strix/tests/test_models.py
devin-ai-integration[bot] 583af23d9a
fix(llm): only attach prompt-cache points on routes LiteLLM serves (#1186)
Co-authored-by: Ahmed Allam <ahmed39652003@gmail.com>
2026-08-28 09:26:57 -07:00

154 lines
5.1 KiB
Python

"""Tests for LLM model recommendation helpers."""
from __future__ import annotations
import pytest
from agents.extensions.models.litellm_model import LitellmModel
from agents.model_settings import ModelSettings
from strix.config.models import (
RECOMMENDED_MODEL_NAMES,
StrixProvider,
_NonStreamingModel,
_TurnGuardModel,
is_recommended_or_frontier_model,
request_timeout_extra_args,
routes_through_litellm,
supports_strict_tool_schemas,
)
@pytest.mark.parametrize("model_name", RECOMMENDED_MODEL_NAMES)
def test_recommended_models_are_accepted(model_name: str) -> None:
assert is_recommended_or_frontier_model(model_name)
def test_request_timeout_extra_args_positive() -> None:
assert request_timeout_extra_args(300) == {"timeout": 300}
assert request_timeout_extra_args(10) == {"timeout": 10}
def test_request_timeout_extra_args_survives_model_settings_json_dump() -> None:
"""The Chat Completions and LiteLLM paths pydantic-serialize ModelSettings for
their tracing span; a non-JSON-serializable timeout fails every turn there."""
settings = ModelSettings(extra_args=request_timeout_extra_args(300))
assert settings.to_json_dict()["extra_args"] == {"timeout": 300}
@pytest.mark.parametrize("value", [None, 0, -1])
def test_request_timeout_extra_args_disabled(value: float | None) -> None:
assert request_timeout_extra_args(value) is None
def test_recommended_models_are_matched_case_insensitively() -> None:
assert is_recommended_or_frontier_model("Vertex_AI/Gemini-3-Pro-Preview")
@pytest.mark.parametrize(
"model_name",
[
"gpt-5.5",
"chatgpt/gpt-5.4",
"litellm/openai/gpt-5.4-pro",
"azure_ai/gpt-5.5-pro",
"bedrock_mantle/openai.gpt-5.5",
"anthropic/claude-opus-5",
"anthropic/claude-opus-4-8",
"anthropic.claude-opus-4-8",
"anthropic/claude-opus-4-7",
"anthropic/claude-fable-5",
"anthropic/claude-sonnet-5",
"vertex_ai/claude-sonnet-5@default",
"vertex_ai/claude-sonnet-4-6@default",
"any-llm/anthropic/claude-sonnet-4-6",
"vertex_ai/gemini-3.1-pro-preview",
"openrouter/google/gemini-3.1-pro-preview",
"deepseek/deepseek-v4-pro",
"deepseek/deepseek-r1-0528",
"deepseek/deepseek-reasoner",
"dashscope/qwen3-max-2026-01-23",
"qwen3.7-max",
"dashscope/qwen3.8-max",
"moonshot/kimi-k2.6",
"kimi-k2.7-code",
"moonshot/kimi-k3",
],
)
def test_frontier_model_families_are_accepted(model_name: str) -> None:
assert is_recommended_or_frontier_model(model_name)
@pytest.mark.parametrize(
"model_name",
[
"",
"openai/gpt-4.1",
"anthropic/claude-3-5-sonnet-latest",
"ollama/llama3.1",
"deepseek/deepseek-chat",
"custom-ollama/gpt-5-mini-local",
"custom-provider/claude-opus-4-local",
"xai/grok-4.5",
"openrouter/x-ai/grok-4",
"mistral/mistral-medium-3-5",
"mistral/magistral-medium-latest",
],
)
def test_non_frontier_models_are_rejected(model_name: str) -> None:
assert not is_recommended_or_frontier_model(model_name)
@pytest.mark.parametrize(
"model_name",
[
"anthropic/claude-sonnet-4-6",
"bedrock/anthropic.claude-opus-4-8-v1:0",
"vertex_ai/claude-sonnet-5",
"Sonnet-5",
],
)
def test_claude_routes_reject_strict_tool_schemas(model_name: str) -> None:
assert not supports_strict_tool_schemas(model_name)
@pytest.mark.parametrize(
"model_name",
["openai/gpt-5.4", "gpt-5.4", "gemini/gemini-3.1-pro-preview", "deepseek/deepseek-v4"],
)
def test_other_routes_keep_strict_tool_schemas(model_name: str) -> None:
assert supports_strict_tool_schemas(model_name)
@pytest.mark.parametrize(
("model_name", "litellm"),
[
("claude-sonnet-4-5", False),
("openai/claude-sonnet-4-5", False),
("any-llm/anthropic/claude-sonnet-4-5", False),
("anthropic/claude-sonnet-4-5", True),
("litellm/anthropic/claude-sonnet-4-5", True),
("bedrock/anthropic.claude-sonnet-4-5-20250929-v1:0", True),
("ollama/llama3", True),
],
)
def test_routes_through_litellm_matches_the_provider(
monkeypatch: pytest.MonkeyPatch, model_name: str, litellm: bool
) -> None:
"""The helper must agree with what StrixProvider actually builds.
Callers use it to decide whether a LiteLLM-only request field is safe to
attach; on the SDK's own clients such a field raises TypeError mid-turn, so
drift here breaks every request on that route.
"""
monkeypatch.setenv("OPENAI_API_KEY", "test-key")
assert routes_through_litellm(model_name) is litellm
try:
model = StrixProvider().get_model(model_name)
except ImportError:
# any-llm's client is an optional dependency; reaching it at all already
# proves the route is not LiteLLM's.
assert not litellm
return
while isinstance(model, _NonStreamingModel | _TurnGuardModel):
model = model._inner
assert isinstance(model, LitellmModel) is litellm