import pytest from src.config import ConfiguredModelSettings, DeriverSettings def _make_deriver_settings( *, MAX_INPUT_TOKENS: int = 25000, MAX_CUSTOM_INSTRUCTIONS_TOKENS: int = 2000, REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS: int = 512, REPRESENTATION_BATCH_TARGET_INPUT_TOKENS: int = 1024, REPRESENTATION_BATCH_MAX_AGE_SECONDS: int = 1800, ) -> DeriverSettings: return DeriverSettings( MODEL_CONFIG=ConfiguredModelSettings( model="gpt-5.4-mini", transport="openai", ), MAX_INPUT_TOKENS=MAX_INPUT_TOKENS, MAX_CUSTOM_INSTRUCTIONS_TOKENS=MAX_CUSTOM_INSTRUCTIONS_TOKENS, REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS=REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS, REPRESENTATION_BATCH_TARGET_INPUT_TOKENS=REPRESENTATION_BATCH_TARGET_INPUT_TOKENS, REPRESENTATION_BATCH_MAX_AGE_SECONDS=REPRESENTATION_BATCH_MAX_AGE_SECONDS, ) def test_deriver_defaults_enable_custom_instructions_at_supported_cap() -> None: settings = _make_deriver_settings() assert settings.MAX_INPUT_TOKENS == 25000 assert settings.MAX_CUSTOM_INSTRUCTIONS_TOKENS == 2000 assert settings.REPRESENTATION_BATCH_MAX_AGE_SECONDS == 1800 def test_custom_instructions_tokens_can_be_disabled_with_zero() -> None: settings = _make_deriver_settings(MAX_CUSTOM_INSTRUCTIONS_TOKENS=0) assert settings.MAX_CUSTOM_INSTRUCTIONS_TOKENS == 0 def test_custom_instructions_tokens_cannot_exceed_supported_cap() -> None: with pytest.raises(ValueError, match="less than or equal to 2000"): _make_deriver_settings(MAX_CUSTOM_INSTRUCTIONS_TOKENS=2001) def test_representation_batch_age_can_be_disabled_with_zero() -> None: settings = _make_deriver_settings(REPRESENTATION_BATCH_MAX_AGE_SECONDS=0) assert settings.REPRESENTATION_BATCH_MAX_AGE_SECONDS == 0 def test_representation_batch_age_rejects_negative_values() -> None: with pytest.raises(ValueError, match="greater than or equal to 0"): _make_deriver_settings(REPRESENTATION_BATCH_MAX_AGE_SECONDS=-1) def test_representation_batch_work_unit_target_can_be_disabled_with_zero() -> None: settings = _make_deriver_settings(REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS=0) assert settings.REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS == 0 def test_representation_batch_work_unit_target_rejects_negative_values() -> None: with pytest.raises(ValueError, match="greater than or equal to 0"): _make_deriver_settings(REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS=-1) def test_representation_batch_tokens_can_diverge() -> None: settings = _make_deriver_settings( REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS=4096, REPRESENTATION_BATCH_TARGET_INPUT_TOKENS=1024, ) assert settings.REPRESENTATION_BATCH_WORK_UNIT_TARGET_TOKENS == 4096 assert settings.REPRESENTATION_BATCH_TARGET_INPUT_TOKENS == 1024 def test_representation_batch_target_input_cannot_exceed_max_input_tokens() -> None: with pytest.raises(ValueError, match="cannot exceed max deriver input tokens"): _make_deriver_settings( MAX_INPUT_TOKENS=1000, REPRESENTATION_BATCH_TARGET_INPUT_TOKENS=2048, ) def test_legacy_representation_batch_max_tokens_is_rejected() -> None: with pytest.raises(ValueError, match="has been split into"): DeriverSettings( MODEL_CONFIG=ConfiguredModelSettings( model="gpt-5.4-mini", transport="openai", ), REPRESENTATION_BATCH_MAX_TOKENS=1024, # pyright: ignore[reportCallIssue] ) def test_legacy_representation_batch_max_tokens_env_var_is_rejected( monkeypatch: pytest.MonkeyPatch, ) -> None: monkeypatch.setenv("DERIVER_REPRESENTATION_BATCH_MAX_TOKENS", "1024") with pytest.raises(ValueError, match="has been split into"): _make_deriver_settings()