321 lines
11 KiB
Python
321 lines
11 KiB
Python
from __future__ import annotations
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import os
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import pytest
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import pytest_asyncio
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from sqlalchemy import JSON, select
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from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
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os.environ["DATABASE_URL"] = "postgresql+asyncpg://tester:tester@localhost:5432/pmflow_test"
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from app.models.base import Base
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from app.models.mounted_ai_runtime import (
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MountedAgentTrace,
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MountedConversationRun,
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MountedSourceActivation,
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MountedTopicWorkspace,
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)
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from app.services.mounted_ai_runtime_write_service import MountedAIRuntimeWriteService
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def _use_sqlite_json_types() -> None:
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for table in (
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MountedTopicWorkspace.__table__,
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MountedConversationRun.__table__,
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MountedAgentTrace.__table__,
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MountedSourceActivation.__table__,
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):
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for column in table.columns:
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if column.name in {
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"facts_json",
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"goals_json",
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"constraints_json",
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"options_json",
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"open_questions",
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"pending_actions",
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"bound_entities",
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"metadata_json",
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"context_layers_hit",
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"tool_calls",
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"execution_outcome",
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"input_summary",
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"output_summary",
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"tool_trace",
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}:
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column.type = JSON()
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@pytest_asyncio.fixture
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async def db_session():
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engine = create_async_engine("sqlite+aiosqlite:///:memory:")
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_use_sqlite_json_types()
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async with engine.begin() as conn:
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await conn.run_sync(
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lambda sync_conn: Base.metadata.create_all(
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sync_conn,
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tables=[
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MountedTopicWorkspace.__table__,
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MountedConversationRun.__table__,
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MountedAgentTrace.__table__,
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MountedSourceActivation.__table__,
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],
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)
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)
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maker = async_sessionmaker(engine, expire_on_commit=False)
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async with maker() as session:
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yield session
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await engine.dispose()
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@pytest.mark.asyncio
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async def test_begin_ingress_run_uses_thread_anchor_and_sets_runtime_context(db_session) -> None:
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db_session.add(
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MountedSourceActivation(
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tenant_id=1,
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source_system="feishu",
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scope_type="chat",
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scope_ref="chat_1",
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status="active",
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cutover_mode="mounted_only",
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auto_reply_enabled=True,
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)
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)
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await db_session.commit()
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service = MountedAIRuntimeWriteService(db_session)
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tracking = await service.begin_ingress_run(
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tenant_id=1,
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source_system="feishu",
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source_message_id="om_message_1",
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message_text="帮我复盘一下这个直播需求。",
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sender="林宇航",
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channel_ref="chat_1",
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thread_context={
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"thread_id": "thread_1",
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"root_message_id": "om_root_1",
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"reply_to_message_id": "om_reply_1",
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},
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)
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await db_session.commit()
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saved_topic = (
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await db_session.execute(select(MountedTopicWorkspace))
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).scalar_one()
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saved_run = (
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await db_session.execute(select(MountedConversationRun))
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).scalar_one()
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assert tracking.topic_workspace.id == saved_topic.id
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assert saved_topic.topic_key == "feishu:chat_1:root:om_root_1"
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assert saved_topic.thread_key == "thread_1"
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assert saved_topic.last_message_id == "om_message_1"
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assert saved_run.status == "running"
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assert saved_run.mode_before is None
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assert saved_run.context_layers_hit == {
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"current_message": True,
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"thread": True,
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"topic": False,
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"source_activation": True,
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}
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assert saved_topic.metadata_json["source_activation"]["cutover_mode"] == "mounted_only"
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assert saved_run.trigger_reason == "ingress:feishu:mounted_only"
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@pytest.mark.asyncio
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async def test_record_decision_and_finalize_run_persist_topic_mode_and_traces(db_session) -> None:
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service = MountedAIRuntimeWriteService(db_session)
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tracking = await service.begin_ingress_run(
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tenant_id=1,
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source_system="feishu",
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source_message_id="om_message_2",
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message_text="分配给谁做比较合适？",
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sender="林宇航",
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channel_ref="chat_2",
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thread_context={"root_message_id": "om_root_2"},
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)
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await service.record_orchestrator_decision(
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tracking=tracking,
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workflow_route="project_signal.create",
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intent_name="signal_create",
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intent_confidence=0.82,
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trigger_reason="manual_review",
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auto_execute=False,
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work_item_id=321,
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route_metadata={"workflow_family": "project_signal", "workflow_action": "create"},
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)
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await service.finalize_run(
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tracking=tracking,
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result={
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"handled": True,
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"status": "captured",
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"classification": "command",
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"work_item_id": 321,
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"workflow_route": "project_signal.create",
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"direct_reply_text": "我先帮你收敛需求，再给负责人建议。",
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},
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)
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await db_session.commit()
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saved_topic = (
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await db_session.execute(select(MountedTopicWorkspace))
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).scalar_one()
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saved_run = (
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await db_session.execute(select(MountedConversationRun))
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).scalar_one()
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traces = (
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await db_session.execute(
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select(MountedAgentTrace).order_by(MountedAgentTrace.id.asc())
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)
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).scalars().all()
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assert saved_topic.mode == "plan"
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assert saved_topic.metadata_json["last_workflow_route"] == "project_signal.create"
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assert saved_run.mode_after == "plan"
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assert saved_run.status == "completed"
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assert saved_run.final_reply == "我先帮你收敛需求，再给负责人建议。"
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assert len(traces) == 2
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assert traces[0].agent_name == "ConversationOrchestrator"
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assert traces[1].agent_name == "ReplyComposer"
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@pytest.mark.asyncio
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async def test_begin_ingress_run_skips_unmatched_chat_when_source_activation_whitelist_exists(db_session) -> None:
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db_session.add(
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MountedSourceActivation(
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tenant_id=1,
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source_system="feishu",
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scope_type="chat",
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scope_ref="whitelisted_chat",
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status="active",
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cutover_mode="mounted_only",
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auto_reply_enabled=True,
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)
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)
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await db_session.commit()
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service = MountedAIRuntimeWriteService(db_session)
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tracking = await service.begin_ingress_run(
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tenant_id=1,
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source_system="feishu",
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source_message_id="om_message_3",
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message_text="这个 chat 不在白名单里。",
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sender="林宇航",
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channel_ref="non_whitelisted_chat",
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thread_context={"root_message_id": "om_root_3"},
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)
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assert tracking is None
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topic_rows = (await db_session.execute(select(MountedTopicWorkspace))).scalars().all()
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run_rows = (await db_session.execute(select(MountedConversationRun))).scalars().all()
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assert topic_rows == []
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assert run_rows == []
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@pytest.mark.asyncio
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async def test_begin_ingress_run_persists_conversation_scope_key_for_feishu(db_session) -> None:
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service = MountedAIRuntimeWriteService(db_session)
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tracking = await service.begin_ingress_run(
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tenant_id=1,
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source_system="feishu",
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source_message_id="om_message_4",
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message_text="想跟你聊一个新需求。",
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sender="林宇航",
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channel_ref="chat_scope_1",
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thread_context=None,
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source_sender_open_id="ou_scope_1",
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)
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await db_session.commit()
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saved_topic = (
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await db_session.execute(select(MountedTopicWorkspace))
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).scalar_one()
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assert tracking is not None
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assert saved_topic.conversation_scope_key == "feishu:chat_scope_1:ou_scope_1"
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assert saved_topic.plan_status == "idle"
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@pytest.mark.asyncio
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async def test_update_topic_plan_state_persists_explicit_plan_status_and_pending_actions(db_session) -> None:
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service = MountedAIRuntimeWriteService(db_session)
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tracking = await service.begin_ingress_run(
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tenant_id=1,
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source_system="feishu",
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source_message_id="om_message_5",
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message_text="先聊需求，不直接创建。",
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sender="林宇航",
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channel_ref="chat_plan_state",
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thread_context=None,
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source_sender_open_id="ou_plan_state",
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)
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await service.update_topic_plan_state(
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tracking=tracking,
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plan_status="awaiting_execute_confirm",
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topic_status="active",
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pending_actions=["confirm_requirement_draft"],
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metadata={"plan_topic_action": "draft_ready"},
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)
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await db_session.commit()
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saved_topic = (
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await db_session.execute(select(MountedTopicWorkspace))
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).scalar_one()
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assert saved_topic.plan_status == "awaiting_execute_confirm"
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assert saved_topic.pending_actions == ["confirm_requirement_draft"]
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assert saved_topic.metadata_json["plan_topic_action"] == "draft_ready"
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@pytest.mark.asyncio
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async def test_record_semantic_shadow_merges_with_finalize_run_execution_outcome(db_session) -> None:
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service = MountedAIRuntimeWriteService(db_session)
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tracking = await service.begin_ingress_run(
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tenant_id=1,
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source_system="feishu",
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source_message_id="om_message_6",
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message_text="先继续整理语义上下文，不要直接执行。",
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sender="林宇航",
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channel_ref="chat_semantic_shadow",
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thread_context={"root_message_id": "om_root_6"},
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source_sender_open_id="ou_semantic_shadow",
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)
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await service.record_semantic_shadow(
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tracking=tracking,
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source_message_preview="先继续整理语义上下文，不要直接执行。",
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semantic_packet_summary={"packet_version": "v1", "recent_turn_count": 2},
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semantic_decision={"topic_relation": "continue_current_topic", "mode_decision": "stay_plan"},
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semantic_gate_result={"accepted": True, "next_plan_status": "collecting"},
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semantic_diff={"changed": True, "legacy_route": "query.answer"},
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)
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await service.finalize_run(
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tracking=tracking,
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result={
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"handled": True,
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"status": "planned",
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"classification": "query",
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"work_item_id": 654,
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"workflow_route": "query.answer",
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"direct_reply_text": "我先把语义上下文整理成 shadow 观测结果。",
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},
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)
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await db_session.commit()
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saved_topic = (await db_session.execute(select(MountedTopicWorkspace))).scalar_one()
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saved_run = (await db_session.execute(select(MountedConversationRun))).scalar_one()
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assert saved_topic.plan_status == "collecting"
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assert saved_run.execution_outcome["handled"] is True
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assert saved_run.execution_outcome["semantic_packet_summary"]["packet_version"] == "v1"
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assert saved_run.execution_outcome["semantic_decision"]["mode_decision"] == "stay_plan"
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assert saved_run.execution_outcome["semantic_gate_result"]["next_plan_status"] == "collecting"
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assert saved_run.execution_outcome["semantic_diff"]["legacy_route"] == "query.answer"
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assert saved_run.execution_outcome["source_message_preview"] == "先继续整理语义上下文，不要直接执行。"
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