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327becb767
Introduce reviewed behavior profiles, host-owned bindings and positive capability ceilings for bounded multi-human presence across reusable transport skills. Preserve authority through promotion, delegation, and scheduled work, add exact provenance and archive-aware recall, and expose compact owner runtime controls. Co-authored-by: Ouroboros <311266734+ouroboros-agent@users.noreply.github.com>
131 lines
4.2 KiB
Python
131 lines
4.2 KiB
Python
from types import SimpleNamespace
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def test_presence_keeps_synthesis_but_skips_global_post_task_effects(tmp_path, monkeypatch):
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import ouroboros.agent_task_pipeline as pipeline
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import ouroboros.llm as llm_module
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import ouroboros.memory as memory_module
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import ouroboros.post_task_evolution as evolution
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calls = []
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monkeypatch.setattr(pipeline, "_is_root_post_task", lambda task: False)
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monkeypatch.setattr(llm_module, "LLMClient", lambda: object())
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monkeypatch.setattr(memory_module, "Memory", lambda **kwargs: object())
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monkeypatch.setattr(
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pipeline,
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"_run_chat_consolidation",
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lambda *args, **kwargs: calls.append("chat_consolidation"),
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)
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monkeypatch.setattr(
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pipeline,
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"_run_scratchpad_consolidation",
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lambda *args, **kwargs: calls.append("scratchpad_consolidation"),
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)
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monkeypatch.setattr(
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pipeline,
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"_run_task_summary",
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lambda *args, **kwargs: calls.append("summary"),
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)
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monkeypatch.setattr(
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pipeline,
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"_run_reflection",
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lambda *args, **kwargs: calls.append("reflection") or {"reflection": "ok"},
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)
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monkeypatch.setattr(
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pipeline,
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"_update_improvement_backlog",
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lambda *args, **kwargs: calls.append("backlog"),
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)
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monkeypatch.setattr(
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pipeline,
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"_apply_reflection_memory_actions",
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lambda *args, **kwargs: calls.append("memory_actions"),
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)
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monkeypatch.setattr(
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evolution,
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"maybe_promote",
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lambda *args, **kwargs: calls.append("maybe_promote"),
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)
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env = SimpleNamespace(
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drive_root=tmp_path,
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repo_dir=tmp_path,
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drive_path=lambda relative: tmp_path / relative,
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)
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task = {
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"id": "presence-1",
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"type": "presence",
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"_presence_turn": True,
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"metadata": {"presence": {"binding_id": "b" * 32}},
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}
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result = pipeline._run_post_task_processing_async(
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env,
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task,
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{"rounds": 2, "cost": 0.0},
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{"tool_calls": []},
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{},
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tmp_path / "logs",
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blocking=True,
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on_reflection=lambda *args: calls.append("on_reflection"),
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)
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assert result == {"reflection": "ok"}
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assert calls == [
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"chat_consolidation",
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"scratchpad_consolidation",
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"summary",
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"reflection",
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]
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def test_ordinary_task_retains_global_post_task_effects(tmp_path, monkeypatch):
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import ouroboros.agent_task_pipeline as pipeline
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import ouroboros.llm as llm_module
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import ouroboros.memory as memory_module
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import ouroboros.post_task_evolution as evolution
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calls = []
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monkeypatch.setattr(pipeline, "_is_root_post_task", lambda task: False)
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monkeypatch.setattr(llm_module, "LLMClient", lambda: object())
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monkeypatch.setattr(memory_module, "Memory", lambda **kwargs: object())
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monkeypatch.setattr(pipeline, "_run_chat_consolidation", lambda *args, **kwargs: None)
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monkeypatch.setattr(pipeline, "_run_scratchpad_consolidation", lambda *args, **kwargs: None)
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monkeypatch.setattr(pipeline, "_run_task_summary", lambda *args, **kwargs: None)
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monkeypatch.setattr(
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pipeline,
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"_run_reflection",
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lambda *args, **kwargs: {"reflection": "ok"},
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)
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monkeypatch.setattr(
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pipeline,
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"_update_improvement_backlog",
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lambda *args, **kwargs: calls.append("backlog"),
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)
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monkeypatch.setattr(
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pipeline,
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"_apply_reflection_memory_actions",
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lambda *args, **kwargs: calls.append("memory_actions"),
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)
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monkeypatch.setattr(
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evolution,
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"maybe_promote",
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lambda *args, **kwargs: calls.append("maybe_promote"),
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)
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env = SimpleNamespace(
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drive_root=tmp_path,
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repo_dir=tmp_path,
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drive_path=lambda relative: tmp_path / relative,
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)
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pipeline._run_post_task_processing_async(
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env,
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{"id": "ordinary-1", "type": "task"},
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{"rounds": 2, "cost": 0.0},
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{"tool_calls": []},
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{},
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tmp_path / "logs",
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blocking=True,
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on_reflection=lambda *args: calls.append("on_reflection"),
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)
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assert calls == ["backlog", "memory_actions", "maybe_promote", "on_reflection"]
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