greatmengqi
8ba01dfd83
* refactor: thread app config through lead prompt * fix: honor explicit app config across runtime paths * style: format subagent executor tests * fix: thread resolved app config and guard subagents-only fallback Address two PR review findings: 1. _create_summarization_middleware passed the original (possibly None) app_config into create_chat_model, forcing the model factory back to ambient get_app_config() and risking config drift between the middleware's resolved view and the model's view. Pass the resolved AppConfig instance through end-to-end. 2. get_available_subagent_names accepted Any-typed config and forwarded it to is_host_bash_allowed, which reads ``.sandbox``. A SubagentsAppConfig (also accepted upstream as a sum-type input) has no ``.sandbox`` attribute and would be silently treated as "no sandbox configured", incorrectly disabling the bash subagent. Guard on hasattr and fall back to ambient lookup otherwise. Adds regression tests for both paths. * chore: simplify hasattr guard and tighten regression tests - Collapse if/else into ternary in get_available_subagent_names; hasattr(None, ...) is False so the explicit None check was redundant. - Drop comments that narrate the change rather than explain non-obvious WHY (test names already convey intent). - Replace stringly-typed sentinel "no-arg" in regression test with direct args tuple comparison. --------- Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
413 lines
16 KiB
Python
413 lines
16 KiB
Python
"""Tests for lead agent runtime model resolution behavior."""
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from __future__ import annotations
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import inspect
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from unittest.mock import MagicMock
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import pytest
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from deerflow.agents.lead_agent import agent as lead_agent_module
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from deerflow.config.app_config import AppConfig
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from deerflow.config.memory_config import MemoryConfig
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from deerflow.config.model_config import ModelConfig
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from deerflow.config.sandbox_config import SandboxConfig
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from deerflow.config.summarization_config import SummarizationConfig
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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="deerflow.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_make_lead_agent_signature_matches_langgraph_server_factory_abi():
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assert list(inspect.signature(lead_agent_module.make_lead_agent).parameters) == ["config"]
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def test_internal_make_lead_agent_uses_explicit_app_config(monkeypatch):
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app_config = _make_app_config([_make_model("explicit-model", supports_thinking=False)])
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import deerflow.tools as tools_module
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def _raise_get_app_config():
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raise AssertionError("ambient get_app_config() must not be used when app_config is explicit")
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monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_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, **kwargs: [])
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captured: dict[str, object] = {}
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def _fake_create_chat_model(*, name, thinking_enabled, reasoning_effort=None, app_config=None):
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captured["name"] = name
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captured["app_config"] = app_config
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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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{"configurable": {"model_name": "explicit-model"}},
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app_config=app_config,
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)
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assert captured == {
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"name": "explicit-model",
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"app_config": app_config,
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}
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assert result["model"] is not None
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def test_make_lead_agent_uses_runtime_app_config_from_context_without_global_read(monkeypatch):
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app_config = _make_app_config([_make_model("context-model", supports_thinking=False)])
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import deerflow.tools as tools_module
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def _raise_get_app_config():
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raise AssertionError("ambient get_app_config() must not be used when runtime context already carries app_config")
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monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_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, **kwargs: [])
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captured: dict[str, object] = {}
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def _fake_create_chat_model(*, name, thinking_enabled, reasoning_effort=None, app_config=None):
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captured["name"] = name
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captured["app_config"] = app_config
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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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"context": {
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"model_name": "context-model",
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"app_config": app_config,
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}
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}
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)
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assert captured == {
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"name": "context-model",
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"app_config": app_config,
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}
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assert result["model"] is not None
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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 deerflow.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, **kwargs: [])
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captured: dict[str, object] = {}
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def _fake_create_chat_model(*, name, thinking_enabled, reasoning_effort=None, app_config=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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captured["app_config"] = app_config
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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 captured["app_config"] is app_config
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assert result["model"] is not None
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def test_make_lead_agent_reads_runtime_options_from_context(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("context-model", supports_thinking=True),
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]
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)
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import deerflow.tools as tools_module
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get_available_tools = MagicMock(return_value=[])
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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", get_available_tools)
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monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
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captured: dict[str, object] = {}
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def _fake_create_chat_model(*, name, thinking_enabled, reasoning_effort=None, app_config=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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captured["app_config"] = app_config
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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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"context": {
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"model_name": "context-model",
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"thinking_enabled": False,
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"reasoning_effort": "high",
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"is_plan_mode": True,
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"subagent_enabled": True,
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"max_concurrent_subagents": 7,
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}
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}
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)
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assert captured == {
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"name": "context-model",
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"thinking_enabled": False,
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"reasoning_effort": "high",
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"app_config": app_config,
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}
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get_available_tools.assert_called_once_with(model_name="context-model", groups=None, subagent_enabled=True, app_config=app_config)
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assert result["model"] is not None
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def test_make_lead_agent_rejects_invalid_bootstrap_agent_name(monkeypatch):
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app_config = _make_app_config([_make_model("safe-model", supports_thinking=False)])
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monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
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with pytest.raises(ValueError, match="Invalid agent name"):
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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": False,
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"is_plan_mode": False,
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"subagent_enabled": False,
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"is_bootstrap": True,
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"agent_name": "../../../tmp/evil",
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}
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}
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)
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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 **kwargs: 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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custom_middlewares=[MagicMock()],
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app_config=app_config,
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)
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assert any(isinstance(m, lead_agent_module.ViewImageMiddleware) for m in middlewares)
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# verify the custom middleware is injected correctly
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assert len(middlewares) > 0 and isinstance(middlewares[-2], MagicMock)
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def test_build_middlewares_passes_explicit_app_config_to_shared_factory(monkeypatch):
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app_config = _make_app_config([_make_model("safe-model", supports_thinking=False)])
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captured: dict[str, object] = {}
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def _raise_get_app_config():
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raise AssertionError("ambient get_app_config() must not be used when app_config is explicit")
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def _fake_build_lead_runtime_middlewares(*, app_config, lazy_init):
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captured["app_config"] = app_config
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captured["lazy_init"] = lazy_init
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return ["base-middleware"]
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monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_app_config)
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monkeypatch.setattr(
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lead_agent_module,
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"build_lead_runtime_middlewares",
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_fake_build_lead_runtime_middlewares,
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)
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monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **kwargs: None)
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monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
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monkeypatch.setattr(
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lead_agent_module,
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"TitleMiddleware",
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lambda *, app_config: captured.setdefault("title_app_config", app_config) or "title-middleware",
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)
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monkeypatch.setattr(
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lead_agent_module,
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"MemoryMiddleware",
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lambda agent_name=None, *, memory_config: captured.setdefault("memory_config", memory_config) or "memory-middleware",
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)
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middlewares = lead_agent_module._build_middlewares(
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{"configurable": {"is_plan_mode": False, "subagent_enabled": False}},
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model_name="safe-model",
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app_config=app_config,
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)
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assert captured == {
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"app_config": app_config,
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"lazy_init": True,
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"title_app_config": app_config,
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"memory_config": app_config.memory,
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}
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assert middlewares[0] == "base-middleware"
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def test_create_summarization_middleware_uses_configured_model_alias(monkeypatch):
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app_config = _make_app_config([_make_model("model-masswork", supports_thinking=False)])
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app_config.summarization = SummarizationConfig(enabled=True, model_name="model-masswork")
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app_config.memory = MemoryConfig(enabled=False)
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from unittest.mock import MagicMock
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captured: dict[str, object] = {}
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fake_model = MagicMock()
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fake_model.with_config.return_value = fake_model
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def _fake_create_chat_model(*, name=None, thinking_enabled, reasoning_effort=None, app_config=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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captured["app_config"] = app_config
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return fake_model
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def _raise_get_app_config():
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raise AssertionError("ambient get_app_config() must not be used when app_config is explicit")
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monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_app_config)
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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, "DeerFlowSummarizationMiddleware", lambda **kwargs: kwargs)
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middleware = lead_agent_module._create_summarization_middleware(app_config=app_config)
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assert captured["name"] == "model-masswork"
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assert captured["thinking_enabled"] is False
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assert captured["app_config"] is app_config
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assert middleware["model"] is fake_model
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fake_model.with_config.assert_called_once_with(tags=["middleware:summarize"])
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def test_create_summarization_middleware_threads_resolved_app_config_to_model(monkeypatch):
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fallback_app_config = _make_app_config([_make_model("fallback-model", supports_thinking=False)])
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fallback_app_config.summarization = SummarizationConfig(enabled=True, model_name="fallback-model")
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fallback_app_config.memory = MemoryConfig(enabled=False)
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from unittest.mock import MagicMock
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captured: dict[str, object] = {}
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fake_model = MagicMock()
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fake_model.with_config.return_value = fake_model
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def _fake_create_chat_model(*, name=None, thinking_enabled, reasoning_effort=None, app_config=None):
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captured["app_config"] = app_config
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return fake_model
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monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: fallback_app_config)
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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, "DeerFlowSummarizationMiddleware", lambda **kwargs: kwargs)
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lead_agent_module._create_summarization_middleware()
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assert captured["app_config"] is fallback_app_config
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def test_memory_middleware_uses_explicit_memory_config_without_global_read(monkeypatch):
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from deerflow.agents.middlewares import memory_middleware as memory_middleware_module
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from deerflow.agents.middlewares.memory_middleware import MemoryMiddleware
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def _raise_get_memory_config():
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raise AssertionError("ambient get_memory_config() must not be used when memory_config is explicit")
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monkeypatch.setattr(memory_middleware_module, "get_memory_config", _raise_get_memory_config)
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middleware = MemoryMiddleware(memory_config=MemoryConfig(enabled=False))
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assert middleware.after_agent({"messages": []}, runtime=MagicMock(context={"thread_id": "thread-1"})) is None
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