mirror of
https://github.com/bytedance/deer-flow.git
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cef4224381
* fix(skills): parse allowed-tools frontmatter * fix(skills): validate allowed-tools metadata * fix(skills): add shared allowed-tools policy * fix(subagents): enforce skill allowed-tools * fix(agent): enforce skill allowed-tools * refactor(skills): dedupe TypeVar and reuse cached enabled skills - Drop redundant module-level TypeVar in tool_policy; rely on PEP 695 syntax. - Expose get_cached_enabled_skills() and have the lead agent reuse it instead of synchronously rescanning skills on every request. * fix(agent): expose config-scoped skill cache * fix(subagents): pass filtered tools explicitly * fix(skills): clean allowed-tools policy feedback
375 lines
15 KiB
Python
375 lines
15 KiB
Python
import threading
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from types import SimpleNamespace
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from typing import cast
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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.app_config import AppConfig
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from deerflow.config.subagents_config import CustomSubagentConfig, SubagentsAppConfig
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from deerflow.skills.types import Skill, SkillCategory
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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_by_config_cache.clear()
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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_self_update_section_empty_for_default_agent():
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assert prompt_module._build_self_update_section(None) == ""
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def test_build_self_update_section_present_for_custom_agent():
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section = prompt_module._build_self_update_section("my-agent")
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assert "<self_update>" in section
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assert "my-agent" in section
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assert "update_agent" in section
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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=SkillCategory.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_explicit_config_enabled_skills_are_cached_by_config_identity(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=SkillCategory.CUSTOM,
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enabled=True,
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)
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config = cast(
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AppConfig,
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cast(
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object,
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SimpleNamespace(
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skills=SimpleNamespace(container_path="/mnt/skills"),
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skill_evolution=SimpleNamespace(enabled=False),
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),
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),
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)
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load_count = 0
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def fake_get_or_new_skill_storage(**kwargs):
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nonlocal load_count
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assert kwargs == {"app_config": config}
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def load_skills(*, enabled_only):
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nonlocal load_count
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load_count += 1
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assert enabled_only is True
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return [make_skill("cached-skill")]
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return SimpleNamespace(load_skills=load_skills)
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monkeypatch.setattr(prompt_module, "get_or_new_skill_storage", fake_get_or_new_skill_storage)
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_set_skills_cache_state()
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try:
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first = prompt_module.get_skills_prompt_section(app_config=config)
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second = prompt_module.get_skills_prompt_section(app_config=config)
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assert "cached-skill" in first
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assert "cached-skill" in second
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assert load_count == 1
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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=SkillCategory.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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