strix/tests/test_models.py

"""Tests for LLM model recommendation helpers."""

from __future__ import annotations

import pytest

from strix.config.models import RECOMMENDED_MODEL_NAMES, is_recommended_or_frontier_model


@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_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",
        "litellm/openai/gpt-5.4-pro",
        "azure_ai/gpt-5.5-pro",
        "bedrock_mantle/openai.gpt-5.5",
        "anthropic/claude-opus-4-8",
        "anthropic.claude-opus-4-8",
        "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",
        "xai/grok-4.3",
        "openrouter/x-ai/grok-4",
        "deepseek/deepseek-v4-pro",
        "deepseek/deepseek-r1-0528",
        "deepseek/deepseek-reasoner",
        "dashscope/qwen3-max-2026-01-23",
        "qwen3.7-max",
        "moonshot/kimi-k2.6",
        "kimi-k2.7-code",
        "mistral/mistral-medium-3-5",
        "mistral/magistral-medium-latest",
    ],
)
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",
    ],
)
def test_non_frontier_models_are_rejected(model_name: str) -> None:
    assert not is_recommended_or_frontier_model(model_name)