251 lines
7.9 KiB
Python
251 lines
7.9 KiB
Python
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"""PPT 异步任务生命周期回归测试。"""
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import asyncio
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import sys
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import types
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "api"))
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from insurance.generation import task_service
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from insurance.ppt import extraction as extraction_module
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from insurance.ppt import regex_extractor
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from insurance.ppt.extraction import ExtractionOrchestrator, ExtractionResult
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from insurance.ppt.llm_client import LLMResponse, _parse_json_content, _parse_timeout_ms
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from insurance.ppt.prompts import select_key_pages
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class _Field:
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def in_(self, _values):
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return self
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class _Query:
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def filter_by(self, **_kwargs):
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return self
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def filter(self, *_args):
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return self
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def first(self):
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return None
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class _Session:
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def __init__(self):
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self.commits = 0
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def add(self, _value):
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return None
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def commit(self):
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self.commits += 1
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class _GenerationTask:
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status = _Field()
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query = _Query()
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def __init__(self, **kwargs):
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self.id = "task-1"
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self.status = "queued"
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self.error_code = ""
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self.error_message = None
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self.finished_at = None
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for key, value in kwargs.items():
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setattr(self, key, value)
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def to_dict(self):
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return {
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"id": self.id,
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"status": self.status,
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"errorCode": self.error_code,
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"errorMessage": self.error_message,
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}
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def test_dispatch_failure_finishes_task(monkeypatch):
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"""消息队列不可用时，不应留下永久 queued 任务。"""
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fake_db = types.SimpleNamespace(session=_Session())
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compat_module = types.ModuleType("insurance.db.compat")
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compat_module.db = fake_db
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model_module = types.ModuleType("insurance.models.generation_task")
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model_module.GenerationTask = _GenerationTask
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monkeypatch.setitem(sys.modules, "insurance.db.compat", compat_module)
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monkeypatch.setitem(sys.modules, "insurance.models.generation_task", model_module)
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synced = []
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monkeypatch.setattr(
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task_service,
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"_dispatch_to_celery",
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lambda _task: (_ for _ in ()).throw(ConnectionError("broker unavailable")),
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)
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monkeypatch.setattr(
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task_service,
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"_sync_failed_ppt_session",
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lambda task, message: synced.append((task.id, message)),
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)
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result = task_service.create_task(
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user_id="user-1",
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artifact_type="ppt",
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operation="parse",
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workspace_id="session-1",
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)
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assert result["code"] == 9999
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assert result["data"]["status"] == "failed"
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assert result["data"]["errorCode"] == "dispatch_failed"
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assert synced and synced[0][0] == result["data"]["id"]
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def test_cached_extraction_reports_completion(tmp_path, monkeypatch):
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"""重复解析应命中缓存，并向调用方报告完成阶段。"""
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pdf_path = tmp_path / "plan.pdf"
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pdf_path.write_bytes(b"%PDF-1.4")
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cached = ExtractionResult(
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pdf_path=str(pdf_path),
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product_name="测试产品",
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plan_type="savings",
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status="success",
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data={"product_name": "测试产品"},
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)
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orchestrator = ExtractionOrchestrator()
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monkeypatch.setattr(orchestrator, "_load_from_cache", lambda _path: cached)
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updates = []
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result = asyncio.run(orchestrator.extract_plan(
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str(pdf_path),
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progress_callback=lambda progress, message: updates.append((progress, message)),
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))
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assert result is cached
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assert updates == [(100, "已使用历史解析结果")]
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def test_default_llm_timeout_is_bounded():
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assert _parse_timeout_ms(None) == 180_000
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assert _parse_timeout_ms("30000") == 30_000
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def test_llm_json_parser_accepts_explanation_and_trailing_comma():
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content = '结果如下：\n```json\n{"product_name": "测试产品",}\n```\n请核对。'
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assert _parse_json_content(content) == {"product_name": "测试产品"}
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def test_pdf_pages_keep_page_numbers_and_select_late_benefit_page():
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text = extraction_module._format_pdf_pages([
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"Product Name: Example IUL",
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"general terms",
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"Policy Year Account Value Cash Surrender Value Death Benefit 1 1000 900 500000",
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])
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assert "[PAGE 1]" in text
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assert "[PAGE 3]" in text
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selected = select_key_pages(text, max_pages=2, max_chars=2000)
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assert "Product Name: Example IUL" in selected
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assert "Cash Surrender Value" in selected
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def test_corrupted_pdf_text_detection_accepts_normal_text_and_rejects_font_garbage():
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normal = "保险计划书 被保人年龄 48 岁\nPolicy Year 1 Cash Value 100000\n" * 3
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corrupted = "\uffff\uffff\x81\x82ĤøùÿxĀ@BQā" * 20
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assert extraction_module._looks_corrupted(normal) is False
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assert extraction_module._looks_corrupted(corrupted) is True
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def test_iul_filename_hint_corrects_ocr_product_name():
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data = {
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"product_name": "SAR Feel",
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"policy": {"product_name": "SAR Feel"},
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}
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corrected = extraction_module._apply_filename_hints(
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data,
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"/tmp/MLS_SIUL3_F-48-N-CN-USD-S3m.pdf",
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"iul",
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)
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assert corrected["product_name"] == "Manulife SIUL 3"
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assert corrected["policy"]["product_name"] == "Manulife SIUL 3"
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def test_savings_milestone_rows_are_warnings_not_blocking_errors():
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from insurance.ppt.validator import validate_formal_savings_plan
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plan = {
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"productName": "测试储蓄计划",
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"insured": {"age": 41},
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"policy": {"annualPremium": 5250, "payYears": 5},
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"benefitRows": [
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{"policyYear": year, "sourcePage": 3}
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for year in [1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 65, 70, 75, 80, 85, 90, 95, 100]
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],
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"withdrawalRows": [],
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"source": {"pdfHash": "abc"},
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}
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issues = validate_formal_savings_plan(plan)
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assert not [issue for issue in issues if issue.level == "error"]
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assert any(issue.code == "BENEFIT_ROWS_MILESTONE_ONLY" for issue in issues)
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assert any(issue.code == "BENEFIT_ROWS_DISCONTINUOUS" for issue in issues)
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def test_savings_rows_without_key_years_remain_blocking():
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from insurance.ppt.validator import validate_formal_savings_plan
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plan = {
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"productName": "测试储蓄计划",
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"insured": {"age": 41},
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"policy": {"annualPremium": 5250, "payYears": 5},
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"benefitRows": [
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{"policyYear": year, "sourcePage": 3}
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for year in [1, 2, 3, 4, 5]
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],
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"withdrawalRows": [],
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"source": {"pdfHash": "abc"},
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}
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issues = validate_formal_savings_plan(plan)
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assert any(
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issue.code == "BENEFIT_ROWS_INCOMPLETE" and issue.level == "error"
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for issue in issues
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)
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def test_partial_extraction_rechecks_and_keeps_better_result(tmp_path, monkeypatch):
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pdf_path = tmp_path / "iul.pdf"
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pdf_path.write_bytes(b"%PDF-1.4")
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monkeypatch.setattr(extraction_module, "_extract_pdf_text", lambda _path: "有效计划书文本" * 100)
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monkeypatch.setattr(regex_extractor, "extract_insurance_regex", lambda _text: {})
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monkeypatch.setattr(regex_extractor, "count_benefit_rows", lambda _data: 0)
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complete = {
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"product_name": "测试 IUL",
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"product_type": "iul",
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"insured": {"age": 35},
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"policy": {"sum_insured": 500000, "index_account_rate": 0.05},
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"index_accounts": [{"name": "S&P 500"}],
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"benefit_illustration": [{"policy_year": 1, "account_value": 1000}],
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}
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responses = iter([
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({}, LLMResponse(content="{}", provider="test")),
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(complete, LLMResponse(content="{}", provider="test")),
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])
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async def fake_structured_output(**_kwargs):
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return next(responses)
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from insurance.ppt.llm_client import llm_client
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monkeypatch.setattr(llm_client, "structured_output", fake_structured_output)
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result = asyncio.run(
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ExtractionOrchestrator(use_cache=False).extract_plan(str(pdf_path), "iul")
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)
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assert result.status == "success"
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assert result.product_name == "测试 IUL"
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assert result.data["benefit_illustration"]
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