688 lines
25 KiB
Python
688 lines
25 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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简化版离线整合测试脚本
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使用已有数据测试integration模块的不同效果
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调用真实AI进行内容整合
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"""
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import os
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import json
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import asyncio
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from typing import Dict, List, Optional, Any
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from datetime import datetime
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from pathlib import Path
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from dataclasses import dataclass
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# 添加项目根目录到路径
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import sys
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project_root = Path(__file__).parent
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sys.path.insert(0, str(project_root))
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# 导入核心模块
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from core.ai.ai_agent import AIAgent
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from core.config import ConfigManager, AIModelConfig
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from utils.prompts import PromptTemplate
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@dataclass
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class SimpleNote:
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"""简化的笔记数据模型"""
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note_id: str
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title: str
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content: str
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author: str
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likes: int
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comments: int
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shares: int
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note_url: str
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images: List[str]
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@dataclass
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class SimpleSearchResult:
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"""简化的搜索结果"""
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keyword: str
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notes: List[SimpleNote]
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total_count: int
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success: bool
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class OfflineIntegrationTester:
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"""离线整合测试器"""
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def __init__(self, data_file: str):
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"""
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初始化测试器
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Args:
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data_file: 离线数据文件路径
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"""
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self.data_file = data_file
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self.raw_data = None
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self.processed_notes = []
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# 初始化配置管理器和AI代理
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self.config_manager = ConfigManager()
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self.config_manager.load_from_directory("config", server_mode=True)
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# 获取AI配置并初始化AI代理
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ai_config = self.config_manager.get_config('ai_model', AIModelConfig)
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self.ai_agent = AIAgent(ai_config)
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# 加载integration prompt模板
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self.prompt_template = PromptTemplate(
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system_prompt_path="resource/prompt/integration/system.txt",
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user_prompt_path="resource/prompt/integration/user.txt"
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)
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# 加载数据
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self._load_data()
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print(f"✅ 离线测试器初始化完成，加载了 {len(self.processed_notes)} 条笔记数据")
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print(f"🤖 AI代理已初始化，模型: {ai_config.model}")
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def _load_data(self):
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"""加载离线数据"""
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try:
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with open(self.data_file, 'r', encoding='utf-8') as f:
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self.raw_data = json.load(f)
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# 转换为SimpleNote对象
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if 'results' in self.raw_data and self.raw_data['results']:
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result = self.raw_data['results'][0] # 取第一个搜索结果
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for note_data in result.get('notes', []):
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note = SimpleNote(
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note_id=note_data.get('note_id', ''),
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title=note_data.get('title', ''),
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content=note_data.get('content', ''),
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author=note_data.get('author', ''),
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likes=note_data.get('like_count', 0),
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comments=note_data.get('comment_count', 0),
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shares=note_data.get('share_count', 0),
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note_url=note_data.get('note_url', ''),
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images=note_data.get('images', [])
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)
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self.processed_notes.append(note)
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except Exception as e:
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print(f"❌ 数据加载失败: {e}")
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self.processed_notes = []
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def get_search_result(self, keyword: str = None) -> SimpleSearchResult:
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"""获取搜索结果"""
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if not keyword:
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keyword = self.raw_data['results'][0]['keyword'] if self.raw_data else '测试关键词'
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return SimpleSearchResult(
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keyword=keyword,
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notes=self.processed_notes,
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total_count=len(self.processed_notes),
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success=True
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)
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def create_mock_documents(self, content_type: str = "travel_guide") -> Dict[str, str]:
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"""创建模拟文档内容"""
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mock_docs = {
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"travel_guide": {
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"上海馥桂萌宠园游玩攻略.txt": """上海馥桂萌宠园游玩攻略
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一、园区简介
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馥桂萌宠园位于上海市嘉定区，是一个集萌宠互动、户外休闲、亲子娱乐为一体的综合性主题公园。
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二、开放信息
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- 开放时间：9:00-17:00（周一至周日）
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- 门票价格：成人票80元，儿童票50元（1.2米以下免费）
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- 地址：上海市嘉定区朱桥镇
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- 交通：地铁11号线嘉定西站转公交
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三、主要区域
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1. 萌宠互动区：可与羊驼、袋鼠、小兔子等动物亲密接触
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2. 户外游乐区：秋千、滑梯等儿童设施
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3. 餐饮休息区：提供简餐和饮品
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4. 桂花林区：春秋季节桂花飘香，适合拍照
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四、游玩建议
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- 建议游玩时间：3-4小时
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- 最佳游玩季节：春秋两季
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- 携带物品：防晒用品、湿巾、零食
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- 注意事项：爱护动物，文明游园""",
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"萌宠园交通指南.md": """# 馥桂萌宠园交通指南
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## 公共交通
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### 地铁+公交
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1. 地铁11号线至嘉定西站
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2. 转乘嘉定69路公交至朱桥站
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3. 步行约10分钟即可到达
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## 自驾路线
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从市区出发：
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1. 走外环高速(A20)
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2. 转嘉定环线(A5)
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3. 在朱桥出口下高速
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4. 沿指示牌行驶约5分钟
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## 停车信息
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- 园区提供免费停车场
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- 停车位约200个
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- 节假日建议早到，避免停车位紧张"""
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},
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"product_info": {
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"门票套餐信息.txt": """门票套餐信息
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基础门票：
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- 成人票：80元/人
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- 儿童票：50元/人（3-12岁）
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- 老年票：60元/人（65岁以上）
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- 免票：1.2米以下儿童
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套餐选择：
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1. 家庭套票（2大1小）：180元
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2. 亲子套票（1大1小）：120元
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3. 团体票（10人以上）：70元/人
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增值服务：
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- 动物喂食包：20元/份
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- 拍照服务：50元/次
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- 导览服务：100元/团"""
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},
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"user_reviews": {
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"游客评价汇总.txt": """游客评价汇总
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正面评价：
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✅ 动物种类丰富，互动性强
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✅ 环境优美，适合拍照
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✅ 工作人员服务态度好
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✅ 停车方便，交通便利
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✅ 价格合理，性价比高
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负面反馈：
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❌ 节假日人流量大
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❌ 餐饮选择相对有限
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❌ 部分设施需要维护
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❌ 雨天游玩体验一般
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综合评分：4.2/5.0"""
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}
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}
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return mock_docs.get(content_type, mock_docs["travel_guide"])
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def _format_xhs_notes(self, notes: List[SimpleNote]) -> str:
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"""格式化小红书笔记内容"""
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if not notes:
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return "暂无相关笔记内容"
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formatted_notes = []
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for i, note in enumerate(notes, 1):
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note_content = f"""第{i}条笔记：
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标题：{note.title}
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作者：{note.author}
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内容：{note.content if note.content else '（无文字内容）'}
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互动数据：👍{note.likes} 💬{note.comments} 🔄{note.shares}
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笔记链接：{note.note_url}
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"""
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if note.images:
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note_content += f"图片数量：{len(note.images)}张\n"
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formatted_notes.append(note_content)
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return "\n".join(formatted_notes)
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def _format_document_content(self, documents: Dict[str, str]) -> str:
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"""格式化文档内容"""
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if not documents:
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return "暂无文档内容"
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formatted_docs = []
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for filename, content in documents.items():
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doc_content = f"""文档：{filename}
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内容：
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{content}
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"""
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formatted_docs.append(doc_content)
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return "\n".join(formatted_docs)
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def test_basic_integration(self):
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"""测试基础整合功能"""
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print("\n" + "="*60)
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print("🔄 测试基础整合功能")
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print("="*60)
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# 获取数据
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search_result = self.get_search_result("上海馥桂萌宠园攻略")
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documents = self.create_mock_documents("travel_guide")
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print(f"📚 文档处理结果：")
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print(f" - 文档数量：{len(documents)}")
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total_doc_length = sum(len(content) for content in documents.values())
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print(f" - 总内容长度：{total_doc_length}")
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print(f"\n📱 小红书数据：")
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print(f" - 笔记数量：{len(search_result.notes)}")
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print(f" - 总点赞数：{sum(note.likes for note in search_result.notes)}")
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print(f" - 总评论数：{sum(note.comments for note in search_result.notes)}")
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# 显示部分内容示例
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print(f"\n📝 内容示例：")
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first_doc = list(documents.values())[0]
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print(f" 文档摘要：{first_doc[:100]}...")
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if search_result.notes:
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popular_note = max(search_result.notes, key=lambda x: x.likes)
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print(f" 热门笔记：{popular_note.title} (👍{popular_note.likes})")
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return {
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"search_result": search_result,
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"documents": documents
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}
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def test_different_document_types(self):
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"""测试不同文档类型的整合效果"""
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print("\n" + "="*60)
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print("📊 测试不同文档类型的整合效果")
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print("="*60)
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doc_types = ["travel_guide", "product_info", "user_reviews"]
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results = {}
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for doc_type in doc_types:
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print(f"\n🔸 处理文档类型：{doc_type}")
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documents = self.create_mock_documents(doc_type)
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total_length = sum(len(content) for content in documents.values())
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results[doc_type] = {
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"document_count": len(documents),
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"content_length": total_length,
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"files": list(documents.keys())
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}
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print(f" ✅ 文档数量：{results[doc_type]['document_count']}")
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print(f" ✅ 内容长度：{results[doc_type]['content_length']}")
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print(f" ✅ 文件列表：{results[doc_type]['files']}")
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return results
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def test_content_filtering(self):
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"""测试内容过滤和筛选"""
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print("\n" + "="*60)
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print("🔍 测试内容过滤和筛选")
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print("="*60)
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search_result = self.get_search_result()
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# 按点赞数筛选
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high_quality_notes = [note for note in search_result.notes if note.likes >= 50]
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print(f"📈 高质量笔记（点赞≥50）：{len(high_quality_notes)} 条")
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# 按评论数筛选
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interactive_notes = [note for note in search_result.notes if note.comments >= 10]
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print(f"💬 高互动笔记（评论≥10）：{len(interactive_notes)} 条")
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# 按标题关键词筛选
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guide_notes = [note for note in search_result.notes if '攻略' in note.title or '指南' in note.title]
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print(f"📋 攻略类笔记：{len(guide_notes)} 条")
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# 显示统计信息
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if search_result.notes:
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avg_likes = sum(note.likes for note in search_result.notes) / len(search_result.notes)
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avg_comments = sum(note.comments for note in search_result.notes) / len(search_result.notes)
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print(f"\n📊 统计信息：")
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print(f" 平均点赞数：{avg_likes:.1f}")
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print(f" 平均评论数：{avg_comments:.1f}")
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# 找出最受欢迎的笔记
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most_liked = max(search_result.notes, key=lambda x: x.likes)
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most_commented = max(search_result.notes, key=lambda x: x.comments)
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print(f"\n🏆 最受欢迎：")
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print(f" 最多点赞：《{most_liked.title}》- {most_liked.likes} 赞")
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print(f" 最多评论：《{most_commented.title}》- {most_commented.comments} 评论")
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return {
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"total_notes": len(search_result.notes),
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"high_quality_notes": len(high_quality_notes),
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"interactive_notes": len(interactive_notes),
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"guide_notes": len(guide_notes)
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}
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async def test_real_ai_integration(self):
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"""测试真实AI整合功能"""
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print("\n" + "="*60)
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print("🤖 测试真实AI整合功能")
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print("="*60)
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try:
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# 准备数据
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search_result = self.get_search_result()
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documents = self.create_mock_documents("travel_guide")
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print("🔄 正在准备数据...")
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# 格式化文档内容
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document_content = self._format_document_content(documents)
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# 格式化小红书笔记内容
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xhs_content = self._format_xhs_notes(search_result.notes)
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# 构建prompt
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system_prompt = self.prompt_template.get_system_prompt()
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user_prompt = self.prompt_template.build_user_prompt(
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keywords=search_result.keyword or "馥桂萌宠园",
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document_content=document_content or "暂无文档内容",
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xhs_notes_content=xhs_content or "暂无笔记内容"
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)
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print(f"📝 System Prompt长度: {len(system_prompt)} 字符")
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print(f"📝 User Prompt长度: {len(user_prompt)} 字符")
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# 调用真实AI
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print("🔄 正在调用AI进行内容整合...")
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start_time = datetime.now()
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response_text, input_tokens, output_tokens, time_cost = await self.ai_agent.generate_text(
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system_prompt=system_prompt,
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user_prompt=user_prompt,
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use_stream=True,
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stage="content_integration",
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)
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end_time = datetime.now()
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print("✅ AI整合完成")
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print(f"📄 生成内容长度：{len(response_text)} 字符")
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print(f"🎯 输入Token数：{input_tokens}")
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print(f"🎯 输出Token数：{output_tokens}")
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print(f"⏱️ 处理时间：{time_cost:.2f} 秒")
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# 尝试解析JSON
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try:
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# 使用file_io模块的JSON处理功能
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from utils.file_io import process_llm_json_text
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parsed_json = process_llm_json_text(response_text)
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if parsed_json:
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print("✅ JSON解析成功")
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print(f"📊 解析结果包含 {len(parsed_json)} 个顶级字段")
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# 显示解析后的结构
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if isinstance(parsed_json, dict):
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print("🏗️ 数据结构：")
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for key, value in parsed_json.items():
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if isinstance(value, dict):
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print(f" {key}: 包含 {len(value)} 个子字段")
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elif isinstance(value, list):
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print(f" {key}: 列表，包含 {len(value)} 个项目")
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else:
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print(f" {key}: {type(value).__name__}")
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formatted_response = json.dumps(parsed_json, ensure_ascii=False, indent=2)
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else:
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print("⚠️ JSON解析失败，使用原始响应")
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formatted_response = response_text
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except Exception as parse_error:
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print(f"⚠️ JSON解析出错: {parse_error}")
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formatted_response = response_text
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print(f"\n📝 AI响应预览：")
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preview_text = formatted_response[:500] + "..." if len(formatted_response) > 500 else formatted_response
|
||
print(preview_text)
|
||
|
||
return {
|
||
"ai_response": formatted_response,
|
||
"content_length": len(response_text),
|
||
"input_tokens": input_tokens,
|
||
"output_tokens": output_tokens,
|
||
"processing_time": time_cost,
|
||
"source_notes": len(search_result.notes),
|
||
"source_docs": len(documents),
|
||
"json_parsed": parsed_json is not None
|
||
}
|
||
|
||
except Exception as e:
|
||
print(f"❌ AI整合测试失败：{e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return None
|
||
|
||
def test_export_formats(self):
|
||
"""测试不同导出格式"""
|
||
print("\n" + "="*60)
|
||
print("📤 测试不同导出格式")
|
||
print("="*60)
|
||
|
||
search_result = self.get_search_result()
|
||
documents = self.create_mock_documents("travel_guide")
|
||
|
||
# 模拟不同格式的导出
|
||
formats = {
|
||
"summary": "简要摘要格式",
|
||
"blog_post": "博客文章格式",
|
||
"travel_guide": "旅游攻略格式",
|
||
"product_sales": "产品销售格式",
|
||
"attraction_standard": "景点标准格式"
|
||
}
|
||
|
||
export_results = {}
|
||
|
||
for format_type, description in formats.items():
|
||
print(f"🔸 生成{description}...")
|
||
|
||
# 模拟不同格式的内容生成
|
||
mock_content = self._generate_format_content(format_type, search_result, documents)
|
||
|
||
export_results[format_type] = {
|
||
"content": mock_content,
|
||
"length": len(mock_content),
|
||
"format": format_type
|
||
}
|
||
|
||
print(f" ✅ 长度：{len(mock_content)} 字符")
|
||
|
||
return export_results
|
||
|
||
def _generate_format_content(self, format_type: str, search_result: SimpleSearchResult, documents: Dict[str, str]) -> str:
|
||
"""根据格式类型生成相应内容"""
|
||
|
||
base_info = f"基于{len(search_result.notes)}篇小红书游记和官方资料"
|
||
|
||
if format_type == "summary":
|
||
return f"【简要摘要】{base_info}，馥桂萌宠园是嘉定区优质亲子游目的地，特色萌宠互动体验，适合周末家庭出游。"
|
||
|
||
elif format_type == "blog_post":
|
||
return f"""# 周末带娃新选择 | 上海馥桂萌宠园深度体验
|
||
|
||
今天想和大家分享一个超棒的亲子游目的地——位于嘉定的馥桂萌宠园！{base_info}，这里真的是遛娃神器！
|
||
|
||
## 为什么推荐这里？
|
||
🦘 可以近距离接触羊驼、袋鼠等萌宠
|
||
🌸 环境优美，特别是桂花季节
|
||
👨👩👧👦 设施完善，非常适合家庭游
|
||
|
||
详细攻略请看下文..."""
|
||
|
||
elif format_type == "travel_guide":
|
||
return f"""## 上海馥桂萌宠园游玩攻略
|
||
|
||
### 基本信息
|
||
- 地址：上海市嘉定区朱桥镇
|
||
- 门票：成人80元，儿童50元
|
||
- 开放时间：9:00-17:00
|
||
|
||
### 交通指南
|
||
地铁11号线嘉定西站转公交，或自驾直达
|
||
|
||
### 游玩亮点
|
||
{base_info}，园区主要特色包括萌宠互动、户外游乐、休闲拍照等。
|
||
|
||
### 注意事项
|
||
建议游玩3-4小时，春秋季节体验最佳。"""
|
||
|
||
elif format_type == "product_sales":
|
||
return f"""🔥【限时特惠】上海馥桂萌宠园门票
|
||
|
||
⭐ 产品亮点：
|
||
• {base_info}，口碑爆棚！
|
||
• 🦘 独特萌宠互动体验
|
||
• 🌸 网红拍照打卡圣地
|
||
• 👨👩👧👦 亲子游首选目的地
|
||
|
||
💰 特价套餐：
|
||
原价130元，现价只要99元！
|
||
包含：成人门票1张 + 动物喂食包1份
|
||
|
||
📞 立即预订：xxx-xxxx-xxxx"""
|
||
|
||
else: # attraction_standard
|
||
return f"""景点名称：上海馥桂萌宠园
|
||
景点类型：主题公园/动物园
|
||
地理位置：上海市嘉定区朱桥镇
|
||
开放状态：正常营业
|
||
门票价格：80-50元
|
||
适宜人群：亲子家庭
|
||
推荐指数：4.2/5.0
|
||
游玩时长：3-4小时
|
||
最佳季节：春秋两季
|
||
|
||
{base_info}，具有良好的口碑和游客体验。"""
|
||
|
||
def test_parameter_effects(self):
|
||
"""测试不同参数的效果"""
|
||
print("\n" + "="*60)
|
||
print("⚙️ 测试不同参数的效果")
|
||
print("="*60)
|
||
|
||
search_result = self.get_search_result()
|
||
|
||
# 测试不同的过滤阈值
|
||
thresholds = [
|
||
{"likes": 20, "comments": 5},
|
||
{"likes": 50, "comments": 10},
|
||
{"likes": 100, "comments": 20}
|
||
]
|
||
|
||
print("🔧 测试不同过滤阈值的效果：")
|
||
for i, threshold in enumerate(thresholds, 1):
|
||
high_likes = [note for note in search_result.notes if note.likes >= threshold["likes"]]
|
||
high_comments = [note for note in search_result.notes if note.comments >= threshold["comments"]]
|
||
|
||
print(f" 阈值{i}（点赞≥{threshold['likes']}, 评论≥{threshold['comments']}）:")
|
||
print(f" - 符合点赞条件：{len(high_likes)} 条")
|
||
print(f" - 符合评论条件：{len(high_comments)} 条")
|
||
|
||
# 测试不同的内容长度限制
|
||
length_limits = [100, 200, 500]
|
||
|
||
print(f"\n📏 测试不同内容长度限制的效果：")
|
||
for limit in length_limits:
|
||
documents = self.create_mock_documents("travel_guide")
|
||
truncated_docs = {}
|
||
for filename, content in documents.items():
|
||
truncated_docs[filename] = content[:limit] + "..." if len(content) > limit else content
|
||
|
||
total_length = sum(len(content) for content in truncated_docs.values())
|
||
print(f" 限制{limit}字符：总长度 {total_length} 字符")
|
||
|
||
return {
|
||
"threshold_tests": len(thresholds),
|
||
"length_tests": len(length_limits)
|
||
}
|
||
|
||
async def main():
|
||
"""主函数"""
|
||
print("🚀 启动真实AI离线整合测试...")
|
||
|
||
# 检查数据文件
|
||
data_file = "batch_search_20250717_104407.json"
|
||
if not os.path.exists(data_file):
|
||
print(f"❌ 数据文件不存在：{data_file}")
|
||
return
|
||
|
||
# 初始化测试器
|
||
try:
|
||
tester = OfflineIntegrationTester(data_file)
|
||
except Exception as e:
|
||
print(f"❌ 测试器初始化失败：{e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return
|
||
|
||
try:
|
||
# 执行各种测试
|
||
print(f"\n{'='*60}")
|
||
print("🧪 开始执行真实AI离线整合测试套件")
|
||
print(f"{'='*60}")
|
||
|
||
# 1. 基础整合测试
|
||
basic_result = tester.test_basic_integration()
|
||
|
||
# 2. 不同文档类型测试
|
||
doc_type_results = tester.test_different_document_types()
|
||
|
||
# 3. 内容过滤测试
|
||
filter_results = tester.test_content_filtering()
|
||
|
||
# 4. 真实AI整合测试（异步）
|
||
ai_results = await tester.test_real_ai_integration()
|
||
with open("ai_results.json", "w") as f:
|
||
json.dump(ai_results, f, ensure_ascii=False, indent=2)
|
||
# 5. 导出格式测试
|
||
export_results = tester.test_export_formats()
|
||
|
||
# 6. 参数效果测试
|
||
param_results = tester.test_parameter_effects()
|
||
|
||
# 输出测试总结
|
||
print(f"\n{'='*60}")
|
||
print("📋 测试结果总结")
|
||
print(f"{'='*60}")
|
||
|
||
print(f"✅ 基础整合测试：成功")
|
||
print(f"✅ 文档类型测试：处理了 {len(doc_type_results)} 种类型")
|
||
print(f"✅ 内容过滤测试：识别出 {filter_results['high_quality_notes']} 条高质量笔记")
|
||
|
||
if ai_results:
|
||
print(f"✅ 真实AI整合测试：成功")
|
||
print(f" - 处理时间：{ai_results['processing_time']:.2f}秒")
|
||
print(f" - 输入Token：{ai_results['input_tokens']}")
|
||
print(f" - 输出Token：{ai_results['output_tokens']}")
|
||
print(f" - JSON解析：{'成功' if ai_results['json_parsed'] else '失败'}")
|
||
else:
|
||
print(f"❌ 真实AI整合测试：失败")
|
||
|
||
# print(f"✅ 导出格式测试：生成了 {len(export_results)} 种格式")
|
||
# print(f"✅ 参数效果测试：测试了 {param_results['threshold_tests']} 种阈值配置")
|
||
|
||
# print(f"\n🎉 所有测试完成！")
|
||
|
||
# # 提供测试建议
|
||
# print(f"\n💡 测试建议：")
|
||
# print(f" 1. 可以调整AI模型参数（temperature、top_p等）来优化输出质量")
|
||
# print(f" 2. 可以修改integration prompt模板来改进整合效果")
|
||
# print(f" 3. 可以测试不同的文档类型组合")
|
||
# print(f" 4. 可以调整内容过滤的阈值")
|
||
# print(f" 5. 可以测试不同的导出格式效果")
|
||
|
||
# # 显示原始数据概览
|
||
# if tester.raw_data:
|
||
# summary = tester.raw_data.get('summary', {})
|
||
# print(f"\n📊 原始数据概览：")
|
||
# print(f" - 总关键词数：{summary.get('total_keywords', 0)}")
|
||
# print(f" - 成功搜索数：{summary.get('successful_searches', 0)}")
|
||
# print(f" - 总笔记数：{summary.get('total_notes', 0)}")
|
||
# print(f" - 总互动数：{summary.get('total_interactions', 0)}")
|
||
|
||
except Exception as e:
|
||
print(f"❌ 测试过程中发生错误：{e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
|
||
if __name__ == "__main__":
|
||
asyncio.run(main()) |