wsb1224
caee27b0d3
海报加载失败根因：html-to-image 给 blob: 底图地址追加缓存参数，导致地址失效。现已关闭该行为。 合成失败后再次点击“重新生成”，会复用已有 AI 底图，只重试浏览器合成和上传，避免重复调用 AI。 增加底图加载、图表超时、导出失败、尺寸越界等分阶段错误提示。 修复计划书 (cid:数字) 字体乱码被误判为正常文本的问题，现在会正确转入 OCR。 增加繁体中文 OCR 运行支持。 补齐 SIUL 文件名中的确定字段，并且不会覆盖正文已识别数据。 增加“首期规划保费/償還至形成基金所需保費”等保费标签识别。 修正 IUL 年龄、保额、退保价值、缴费期、公司信息等字段映射。 LLM 返回空对象或缺字段时不再视为成功。 增加错误利益数值和年龄/保单年度错位校验。 修复依赖版本降级导致 API/Worker 无法启动的风险。 真实计划书复验结果： 产品：Manulife SIUL 3 投保年龄：48 岁 性别：女性 吸烟状态：非吸烟 币种：USD 基本保额：3,000,000 年缴保费：80,060 缴费期：5 年 利益演示：识别到 10 行 验证结果： 后端相关回归测试：91 passed 前端生产构建：通过 API、数据库、Redis、存储、数据表健康检查：全部正常 Celery Worker：已重启并连接 Redis 真实 PDF：确认进入 OCR，不再使用 (cid:...) 乱码 前端构建目录由运行容器挂载，修复已生效
381 lines
13 KiB
Python
381 lines
13 KiB
Python
"""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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import pytest
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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 (
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LLMResponse,
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_parse_json_content,
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_parse_timeout_ms,
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_validate_required_fields,
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)
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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_structured_schema_rejects_empty_or_incomplete_success_payload():
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schema = {
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"type": "object",
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"required": ["insured", "policy"],
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"properties": {
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"insured": {"type": "object", "required": ["age"]},
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"policy": {"type": "object", "required": ["annual_premium"]},
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},
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}
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with pytest.raises(ValueError, match="缺少必填字段"):
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_validate_required_fields({}, schema)
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with pytest.raises(ValueError, match="annual_premium"):
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_validate_required_fields({"insured": {"age": 48}, "policy": {}}, schema)
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_validate_required_fields(
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{"insured": {"age": 48}, "policy": {"annual_premium": 80060}},
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schema,
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)
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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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cid_garbage = "[PAGE 1]\n" + "(cid:4)(cid:17)(cid:238)(cid:99)" * 30
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assert extraction_module._looks_corrupted(cid_garbage) 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-5x_coi__SC_.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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assert corrected["insured"] == {"gender": "female", "age": 48, "smoker": "no"}
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assert corrected["policy"]["currency"] == "USD"
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assert corrected["policy"]["sum_insured"] == 3_000_000
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assert corrected["policy"]["premium_payment_period"] == 5
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def test_iul_filename_hint_does_not_override_extracted_values():
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data = {
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"product_name": "unknown",
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"insured": {"age": 49, "gender": "female", "smoker": "no"},
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"policy": {"currency": "HKD", "sum_insured": 2_000_000, "premium_payment_period": 8},
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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-5x.pdf",
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"iul",
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)
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assert corrected["insured"]["age"] == 49
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assert corrected["policy"]["currency"] == "HKD"
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assert corrected["policy"]["sum_insured"] == 2_000_000
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assert corrected["policy"]["premium_payment_period"] == 8
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def test_iul_ocr_label_extracts_planned_annual_premium():
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from insurance.ppt.regex_extractor import _extract_annual_premium
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text = "性别 Female 首期规划保费 US$80,060.00\n偿还至形成基金所需保费 US$80,060.00 从第1年至第5年"
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assert _extract_annual_premium(text) == 80_060
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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, "smoker": "no"},
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"policy": {"currency": "USD", "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_are_non_blocking_warnings():
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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, "smoker": "no"},
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"policy": {"currency": "USD", "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 == "warn"
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for issue in issues
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)
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assert not [issue for issue in issues if issue.level == "error"]
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def test_split_extraction_merges_identity_and_benefit_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(
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extraction_module,
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"_extract_pdf_text",
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lambda _path: ("有效计划书文本" * 100, []),
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)
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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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async def fake_structured_output(**kwargs):
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prompt = kwargs.get("prompt", "")
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if "身份和保单字段" in prompt:
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data = {key: value for key, value in complete.items() if key != "benefit_illustration"}
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elif "利益演示表" in prompt:
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data = {"benefit_illustration": complete["benefit_illustration"]}
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elif "提领/提款演示表" in prompt:
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data = {"withdrawal_illustration": []}
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else:
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data = {}
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return data, LLMResponse(content="{}", provider="test")
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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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def test_generate_ppt_task_marks_failure_and_syncs_workspace(monkeypatch):
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"""生成入口自身异常也必须结束任务，不能永久停在 running。"""
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celery_module = types.ModuleType("celery")
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def shared_task(*_args, **_kwargs):
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return lambda func: func
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celery_module.shared_task = shared_task
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monkeypatch.setitem(sys.modules, "celery", celery_module)
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sys.modules.pop("insurance.generation.celery_tasks", None)
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from insurance.generation import celery_tasks
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task = types.SimpleNamespace(id="task-1", workspace_id="session-1")
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session = types.SimpleNamespace(workflow_step="ready")
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class TaskQuery:
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@staticmethod
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def get(_task_id):
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return task
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class SessionQuery:
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@staticmethod
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def get(_session_id):
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return session
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generation_model = types.ModuleType("insurance.models.generation_task")
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generation_model.GenerationTask = types.SimpleNamespace(query=TaskQuery())
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session_model = types.ModuleType("insurance.models.ppt_session")
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session_model.PptSession = types.SimpleNamespace(query=SessionQuery())
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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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monkeypatch.setitem(sys.modules, "insurance.models.generation_task", generation_model)
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monkeypatch.setitem(sys.modules, "insurance.models.ppt_session", session_model)
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monkeypatch.setitem(sys.modules, "insurance.db.compat", compat_module)
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monkeypatch.setattr(celery_tasks, "_claim_task", lambda _task_id: True)
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updates = []
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monkeypatch.setattr(
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celery_tasks,
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"_update_task_status",
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lambda _task_id, **kwargs: updates.append(kwargs),
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)
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monkeypatch.setattr(
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celery_tasks,
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"_execute_ppt_generate",
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lambda _task_id: (_ for _ in ()).throw(RuntimeError("render failed")),
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)
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synced = []
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monkeypatch.setattr(task_service, "sync_workspace_status", lambda value: synced.append(value))
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with pytest.raises(RuntimeError, match="render failed"):
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celery_tasks.generate_ppt_task(None, "task-1")
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assert session.workflow_step == "generating"
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assert any(update.get("status") == "failed" for update in updates)
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assert synced == [task]
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