120 lines
4.5 KiB
Python
120 lines
4.5 KiB
Python
from __future__ import annotations
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import asyncio
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from typing import Any
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import pytest
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from app.services.ai_pmo.semantic_context.decision_schema import SemanticDecision
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from app.services.ai_pmo.workflow_semantic_planner import WorkflowSemanticPlanner
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def _decision(*, workflows: list[dict[str, Any]], scene_metadata: dict[str, Any] | None = None) -> SemanticDecision:
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return SemanticDecision(
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topic_relation="new_topic",
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mode_decision="answer_only",
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workflow_plans=workflows,
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scene_metadata=scene_metadata or {},
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requested_actions=["workflow.bundle.compose"],
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confidence=0.91,
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)
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def test_workflow_semantic_planner_plan_message_uses_model_decision(monkeypatch: pytest.MonkeyPatch) -> None:
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async def _fake_decide(cls, *, message_text: str, source_system: str, metadata: dict[str, Any] | None = None):
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assert message_text == "帮我创建一个项目，并把这个需求接入信号源"
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assert source_system == "feishu"
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return _decision(
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workflows=[
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{
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"workflow_type": "new_project_flow",
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"workflow_action": "create",
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"target_scope": "global",
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"operation_codes": ["project.create"],
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"confidence": 0.93,
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},
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{
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"workflow_type": "signal_source_flow",
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"workflow_action": "onboard",
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"target_scope": "global",
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"operation_codes": ["signal_source.onboard"],
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"confidence": 0.92,
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},
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]
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)
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monkeypatch.setattr(WorkflowSemanticPlanner, "_decide_cold_start_semantics", classmethod(_fake_decide))
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bundle = WorkflowSemanticPlanner.plan_message(
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message_text="帮我创建一个项目，并把这个需求接入信号源",
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source_system="feishu",
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)
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assert bundle.primary_workflow == "new_project_flow"
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assert [item.workflow_type for item in bundle.workflows] == ["new_project_flow", "signal_source_flow"]
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assert bundle.reply_contract.mode == "aggregate_card"
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@pytest.mark.asyncio
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async def test_workflow_semantic_planner_aplan_message_preserves_scene_metadata(monkeypatch: pytest.MonkeyPatch) -> None:
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async def _fake_decide(cls, *, message_text: str, source_system: str, metadata: dict[str, Any] | None = None):
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assert message_text == "想跟你聊个新需求"
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return _decision(
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workflows=[
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{
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"workflow_type": "query_flow",
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"workflow_action": "answer",
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"target_scope": "global",
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"operation_codes": ["query.answer"],
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"confidence": 0.88,
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"metadata": {"message_intent": "requirement_plan"},
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}
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],
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scene_metadata={
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"message_intent": "requirement_plan",
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"consultant_mode_preference": "clarify",
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"topic_switch": "new",
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},
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)
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monkeypatch.setattr(WorkflowSemanticPlanner, "_decide_cold_start_semantics", classmethod(_fake_decide))
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bundle = await WorkflowSemanticPlanner.aplan_message(
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message_text="想跟你聊个新需求",
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source_system="feishu",
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)
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assert bundle.primary_workflow == "query_flow"
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assert bundle.workflows[0].metadata["message_intent"] == "requirement_plan"
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assert bundle.diagnostics["topic_switch"] == "new"
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def test_workflow_semantic_planner_sync_wrapper_fails_inside_running_loop() -> None:
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async def _runner() -> None:
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with pytest.raises(RuntimeError):
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WorkflowSemanticPlanner.plan_message(message_text="test", source_system="feishu")
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asyncio.run(_runner())
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def test_workflow_semantic_planner_no_longer_exposes_legacy_semantic_helpers() -> None:
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legacy_names = (
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"plan_from_intent",
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"classify_scene",
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"is_action_request_capture",
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"parse_followup_action",
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"extract_project_lookup_keyword",
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"wants_followup_continue",
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"wants_followup_status",
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"looks_like_project_create_request",
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"looks_like_task_create_request",
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"looks_like_signal_source_request",
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"looks_like_external_connect_request",
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"looks_like_contextual_write_confirmation",
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"is_query_like_question",
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"is_obvious_question",
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)
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for name in legacy_names:
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assert not hasattr(WorkflowSemanticPlanner, name), name
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