nanobot/tests/agent/test_self_model_preset.py
chengyongru 6f78267c82 feat(config): add ModelPresetConfig and runtime preset switching
- Add `ModelPresetConfig` schema for named model presets
- Add `model_presets` dict to `Config` and `model_preset` field to `AgentDefaults`
- Add `resolve_preset()` to return effective model params from preset or defaults
- Add `@model_validator` to reject unknown preset names
- Update `_match_provider()` to use resolved preset model/provider
- Update `make_provider()` and `provider_signature()` to use `resolve_preset()`
- Add `model_preset` property to `AgentLoop` for atomic runtime switching
- Update `AgentLoop.from_config()` to inject a runtime `default` preset
- Wire self-tool to inspect/clear preset state
- Update CLI display strings to show active preset
2026-05-12 20:06:22 +08:00

135 lines
4.5 KiB
Python

from types import SimpleNamespace
from unittest.mock import MagicMock
import pytest
from nanobot.agent.loop import AgentLoop
from nanobot.agent.tools.self import MyTool
from nanobot.bus.queue import MessageBus
from nanobot.config.schema import ModelPresetConfig
def _provider(default_model: str, max_tokens: int = 123) -> MagicMock:
provider = MagicMock()
provider.get_default_model.return_value = default_model
provider.generation = SimpleNamespace(
max_tokens=max_tokens, temperature=0.1, reasoning_effort=None
)
return provider
def _make_loop(tmp_path, presets=None, active_preset=None):
provider = _provider("base-model")
return AgentLoop(
bus=MessageBus(),
provider=provider,
workspace=tmp_path,
model="base-model",
context_window_tokens=1000,
model_presets=presets or {},
model_preset=active_preset,
)
def test_model_preset_getter_none_when_not_set(tmp_path) -> None:
loop = _make_loop(tmp_path)
assert loop.model_preset is None
def test_model_preset_setter_updates_state(tmp_path) -> None:
presets = {
"fast": ModelPresetConfig(
model="openai/gpt-4.1",
provider="openai",
max_tokens=4096,
context_window_tokens=32_768,
temperature=0.5,
reasoning_effort="low",
)
}
loop = _make_loop(tmp_path, presets=presets)
loop.model_preset = "fast"
assert loop.model_preset == "fast"
assert loop.model == "openai/gpt-4.1"
assert loop.context_window_tokens == 32_768
assert loop.provider.generation.temperature == 0.5
assert loop.provider.generation.max_tokens == 4096
assert loop.provider.generation.reasoning_effort == "low"
def test_model_preset_setter_raises_on_unknown(tmp_path) -> None:
loop = _make_loop(tmp_path)
with pytest.raises(KeyError, match="model_preset 'missing' not found"):
loop.model_preset = "missing"
def test_model_preset_setter_raises_on_empty_string(tmp_path) -> None:
loop = _make_loop(tmp_path)
with pytest.raises(ValueError, match="model_preset must be a non-empty string"):
loop.model_preset = ""
def test_self_tool_inspect_shows_model_preset(tmp_path) -> None:
presets = {
"fast": ModelPresetConfig(model="openai/gpt-4.1"),
}
loop = _make_loop(tmp_path, presets=presets, active_preset="fast")
tool = MyTool(runtime_state=loop, modify_allowed=True)
output = tool._inspect_all()
assert "model_preset: 'fast'" in output
def test_self_tool_set_model_preset_via_modify(tmp_path) -> None:
presets = {
"fast": ModelPresetConfig(model="openai/gpt-4.1"),
}
loop = _make_loop(tmp_path, presets=presets)
tool = MyTool(runtime_state=loop, modify_allowed=True)
result = tool._modify("model_preset", "fast")
assert "Error" not in result
assert loop.model_preset == "fast"
assert loop.model == "openai/gpt-4.1"
def test_self_tool_set_model_clears_active_preset(tmp_path) -> None:
presets = {
"fast": ModelPresetConfig(model="openai/gpt-4.1"),
}
loop = _make_loop(tmp_path, presets=presets, active_preset="fast")
tool = MyTool(runtime_state=loop, modify_allowed=True)
result = tool._modify("model", "anthropic/claude-opus-4-5")
assert "Error" not in result
assert loop._active_preset is None
assert loop.model == "anthropic/claude-opus-4-5"
def test_from_config_injects_default_preset(tmp_path) -> None:
from unittest.mock import patch
from nanobot.config.schema import Config
config = Config.model_validate({
"agents": {"defaults": {"model": "openai/gpt-4.1", "workspace": str(tmp_path)}},
})
fake_provider = _provider("openai/gpt-4.1")
with patch("nanobot.providers.factory.make_provider", return_value=fake_provider):
loop = AgentLoop.from_config(config)
assert "default" in loop.model_presets
assert loop.model_presets["default"].model == "openai/gpt-4.1"
def test_from_config_preserves_existing_default_preset(tmp_path) -> None:
from unittest.mock import patch
from nanobot.config.schema import Config
config = Config.model_validate({
"agents": {"defaults": {"model": "openai/gpt-4.1", "workspace": str(tmp_path)}},
"model_presets": {
"default": {"model": "custom-model"}
},
})
fake_provider = _provider("openai/gpt-4.1")
with patch("nanobot.providers.factory.make_provider", return_value=fake_provider):
loop = AgentLoop.from_config(config)
assert loop.model_presets["default"].model == "custom-model"