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https://github.com/bytedance/deer-flow.git
synced 2026-05-23 08:25:57 +00:00
Merge refactor/config-deerflow-context into release/2.0-rc
Cherry-pick PR #2271's config refactor onto release/2.0-rc. Used 'git merge -X theirs' to auto-resolve content conflicts in favor of the PR's design (frozen AppConfig + explicit-parameter passing). Limitations: - Release-only changes that overlapped with PR's refactor in 119 files are NOT preserved — those files reflect PR's version. Follow-up commits on this branch will need to re-apply release-only modifications where meaningful. - See PR #2271 for design rationale.
This commit is contained in:
greatmengqi
@@ -8,7 +8,6 @@ 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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@@ -33,7 +32,7 @@ def _make_model(name: str, *, supports_thinking: bool) -> ModelConfig:
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)
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def test_resolve_model_name_falls_back_to_default(monkeypatch, caplog):
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def test_resolve_model_name_falls_back_to_default(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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@@ -41,16 +40,14 @@ def test_resolve_model_name_falls_back_to_default(monkeypatch, caplog):
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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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resolved = lead_agent_module._resolve_model_name(app_config, "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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def test_resolve_model_name_uses_default_when_none():
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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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@@ -58,23 +55,19 @@ def test_resolve_model_name_uses_default_when_none(monkeypatch):
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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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resolved = lead_agent_module._resolve_model_name(app_config, 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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def test_resolve_model_name_raises_when_no_models_configured():
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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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lead_agent_module._resolve_model_name(app_config, "missing-model")
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def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkeypatch):
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@@ -82,13 +75,12 @@ def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkey
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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: [])
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monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda app_config, 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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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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@@ -105,7 +97,8 @@ def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkey
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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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app_config=app_config,
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)
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assert captured["name"] == "safe-model"
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@@ -113,74 +106,6 @@ def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkey
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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: [])
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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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"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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}
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get_available_tools.assert_called_once_with(model_name="context-model", groups=None, subagent_enabled=True)
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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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@@ -197,11 +122,10 @@ def test_build_middlewares_uses_resolved_model_name_for_vision(monkeypatch):
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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_summarization_middleware", lambda _ac: 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({"configurable": {"model_name": "stale-model", "is_plan_mode": False, "subagent_enabled": False}}, model_name="vision-model", custom_middlewares=[MagicMock()])
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middlewares = lead_agent_module._build_middlewares(app_config, {"configurable": {"model_name": "stale-model", "is_plan_mode": False, "subagent_enabled": False}}, model_name="vision-model", custom_middlewares=[MagicMock()])
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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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@@ -209,12 +133,10 @@ def test_build_middlewares_uses_resolved_model_name_for_vision(monkeypatch):
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def test_create_summarization_middleware_uses_configured_model_alias(monkeypatch):
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monkeypatch.setattr(
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lead_agent_module,
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"get_summarization_config",
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lambda: SummarizationConfig(enabled=True, model_name="model-masswork"),
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)
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monkeypatch.setattr(lead_agent_module, "get_memory_config", lambda: MemoryConfig(enabled=False))
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app_config = _make_app_config([_make_model("default", supports_thinking=False)])
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patched = app_config.model_copy(update={"summarization": SummarizationConfig(enabled=True, model_name="model-masswork")})
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from unittest.mock import MagicMock
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from unittest.mock import MagicMock
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@@ -222,16 +144,16 @@ def test_create_summarization_middleware_uses_configured_model_alias(monkeypatch
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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):
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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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return fake_model
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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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monkeypatch.setattr(lead_agent_module, "SummarizationMiddleware", lambda **kwargs: kwargs)
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middleware = lead_agent_module._create_summarization_middleware()
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middleware = lead_agent_module._create_summarization_middleware(patched)
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assert captured["name"] == "model-masswork"
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assert captured["thinking_enabled"] is False
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