342 lines
13 KiB
Python
342 lines
13 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
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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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MountedConversationRun,
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MountedDraftWorkspace,
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MountedTopicWorkspace,
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)
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from app.services.ai_pmo.semantic_context.assembler import SemanticContextAssembler
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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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MountedDraftWorkspace.__table__,
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MountedConversationRun.__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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"requirement_card",
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"draft_payload",
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"required_confirmations",
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"context_layers_hit",
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"tool_calls",
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"execution_outcome",
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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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MountedDraftWorkspace.__table__,
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MountedConversationRun.__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_semantic_context_assembler_builds_packet_from_runtime_state(db_session) -> None:
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topic = MountedTopicWorkspace(
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tenant_id=7,
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topic_key="feishu:chat_semantic:root:om_root_semantic",
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source_system="feishu",
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channel_ref="chat_semantic",
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conversation_scope_key="feishu:chat_semantic:ou_semantic",
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thread_key="thread_semantic",
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root_message_id="om_root_semantic",
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mode="plan",
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status="active",
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plan_status="collecting",
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facts_json={"title": "OpenCow 风格语义上下文迁移"},
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goals_json=["统一语义入口"],
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constraints_json={"must_not": ["db.write"]},
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open_questions=["当前是不是新需求 topic"],
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pending_actions=["continue_requirement_plan"],
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readiness_score=0.4,
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metadata_json={"last_message_preview": "这次先把语义上下文统一掉"},
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)
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db_session.add(topic)
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await db_session.flush()
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draft = MountedDraftWorkspace(
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tenant_id=7,
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topic_workspace_id=int(topic.id),
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state="collecting",
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draft_version=2,
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requirement_card={"goal": "统一语义入口", "scope": "先做 shadow mode"},
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draft_payload={"draft_text": "当前先保留 mounted runtime 作为底座"},
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required_confirmations=["需求草稿需要人工确认后才允许正式创建"],
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)
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db_session.add(draft)
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db_session.add(
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MountedConversationRun(
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tenant_id=7,
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trace_id="mounted:feishu:prev",
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topic_workspace_id=int(topic.id),
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source_system="feishu",
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source_message_id="om_prev",
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mode_before="plan",
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mode_after="plan",
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active_agent="PlanCoach",
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status="completed",
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trigger_reason="shadow",
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context_layers_hit={"topic": True},
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execution_outcome={
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"source_message_preview": "先别执行，先整理需求上下文",
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"semantic_decision": {"mode_decision": "stay_plan"},
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},
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final_reply="我先把上下文和草稿整理出来。",
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)
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)
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await db_session.commit()
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packet = await SemanticContextAssembler(db_session).assemble(
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tenant_id=7,
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operator_user_id=99,
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topic_workspace_id=int(topic.id),
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latest_user_message="这轮继续按 OpenCow 风格整理语义上下文。",
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)
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assert packet.packet_version == "v1"
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assert packet.topic.topic_key == "feishu:chat_semantic:root:om_root_semantic"
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assert packet.topic.plan_status == "collecting"
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assert packet.draft is not None
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assert packet.draft.draft_version == 2
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assert packet.mode_card.workflow_mode == "PLAN"
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assert "draft.patch" in packet.mode_card.allowed_actions
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assert "project.create" in packet.mode_card.forbidden_actions
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assert packet.thread.recent_turns[0].role == "user"
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assert packet.thread.recent_turns[-1].role == "assistant"
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assert packet.thread.open_questions == ["当前是不是新需求 topic"]
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@pytest.mark.asyncio
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async def test_semantic_context_assembler_prefers_accepted_semantic_requirement_reply_over_stale_final_reply(db_session) -> None:
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topic = MountedTopicWorkspace(
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tenant_id=7,
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topic_key="feishu:chat_semantic:root:om_root_semantic_prefer",
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source_system="feishu",
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channel_ref="chat_semantic_prefer",
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conversation_scope_key="feishu:chat_semantic_prefer:ou_semantic",
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root_message_id="om_root_semantic_prefer",
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mode="plan",
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status="active",
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plan_status="collecting",
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metadata_json={"plan_mode": True, "last_message_preview": "确认A，继续往下收。"},
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)
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db_session.add(topic)
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await db_session.flush()
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db_session.add(
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MountedConversationRun(
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tenant_id=7,
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trace_id="mounted:feishu:semantic-prefer",
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topic_workspace_id=int(topic.id),
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source_system="feishu",
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source_message_id="om_semantic_prefer_prev",
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mode_before="plan",
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mode_after="plan",
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active_agent="PlanCoach",
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status="completed",
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trigger_reason="shadow",
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context_layers_hit={"topic": True},
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execution_outcome={
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"source_message_preview": "做一个门店库存异常日报助手，先不创建项目，继续收第一版。",
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"rag_result": {
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"query_type": "plan",
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"sources": [
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{
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"source": "system",
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"metadata": {"reason_code": "requirement_planning_direct"},
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}
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],
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},
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"semantic_decision": {
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"assistant_reply": "已确认选项 A（单一层级区域经理），继续收第二轮关键信息。",
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},
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"semantic_gate_result": {"accepted": True},
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},
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final_reply="收到，确认A方向，继续收敛项目性质。",
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)
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)
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await db_session.commit()
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packet = await SemanticContextAssembler(db_session).assemble(
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tenant_id=7,
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operator_user_id=99,
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topic_workspace_id=int(topic.id),
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latest_user_message="确认A，继续往下收。",
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)
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assistant_turns = [turn.text for turn in packet.thread.recent_turns if turn.role == "assistant"]
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assert assistant_turns[-1] == "已确认选项 A（单一层级区域经理），继续收第二轮关键信息。"
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@pytest.mark.asyncio
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async def test_semantic_context_assembler_prefers_draft_title_for_thread_summary_when_topic_facts_are_minimal(db_session) -> None:
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topic = MountedTopicWorkspace(
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tenant_id=7,
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topic_key="feishu:chat_semantic:root:om_root_semantic_draft_summary",
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source_system="feishu",
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channel_ref="chat_semantic_draft_summary",
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conversation_scope_key="feishu:chat_semantic_draft_summary:ou_semantic",
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root_message_id="om_root_semantic_draft_summary",
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mode="plan",
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status="active",
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plan_status="collecting",
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facts_json={"plan_profile": "it_project"},
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metadata_json={},
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)
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db_session.add(topic)
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await db_session.flush()
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db_session.add(
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MountedDraftWorkspace(
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tenant_id=7,
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topic_workspace_id=int(topic.id),
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state="collecting",
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draft_version=1,
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requirement_card={"title": "门店库存异常晨报助手", "goal": "先收第一版需求"},
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draft_payload=None,
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required_confirmations=[],
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)
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)
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await db_session.commit()
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packet = await SemanticContextAssembler(db_session).assemble(
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tenant_id=7,
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operator_user_id=99,
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topic_workspace_id=int(topic.id),
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latest_user_message="继续往下收。",
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)
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assert packet.thread.thread_summary == "门店库存异常晨报助手"
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@pytest.mark.asyncio
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async def test_semantic_context_assembler_adds_draft_followup_ingress_actions(db_session) -> None:
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topic = MountedTopicWorkspace(
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tenant_id=7,
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topic_key="feishu:chat_semantic:root:om_root_followup",
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source_system="feishu",
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channel_ref="chat_semantic",
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conversation_scope_key="feishu:chat_semantic:ou_semantic",
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thread_key="thread_semantic",
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root_message_id="om_root_followup",
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mode="plan",
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status="active",
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plan_status="awaiting_execute_confirm",
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facts_json={"title": "换季穿搭推荐"},
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goals_json=["确认草稿"],
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constraints_json={},
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open_questions=[],
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pending_actions=[],
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readiness_score=0.8,
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metadata_json={"last_message_preview": "请确认当前草稿"},
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)
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db_session.add(topic)
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await db_session.flush()
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packet = await SemanticContextAssembler(db_session).assemble(
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tenant_id=7,
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operator_user_id=99,
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topic_workspace_id=int(topic.id),
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latest_user_message="是这种的可以很长，但是聊天内容发的那种就不行这么长",
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ingress_context={
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"candidate_kind": "draft_followup",
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"source_system": "feishu",
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"reply_anchor_present": True,
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"allowed_followup_actions": ["confirm", "revise", "regenerate", "cancel", "answer_only"],
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"thread_context": {"reply_to_message_id": "om_reply_1"},
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},
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)
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assert packet.ingress is not None
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assert packet.ingress.candidate_kind == "draft_followup"
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assert packet.ingress.reply_anchor_present is True
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assert "draft.followup.answer_only" in packet.mode_card.allowed_actions
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assert "draft.followup.regenerate" in packet.mode_card.allowed_actions
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assert "draft.followup.revise" in packet.mode_card.allowed_actions
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@pytest.mark.asyncio
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async def test_semantic_context_assembler_adds_active_context_followup_actions(db_session) -> None:
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topic = MountedTopicWorkspace(
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tenant_id=7,
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topic_key="feishu:chat_semantic:root:om_root_active_followup",
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source_system="feishu",
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channel_ref="chat_semantic",
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conversation_scope_key="feishu:chat_semantic:ou_semantic",
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thread_key="thread_semantic",
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root_message_id="om_root_active_followup",
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mode="plan",
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status="active",
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plan_status="collecting",
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facts_json={"title": "AI 直播复盘工具"},
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goals_json=["继续收敛信号源模块"],
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constraints_json={},
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open_questions=["信号源这块第一版怎么收"],
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pending_actions=[],
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readiness_score=0.5,
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metadata_json={"last_message_preview": "先把这版需求收清楚"},
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)
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db_session.add(topic)
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await db_session.flush()
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packet = await SemanticContextAssembler(db_session).assemble(
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tenant_id=7,
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operator_user_id=99,
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topic_workspace_id=int(topic.id),
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latest_user_message="信号源呢？",
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ingress_context={
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"candidate_kind": "active_context_followup",
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"source_system": "feishu",
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"reply_anchor_present": False,
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"active_context_kind": "requirement_plan",
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"allowed_context_scopes": [
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"current_requirement",
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"current_draft",
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"independent_workflow",
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"clarify",
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],
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"thread_context": {},
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},
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)
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assert packet.ingress is not None
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assert packet.ingress.candidate_kind == "active_context_followup"
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assert packet.ingress.active_context_kind == "requirement_plan"
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assert "context.followup.current_requirement" in packet.mode_card.allowed_actions
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assert "context.followup.current_draft" in packet.mode_card.allowed_actions
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assert "context.followup.independent_workflow" in packet.mode_card.allowed_actions
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assert "context.followup.clarify" in packet.mode_card.allowed_actions
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