open-swe/tests/models/test_fireworks_model.py

import pytest

from agent.dashboard.options import (
    SUPPORTED_MODEL_IDS,
    SUPPORTED_MODELS,
    model_supports_effort,
    model_supports_images,
)
from agent.utils.model import (
    fallback_model_id_for,
    fireworks_reasoning_effort_for,
    provider_model_kwargs,
)

_FIREWORKS_PREFIX = "fireworks:accounts/fireworks/models/"

NEW_FIREWORKS_MODELS = {
    "minimax-m3": (["medium", "high"], "high", True),
    "gpt-oss-120b": (["low", "medium", "high"], "medium", False),
    "deepseek-v4-flash": (["none", "medium", "high"], "high", False),
}

_ALL_EFFORTS = ("none", "low", "medium", "high", "xhigh", "max")


def test_fireworks_reasoning_effort_maps_effort() -> None:
    for effort in ("none", "low", "medium", "high", "xhigh", "max"):
        assert fireworks_reasoning_effort_for(effort) == effort
    assert fireworks_reasoning_effort_for("bogus") is None
    assert fireworks_reasoning_effort_for(None) is None


def test_provider_model_kwargs_for_fireworks() -> None:
    kwargs = provider_model_kwargs(
        "fireworks:accounts/fireworks/models/kimi-k2p7-code",
        "high",
        max_tokens=16_000,
    )
    assert kwargs["max_tokens"] == 16_000
    assert kwargs["model_kwargs"] == {"reasoning_effort": "high"}


def test_kimi_k2p7_is_supported() -> None:
    kimi_k2p7 = next(
        (m for m in SUPPORTED_MODELS if m["id"].endswith("kimi-k2p7-code")),
        None,
    )
    assert kimi_k2p7 is not None
    assert kimi_k2p7["efforts"] == ["low", "medium", "high"]
    assert "none" not in kimi_k2p7["efforts"]
    assert kimi_k2p7["default_effort"] == "high"
    kwargs = provider_model_kwargs(kimi_k2p7["id"], "high", max_tokens=16_000)
    assert kwargs["model_kwargs"] == {"reasoning_effort": "high"}


def test_provider_model_kwargs_for_fireworks_none_disables_reasoning() -> None:
    kwargs = provider_model_kwargs(
        "fireworks:accounts/fireworks/models/deepseek-v4-pro",
        "none",
        max_tokens=16_000,
    )
    assert kwargs["model_kwargs"] == {"reasoning_effort": "none"}


def test_provider_model_kwargs_for_fireworks_unknown_effort_omits_reasoning() -> None:
    kwargs = provider_model_kwargs(
        "fireworks:accounts/fireworks/models/glm-5p1",
        "bogus",
        max_tokens=16_000,
    )
    assert "model_kwargs" not in kwargs


@pytest.mark.parametrize("slug", sorted(NEW_FIREWORKS_MODELS))
def test_new_fireworks_model_is_supported(slug: str) -> None:
    model_id = _FIREWORKS_PREFIX + slug
    assert model_id in SUPPORTED_MODEL_IDS
    model = next(m for m in SUPPORTED_MODELS if m["id"] == model_id)
    efforts, default_effort, supports_images = NEW_FIREWORKS_MODELS[slug]
    assert model["efforts"] == efforts
    assert model["default_effort"] == default_effort
    assert model["supports_images"] is supports_images


@pytest.mark.parametrize("slug", sorted(NEW_FIREWORKS_MODELS))
def test_new_fireworks_model_supports_only_listed_efforts(slug: str) -> None:
    model_id = _FIREWORKS_PREFIX + slug
    efforts = NEW_FIREWORKS_MODELS[slug][0]
    for effort in efforts:
        assert model_supports_effort(model_id, effort) is True
    for effort in _ALL_EFFORTS:
        if effort not in efforts:
            assert model_supports_effort(model_id, effort) is False


@pytest.mark.parametrize(
    "slug",
    [
        "qwen3-coder-480b-a35b-instruct",
        "kimi-k2-thinking",
        "kimi-k2-instruct-0905",
        "glm-4p6",
        "mistral-large-3-fp8",
        "deepseek-v3p2",
        "qwen3-30b-a3b-instruct-2507",
    ],
)
def test_unavailable_fireworks_models_are_gated_out(slug: str) -> None:
    assert _FIREWORKS_PREFIX + slug not in SUPPORTED_MODEL_IDS


@pytest.mark.parametrize("slug", sorted(NEW_FIREWORKS_MODELS))
def test_only_minimax_m3_supports_images(slug: str) -> None:
    model_id = _FIREWORKS_PREFIX + slug
    assert model_supports_images(model_id) is (slug == "minimax-m3")


def test_fireworks_falls_back_to_bedrock() -> None:
    assert (
        fallback_model_id_for("fireworks:accounts/fireworks/models/deepseek-v4-pro")
        == "bedrock_converse:us.anthropic.claude-opus-4-8"
    )


@pytest.mark.parametrize(
    ("model_id", "effort"),
    [(m["id"], effort) for m in SUPPORTED_MODELS for effort in m["efforts"]],
)
def test_every_supported_effort_translates_to_a_reasoning_kwarg(model_id: str, effort: str) -> None:
    """Each effort surfaced in the UI must map to a provider reasoning param."""
    kwargs = provider_model_kwargs(model_id, effort, max_tokens=16_000)
    assert set(kwargs) - {"max_tokens"}, (
        f"{model_id} effort {effort!r} did not produce a reasoning kwarg"
    )