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