040aada160
基于项目需求文档（PRD.md, FeatureSummary.md, DevelopmentPlan.md, UIDesign.md, User_Role_Interfaces.md）编写的 TDD 测试用例。 后端测试 (Python/pytest): - 单元测试: rule_engine, brief_parser, timestamp_alignment, video_auditor, validators - 集成测试: API Brief, Video, Review 端点 - AI 模块测试: ASR, OCR, Logo 检测服务 - 全局 fixtures 和 pytest 配置 前端测试 (TypeScript/Vitest): - 工具函数测试: utils.test.ts - 组件测试: Button, VideoPlayer, ViolationList - Hooks 测试: useVideoAudit, useVideoPlayer, useAppeal - MSW mock handlers 配置 E2E 测试 (Playwright): - 认证流程测试 - 视频上传流程测试 - 视频审核流程测试 - 申诉流程测试 所有测试当前使用 pytest.skip() / it.skip() 作为占位符， 遵循 TDD 红灯阶段 - 等待实现代码后运行。 验收标准覆盖: - ASR WER ≤ 10% - OCR 准确率 ≥ 95% - Logo F1 ≥ 0.85 - 时间戳误差 ≤ 0.5s - 频次统计准确率 ≥ 95% Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
272 lines
9.4 KiB
Python
272 lines
9.4 KiB
Python
"""
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SmartAudit 测试全局配置
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本文件定义所有测试共享的 fixtures 和配置。
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遵循 TDD 原则：先写测试，后写实现。
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"""
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import pytest
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from typing import Any
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from pathlib import Path
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# ============================================================================
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# 路径配置
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# ============================================================================
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@pytest.fixture
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def fixtures_path() -> Path:
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"""测试数据目录"""
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return Path(__file__).parent / "fixtures"
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@pytest.fixture
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def sample_brief_pdf(fixtures_path: Path) -> Path:
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"""示例 Brief PDF 文件路径"""
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return fixtures_path / "briefs" / "sample_brief.pdf"
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@pytest.fixture
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def sample_video_path(fixtures_path: Path) -> Path:
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"""示例视频文件路径"""
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return fixtures_path / "videos" / "sample_video.mp4"
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# ============================================================================
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# Brief 规则 Fixtures
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# ============================================================================
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@pytest.fixture
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def sample_brief_rules() -> dict[str, Any]:
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"""标准 Brief 规则示例"""
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return {
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"selling_points": [
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{"text": "24小时持妆", "priority": "high"},
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{"text": "天然成分", "priority": "medium"},
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{"text": "敏感肌适用", "priority": "medium"},
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],
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"forbidden_words": [
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{"word": "最", "reason": "广告法极限词", "severity": "hard"},
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{"word": "第一", "reason": "广告法极限词", "severity": "hard"},
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{"word": "药用", "reason": "化妆品禁用", "severity": "hard"},
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{"word": "治疗", "reason": "化妆品禁用", "severity": "hard"},
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],
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"brand_tone": {
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"style": "年轻活力",
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"description": "面向 18-35 岁女性用户"
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},
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"timing_requirements": [
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{"type": "product_visible", "min_duration_seconds": 5},
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{"type": "brand_mention", "min_frequency": 3},
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],
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"platform": "douyin",
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"region": "mainland_china",
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}
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@pytest.fixture
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def sample_platform_rules() -> dict[str, Any]:
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"""抖音平台规则示例"""
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return {
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"platform": "douyin",
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"version": "2026.01",
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"forbidden_words": [
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{"word": "最", "category": "ad_law"},
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{"word": "第一", "category": "ad_law"},
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{"word": "国家级", "category": "ad_law"},
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{"word": "绝对", "category": "ad_law"},
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],
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"content_rules": [
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{"rule": "不得含有虚假宣传", "category": "compliance"},
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{"rule": "不得使用竞品 Logo", "category": "brand_safety"},
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],
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}
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# ============================================================================
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# 视频审核 Fixtures
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# ============================================================================
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@pytest.fixture
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def sample_asr_result() -> dict[str, Any]:
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"""ASR 语音识别结果示例"""
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return {
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"text": "大家好，这款产品真的非常好用，24小时持妆效果特别棒",
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"segments": [
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{"word": "大家好", "start_ms": 0, "end_ms": 800, "confidence": 0.98},
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{"word": "这款产品", "start_ms": 850, "end_ms": 1500, "confidence": 0.97},
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{"word": "真的非常好用", "start_ms": 1550, "end_ms": 2800, "confidence": 0.96},
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{"word": "24小时持妆", "start_ms": 2900, "end_ms": 4000, "confidence": 0.99},
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{"word": "效果特别棒", "start_ms": 4100, "end_ms": 5200, "confidence": 0.95},
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],
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}
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@pytest.fixture
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def sample_ocr_result() -> dict[str, Any]:
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"""OCR 字幕识别结果示例"""
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return {
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"frames": [
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{"timestamp_ms": 1000, "text": "产品名称", "confidence": 0.98, "bbox": [100, 450, 300, 480]},
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{"timestamp_ms": 3000, "text": "24小时持妆", "confidence": 0.97, "bbox": [150, 450, 350, 480]},
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{"timestamp_ms": 5000, "text": "立即购买", "confidence": 0.96, "bbox": [200, 500, 400, 530]},
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],
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}
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@pytest.fixture
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def sample_cv_result() -> dict[str, Any]:
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"""CV 视觉检测结果示例"""
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return {
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"detections": [
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{
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"object_type": "product",
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"start_frame": 30,
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"end_frame": 180,
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"fps": 30,
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"confidence": 0.95,
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"bbox": [200, 100, 400, 350],
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},
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{
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"object_type": "competitor_logo",
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"start_frame": 200,
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"end_frame": 230,
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"fps": 30,
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"confidence": 0.88,
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"bbox": [50, 50, 100, 100],
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"logo_id": "competitor_001",
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},
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],
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}
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# ============================================================================
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# 违禁词测试数据
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# ============================================================================
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@pytest.fixture
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def prohibited_word_test_cases() -> list[dict[str, Any]]:
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"""违禁词检测测试用例集"""
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return [
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# 广告语境下应检出
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{"text": "这是全网销量第一的产品", "context": "advertisement", "expected": ["第一"], "should_detect": True},
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{"text": "我们是行业领导者", "context": "advertisement", "expected": ["领导者"], "should_detect": True},
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{"text": "史上最低价促销", "context": "advertisement", "expected": ["最", "史上"], "should_detect": True},
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{"text": "绝对有效，药用级别", "context": "advertisement", "expected": ["绝对", "药用"], "should_detect": True},
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# 日常语境下不应检出（语境感知）
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{"text": "今天是我最开心的一天", "context": "daily", "expected": [], "should_detect": False},
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{"text": "这是我第一次来这里", "context": "daily", "expected": [], "should_detect": False},
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{"text": "我们家排行第一", "context": "daily", "expected": [], "should_detect": False},
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# 边界情况
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{"text": "", "context": "advertisement", "expected": [], "should_detect": False},
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{"text": "这是一个普通的产品介绍", "context": "advertisement", "expected": [], "should_detect": False},
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# 组合违禁词
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{"text": "全网销量第一，史上最低价", "context": "advertisement", "expected": ["第一", "最", "史上"], "should_detect": True},
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]
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@pytest.fixture
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def context_understanding_test_cases() -> list[dict[str, Any]]:
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"""语境理解测试用例集"""
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return [
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{"text": "这款产品是最好的选择", "expected_context": "advertisement", "should_flag": True},
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{"text": "最近天气真好", "expected_context": "daily", "should_flag": False},
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{"text": "今天心情最棒了", "expected_context": "daily", "should_flag": False},
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{"text": "我们的产品效果最显著", "expected_context": "advertisement", "should_flag": True},
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{"text": "这是我见过最美的风景", "expected_context": "daily", "should_flag": False},
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]
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# ============================================================================
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# 时间戳对齐测试数据
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# ============================================================================
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@pytest.fixture
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def multimodal_alignment_test_cases() -> list[dict[str, Any]]:
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"""多模态时间戳对齐测试用例"""
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return [
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# 完全对齐情况
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{
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"asr_ts": 1000,
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"ocr_ts": 1000,
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"cv_ts": 1000,
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"tolerance_ms": 500,
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"expected_merged": True,
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"expected_timestamp": 1000,
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},
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# 容差范围内对齐
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{
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"asr_ts": 1000,
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"ocr_ts": 1200,
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"cv_ts": 1100,
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"tolerance_ms": 500,
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"expected_merged": True,
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"expected_timestamp": 1100, # 取中位数
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},
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# 超出容差
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{
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"asr_ts": 1000,
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"ocr_ts": 2000,
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"cv_ts": 3000,
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"tolerance_ms": 500,
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"expected_merged": False,
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"expected_timestamp": None,
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},
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# 部分对齐
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{
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"asr_ts": 1000,
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"ocr_ts": 1300,
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"cv_ts": 5000,
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"tolerance_ms": 500,
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"expected_merged": "partial", # ASR 和 OCR 对齐，CV 独立
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"expected_timestamp": 1150,
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},
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]
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# ============================================================================
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# API 测试数据
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# ============================================================================
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@pytest.fixture
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def valid_brief_upload_request() -> dict[str, Any]:
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"""有效的 Brief 上传请求"""
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return {
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"task_id": "task_001",
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"platform": "douyin",
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"region": "mainland_china",
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}
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@pytest.fixture
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def valid_video_submit_request() -> dict[str, Any]:
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"""有效的视频提交请求"""
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return {
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"task_id": "task_001",
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"video_id": "video_001",
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"brief_id": "brief_001",
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}
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@pytest.fixture
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def valid_review_decision_request() -> dict[str, Any]:
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"""有效的审核决策请求"""
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return {
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"report_id": "report_001",
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"decision": "passed",
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"selected_violations": [],
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}
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@pytest.fixture
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def force_pass_decision_request() -> dict[str, Any]:
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"""强制通过请求（需填写原因）"""
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return {
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"report_id": "report_001",
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"decision": "force_passed",
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"selected_violations": ["violation_001"],
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"force_pass_reason": "达人玩的新梗，品牌方认可",
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}
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