340 lines
20 KiB
Python
340 lines
20 KiB
Python
import sys
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import unittest
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from pathlib import Path
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from unittest.mock import patch
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ROOT = Path(__file__).resolve().parents[1]
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sys.path.insert(0, str(ROOT / 'server'))
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from analysis import analyze, ensure_experience_solution, normalize, _review_issue, _buyer_evidence, detect_category, _category_parameter_facts, core_solution_diagnostics, repair_core_solution_with_evidence
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from renderer import render
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from server import TASK_JS, task_evidence_summary, task_page
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class EvidenceOnlyReportTest(unittest.TestCase):
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def setUp(self):
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self.analysis = {
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'facts': {
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'product': {'title': '用户评价·51', 'itemId': '900653753390'},
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'sales': {'sold': '700+', 'currentPrice': '395.25'},
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'attributes': [
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{'name': '1024', 'value': '"lg",'},
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{'name': 'console.log("onload]', 'value': 'performance.now()'},
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{'name': '面料支数', 'value': '60支'},
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{'name': '床单面料材质', 'value': '全棉'},
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{'name': '适用床尺寸', 'value': '1.2m床三件套'},
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],
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'reviews': [
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{'content': '2025年4月18日已购：【四件套】测试规格'},
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{'content': '花色好看，摸起来很舒服', 'images': ['https://img.alicdn.com/review-rate.jpg'], 'source': 'dom_visible'},
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{'content': '1米2床单尺寸小，床边不够'},
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],
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'questions': [
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{'question': '问大家·5 问 有味道吗 更多回答 问 盖上舒服吗 更多回答'},
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{'question': '问 有味道吗 更多回答'},
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],
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'collection': {
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'reviewCollectionComplete': False,
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'publicReviewCount': '51',
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'reviewStopReason': 'no_progress_after_4_rounds',
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'reviewPagesVisited': 35,
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},
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'images': {'main': [
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'https://img.alicdn.com/tps-120-60.png',
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'https://img.alicdn.com/item_pic.jpg',
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], 'detail': [], 'sku': [], 'buyerShow': [], 'all': []},
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},
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'experienceSolution': {},
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'meta': {},
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}
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def test_empty_model_result_repairs_core_modules_before_report(self):
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result = ensure_experience_solution(self.analysis)
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self.assertFalse(result['meta']['fallbackReport'])
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self.assertTrue(result['meta']['reportReady'])
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self.assertTrue(result['meta']['reportAuditPassed'])
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self.assertEqual('passed', result['meta']['reportQuality'])
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self.assertEqual([], result['meta']['reportValidation']['missing'])
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self.assertEqual('', result['facts']['product']['title'])
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self.assertEqual(['面料支数', '床单面料材质', '适用床尺寸'], [x['name'] for x in result['facts']['attributes']])
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self.assertEqual(2, result['baseline']['reviewCount'])
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self.assertEqual(2, result['baseline']['questionCount'])
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cards = result['experienceSolution']['ownerOverview']['cards']
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self.assertTrue(cards)
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self.assertEqual('下一款明确卖点', cards[0]['label'])
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self.assertIn('ATTR_0003', cards[0]['evidenceIds'])
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self.assertGreaterEqual(len(result['experienceSolution']['productExperience']['parameterFacts']), 2)
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self.assertGreaterEqual(len(result['experienceSolution']['productExperience']['gates']), 2)
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self.assertGreaterEqual(len(result['experienceSolution']['validationLoop']['rows']), 3)
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html = render(result, 'fixture')
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self.assertNotIn('审核未通过', html)
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def test_unrepairable_core_audit_blocks_report(self):
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with patch('analysis.repair_core_solution_with_evidence', side_effect=lambda draft, raw, base=None: draft):
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result = ensure_experience_solution(self.analysis)
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self.assertFalse(result['meta']['reportReady'])
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self.assertFalse(result['meta']['reportAuditPassed'])
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self.assertEqual('blocked', result['meta']['reportQuality'])
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self.assertIn('已停止生成', result['meta']['reportBlockedReason'])
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self.assertNotIn('reportNotice', result['meta'])
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def test_analysis_runs_without_model_channel_uses_evidence_fallback(self):
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raw = dict(self.analysis['facts'])
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raw['_model_available'] = False
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result = analyze(raw)
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self.assertFalse(result['meta']['modelUsed'])
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self.assertEqual('9.3.0', result['meta']['engineVersion'])
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self.assertEqual('home_textile', result['meta']['industryTemplate'])
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self.assertFalse(result['meta']['fallbackReport'])
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self.assertTrue(result['meta']['reportReady'])
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self.assertTrue(result['experienceSolution']['reportSummary']['title'])
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self.assertEqual(7, len(result['roleOutputs']))
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def test_historical_fallback_json_is_rejected(self):
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result = ensure_experience_solution({
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'facts': self.analysis['facts'],
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'experienceSolution': {'reportSummary': {'title': '旧报告', 'verdict': '旧结论'}},
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'meta': {'fallbackReport': True},
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})
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self.assertFalse(result['meta']['reportReady'])
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self.assertIn('历史分析标记为兜底结果', result['meta']['reportBlockedReason'])
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def test_dormitory_spec_never_invents_12m_issue_and_title_is_clean(self):
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facts = {
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'product': {'title': '宿舍七件套新生床品-tmall.com天猫', 'itemId': '2'},
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'sales': {'sold': '1万+', 'currentPrice': '637.5'},
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'attributes': [
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{'name': '套件组成', 'value': '被芯、床垫、床单、被套、枕芯、枕套、床帘'},
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{'name': '适用床尺寸', 'value': '80×190cm、90×190cm、90×200cm；床垫厚4cm/6cm'},
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{'name': '面料材质', 'value': '聚酯纤维'},
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{'name': '适用人群', 'value': '学生'},
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],
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'reviews': [
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{'content': '七件配齐，开学直接用，尺寸合适'},
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{'content': '枕套实物和页面有色差', 'sku': '90×190cm / 4cm床垫'},
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],
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'questions': [], 'images': {},
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}
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clean = normalize(facts);issue = _review_issue(clean)
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self.assertEqual('宿舍七件套新生床品', clean['product']['title'])
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self.assertEqual('实物色差', issue['label'])
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self.assertNotIn('1.2m', str(issue))
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self.assertNotIn('1米2', str(issue))
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def test_real_12m_comment_keeps_12m_evidence(self):
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clean = normalize(self.analysis['facts']);issue = _review_issue(clean)
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self.assertIn('1米2床单尺寸小，床边不够', issue['text'])
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self.assertEqual('尺寸与床型适配', issue['label'])
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def test_apparel_uses_dynamic_category_dimensions(self):
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raw=normalize({'product':{'title':'女士宽松连衣裙'},'attributes':[{'name':'尺码','value':'S M L XL'},{'name':'面料成分','value':'棉 95% 氨纶 5%'},{'name':'版型','value':'宽松'}],'reviews':[{'content':'尺码合身，版型显瘦'}],'images':{}})
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route=detect_category(raw)
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facts=_category_parameter_facts(raw)
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self.assertEqual('apparel',route['key'])
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self.assertIn('尺码与适配',[x['label'] for x in facts])
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self.assertIn('面料与成分',[x['label'] for x in facts])
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self.assertNotIn('套件 BOM',[x['label'] for x in facts])
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def test_food_beauty_and_digital_route_to_their_own_dimensions(self):
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fixtures=[
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('food',{'product':{'title':'坚果零食礼盒'},'attributes':[{'name':'净含量','value':'750g'},{'name':'配料表','value':'坚果'}]}),
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('beauty',{'product':{'title':'敏感肌保湿精华'},'attributes':[{'name':'主要成分','value':'透明质酸'},{'name':'适用肤质','value':'敏感肌'}]}),
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('digital',{'product':{'title':'无线蓝牙耳机'},'attributes':[{'name':'兼容系统','value':'iOS/Android'},{'name':'续航时间','value':'30小时'}]}),
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]
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for expected,data in fixtures:
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data.update({'reviews':[],'images':{}})
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clean=normalize(data); route=detect_category(clean)
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self.assertEqual(expected,route['key'])
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self.assertTrue(_category_parameter_facts(clean))
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def test_complete_evidence_backed_ai_output_is_rendered_and_sanitized(self):
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facts = {
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'product': {'title': '全棉三件套-taobao.com淘宝网', 'itemId': '3'},
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'sales': {},
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'attributes': [
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{'name': '床单面料材质', 'value': '全棉'},
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{'name': '套件组成', 'value': '床单、被套、枕套'},
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{'name': '适用床尺寸', 'value': '0.9m床三件套'},
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],
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'reviews': [{'content': '摸起来柔软舒服'}],
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'questions': [{'question': '会不会起球？'}],
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'images': {},
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}
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exp = {
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'reportSummary': {'title': '省心型大众爆款，提升转化', 'verdict': '先完成样品验证'},
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'ownerOverview': {'chapterTitle': '页面事实与评论结果已形成', 'cards': [
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{'label': '客户为什么购买', 'headline': '决定成交', 'evidenceIds': ['REV_000001']},
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{'label': '页面产品定义', 'headline': '全棉三件套', 'evidenceIds': ['ATTR_0001', 'ATTR_0002']},
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{'label': '下一款怎么开', 'headline': '先校准规格', 'evidenceIds': ['ATTR_0003']},
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]},
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'customerExperience': {
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'chapterTitle': '1 条评论确认柔软触感', 'journeyTitle': '只显示评论已确认结果',
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'stats': [{'label': '有效评论', 'value': '1'}],
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'stages': [
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{'stageNo': '01', 'label': '实际使用', 'positiveConfirmation': '1 条确认柔软舒服', 'evidenceIds': ['REV_000001']},
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{'stageNo': '02', 'label': '选择规格', 'positiveConfirmation': '页面标注0.9m床三件套', 'evidenceIds': ['ATTR_0003']},
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],
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'signals': {'positive': [], 'questions': [], 'risks': [
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{'label': '起球产品缺陷', 'evidenceIds': ['QA_00001']},
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]},
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},
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'productExperience': {'chapterTitle': '材质、BOM与床型必须一致', 'parameterFacts': [
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{'label': '材质 / 成分', 'value': '全棉', 'evidenceIds': ['ATTR_0001']},
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{'label': '套件 BOM', 'value': '床单、被套、枕套', 'evidenceIds': ['ATTR_0002']},
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], 'gates': [
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{'priority': 'P0', 'label': '材质核对', 'action': '核对标签与样品', 'evidenceIds': ['ATTR_0001']},
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{'priority': 'P0', 'label': '规格实测', 'action': '按0.9m床铺装', 'evidenceIds': ['ATTR_0003']},
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]},
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'newProductPlans': {'plans': [
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{'type': '主销款', 'name': '主销', 'positioning': '保持全棉三件套定义', 'evidenceIds': ['ATTR_0001']},
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{'name': '无证据升级', 'evidenceIds': []},
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{'type': '升级款', 'name': '第三套', 'positioning': '按BOM校准', 'evidenceIds': ['ATTR_0002']},
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], 'chapterTitle': '只输出有证据的开品方向'},
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'validationLoop': {'chapterTitle': '三道验证门决定是否上架', 'rows': [
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{'stage': '商品定义', 'owner': '商品企划 / 商品运营', 'metrics': '核对定义', 'successMeaning': '参数一致', 'nextAction': '进入打样', 'evidenceIds': ['ATTR_0001']},
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{'stage': '规格实测', 'owner': '供应链 / 品控', 'metrics': '实床铺装', 'successMeaning': '规格适配', 'nextAction': '锁定SKU', 'evidenceIds': ['ATTR_0003']},
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{'stage': '页面验收', 'owner': '视觉与内容', 'metrics': '核对页面', 'successMeaning': '页面一致', 'nextAction': '上架', 'evidenceIds': ['ATTR_0002']},
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]},
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}
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result = ensure_experience_solution({'facts': facts, 'experienceSolution': exp, 'meta': {}})
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output = str(result['experienceSolution'])
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labels = [x['label'] for x in result['experienceSolution']['productExperience']['parameterFacts']]
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signals = result['experienceSolution']['customerExperience']['signals']
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self.assertTrue(result['meta']['reportReady'])
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self.assertEqual('全棉三件套', result['facts']['product']['title'])
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self.assertIn('套件 BOM', labels)
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self.assertIn('材质 / 成分', labels)
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self.assertEqual([], signals['risks'])
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self.assertTrue(signals['questions'][0]['label'].startswith('购买前关注：'))
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plans = result['experienceSolution']['newProductPlans']['plans']
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self.assertEqual(3, len(plans))
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self.assertEqual(['证据驱动优化', '反馈驱动升级', '探索性方向'], [x['sourceType'] for x in plans])
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self.assertTrue(all(x['name'].endswith('款') for x in plans))
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self.assertNotIn('无证据升级', output)
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self.assertNotIn('项目负责人', output)
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self.assertNotIn('客户为什么购买', output)
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self.assertNotIn('提升转化', output)
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self.assertNotIn('决定成交', output)
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self.assertNotIn('爆款', output)
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doc = render(result, 'evidence-only')
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self.assertIn('window.REPORT_DATA=', doc)
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self.assertIn('Sansong Product Intelligence V9.3.0', doc)
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self.assertIn('<script src="/report.js?v=', doc)
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self.assertNotIn('项目负责人', doc)
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def test_incomplete_final_editor_output_is_repaired_from_real_evidence(self):
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facts = {
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'product': {'title': '学生宿舍全棉三件套', 'itemId': 'repair-1'},
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'sales': {'sold': '1000+', 'currentPrice': '129'},
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'attributes': [
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{'name': '床单面料材质', 'value': '全棉'},
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{'name': '套件组成', 'value': '床单、被套、枕套'},
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{'name': '适用床尺寸', 'value': '0.9m床三件套'},
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{'name': '产品等级', 'value': '合格品'},
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],
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'reviews': [
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{'content': '面料柔软，尺寸合适'},
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{'content': '花色好看，宿舍床铺上正好'},
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],
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'questions': [{'question': '洗后会不会缩水？'}],
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'images': {},
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}
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repaired = repair_core_solution_with_evidence({}, facts)
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result = ensure_experience_solution({'facts': facts, 'experienceSolution': repaired, 'meta': {}})
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self.assertTrue(result['meta']['reportReady'])
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self.assertTrue(result['meta']['reportValidation']['ok'])
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self.assertEqual([], result['meta']['reportValidation']['missing'])
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self.assertFalse(result['meta']['fallbackReport'])
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self.assertIn('evidenceIds', result['experienceSolution']['validationLoop']['rows'][0])
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def test_legacy_grouped_images_are_preserved_without_strict_provenance(self):
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raw={
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'product':{'title':'测试商品','itemId':'1'},
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'reviews':[],
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'images':{
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'main':['https://img.alicdn.com/item_pic.jpg'],
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'detail':['https://img.alicdn.com/detail_01.jpg'],
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'sku':['https://img.alicdn.com/sku_01.jpg'],
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'buyerShow':[]
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}
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}
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clean=normalize(raw)
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self.assertEqual(['https://img.alicdn.com/item_pic.jpg'], clean['images']['main'])
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self.assertEqual(['https://img.alicdn.com/detail_01.jpg'], clean['images']['detail'])
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self.assertEqual(['https://img.alicdn.com/sku_01.jpg'], clean['images']['sku'])
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self.assertEqual('legacy-review-only', clean['images']['classification']['version'])
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sources={x['group']:x['source'] for x in clean['images']['provenance'] if x['group'] in ('main','detail','sku')}
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self.assertEqual('legacy_group_main', sources['main'])
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self.assertEqual('legacy_group_detail', sources['detail'])
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self.assertEqual('legacy_group_sku', sources['sku'])
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def test_validation_reports_exact_missing_fields(self):
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validation = core_solution_diagnostics({'reportSummary': {'title': '有标题'}})
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self.assertFalse(validation['ok'])
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self.assertNotIn('reportSummary.title', validation['missing'])
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self.assertIn('reportSummary.verdict', validation['missing'])
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self.assertIn('validationLoop.rows', validation['missing'])
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def test_task_progress_exposes_real_evidence_counts(self):
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raw = self.analysis['facts']
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summary = task_evidence_summary(raw)
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self.assertEqual(3, summary['counts']['parameters'])
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self.assertEqual(2, summary['counts']['reviews'])
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self.assertEqual(1, summary['counts']['main'])
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self.assertEqual(0, summary['counts']['detail'])
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self.assertEqual(1, summary['counts']['buyerShow'])
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self.assertEqual('51', summary['publicReviewCount'])
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self.assertFalse(summary['reviewComplete'])
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page = task_page('fixture')
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self.assertIn('本次证据', page)
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self.assertIn('生成进度', page)
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self.assertIn('evidenceStats', page)
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self.assertIn("not_collected:'未采到'", TASK_JS)
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self.assertIn("visual:'商品主图核验'", TASK_JS)
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self.assertIn("detail:'商品详情图核验'", TASK_JS)
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self.assertIn("editor:'最终报告汇总与校验'", TASK_JS)
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self.assertIn("failed:'失败'", TASK_JS)
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self.assertNotIn("visual:'主图成交'", TASK_JS)
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def test_strict_image_groups_are_disjoint_and_traceable(self):
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shared = 'https://img.alicdn.com/shared-review.jpg'
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buyer_two = 'https://img.alicdn.com/second-review.jpg'
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main = 'https://img.alicdn.com/verified-main.jpg'
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structured_main = 'https://img.alicdn.com/structured-main.jpg'
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detail = 'https://img.alicdn.com/verified-detail.jpg'
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structured_detail = 'https://img.alicdn.com/structured-detail.jpg'
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facts = {
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'meta': {'imageClassificationVersion': 'strict-v1'},
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'product': {'title': '真实商品标题', 'itemId': '1'},
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'sales': {}, 'attributes': [], 'questions': [],
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'reviews': [{'content': '评论原文', 'images': [shared, buyer_two], 'source': 'dom_visible'}],
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'images': {
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'main': [shared, main, structured_main], 'detail': [shared, detail, structured_detail], 'sku': [], 'buyerShow': [shared, buyer_two],
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'provenance': [
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{'url': shared, 'group': 'buyerShow', 'source': 'review_record'},
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{'url': buyer_two, 'group': 'buyerShow', 'source': 'review_record'},
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{'url': shared, 'group': 'main', 'source': 'dom_main_gallery'},
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{'url': main, 'group': 'main', 'source': 'dom_main_gallery'},
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{'url': structured_main, 'group': 'main', 'source': 'structured_main_gallery'},
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{'url': detail, 'group': 'detail', 'source': 'dom_product_description'},
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{'url': structured_detail, 'group': 'detail', 'source': 'structured_product_description'},
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],
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},
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}
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clean = normalize(facts)
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groups = clean['images']
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self.assertEqual([shared, buyer_two], groups['buyerShow'])
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self.assertEqual([main, structured_main], groups['main'])
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self.assertEqual([detail, structured_detail], groups['detail'])
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self.assertTrue(groups['classification']['groupsAreDisjoint'])
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self.assertEqual(6, len(set(groups['buyerShow'] + groups['main'] + groups['detail'])))
|
||
buyer_items = _buyer_evidence(clean)
|
||
buyer = buyer_items[0]
|
||
self.assertEqual('REV_000001', buyer['reviewEvidenceId'])
|
||
self.assertEqual(2, len(buyer_items))
|
||
|
||
|
||
if __name__ == '__main__':
|
||
unittest.main()
|