"""品牌引用LLM服务测试 - 迁移自 test_llm_adapter.py 原 LLMAdapter (System 3) 已被 BrandCitationLLMService (System 1) 替代。 本文件保留了所有原有的测试场景,使用新的服务接口。 """ import pytest from unittest.mock import AsyncMock, patch, MagicMock from app.services.llm.brand_citation_service import BrandCitationLLMService, BRAND_CITATION_PROMPT from app.services.llm.base import LLMError class TestBrandCitationLLMService: """品牌引用LLM服务测试(原 LLMAdapter 测试迁移)""" @pytest.fixture def service(self): """创建BrandCitationLLMService实例""" return BrandCitationLLMService() @pytest.mark.asyncio async def test_cited_brand(self, service): """测试检测到品牌引用""" mock_provider = AsyncMock() mock_provider.chat.return_value = MagicMock( content='{"cited": true, "position": 1, "citation_text": "XXX是一款非常优秀的品牌产品", "sentiment": "positive", "confidence": 0.95}' ) with patch.object(service, '_get_provider', return_value=mock_provider): with patch('app.services.llm.brand_citation_service.settings') as mock_settings: mock_settings.ENABLE_LLM = True result = await service.query_brand_citation( keyword="AI搜索", brand_name="XXX", brand_aliases=["品牌别名1", "品牌别名2"] ) assert result.cited is True assert result.position == 1 assert result.citation_text == "XXX是一款非常优秀的品牌产品" assert result.sentiment == "positive" assert result.confidence == 0.95 @pytest.mark.asyncio async def test_not_cited(self, service): """测试未检测到品牌引用""" mock_provider = AsyncMock() mock_provider.chat.return_value = MagicMock( content='{"cited": false, "position": null, "citation_text": null, "sentiment": "neutral", "confidence": 0.90}' ) with patch.object(service, '_get_provider', return_value=mock_provider): with patch('app.services.llm.brand_citation_service.settings') as mock_settings: mock_settings.ENABLE_LLM = True result = await service.query_brand_citation( keyword="AI搜索", brand_name="YYY", brand_aliases=[] ) assert result.cited is False assert result.position is None assert result.citation_text is None assert result.sentiment == "neutral" @pytest.mark.asyncio async def test_sentiment_positive(self, service): """测试正面情感""" mock_provider = AsyncMock() mock_provider.chat.return_value = MagicMock( content='{"cited": true, "position": 2, "citation_text": "YYY品牌产品质量非常好,用户口碑极佳", "sentiment": "positive", "confidence": 0.92}' ) with patch.object(service, '_get_provider', return_value=mock_provider): with patch('app.services.llm.brand_citation_service.settings') as mock_settings: mock_settings.ENABLE_LLM = True result = await service.query_brand_citation( keyword="AI搜索", brand_name="YYY", brand_aliases=[] ) assert result.sentiment == "positive" @pytest.mark.asyncio async def test_sentiment_negative(self, service): """测试负面情感""" mock_provider = AsyncMock() mock_provider.chat.return_value = MagicMock( content='{"cited": true, "position": 3, "citation_text": "ZZZ品牌存在质量问题,遭到用户投诉", "sentiment": "negative", "confidence": 0.88}' ) with patch.object(service, '_get_provider', return_value=mock_provider): with patch('app.services.llm.brand_citation_service.settings') as mock_settings: mock_settings.ENABLE_LLM = True result = await service.query_brand_citation( keyword="AI搜索", brand_name="ZZZ", brand_aliases=[] ) assert result.sentiment == "negative" @pytest.mark.asyncio async def test_parse_error(self, service): """测试响应解析错误""" mock_provider = AsyncMock() mock_provider.chat.return_value = MagicMock( content='{"invalid": "response"}' ) with patch.object(service, '_get_provider', return_value=mock_provider): with patch('app.services.llm.brand_citation_service.settings') as mock_settings: mock_settings.ENABLE_LLM = True with pytest.raises(LLMError) as exc_info: await service.query_brand_citation( keyword="AI搜索", brand_name="测试品牌", brand_aliases=[] ) error_msg = str(exc_info.value) assert "响应缺少必需字段" in error_msg or "解析响应失败" in error_msg def test_build_prompt(self, service): """测试Prompt构建""" prompt = service._build_prompt( keyword="AI搜索", brand_name="测试品牌", brand_aliases=["别名1", "别名2"] ) assert "AI搜索" in prompt assert "测试品牌" in prompt assert "别名1" in prompt assert "别名2" in prompt