98 lines
3.6 KiB
Python
98 lines
3.6 KiB
Python
"""Reasoning-effort resolution for LM Studio.
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Covers the contract that Hermes' generic effort ladder must stay monotonic
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once it is mapped onto LM Studio's narrower vocabulary: a stronger requested
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level may resolve to an equal-or-stronger LM Studio level, never a weaker one.
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"""
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from __future__ import annotations
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import pytest
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from agent.lmstudio_reasoning import resolve_lmstudio_effort
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from hermes_constants import VALID_REASONING_EFFORTS
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# Rank of each value LM Studio accepts, weakest to strongest. Used to assert
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# the resolved ladder never inverts.
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_LM_RANK = {"minimal": 0, "low": 1, "medium": 2, "high": 3, "xhigh": 4}
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@pytest.mark.parametrize("effort", ["max", "ultra"])
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def test_strong_efforts_clamp_to_lmstudio_ceiling(effort):
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""""max"/"ultra" exceed LM Studio's vocabulary and clamp to its ceiling.
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Without the clamp they miss the valid set, keep the "medium" default and
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resolve *below* "xhigh" -- more requested reasoning yielding less.
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"""
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assert resolve_lmstudio_effort({"enabled": True, "effort": effort}, None) == "xhigh"
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def test_effort_ladder_is_monotonic():
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"""Resolving Hermes' canonical ladder never produces an inversion."""
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resolved = [
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resolve_lmstudio_effort({"enabled": True, "effort": effort}, None)
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for effort in VALID_REASONING_EFFORTS
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]
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ranks = [_LM_RANK[value] for value in resolved]
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assert ranks == sorted(ranks), dict(zip(VALID_REASONING_EFFORTS, resolved))
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@pytest.mark.parametrize(
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"effort,expected",
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[
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("minimal", "minimal"),
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("low", "low"),
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("medium", "medium"),
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("high", "high"),
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("xhigh", "xhigh"),
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],
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)
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def test_levels_within_lmstudio_vocabulary_are_unchanged(effort, expected):
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"""Negative control: the clamp must not disturb levels LM Studio knows."""
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assert resolve_lmstudio_effort({"enabled": True, "effort": effort}, None) == expected
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def test_unparseable_effort_still_falls_back_to_medium():
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"""Negative control: clamping must not change the unrecognized-input path.
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This is the behaviour "max"/"ultra" were previously conflated with.
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"""
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assert resolve_lmstudio_effort({"enabled": True, "effort": "banana"}, None) == "medium"
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def test_disabled_reasoning_still_resolves_to_none():
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"""Negative control: the clamp sits after the enabled=False short-circuit."""
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assert resolve_lmstudio_effort({"enabled": False, "effort": "max"}, None) == "none"
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@pytest.mark.parametrize("effort", ["max", "ultra"])
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def test_clamped_effort_is_still_checked_against_allowed_options(effort):
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"""A clamped value stays subject to the model's published allowed set.
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"max" resolves to "xhigh"; a model that does not publish "xhigh" gets the
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field omitted (``None``) so LM Studio applies the model's own default --
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exactly how a directly-requested "xhigh" already behaves.
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"""
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assert (
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resolve_lmstudio_effort(
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{"enabled": True, "effort": effort}, ["off", "minimal", "low"]
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)
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is None
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)
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assert (
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resolve_lmstudio_effort(
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{"enabled": True, "effort": effort}, ["low", "medium", "high", "xhigh"]
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)
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== "xhigh"
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)
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def test_clamp_does_not_rewrite_published_allowed_options():
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"""The clamp must not leak into allowed_options normalization.
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A model publishing "max" is not claiming LM Studio's request vocabulary
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accepts it; allowed_options passes through untouched, so a resolved
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"xhigh" that the model does not publish is still omitted.
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"""
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assert resolve_lmstudio_effort({"enabled": True, "effort": "max"}, ["max"]) is None
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