""" 规则引擎单元测试 TDD 测试用例 - 基于 FeatureSummary.md (F-03, F-04, F-05-A, F-06) 的验收标准 验收标准： - 违禁词召回率 ≥ 95% - 违禁词误报率 ≤ 5% - 语境理解误报率 ≤ 5% - 规则冲突提示清晰可追溯 """ import pytest from typing import Any # 导入待实现的模块（TDD 红灯阶段 - 模块尚未实现） # from app.services.rule_engine import RuleEngine, ProhibitedWordDetector, RuleConflictDetector class TestProhibitedWordDetector: """ 违禁词检测器测试 验收标准 (FeatureSummary.md): - 召回率 ≥ 95% - 误报率 ≤ 5% """ @pytest.mark.unit @pytest.mark.parametrize("text,context,expected_violations,should_detect", [ # 广告语境 - 应检出 ("这是全网销量第一的产品", "advertisement", ["第一"], True), ("我们是行业领导者", "advertisement", ["领导者"], True), ("史上最低价促销", "advertisement", ["最", "史上"], True), ("绝对有效果", "advertisement", ["绝对"], True), # 日常语境 - 不应检出 (语境感知) ("今天是我最开心的一天", "daily", [], False), ("这是我第一次来这里", "daily", [], False), ("我最喜欢吃苹果", "daily", [], False), # 边界情况 ("", "advertisement", [], False), ("普通的产品介绍，没有违禁词", "advertisement", [], False), ]) def test_detect_prohibited_words( self, text: str, context: str, expected_violations: list[str], should_detect: bool, ) -> None: """测试违禁词检测的准确性""" # TODO: 实现 ProhibitedWordDetector # detector = ProhibitedWordDetector() # result = detector.detect(text, context=context) # # if should_detect: # assert len(result.violations) > 0 # for word in expected_violations: # assert any(word in v.content for v in result.violations) # else: # assert len(result.violations) == 0 pytest.skip("待实现：ProhibitedWordDetector") @pytest.mark.unit def test_recall_rate_above_threshold( self, prohibited_word_test_cases: list[dict[str, Any]], ) -> None: """ 验证召回率 ≥ 95% 召回率 = 正确检出数 / 应检出总数 """ # TODO: 使用完整测试集验证召回率 # detector = ProhibitedWordDetector() # positive_cases = [c for c in prohibited_word_test_cases if c["should_detect"]] # # true_positives = 0 # for case in positive_cases: # result = detector.detect(case["text"], context=case["context"]) # if result.violations: # true_positives += 1 # # recall = true_positives / len(positive_cases) # assert recall >= 0.95, f"召回率 {recall:.2%} 低于阈值 95%" pytest.skip("待实现：召回率测试") @pytest.mark.unit def test_false_positive_rate_below_threshold( self, prohibited_word_test_cases: list[dict[str, Any]], ) -> None: """ 验证误报率 ≤ 5% 误报率 = 错误检出数 / 不应检出总数 """ # TODO: 使用完整测试集验证误报率 # detector = ProhibitedWordDetector() # negative_cases = [c for c in prohibited_word_test_cases if not c["should_detect"]] # # false_positives = 0 # for case in negative_cases: # result = detector.detect(case["text"], context=case["context"]) # if result.violations: # false_positives += 1 # # fpr = false_positives / len(negative_cases) # assert fpr <= 0.05, f"误报率 {fpr:.2%} 超过阈值 5%" pytest.skip("待实现：误报率测试") class TestContextUnderstanding: """ 语境理解测试 验收标准 (DevelopmentPlan.md 第 8 章): - 广告极限词与非广告语境区分误报率 ≤ 5% - 不将「最开心的一天」误判为违规 """ @pytest.mark.unit @pytest.mark.parametrize("text,expected_context,should_flag", [ ("这款产品是最好的选择", "advertisement", True), ("最近天气真好", "daily", False), ("今天心情最棒了", "daily", False), ("我们的产品效果最显著", "advertisement", True), ("这是我见过最美的风景", "daily", False), ("全网销量第一，值得信赖", "advertisement", True), ("我第一次尝试这个运动", "daily", False), ]) def test_context_classification( self, text: str, expected_context: str, should_flag: bool, ) -> None: """测试语境分类准确性""" # TODO: 实现语境分类器 # classifier = ContextClassifier() # result = classifier.classify(text) # # assert result.context == expected_context # if should_flag: # assert result.is_advertisement_context # else: # assert not result.is_advertisement_context pytest.skip("待实现：ContextClassifier") @pytest.mark.unit def test_happy_day_not_flagged(self) -> None: """ 关键测试：「最开心的一天」不应被误判 这是 DevelopmentPlan.md 明确要求的测试用例 """ text = "今天是我最开心的一天" # TODO: 实现检测器 # detector = ProhibitedWordDetector() # result = detector.detect(text, context="auto") # 自动识别语境 # # assert len(result.violations) == 0, "「最开心的一天」被误判为违规" pytest.skip("待实现：语境感知检测") class TestRuleConflictDetector: """ 规则冲突检测测试 验收标准 (FeatureSummary.md F-03): - 规则冲突提示清晰可追溯 """ @pytest.mark.unit def test_detect_brief_platform_conflict( self, sample_brief_rules: dict[str, Any], sample_platform_rules: dict[str, Any], ) -> None: """测试 Brief 规则与平台规则冲突检测""" # 构造冲突场景：Brief 允许使用「最佳效果」，但平台禁止「最」 brief_rules = { **sample_brief_rules, "allowed_words": ["最佳效果"], } # TODO: 实现冲突检测器 # detector = RuleConflictDetector() # conflicts = detector.detect(brief_rules, sample_platform_rules) # # assert len(conflicts) > 0 # assert any("最" in c.conflicting_term for c in conflicts) # assert all(c.resolution_suggestion is not None for c in conflicts) pytest.skip("待实现：RuleConflictDetector") @pytest.mark.unit def test_no_conflict_when_compatible( self, sample_brief_rules: dict[str, Any], sample_platform_rules: dict[str, Any], ) -> None: """测试规则兼容时无冲突""" # TODO: 实现冲突检测器 # detector = RuleConflictDetector() # conflicts = detector.detect(sample_brief_rules, sample_platform_rules) # # # 标准 Brief 规则应与平台规则兼容 # assert len(conflicts) == 0 pytest.skip("待实现：规则兼容性测试") class TestRuleVersioning: """ 规则版本管理测试 验收标准 (FeatureSummary.md F-06): - 规则变更历史可追溯 - 支持回滚到历史版本 """ @pytest.mark.unit def test_rule_version_tracking(self) -> None: """测试规则版本追踪""" # TODO: 实现规则版本管理 # rule_manager = RuleVersionManager() # # # 创建规则 # rule_v1 = rule_manager.create_rule({"word": "最", "severity": "hard"}) # assert rule_v1.version == "v1.0.0" # # # 更新规则 # rule_v2 = rule_manager.update_rule(rule_v1.id, {"severity": "soft"}) # assert rule_v2.version == "v1.1.0" # # # 查看历史 # history = rule_manager.get_history(rule_v1.id) # assert len(history) == 2 pytest.skip("待实现：RuleVersionManager") @pytest.mark.unit def test_rule_rollback(self) -> None: """测试规则回滚""" # TODO: 实现规则回滚 # rule_manager = RuleVersionManager() # # rule_v1 = rule_manager.create_rule({"word": "最", "severity": "hard"}) # rule_v2 = rule_manager.update_rule(rule_v1.id, {"severity": "soft"}) # # # 回滚到 v1 # rolled_back = rule_manager.rollback(rule_v1.id, "v1.0.0") # assert rolled_back.severity == "hard" pytest.skip("待实现：规则回滚") class TestPlatformRuleSync: """ 平台规则同步测试 验收标准 (PRD.md): - 平台规则变更后 ≤ 1 工作日内更新 """ @pytest.mark.unit def test_platform_rule_update_notification(self) -> None: """测试平台规则更新通知""" # TODO: 实现平台规则同步 # sync_service = PlatformRuleSyncService() # # # 模拟抖音规则更新 # new_rules = {"forbidden_words": [{"word": "新违禁词", "category": "ad_law"}]} # result = sync_service.sync_platform_rules("douyin", new_rules) # # assert result.updated # assert result.notification_sent pytest.skip("待实现：PlatformRuleSyncService")