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1f031db66b
Add ModelPresetConfig schema and model_presets dictionary to config, enabling named bundles of model parameters (model, temperature, max_tokens, reasoning_effort, context_window_tokens) that can be switched atomically at runtime via the self tool.
85 lines
2.9 KiB
Python
85 lines
2.9 KiB
Python
# tests/agent/test_self_model_preset.py
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import asyncio
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from pathlib import Path
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from unittest.mock import MagicMock
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from nanobot.agent.loop import AgentLoop
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from nanobot.config.schema import ModelPresetConfig, MyToolConfig, ToolsConfig
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from nanobot.providers.base import GenerationSettings
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def _make_loop(presets: dict | None = None) -> tuple[AgentLoop, "MyTool"]:
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provider = MagicMock()
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provider.get_default_model.return_value = "test-model"
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provider.generation = GenerationSettings(temperature=0.1, max_tokens=8192)
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loop = AgentLoop(
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bus=MagicMock(),
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provider=provider,
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workspace=Path("/tmp/test"),
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model="test-model",
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context_window_tokens=65536,
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model_presets=presets or {},
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tools_config=ToolsConfig(my=MyToolConfig(allow_set=True)),
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)
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tool = loop.tools.get("my")
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return loop, tool
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async def test_set_model_preset_updates_all_fields() -> None:
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presets = {
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"gpt5": ModelPresetConfig(
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model="gpt-5",
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provider="openai",
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max_tokens=16384,
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context_window_tokens=128000,
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temperature=0.2,
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),
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}
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loop, tool = _make_loop(presets)
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result = await tool.execute(action="set", key="model_preset", value="gpt5")
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assert loop.model == "gpt-5"
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assert loop.context_window_tokens == 128000
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assert loop.provider.generation.temperature == 0.2
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assert loop.provider.generation.max_tokens == 16384
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assert loop._active_preset == "gpt5"
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async def test_set_model_preset_unknown_returns_error() -> None:
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loop, tool = _make_loop({})
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result = await tool.execute(action="set", key="model_preset", value="nope")
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assert "Error" in result or "not found" in result
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async def test_check_model_preset_shows_current() -> None:
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presets = {"gpt5": ModelPresetConfig(model="gpt-5", provider="openai")}
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loop, tool = _make_loop(presets)
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await tool.execute(action="set", key="model_preset", value="gpt5")
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result = await tool.execute(action="check", key="model_preset")
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assert "gpt5" in result
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async def test_check_model_presets_shows_available() -> None:
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presets = {
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"gpt5": ModelPresetConfig(model="gpt-5", provider="openai"),
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"ds": ModelPresetConfig(model="deepseek-chat", provider="deepseek"),
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}
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loop, tool = _make_loop(presets)
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result = await tool.execute(action="check", key="model_presets")
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assert "gpt5" in result
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assert "ds" in result
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async def test_set_model_directly_clears_preset() -> None:
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presets = {"gpt5": ModelPresetConfig(model="gpt-5", provider="openai")}
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loop, tool = _make_loop(presets)
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await tool.execute(action="set", key="model_preset", value="gpt5")
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assert loop._active_preset == "gpt5"
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await tool.execute(action="set", key="model", value="other-model")
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assert loop._active_preset is None
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assert loop.model == "other-model"
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