video-compliance-ai/backend/tests/test_script_review_api.py

"""
脚本预审 API 测试 (TDD - 红色阶段)
测试覆盖: 脚本提交、违规检测、语境理解
"""
import pytest
from httpx import AsyncClient

from app.schemas.review import ScriptReviewResponse, ViolationType, SoftRiskAction


class TestSubmitScript:
    """提交脚本预审"""

    @pytest.mark.asyncio
    async def test_submit_script_returns_200(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """提交脚本返回 200"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "这是一段测试脚本内容",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        assert response.status_code == 200

    @pytest.mark.asyncio
    async def test_submit_script_returns_review_result(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """提交脚本返回审核结果"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "这是一段测试脚本内容",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert isinstance(parsed.summary, str) and parsed.summary
        assert 0 <= parsed.score <= 100

    @pytest.mark.asyncio
    async def test_submit_empty_script_returns_422(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """提交空脚本返回 422"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        assert response.status_code == 422


class TestForbiddenWordDetection:
    """违禁词检测"""

    @pytest.mark.asyncio
    async def test_detect_absolute_word(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """检测广告极限词：最好、第一"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "我们的产品是全网最好的，销量第一",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert len(parsed.violations) > 0
        violation_types = [v.type for v in parsed.violations]
        assert ViolationType.FORBIDDEN_WORD in violation_types

    @pytest.mark.asyncio
    async def test_detect_efficacy_word(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """检测功效词：根治、治愈"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "使用我们的产品可以根治失眠问题",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        violation_types = [v.type for v in parsed.violations]
        assert ViolationType.EFFICACY_CLAIM in violation_types

    @pytest.mark.asyncio
    async def test_return_violation_position(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """返回违规词位置"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "这是最好的产品",  # "最好"是违禁词
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert len(parsed.violations) > 0, "应检测到'最好'违规"
        violation = parsed.violations[0]
        assert violation.position is not None
        assert violation.position.start >= 0
        assert violation.position.end > violation.position.start

    @pytest.mark.asyncio
    async def test_return_violation_suggestion(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """每个违规项包含修改建议"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "这是最好的产品",  # "最好"是违禁词
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert len(parsed.violations) > 0, "应检测到'最好'违规"
        assert isinstance(parsed.violations[0].suggestion, str)
        assert parsed.violations[0].suggestion


class TestContextUnderstanding:
    """语境理解（降低误报）"""

    @pytest.mark.asyncio
    async def test_non_ad_context_not_flagged(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """非广告语境不应标记为违规：最开心的一天"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "今天是我最开心的一天，因为见到了老朋友",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        forbidden_violations = [
            v for v in parsed.violations
            if v.type == ViolationType.FORBIDDEN_WORD and "最" in v.content
        ]
        assert len(forbidden_violations) == 0

    @pytest.mark.asyncio
    async def test_story_context_not_flagged(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """故事情节语境不应标记：他是第一个到达的人"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "他是第一个到达终点的人，大家都为他鼓掌",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        forbidden_violations = [
            v for v in parsed.violations
            if v.type == ViolationType.FORBIDDEN_WORD and "第一" in v.content
        ]
        assert len(forbidden_violations) == 0

    @pytest.mark.asyncio
    async def test_ad_context_flagged(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """广告语境应标记：我们的产品第一"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "我们的产品销量第一，品质最好",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert len(parsed.violations) > 0


class TestSellingPointCheck:
    """卖点遗漏检查"""

    @pytest.mark.asyncio
    async def test_check_missing_selling_points(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """检查是否遗漏必要卖点"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "这个产品很好用",
                "platform": "douyin",
                "brand_id": brand_id,
                "required_points": ["功效说明", "使用方法", "品牌名称"],
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert parsed.missing_points is not None
        assert isinstance(parsed.missing_points, list)

    @pytest.mark.asyncio
    async def test_all_points_covered(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """所有卖点都覆盖时返回空"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "品牌A的护肤精华，每天早晚各用一次，可以让肌肤更水润",
                "platform": "douyin",
                "brand_id": brand_id,
                "required_points": ["品牌名称", "使用方法", "功效说明"],
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert parsed.missing_points == []


class TestScoreCalculation:
    """合规分数计算"""

    @pytest.mark.asyncio
    async def test_clean_content_returns_high_score(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """合规内容返回高分（>=90）"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "今天给大家分享一个护肤小技巧，记得每天早晚洁面哦",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert parsed.score >= 90
        high_risk = [v for v in parsed.violations if v.severity.value == "high"]
        assert len(high_risk) == 0

    @pytest.mark.asyncio
    async def test_violation_content_returns_low_score(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """违规内容返回低分（<80）"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "这是最好的产品，可以根治所有问题，效果第一",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert parsed.score < 80
        assert len(parsed.violations) > 0

    @pytest.mark.asyncio
    async def test_score_range_valid(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """分数在有效范围内 0-100"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "任意内容",
                "platform": "douyin",
                "brand_id": brand_id,
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        assert 0 <= parsed.score <= 100


class TestSoftRiskWarnings:
    """软性风控提示"""

    @pytest.mark.asyncio
    async def test_near_threshold_returns_warning(self, client: AsyncClient, tenant_id: str, brand_id: str):
        """临界值接近阈值时返回软性提示（不阻断）"""
        response = await client.post(
            "/api/v1/scripts/review",
            headers={"X-Tenant-ID": tenant_id},
            json={
                "content": "内容正常但指标接近阈值",
                "platform": "douyin",
                "brand_id": brand_id,
                "soft_risk_context": {
                    "violation_rate": 0.045,
                    "violation_threshold": 0.05,
                }
            }
        )
        data = response.json()
        parsed = ScriptReviewResponse.model_validate(data)

        matched = [
            w for w in parsed.soft_warnings
            if w.code == "NEAR_THRESHOLD" and w.action_required == SoftRiskAction.CONFIRM
        ]
        assert matched, "应返回临界值软性提示"
        assert all(w.blocking is False for w in matched)