269 lines
10 KiB
Python
269 lines
10 KiB
Python
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from __future__ import annotations
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from typing import Any
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import pytest
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from app.api.v1.endpoints import steward as steward_endpoint
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from app.core.config import get_settings
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from app.schemas.steward import (
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StewardRuntimeDecisionRequest,
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StewardSlotDecisionRequest,
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)
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from app.services.runtime_chat import (
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RuntimeChatCallTrace,
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RuntimeChatToolCall,
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RuntimeToolCallResult,
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)
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from app.services.steward_graph_runtime import StewardGraphRuntime
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from app.services.steward_runtime_decision_agent import STEWARD_RUNTIME_DECISION_FUNCTION_NAME
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from app.services.steward_slot_decision_agent import STEWARD_SLOT_DECISION_FUNCTION_NAME
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class _FakeRuntime:
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def __init__(
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self,
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payloads: dict[str, dict[str, Any] | None] | None = None,
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*,
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fail_functions: set[str] | None = None,
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) -> None:
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self.payloads = payloads or {}
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self.fail_functions = fail_functions or set()
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self.called_functions: list[str] = []
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self.last_messages: list[dict[str, Any]] = []
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def complete_with_tool_call(self, messages, tools, tool_choice, **kwargs):
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function_name = str(tool_choice["function"]["name"])
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self.called_functions.append(function_name)
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self.last_messages = messages
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if function_name in self.fail_functions:
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raise RuntimeError(f"{function_name} failed")
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payload = self.payloads.get(function_name)
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if payload is None:
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return RuntimeToolCallResult(tool_call=None, calls=[])
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return RuntimeToolCallResult(
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tool_call=RuntimeChatToolCall(name=function_name, arguments=payload),
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calls=[
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RuntimeChatCallTrace(
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slot=function_name,
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provider="fake",
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model="fake",
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attempt=1,
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status="succeeded",
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)
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],
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)
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class _FailingGraphRuntime:
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def __init__(self, runtime_chat_service) -> None:
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self.runtime_chat_service = runtime_chat_service
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def decide_slot(self, request):
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raise RuntimeError("langgraph runtime unavailable")
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def decide_runtime(self, request):
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raise RuntimeError("langgraph runtime unavailable")
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@pytest.fixture(autouse=True)
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def _clear_settings_cache():
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get_settings.cache_clear()
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yield
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get_settings.cache_clear()
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def test_graph_runtime_routes_slot_decision_through_langgraph_tool_node() -> None:
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runtime = _FakeRuntime(
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{
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STEWARD_SLOT_DECISION_FUNCTION_NAME: {
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"next_action": "ask_user",
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"required_fields": ["expense_type", "time_range", "location", "reason", "transport_mode"],
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"missing_fields": ["transport_mode"],
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"question": "请问您这次打算怎么出行？",
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"options": [
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{"field_key": "transport_mode", "label": "火车", "value": "火车"},
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{"field_key": "transport_mode", "label": "飞机", "value": "飞机"},
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],
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"rationale": "出行方式会影响交通费用测算。",
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}
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}
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)
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result = StewardGraphRuntime(runtime).decide_slot(
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StewardSlotDecisionRequest(
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task_type="expense_application",
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user_message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署",
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ontology_fields={
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"expense_type": "travel",
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"time_range": "2026-02-20 至 2026-02-23",
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"location": "上海",
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"reason": "国网仿生产服务器部署",
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},
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missing_fields=["transport_mode"],
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)
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)
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assert result.decision_source == "llm_function_call"
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assert result.next_action == "ask_user"
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assert result.missing_fields == ["transport_mode"]
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assert runtime.called_functions == [STEWARD_SLOT_DECISION_FUNCTION_NAME]
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def test_graph_runtime_slot_graph_falls_back_when_tool_node_fails() -> None:
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runtime = _FakeRuntime(fail_functions={STEWARD_SLOT_DECISION_FUNCTION_NAME})
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result = StewardGraphRuntime(runtime).decide_slot(
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StewardSlotDecisionRequest(
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task_type="expense_application",
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user_message="上海出差，辅助国网仿生产部署",
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ontology_fields={
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"expense_type": "travel",
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"location": "上海",
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"reason": "辅助国网仿生产部署",
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},
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missing_fields=["transport_mode"],
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)
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)
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assert result.decision_source == "rule_fallback"
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assert result.next_action == "ask_user"
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assert result.missing_fields == ["transport_mode"]
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assert any(
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trace.get("slot") == "langgraph_slot_decision"
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and trace.get("status") == "failed"
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for trace in result.model_call_traces
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)
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def test_graph_runtime_merges_memory_before_runtime_action_node() -> None:
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runtime = _FakeRuntime({STEWARD_RUNTIME_DECISION_FUNCTION_NAME: None})
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result = StewardGraphRuntime(runtime).decide_runtime(
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StewardRuntimeDecisionRequest(
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user_message="我坐高铁",
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runtime_state={},
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context_json={
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"conversation_state": {
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"steward_state": {
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"active_flow": "travel_application",
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"flows": {
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"travel_application": {
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"flow_id": "travel_application",
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"intent": "travel_application_create",
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"fields": {
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"expense_type": "travel",
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"time_range": "2026-07-02",
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"location": "北京",
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"reason": "客户现场支撑",
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},
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"missing_fields": ["transport_mode"],
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}
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},
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}
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}
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},
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)
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)
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assert result.decision_source == "rule_fallback"
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assert result.next_action == "fill_current_slot"
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assert result.field_key == "transport_mode"
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assert result.field_value == "我坐高铁"
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assert result.steward_state["flows"]["travel_application"]["fields"]["transport_mode"] == "我坐高铁"
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assert result.steward_state["flows"]["travel_application"]["missing_fields"] == []
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assert runtime.called_functions == [STEWARD_RUNTIME_DECISION_FUNCTION_NAME]
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assert "steward_state" in runtime.last_messages[-1]["content"]
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def test_graph_runtime_selected_flow_action_node_skips_model_call() -> None:
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runtime = _FakeRuntime()
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result = StewardGraphRuntime(runtime).decide_runtime(
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StewardRuntimeDecisionRequest(
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user_message="补办出差申请",
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runtime_state={
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"steward_state": {
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"active_flow": "",
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"pending_flow_confirmation": {
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"status": "pending",
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"candidate_flows": [
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{"flow_id": "travel_application", "label": "补办出差申请"},
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{"flow_id": "travel_reimbursement", "label": "发起费用报销"},
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],
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},
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"flows": {
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"travel_application": {
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"flow_id": "travel_application",
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"intent": "travel_application_create",
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"status": "pending_flow_confirmation",
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"fields": {
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"time_range": "2026-02-20",
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"location": "上海",
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"expense_type": "travel",
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"reason": "辅助国网仿生产环境部署",
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},
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"missing_fields": ["transport_mode"],
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}
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},
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}
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},
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)
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)
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assert result.decision_source == "rule_fallback"
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assert result.next_action == "continue_selected_flow"
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assert result.target_task_id == "travel_application"
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assert result.steward_state["active_flow"] == "travel_application"
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assert runtime.called_functions == []
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def test_slot_endpoint_helper_falls_back_to_legacy_agent_when_langgraph_runtime_fails(monkeypatch) -> None:
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monkeypatch.setenv("STEWARD_AGENT_RUNTIME", "langgraph")
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get_settings.cache_clear()
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monkeypatch.setattr(steward_endpoint, "StewardGraphRuntime", _FailingGraphRuntime)
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runtime = _FakeRuntime({STEWARD_SLOT_DECISION_FUNCTION_NAME: None})
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result = steward_endpoint._decide_steward_slot(
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StewardSlotDecisionRequest(
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task_type="expense_application",
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user_message="上海出差，辅助国网仿生产部署",
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ontology_fields={
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"expense_type": "travel",
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"location": "上海",
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"reason": "辅助国网仿生产部署",
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},
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missing_fields=["transport_mode"],
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),
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runtime,
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)
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assert result.decision_source == "rule_fallback"
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assert result.next_action == "ask_user"
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assert runtime.called_functions == [STEWARD_SLOT_DECISION_FUNCTION_NAME]
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def test_runtime_endpoint_helper_falls_back_to_legacy_agent_when_langgraph_runtime_fails(monkeypatch) -> None:
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monkeypatch.setenv("STEWARD_AGENT_RUNTIME", "langgraph")
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get_settings.cache_clear()
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monkeypatch.setattr(steward_endpoint, "StewardGraphRuntime", _FailingGraphRuntime)
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runtime = _FakeRuntime({STEWARD_RUNTIME_DECISION_FUNCTION_NAME: None})
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result = steward_endpoint._decide_steward_runtime(
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StewardRuntimeDecisionRequest(
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user_message="确认",
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runtime_state={
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"pending_steward_action": {
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"message_id": "msg-next-task",
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"target_task_id": "task-reimbursement-meal",
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}
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},
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),
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runtime,
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)
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assert result.decision_source == "rule_fallback"
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assert result.next_action == "continue_next_task"
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assert result.target_message_id == "msg-next-task"
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assert runtime.called_functions == [STEWARD_RUNTIME_DECISION_FUNCTION_NAME]
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