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https://github.com/hansjone/oclaw.git
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- Add runtime/plan_agent_v2 package and shims; gateway/direct_loop/WS wiring - Admin chat: interaction mode and specialist only in user menu; session API stores memory_mode and execution_mode only - POST /admin/api/chat/user-mode mirrors plan_agent_version to AIA_EXPERT_PLAN_AGENT_V2_ENABLED (v2 to 1, v1 to 0) - Composer cleanup (hidden mode select, no reasoning toggle in meta bar); tests and _local/system.env.example Co-authored-by: Cursor <cursoragent@cursor.com>
220 lines
7.5 KiB
Python
220 lines
7.5 KiB
Python
from __future__ import annotations
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from types import SimpleNamespace
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from oclaw.platform.persistence.sqlite_store import SqliteStore
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from oclaw.runtime.direct_loop import run_oclaw_direct_loop
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from oclaw.runtime.tools.base import ToolRegistry, ToolSpec
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class _Model:
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base_url = ""
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thinking_mode_enabled = False
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def chat(self, msgs, tools, on_token=None): # noqa: ANN001,ARG002
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return SimpleNamespace(content="", reasoning_content="", tool_calls=[])
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def test_direct_loop_keeps_empty_assistant_without_stub(tmp_path) -> None: # noqa: ANN001
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db = tmp_path / "ops.sqlite"
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store = SqliteStore(str(db))
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sess = store.create_session("t")
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out = run_oclaw_direct_loop(
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store=store,
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session_id=sess.id,
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lang="zh",
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system_prompt="x",
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model=_Model(),
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tools=ToolRegistry([]),
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user_text="hi",
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persist_user_message=True,
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max_tool_rounds=1,
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)
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assert out.final_text == ""
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rows = store.get_messages(session_id=sess.id, limit=10)
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assistant = [r for r in rows if getattr(r, "role", "") == "assistant"]
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assert not any("空响应" in str(getattr(r, "content", "") or "") for r in assistant)
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class _ModelRetryOnce:
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base_url = ""
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thinking_mode_enabled = False
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def __init__(self) -> None:
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self.calls = 0
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def chat(self, msgs, tools, on_token=None): # noqa: ANN001,ARG002
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self.calls += 1
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if self.calls == 1:
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return SimpleNamespace(content="", reasoning_content="", tool_calls=[])
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return SimpleNamespace(content="ok-after-retry", reasoning_content="", tool_calls=[])
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def test_direct_loop_retries_once_before_stub(tmp_path, monkeypatch) -> None: # noqa: ANN001
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db = tmp_path / "ops.sqlite"
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store = SqliteStore(str(db))
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sess = store.create_session("t")
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model = _ModelRetryOnce()
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_MAX", "1")
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_DELAY_MS", "0")
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out = run_oclaw_direct_loop(
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store=store,
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session_id=sess.id,
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lang="zh",
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system_prompt="x",
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model=model,
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tools=ToolRegistry([]),
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user_text="hi",
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persist_user_message=True,
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max_tool_rounds=1,
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)
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assert out.final_text == "ok-after-retry"
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assert model.calls == 2
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rows = store.get_messages(session_id=sess.id, limit=10)
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assistant = [r for r in rows if getattr(r, "role", "") == "assistant"]
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assert not any("空响应" in str(getattr(r, "content", "") or "") for r in assistant)
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monkeypatch.delenv("AIA_EMPTY_ASSISTANT_RETRY_MAX", raising=False)
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monkeypatch.delenv("AIA_EMPTY_ASSISTANT_RETRY_DELAY_MS", raising=False)
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class _ModelDsmlThenText:
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base_url = ""
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thinking_mode_enabled = False
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def __init__(self) -> None:
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self.calls = 0
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def chat(self, msgs, tools, on_token=None): # noqa: ANN001,ARG002
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self.calls += 1
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if self.calls == 1:
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return SimpleNamespace(
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content='<||DSML||tool_calls><||DSML||invoke name="run_command"></||DSML||invoke></||DSML||tool_calls>',
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reasoning_content="",
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tool_calls=[],
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)
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return SimpleNamespace(content="native-tools-recovered", reasoning_content="", tool_calls=[])
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def test_direct_loop_retries_when_dsml_text_tool_call(tmp_path, monkeypatch) -> None: # noqa: ANN001
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db = tmp_path / "ops.sqlite"
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store = SqliteStore(str(db))
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sess = store.create_session("t")
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model = _ModelDsmlThenText()
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_MAX", "1")
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_DELAY_MS", "0")
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dummy_tool = ToolSpec(
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name="run_command",
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description="dummy",
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parameters={"type": "object", "properties": {}, "additionalProperties": True},
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handler=lambda args: {"ok": True, "args": args},
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read_only=True,
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)
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out = run_oclaw_direct_loop(
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store=store,
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session_id=sess.id,
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lang="zh",
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system_prompt="x",
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model=model,
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tools=ToolRegistry([dummy_tool]),
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user_text="hi",
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persist_user_message=True,
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max_tool_rounds=1,
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)
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assert out.final_text == "native-tools-recovered"
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assert model.calls == 2
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class _ModelAlwaysDsml:
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base_url = ""
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thinking_mode_enabled = False
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def chat(self, msgs, tools, on_token=None): # noqa: ANN001,ARG002
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return SimpleNamespace(
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content='<||DSML||tool_calls><||DSML||invoke name="read_file"></||DSML||invoke></||DSML||tool_calls>',
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reasoning_content="",
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tool_calls=[],
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)
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def test_direct_loop_dsml_text_persisted_as_failed_tool_pair(tmp_path, monkeypatch) -> None: # noqa: ANN001
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db = tmp_path / "ops.sqlite"
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store = SqliteStore(str(db))
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sess = store.create_session("t")
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model = _ModelAlwaysDsml()
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_MAX", "1")
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_DELAY_MS", "0")
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dummy_tool = ToolSpec(
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name="read_file",
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description="dummy",
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parameters={"type": "object", "properties": {}, "additionalProperties": True},
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handler=lambda args: {"ok": True, "args": args},
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read_only=True,
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)
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out = run_oclaw_direct_loop(
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store=store,
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session_id=sess.id,
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lang="zh",
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system_prompt="x",
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model=model,
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tools=ToolRegistry([dummy_tool]),
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user_text="hi",
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persist_user_message=True,
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max_tool_rounds=1,
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)
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assert out.final_text == ""
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rows = store.get_messages(session_id=sess.id, limit=20)
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tool_rows = [r for r in rows if getattr(r, "role", "") == "tool"]
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assert tool_rows
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assert any("model_protocol_mismatch_dsml" in str(getattr(r, "content", "") or "") for r in tool_rows)
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class _ModelMixedTextualToolIntent:
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base_url = ""
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thinking_mode_enabled = False
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def chat(self, msgs, tools, on_token=None): # noqa: ANN001,ARG002
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return SimpleNamespace(
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content=(
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"输出没抓到。再来:\n\n"
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"<||DSML||tool_calls>\n"
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"<||DSML||invoke name=\"run_command\">\n"
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"<||DSML||parameter name=\"command\" string=\"true\">echo test</||DSML||parameter>\n"
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"</||DSML||invoke>\n"
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"</||DSML||tool_calls>"
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),
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reasoning_content="",
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tool_calls=[],
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)
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def test_direct_loop_mixed_text_with_tool_intent_is_blocked(tmp_path, monkeypatch) -> None: # noqa: ANN001
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db = tmp_path / "ops.sqlite"
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store = SqliteStore(str(db))
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sess = store.create_session("t")
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model = _ModelMixedTextualToolIntent()
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_MAX", "1")
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monkeypatch.setenv("AIA_EMPTY_ASSISTANT_RETRY_DELAY_MS", "0")
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dummy_tool = ToolSpec(
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name="run_command",
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description="dummy",
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parameters={"type": "object", "properties": {}, "additionalProperties": True},
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handler=lambda args: {"ok": True, "args": args},
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read_only=True,
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)
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out = run_oclaw_direct_loop(
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store=store,
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session_id=sess.id,
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lang="zh",
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system_prompt="x",
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model=model,
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tools=ToolRegistry([dummy_tool]),
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user_text="hi",
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persist_user_message=True,
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max_tool_rounds=1,
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)
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assert out.final_text == ""
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rows = store.get_messages(session_id=sess.id, limit=20)
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tool_rows = [r for r in rows if getattr(r, "role", "") == "tool"]
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assert tool_rows
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assert any("run_command" in str(getattr(r, "tool_calls", "") or "") for r in tool_rows)
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