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