Files
deer-flow/backend/tests/test_lead_agent_model_resolution.py
JeffJiang 7de94394d4 feat(agent):Supports custom agent and chat experience with refactoring (#957)
* feat: add agent management functionality with creation, editing, and deletion

* feat: enhance agent creation and chat experience

- Added AgentWelcome component to display agent description on new thread creation.
- Improved agent name validation with availability check during agent creation.
- Updated NewAgentPage to handle agent creation flow more effectively, including enhanced error handling and user feedback.
- Refactored chat components to streamline message handling and improve user experience.
- Introduced new bootstrap skill for personalized onboarding conversations, including detailed conversation phases and a structured SOUL.md template.
- Updated localization files to reflect new features and error messages.
- General code cleanup and optimizations across various components and hooks.

* Refactor workspace layout and agent management components

- Updated WorkspaceLayout to use useLayoutEffect for sidebar state initialization.
- Removed unused AgentFormDialog and related edit functionality from AgentCard.
- Introduced ArtifactTrigger component to manage artifact visibility.
- Enhanced ChatBox to handle artifact selection and display.
- Improved message list rendering logic to avoid loading states.
- Updated localization files to remove deprecated keys and add new translations.
- Refined hooks for local settings and thread management to improve performance and clarity.
- Added temporal awareness guidelines to deep research skill documentation.

* feat: refactor chat components and introduce thread management hooks

* feat: improve artifact file detail preview logic and clean up console logs

* feat: refactor lead agent creation logic and improve logging details

* feat: validate agent name format and enhance error handling in agent setup

* feat: simplify thread search query by removing unnecessary metadata

* feat: update query key in useDeleteThread and useRenameThread for consistency

* feat: add isMock parameter to thread and artifact handling for improved testing

* fix: reorder import of setup_agent for consistency in builtins module

* feat: append mock parameter to thread links in CaseStudySection for testing purposes

* fix: update load_agent_soul calls to use cfg.name for improved clarity

* fix: update date format in apply_prompt_template for consistency

* feat: integrate isMock parameter into artifact content loading for enhanced testing

* docs: add license section to SKILL.md for clarity and attribution

* feat(agent): enhance model resolution and agent configuration handling

* chore: remove unused import of _resolve_model_name from agents

* feat(agent): remove unused field

* fix(agent): set default value for requested_model_name in _resolve_model_name function

* feat(agent): update get_available_tools call to handle optional agent_config and improve middleware function signature

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-03-03 21:32:01 +08:00

138 lines
4.6 KiB
Python

"""Tests for lead agent runtime model resolution behavior."""
from __future__ import annotations
import pytest
from src.agents.lead_agent import agent as lead_agent_module
from src.config.app_config import AppConfig
from src.config.model_config import ModelConfig
from src.config.sandbox_config import SandboxConfig
def _make_app_config(models: list[ModelConfig]) -> AppConfig:
return AppConfig(
models=models,
sandbox=SandboxConfig(use="src.sandbox.local:LocalSandboxProvider"),
)
def _make_model(name: str, *, supports_thinking: bool) -> ModelConfig:
return ModelConfig(
name=name,
display_name=name,
description=None,
use="langchain_openai:ChatOpenAI",
model=name,
supports_thinking=supports_thinking,
supports_vision=False,
)
def test_resolve_model_name_falls_back_to_default(monkeypatch, caplog):
app_config = _make_app_config(
[
_make_model("default-model", supports_thinking=False),
_make_model("other-model", supports_thinking=True),
]
)
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
with caplog.at_level("WARNING"):
resolved = lead_agent_module._resolve_model_name("missing-model")
assert resolved == "default-model"
assert "fallback to default model 'default-model'" in caplog.text
def test_resolve_model_name_uses_default_when_none(monkeypatch):
app_config = _make_app_config(
[
_make_model("default-model", supports_thinking=False),
_make_model("other-model", supports_thinking=True),
]
)
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
resolved = lead_agent_module._resolve_model_name(None)
assert resolved == "default-model"
def test_resolve_model_name_raises_when_no_models_configured(monkeypatch):
app_config = _make_app_config([])
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
with pytest.raises(
ValueError,
match="No chat models are configured",
):
lead_agent_module._resolve_model_name("missing-model")
def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkeypatch):
app_config = _make_app_config([_make_model("safe-model", supports_thinking=False)])
import src.tools as tools_module
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None: [])
captured: dict[str, object] = {}
def _fake_create_chat_model(*, name, thinking_enabled, reasoning_effort=None):
captured["name"] = name
captured["thinking_enabled"] = thinking_enabled
captured["reasoning_effort"] = reasoning_effort
return object()
monkeypatch.setattr(lead_agent_module, "create_chat_model", _fake_create_chat_model)
monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
result = lead_agent_module.make_lead_agent(
{
"configurable": {
"model_name": "safe-model",
"thinking_enabled": True,
"is_plan_mode": False,
"subagent_enabled": False,
}
}
)
assert captured["name"] == "safe-model"
assert captured["thinking_enabled"] is False
assert result["model"] is not None
def test_build_middlewares_uses_resolved_model_name_for_vision(monkeypatch):
app_config = _make_app_config(
[
_make_model("stale-model", supports_thinking=False),
ModelConfig(
name="vision-model",
display_name="vision-model",
description=None,
use="langchain_openai:ChatOpenAI",
model="vision-model",
supports_thinking=False,
supports_vision=True,
),
]
)
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda: None)
monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
middlewares = lead_agent_module._build_middlewares(
{"configurable": {"model_name": "stale-model", "is_plan_mode": False, "subagent_enabled": False}},
model_name="vision-model",
)
assert any(isinstance(m, lead_agent_module.ViewImageMiddleware) for m in middlewares)