a_non_string_model_is_refused_at_the_gateway_without_an_upstream_call(
gateway: Gateway, model: JsonValue
) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _AI_DECIDE_BODY)
_wildcard_deployment(scenario, api_base=handle.api_base(), api_key=_API_KEY)
response: Final = gateway.request(
"POST", "/v1/systemone", {"model": model, "state": _STATE, "questions": _QUESTIONS}
)
assert 400 <= response.status_code < 500, response.text
assert _upstream_calls(gateway, handle) == []
def test_a_five_kilobyte_endpoint_name_reaches_the_upstream_and_its_not_found_answer_is_kept(gateway: Gateway) -> None:
name: Final = "n" * 5000
with gateway.scenario() as scenario:
handle: Final = _register(
scenario,
{"error_code": "RESOURCE_DOES_NOT_EXIST", "message": f"Endpoint with name '{name}' does not exist."},
status=404,
)
prefix: Final = _wildcard_deployment(scenario, api_base=handle.api_base(), api_key=_API_KEY)
response: Final = _decide(gateway, f"{prefix}/{name}")
assert response.status_code == 404, response.text[:500]
assert "RESOURCE_DOES_NOT_EXIST" in response.text, response.text[:500]
(call,) = _upstream_calls(gateway, handle)
assert call["path"] == f"/{handle.scenario_id}/{name}/invocations", call["path"][:200]
assert call["authorization"] == f"Bearer {_API_KEY}", call["authorization"]
assert call["body"] == {"model": name, "state": _STATE, "questions": _QUESTIONS}
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (row["status"], row["call_type"], row["model_group"], _number(row["spend"])) == (
"failure",
"asystemone",
f"{prefix}/{name}",
0.0,
), row
@pytest.mark.parametrize(
"name,path,status,body", _DATABRICKS_ERRORS, ids=("ai_decide-400", "ai_decide-403", "serving_endpoint-404")
)
def test_a_databricks_error_keeps_its_status_and_message_and_bills_nothing(
gateway: Gateway, name: str, path: str, status: int, body: dict[str, JsonValue]
) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, body, status=status)
model: Final = scenario.model(model=f"databricks/{name}", api_base=handle.api_base(), api_key=_API_KEY)
response: Final = _decide(gateway, model)
assert response.status_code == status, response.text
assert string_value(body["message"]) in response.text, response.text
(call,) = _upstream_calls(gateway, handle)
assert call["path"] == f"/{handle.scenario_id}{path}", call
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (row["status"], row["call_type"], row["model_group"], _number(row["spend"])) == (
"failure",
"asystemone",
model,
0.0,
), row
def test_a_deployment_without_a_key_and_no_environment_key_is_refused_before_any_upstream_call(
gateway: Gateway,
) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _AI_DECIDE_BODY)
model: Final = scenario.model(model=f"databricks/{_MODEL}", api_base=handle.api_base(), api_key=None)
response: Final = _decide(gateway, model)
assert response.status_code == 401, response.text
assert _MISSING_KEY in response.text, response.text
assert _upstream_calls(gateway, handle) == []
@pytest.mark.timeout(_OWNED_PROXY_BUDGET)
def test_the_environment_key_and_base_serve_a_deployment_a_classifier_and_a_team_member_that_leave_them_unset(
gateway: Gateway, tmp_path: Path
) -> None:
with gateway.scenario() as rig_scenario:
handle: Final = _register(rig_scenario, _AI_DECIDE_BODY)
environment_base: Final = f"{handle.api_base()}/environment-workspace/serving-endpoints"
environment_path: Final = f"/{handle.scenario_id}/environment-workspace{_ROUTE}"
environment: Final = {
"DATABRICKS_API_KEY": _ENV_KEY,
"DATABRICKS_TOKEN": _ENV_TOKEN,
"DATABRICKS_API_BASE": environment_base,
}
with owned_proxy_process(gateway, tmp_path, environment) as owned, owned.gateway.scenario() as scenario:
candidate: Final = owned.gateway
with_base: Final = scenario.model(model=f"databricks/{_MODEL}", api_base=handle.api_base(), api_key=None)
bare: Final = scenario.model(model=f"databricks/{_MODEL}", api_base=None, api_key=None)
decided: Final = tuple(_decide(candidate, model) for model in (with_base, bare))
for response in decided:
assert response.status_code == 200, response.text
assert response.json() == _SYSTEM_ONE_BODY, response.text
assert [(call["path"], call["authorization"]) for call in _upstream_calls(candidate, handle)] == [
(f"/{handle.scenario_id}{_ROUTE}", f"Bearer {_ENV_KEY}"),
(environment_path, f"Bearer {_ENV_KEY}"),
]
for response, model in zip(decided, (with_base, bare)):
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (row["status"], row["model_group"], _number(row["spend"])) == ("success", model, 0.0), row
assert (
_spend_row(decided[1].headers["x-litellm-call-id"])["api_base"]
== f"{handle.api_base()}/environment-workspace{_ROUTE}"
)
_reset_observations(candidate)
router: Final = _router(scenario, _environment_classifier())
routed: Final = _chat(candidate, router)
_assert_classified_by_the_complex_tier(routed, router)
(judge_call,) = _upstream_calls(candidate, handle)
_assert_classifier_call(
judge_call,
path=environment_path,
authorization=f"Bearer {_ENV_KEY}",
prompt_marker="design a distributed cache",
)
_reset_observations(candidate)
team: Final = scenario.team(team_member_permissions=["/auto_router/manage"])
member: Final = scenario.member(team)
member_key: Final = scenario.key(user_id=member, team_id=team)
simple: Final = scenario.model(model="openai/simple-tier")
complex_: Final = scenario.model(model="openai/complex-tier")
team_router: Final = f"team-router-{uuid.uuid4().hex[:8]}"
created: Final = candidate.request(
"POST",
"/model/new",
{
"model_name": team_router,
"litellm_params": {
"model": "auto_router/complexity_router",
"complexity_router_config": _router_config(_environment_classifier(), simple, complex_),
},
"model_info": {"team_id": team},
},
key=member_key,
)
assert created.status_code == 200, created.text
team_router_id: Final = string_value(object_value(object_value(created.json())["model_info"])["id"])
scenario.cleanups.callback(scenario.delete_model, team_router_id)
stored: Final = candidate.request("GET", "/model/info", params={"litellm_model_id": team_router_id})
assert stored.status_code == 200, stored.text
(entry,) = stored.json()["data"]
stored_classifier: Final = object_value(
object_value(object_value(object_value(entry)["litellm_params"])["complexity_router_config"])[
"opensource_classifier_config"
]
)
assert (stored_classifier["provider"], stored_classifier["model"]) == ("databricks", _MODEL), entry
assert "api_key" not in stored_classifier and "api_base" not in stored_classifier, entry
member_chat: Final = _chat(candidate, team_router, key=member_key)
_assert_classified_by_the_complex_tier(member_chat, team_router)
(member_judge_call,) = _upstream_calls(candidate, handle)
_assert_classifier_call(
member_judge_call,
path=environment_path,
authorization=f"Bearer {_ENV_KEY}",
prompt_marker="design a distributed cache",
)
@pytest.mark.timeout(_OWNED_PROXY_BUDGET)
def test_the_environment_token_serves_a_deployment_and_a_classifier_when_no_environment_key_is_set(
gateway: Gateway, tmp_path: Path
) -> None:
with gateway.scenario() as rig_scenario:
handle: Final = _register(rig_scenario, _AI_DECIDE_BODY)
environment_path: Final = f"/{handle.scenario_id}/environment-workspace{_ROUTE}"
environment: Final = {
"DATABRICKS_TOKEN": _ENV_TOKEN,
"DATABRICKS_API_BASE": f"{handle.api_base()}/environment-workspace/serving-endpoints",
}
with (
owned_proxy_process(gateway, tmp_path, environment, remove_environment=("DATABRICKS_API_KEY",)) as owned,
owned.gateway.scenario() as scenario,
):
candidate: Final = owned.gateway
bare: Final = scenario.model(model=f"databricks/{_MODEL}", api_base=None, api_key=None)
decided: Final = _decide(candidate, bare)
assert decided.status_code == 200, decided.text
assert decided.json() == _SYSTEM_ONE_BODY, decided.text
(decision_call,) = _upstream_calls(candidate, handle)
assert (decision_call["path"], decision_call["authorization"]) == (environment_path, f"Bearer {_ENV_TOKEN}")
assert _spend_row(decided.headers["x-litellm-call-id"])["status"] == "success"
_reset_observations(candidate)
router: Final = _router(scenario, _environment_classifier())
routed: Final = _chat(candidate, router)
_assert_classified_by_the_complex_tier(routed, router)
(judge_call,) = _upstream_calls(candidate, handle)
_assert_classifier_call(
judge_call,
path=environment_path,
authorization=f"Bearer {_ENV_TOKEN}",
prompt_marker="design a distributed cache",
)
def test_a_megabyte_model_name_is_refused_in_linear_time_while_liveliness_stays_up(gateway: Gateway) -> None:
with gateway.scenario() as scenario:
handle: Final = _register(scenario, _AI_DECIDE_BODY)
prefix: Final = _wildcard_deployment(scenario, api_base=handle.api_base(), api_key=_API_KEY)
model: Final = f"{prefix}/{_MEGABYTE_NAME}"
anonymous: Final = gateway.client.post(
"/v1/systemone", json={"model": model, "state": _STATE, "questions": _QUESTIONS}
)
assert anonymous.status_code == 401, anonymous.text[:300]
tenth_response, tenth_elapsed, _ = _timed_decide_under_liveliness_probes(
gateway, f"{prefix}/{_TENTH_MEGABYTE_NAME}"
)
response, elapsed, liveliness = _timed_decide_under_liveliness_probes(gateway, model)
assert tenth_response.status_code == 400, tenth_response.text[:300]
assert_within_factor_of_control(elapsed, control=tenth_elapsed, factor=25)
assert liveliness and all(status == 200 for status, _ in liveliness), liveliness
assert max(seconds for _, seconds in liveliness) < max(1.0, elapsed / 2), (elapsed, liveliness)
assert response.status_code == 400, response.text[:300]
assert _MODEL_RULE in response.text, response.text[:400]
assert _upstream_calls(gateway, handle) == []
row: Final = _spend_row(response.headers["x-litellm-call-id"])
assert (row["status"], row["call_type"], _number(row["spend"])) == ("failure", "asystemone", 0.0), row
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