axelray-devandXubin Ren
d1ae73a8a8
Widen thinking_style from Literal to str | None and add a @field_validator that produces a helpful error message listing valid options when an invalid value is provided. Addresses the review feedback on #4482.
63 lines
2.5 KiB
Python
63 lines
2.5 KiB
Python
"""Tests for custom provider thinking_style config passthrough."""
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from __future__ import annotations
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from nanobot.config.schema import ProviderConfig, ProvidersConfig
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from nanobot.providers.registry import create_dynamic_spec
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class TestCustomProviderThinkingStyle:
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"""Verify that thinking_style flows from config to ProviderSpec."""
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def test_default_thinking_style_is_empty(self) -> None:
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cfg = ProviderConfig()
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assert cfg.thinking_style is None
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def test_create_dynamic_spec_default(self) -> None:
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spec = create_dynamic_spec("custom")
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assert spec.thinking_style == ""
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def test_create_dynamic_spec_with_thinking_type(self) -> None:
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spec = create_dynamic_spec("custom", thinking_style="thinking_type")
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assert spec.thinking_style == "thinking_type"
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def test_create_dynamic_spec_with_enable_thinking(self) -> None:
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spec = create_dynamic_spec("custom", thinking_style="enable_thinking")
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assert spec.thinking_style == "enable_thinking"
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def test_create_dynamic_spec_with_reasoning_split(self) -> None:
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spec = create_dynamic_spec("custom", thinking_style="reasoning_split")
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assert spec.thinking_style == "reasoning_split"
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def test_provider_config_accepts_camel_case(self) -> None:
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"""Config JSON uses camelCase: thinkingStyle."""
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cfg = ProviderConfig.model_validate({"thinkingStyle": "thinking_type"})
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assert cfg.thinking_style == "thinking_type"
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def test_providers_config_custom_has_thinking_style(self) -> None:
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"""Full providers config round-trip."""
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data = {
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"custom": {
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"apiKey": "sk-test",
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"apiBase": "https://example.com/v1",
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"thinkingStyle": "enable_thinking",
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}
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}
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pc = ProvidersConfig.model_validate(data)
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assert pc.custom.thinking_style == "enable_thinking"
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def test_invalid_thinking_style_raises_with_clear_message(self) -> None:
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"""An invalid thinking_style must raise a ValidationError whose message
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lists the valid options (not just Pydantic's generic Literal error)."""
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import pytest
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from pydantic import ValidationError
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with pytest.raises(ValidationError) as exc_info:
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ProviderConfig.model_validate({"thinkingStyle": "thinking_typ"})
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message = str(exc_info.value)
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assert "Invalid thinking_style" in message
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assert "thinking_type" in message
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assert "enable_thinking" in message
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assert "reasoning_split" in message
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