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https://github.com/bytedance/deer-flow.git
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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>
308 lines
12 KiB
Python
308 lines
12 KiB
Python
import threading
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from types import SimpleNamespace
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import anyio
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from deerflow.agents.lead_agent import prompt as prompt_module
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from deerflow.config.subagents_config import CustomSubagentConfig, SubagentsAppConfig
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from deerflow.skills.types import Skill
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def _set_skills_cache_state(*, skills=None, active=False, version=0):
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prompt_module._get_cached_skills_prompt_section.cache_clear()
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with prompt_module._enabled_skills_lock:
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prompt_module._enabled_skills_cache = skills
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prompt_module._enabled_skills_refresh_active = active
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prompt_module._enabled_skills_refresh_version = version
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prompt_module._enabled_skills_refresh_event.clear()
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def test_build_custom_mounts_section_returns_empty_when_no_mounts(monkeypatch):
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config = SimpleNamespace(sandbox=SimpleNamespace(mounts=[]))
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monkeypatch.setattr("deerflow.config.get_app_config", lambda: config)
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assert prompt_module._build_custom_mounts_section() == ""
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def test_build_custom_mounts_section_lists_configured_mounts(monkeypatch):
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mounts = [
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SimpleNamespace(container_path="/home/user/shared", read_only=False),
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SimpleNamespace(container_path="/mnt/reference", read_only=True),
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]
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config = SimpleNamespace(sandbox=SimpleNamespace(mounts=mounts))
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monkeypatch.setattr("deerflow.config.get_app_config", lambda: config)
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section = prompt_module._build_custom_mounts_section()
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assert "**Custom Mounted Directories:**" in section
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assert "`/home/user/shared`" in section
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assert "read-write" in section
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assert "`/mnt/reference`" in section
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assert "read-only" in section
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def test_build_custom_mounts_section_uses_explicit_app_config_without_global_read(monkeypatch):
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mounts = [SimpleNamespace(container_path="/home/user/shared", read_only=False)]
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config = SimpleNamespace(sandbox=SimpleNamespace(mounts=mounts))
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def fail_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("deerflow.config.get_app_config", fail_get_app_config)
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section = prompt_module._build_custom_mounts_section(app_config=config)
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assert "`/home/user/shared`" in section
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assert "read-write" in section
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def test_apply_prompt_template_includes_custom_mounts(monkeypatch):
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mounts = [SimpleNamespace(container_path="/home/user/shared", read_only=False)]
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config = SimpleNamespace(
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sandbox=SimpleNamespace(mounts=mounts),
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skills=SimpleNamespace(container_path="/mnt/skills"),
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)
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monkeypatch.setattr("deerflow.config.get_app_config", lambda: config)
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monkeypatch.setattr(prompt_module, "_get_enabled_skills", lambda: [])
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monkeypatch.setattr(prompt_module, "get_deferred_tools_prompt_section", lambda **kwargs: "")
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monkeypatch.setattr(prompt_module, "_build_acp_section", lambda **kwargs: "")
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monkeypatch.setattr(prompt_module, "_get_memory_context", lambda agent_name=None, **kwargs: "")
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monkeypatch.setattr(prompt_module, "get_agent_soul", lambda agent_name=None: "")
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prompt = prompt_module.apply_prompt_template()
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assert "`/home/user/shared`" in prompt
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assert "Custom Mounted Directories" in prompt
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def test_apply_prompt_template_includes_relative_path_guidance(monkeypatch):
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config = SimpleNamespace(
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sandbox=SimpleNamespace(mounts=[]),
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skills=SimpleNamespace(container_path="/mnt/skills"),
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)
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monkeypatch.setattr("deerflow.config.get_app_config", lambda: config)
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monkeypatch.setattr(prompt_module, "_get_enabled_skills", lambda: [])
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monkeypatch.setattr(prompt_module, "get_deferred_tools_prompt_section", lambda **kwargs: "")
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monkeypatch.setattr(prompt_module, "_build_acp_section", lambda **kwargs: "")
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monkeypatch.setattr(prompt_module, "_get_memory_context", lambda agent_name=None, **kwargs: "")
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monkeypatch.setattr(prompt_module, "get_agent_soul", lambda agent_name=None: "")
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prompt = prompt_module.apply_prompt_template()
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assert "Treat `/mnt/user-data/workspace` as your default current working directory" in prompt
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assert "`hello.txt`, `../uploads/data.csv`, and `../outputs/report.md`" in prompt
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def test_apply_prompt_template_threads_explicit_app_config_without_global_config(monkeypatch):
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mounts = [SimpleNamespace(container_path="/home/user/shared", read_only=False)]
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explicit_config = SimpleNamespace(
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sandbox=SimpleNamespace(mounts=mounts),
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skills=SimpleNamespace(container_path="/mnt/explicit-skills"),
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skill_evolution=SimpleNamespace(enabled=False),
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tool_search=SimpleNamespace(enabled=False),
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memory=SimpleNamespace(enabled=False, injection_enabled=True, max_injection_tokens=2000),
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acp_agents={},
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)
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def fail_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 fail_get_memory_config():
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raise AssertionError("ambient get_memory_config() must not be used when app_config is explicit")
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monkeypatch.setattr("deerflow.config.get_app_config", fail_get_app_config)
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monkeypatch.setattr("deerflow.config.memory_config.get_memory_config", fail_get_memory_config)
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monkeypatch.setattr(prompt_module, "get_or_new_skill_storage", lambda app_config=None: SimpleNamespace(load_skills=lambda enabled_only=True: []))
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monkeypatch.setattr(prompt_module, "get_agent_soul", lambda agent_name=None: "")
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prompt = prompt_module.apply_prompt_template(app_config=explicit_config)
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assert "`/home/user/shared`" in prompt
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assert "Custom Mounted Directories" in prompt
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def test_apply_prompt_template_threads_explicit_app_config_to_subagents_without_global_config(monkeypatch):
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explicit_config = SimpleNamespace(
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sandbox=SimpleNamespace(
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use="deerflow.sandbox.local:LocalSandboxProvider",
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allow_host_bash=False,
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mounts=[],
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),
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subagents=SubagentsAppConfig(
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custom_agents={
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"researcher": CustomSubagentConfig(
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description="Research agent\nwith details",
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system_prompt="You research.",
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)
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}
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),
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skills=SimpleNamespace(container_path="/mnt/skills"),
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skill_evolution=SimpleNamespace(enabled=False),
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tool_search=SimpleNamespace(enabled=False),
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memory=SimpleNamespace(enabled=False, injection_enabled=True, max_injection_tokens=2000),
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acp_agents={},
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)
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def fail_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 fail_get_subagents_app_config():
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raise AssertionError("ambient get_subagents_app_config() must not be used when app_config is explicit")
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monkeypatch.setattr("deerflow.config.get_app_config", fail_get_app_config)
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monkeypatch.setattr("deerflow.config.subagents_config.get_subagents_app_config", fail_get_subagents_app_config)
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monkeypatch.setattr(prompt_module, "get_or_new_skill_storage", lambda app_config=None: SimpleNamespace(load_skills=lambda enabled_only=True: []))
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monkeypatch.setattr(prompt_module, "get_agent_soul", lambda agent_name=None: "")
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prompt = prompt_module.apply_prompt_template(subagent_enabled=True, app_config=explicit_config)
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assert "**researcher**: Research agent" in prompt
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assert "**bash**" not in prompt
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def test_build_acp_section_uses_explicit_app_config_without_global_config(monkeypatch):
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explicit_config = SimpleNamespace(acp_agents={"codex": object()})
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def fail_get_acp_agents():
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raise AssertionError("ambient get_acp_agents() must not be used when app_config is explicit")
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monkeypatch.setattr("deerflow.config.acp_config.get_acp_agents", fail_get_acp_agents)
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section = prompt_module._build_acp_section(app_config=explicit_config)
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assert "ACP Agent Tasks" in section
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assert "/mnt/acp-workspace/" in section
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def test_get_memory_context_uses_explicit_app_config_without_global_config(monkeypatch):
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explicit_config = SimpleNamespace(
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memory=SimpleNamespace(enabled=True, injection_enabled=True, max_injection_tokens=1234),
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)
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captured: dict[str, object] = {}
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def fail_get_memory_config():
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raise AssertionError("ambient get_memory_config() must not be used when app_config is explicit")
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def fake_get_memory_data(agent_name=None, *, user_id=None):
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captured["agent_name"] = agent_name
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captured["user_id"] = user_id
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return {"facts": []}
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def fake_format_memory_for_injection(memory_data, *, max_tokens):
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captured["memory_data"] = memory_data
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captured["max_tokens"] = max_tokens
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return "remember this"
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monkeypatch.setattr("deerflow.config.memory_config.get_memory_config", fail_get_memory_config)
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monkeypatch.setattr("deerflow.runtime.user_context.get_effective_user_id", lambda: "user-1")
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monkeypatch.setattr("deerflow.agents.memory.get_memory_data", fake_get_memory_data)
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monkeypatch.setattr("deerflow.agents.memory.format_memory_for_injection", fake_format_memory_for_injection)
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context = prompt_module._get_memory_context("agent-a", app_config=explicit_config)
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assert "<memory>" in context
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assert "remember this" in context
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assert captured == {
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"agent_name": "agent-a",
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"user_id": "user-1",
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"memory_data": {"facts": []},
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"max_tokens": 1234,
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}
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def test_refresh_skills_system_prompt_cache_async_reloads_immediately(monkeypatch, tmp_path):
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def make_skill(name: str) -> Skill:
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skill_dir = tmp_path / name
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return Skill(
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name=name,
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description=f"Description for {name}",
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license="MIT",
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skill_dir=skill_dir,
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skill_file=skill_dir / "SKILL.md",
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relative_path=skill_dir.relative_to(tmp_path),
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category="custom",
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enabled=True,
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)
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state = {"skills": [make_skill("first-skill")]}
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monkeypatch.setattr(prompt_module, "get_or_new_skill_storage", lambda **kwargs: __import__("types").SimpleNamespace(load_skills=lambda *, enabled_only: list(state["skills"])))
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_set_skills_cache_state()
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try:
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prompt_module.warm_enabled_skills_cache()
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assert [skill.name for skill in prompt_module._get_enabled_skills()] == ["first-skill"]
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state["skills"] = [make_skill("second-skill")]
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anyio.run(prompt_module.refresh_skills_system_prompt_cache_async)
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assert [skill.name for skill in prompt_module._get_enabled_skills()] == ["second-skill"]
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finally:
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_set_skills_cache_state()
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def test_clear_cache_does_not_spawn_parallel_refresh_workers(monkeypatch, tmp_path):
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started = threading.Event()
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release = threading.Event()
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active_loads = 0
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max_active_loads = 0
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call_count = 0
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lock = threading.Lock()
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def make_skill(name: str) -> Skill:
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skill_dir = tmp_path / name
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return Skill(
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name=name,
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description=f"Description for {name}",
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license="MIT",
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skill_dir=skill_dir,
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skill_file=skill_dir / "SKILL.md",
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relative_path=skill_dir.relative_to(tmp_path),
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category="custom",
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enabled=True,
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)
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def fake_load_skills(enabled_only=True):
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nonlocal active_loads, max_active_loads, call_count
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with lock:
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active_loads += 1
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max_active_loads = max(max_active_loads, active_loads)
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call_count += 1
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current_call = call_count
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started.set()
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if current_call == 1:
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release.wait(timeout=5)
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with lock:
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active_loads -= 1
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return [make_skill(f"skill-{current_call}")]
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monkeypatch.setattr(prompt_module, "get_or_new_skill_storage", lambda **kwargs: __import__("types").SimpleNamespace(load_skills=lambda *, enabled_only: fake_load_skills(enabled_only=enabled_only)))
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_set_skills_cache_state()
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try:
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prompt_module.clear_skills_system_prompt_cache()
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assert started.wait(timeout=5)
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prompt_module.clear_skills_system_prompt_cache()
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release.set()
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prompt_module.warm_enabled_skills_cache()
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assert max_active_loads == 1
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assert [skill.name for skill in prompt_module._get_enabled_skills()] == ["skill-2"]
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finally:
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release.set()
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_set_skills_cache_state()
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def test_warm_enabled_skills_cache_logs_on_timeout(monkeypatch, caplog):
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event = threading.Event()
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monkeypatch.setattr(prompt_module, "_ensure_enabled_skills_cache", lambda: event)
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with caplog.at_level("WARNING"):
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warmed = prompt_module.warm_enabled_skills_cache(timeout_seconds=0.01)
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assert warmed is False
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assert "Timed out waiting" in caplog.text
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