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a26d5d32cb
* feat: add Fireworks model provider with accurate reasoning levels Adds Kimi K2.6, DeepSeek V4 Pro, Nemotron 3 Ultra, GLM 5.1 via fireworks: provider, mapping per-model reasoning_effort. Surfaces each model's real effort range (incl. openai none, deepseek xhigh/max). * fix: drop serverless-unsupported Nemotron 3 Ultra, document FIREWORKS_API_KEY --------- Co-authored-by: open-swe[bot] <215916821+open-swe[bot]@users.noreply.github.com>
59 lines
2 KiB
Python
59 lines
2 KiB
Python
import pytest
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from agent.dashboard.options import SUPPORTED_MODELS
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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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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-k2p6",
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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_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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def test_fireworks_has_no_cross_provider_fallback() -> None:
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assert fallback_model_id_for("fireworks:accounts/fireworks/models/deepseek-v4-pro") is None
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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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