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* Add 10 Fireworks models to selectable set Surface additional Fireworks-served models in the profile editor so they can be chosen per-thread, per-profile, and as team defaults. Each entry carries its recommended efforts and image support; only MiniMax M3 is multimodal. Refs: #78 * Suppress reasoning_effort on non-reasoning models Instruct-only Fireworks ids (kimi-k2-instruct-0905, mistral-large-3-fp8, qwen3-30b-a3b-instruct-2507) don't reason, so sending reasoning_effort either 400s (unusable at default effort) or is a silent no-op. Add a per-model reasoning flag (default True) and omit the param entirely for ids marked non-reasoning. Refs: #78 * Gate out 7 undeployed Fireworks models Account serverless probe returned 404 for 7 of the 10 proposed ids, so only minimax-m3, gpt-oss-120b, and deepseek-v4-flash are callable. Keep those 3 and drop the rest. All 3 survivors are reasoning-capable, so the per-model reasoning-effort suppression added earlier is no longer needed and is reverted. Refs: #78 --------- Co-authored-by: amoussa1229 <166072409+amoussa1229@users.noreply.github.com>
134 lines
4.5 KiB
Python
134 lines
4.5 KiB
Python
import pytest
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from agent.dashboard.options import (
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SUPPORTED_MODEL_IDS,
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SUPPORTED_MODELS,
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model_supports_effort,
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model_supports_images,
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)
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from agent.utils.model import (
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fallback_model_id_for,
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fireworks_reasoning_effort_for,
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provider_model_kwargs,
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)
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_FIREWORKS_PREFIX = "fireworks:accounts/fireworks/models/"
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NEW_FIREWORKS_MODELS = {
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"minimax-m3": (["medium", "high"], "high", True),
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"gpt-oss-120b": (["low", "medium", "high"], "medium", False),
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"deepseek-v4-flash": (["none", "medium", "high"], "high", False),
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}
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_ALL_EFFORTS = ("none", "low", "medium", "high", "xhigh", "max")
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def test_fireworks_reasoning_effort_maps_effort() -> None:
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for effort in ("none", "low", "medium", "high", "xhigh", "max"):
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assert fireworks_reasoning_effort_for(effort) == effort
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assert fireworks_reasoning_effort_for("bogus") is None
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assert fireworks_reasoning_effort_for(None) is None
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def test_provider_model_kwargs_for_fireworks() -> None:
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kwargs = provider_model_kwargs(
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"fireworks:accounts/fireworks/models/kimi-k2p7-code",
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"high",
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max_tokens=16_000,
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)
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assert kwargs["max_tokens"] == 16_000
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assert kwargs["model_kwargs"] == {"reasoning_effort": "high"}
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def test_kimi_k2p7_is_supported() -> None:
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kimi_k2p7 = next(
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(m for m in SUPPORTED_MODELS if m["id"].endswith("kimi-k2p7-code")),
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None,
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)
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assert kimi_k2p7 is not None
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assert kimi_k2p7["efforts"] == ["low", "medium", "high"]
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assert "none" not in kimi_k2p7["efforts"]
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assert kimi_k2p7["default_effort"] == "high"
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kwargs = provider_model_kwargs(kimi_k2p7["id"], "high", max_tokens=16_000)
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assert kwargs["model_kwargs"] == {"reasoning_effort": "high"}
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def test_provider_model_kwargs_for_fireworks_none_disables_reasoning() -> None:
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kwargs = provider_model_kwargs(
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"fireworks:accounts/fireworks/models/deepseek-v4-pro",
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"none",
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max_tokens=16_000,
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)
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assert kwargs["model_kwargs"] == {"reasoning_effort": "none"}
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def test_provider_model_kwargs_for_fireworks_unknown_effort_omits_reasoning() -> None:
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kwargs = provider_model_kwargs(
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"fireworks:accounts/fireworks/models/glm-5p1",
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"bogus",
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max_tokens=16_000,
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)
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assert "model_kwargs" not in kwargs
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@pytest.mark.parametrize("slug", sorted(NEW_FIREWORKS_MODELS))
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def test_new_fireworks_model_is_supported(slug: str) -> None:
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model_id = _FIREWORKS_PREFIX + slug
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assert model_id in SUPPORTED_MODEL_IDS
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model = next(m for m in SUPPORTED_MODELS if m["id"] == model_id)
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efforts, default_effort, supports_images = NEW_FIREWORKS_MODELS[slug]
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assert model["efforts"] == efforts
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assert model["default_effort"] == default_effort
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assert model["supports_images"] is supports_images
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@pytest.mark.parametrize("slug", sorted(NEW_FIREWORKS_MODELS))
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def test_new_fireworks_model_supports_only_listed_efforts(slug: str) -> None:
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model_id = _FIREWORKS_PREFIX + slug
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efforts = NEW_FIREWORKS_MODELS[slug][0]
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for effort in efforts:
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assert model_supports_effort(model_id, effort) is True
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for effort in _ALL_EFFORTS:
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if effort not in efforts:
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assert model_supports_effort(model_id, effort) is False
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@pytest.mark.parametrize(
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"slug",
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[
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"qwen3-coder-480b-a35b-instruct",
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"kimi-k2-thinking",
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"kimi-k2-instruct-0905",
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"glm-4p6",
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"mistral-large-3-fp8",
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"deepseek-v3p2",
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"qwen3-30b-a3b-instruct-2507",
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],
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)
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def test_unavailable_fireworks_models_are_gated_out(slug: str) -> None:
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assert _FIREWORKS_PREFIX + slug not in SUPPORTED_MODEL_IDS
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@pytest.mark.parametrize("slug", sorted(NEW_FIREWORKS_MODELS))
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def test_only_minimax_m3_supports_images(slug: str) -> None:
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model_id = _FIREWORKS_PREFIX + slug
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assert model_supports_images(model_id) is (slug == "minimax-m3")
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def test_fireworks_falls_back_to_bedrock() -> None:
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assert (
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fallback_model_id_for("fireworks:accounts/fireworks/models/deepseek-v4-pro")
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== "bedrock_converse:us.anthropic.claude-opus-4-8"
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)
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@pytest.mark.parametrize(
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("model_id", "effort"),
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[(m["id"], effort) for m in SUPPORTED_MODELS for effort in m["efforts"]],
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)
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def test_every_supported_effort_translates_to_a_reasoning_kwarg(model_id: str, effort: str) -> None:
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"""Each effort surfaced in the UI must map to a provider reasoning param."""
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kwargs = provider_model_kwargs(model_id, effort, max_tokens=16_000)
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assert set(kwargs) - {"max_tokens"}, (
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f"{model_id} effort {effort!r} did not produce a reasoning kwarg"
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)
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