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构建并部署 AI Agent 服务 / deploy (push) Failing after 6m13s
- 将默认嵌入模型从 embedding-3 (2048维) 改为 embedding-2 (1024维)，解决Qdrant维度不匹配问题 - 优化web_search.py，增加详细日志输出和更好的错误处理 - 更新模拟搜索结果，增加提示信息
181 lines
6.1 KiB
Python
181 lines
6.1 KiB
Python
"""
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联网搜索公共工具 - 无需 API Key，免费使用 DuckDuckGo
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Web Search Public Utility - Free, no API Key, using DuckDuckGo
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"""
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from typing import List, Dict, Any, Optional
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from dataclasses import dataclass
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from datetime import datetime
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@dataclass
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class SearchResult:
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"""搜索结果数据类"""
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title: str
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url: str
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snippet: str
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source: str = "DuckDuckGo"
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timestamp: datetime = None
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def __post_init__(self):
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if self.timestamp is None:
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self.timestamp = datetime.now()
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class WebSearchTool:
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"""联网搜索公共工具类"""
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def __init__(self, max_results: int = 5):
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self.max_results = max_results
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def search(self, query: str, max_results: Optional[int] = None) -> List[SearchResult]:
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"""
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使用 DuckDuckGo 搜索
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Args:
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query: 搜索关键词
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max_results: 返回结果数量，默认使用初始化时的设置
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Returns:
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搜索结果列表
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"""
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num_results = max_results or self.max_results
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# 方法1: 尝试使用 duckduckgo-search 库
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try:
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from duckduckgo_search import DDGS
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print(f"[WebSearch] 使用 DuckDuckGo 搜索: {query}")
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with DDGS() as ddgs:
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results = list(ddgs.text(query, max_results=num_results))
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if results:
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search_results = []
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for r in results:
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search_results.append(SearchResult(
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title=r.get("title", ""),
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url=r.get("href", ""),
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snippet=r.get("body", ""),
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source="DuckDuckGo"
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))
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print(f"[WebSearch] DuckDuckGo 返回 {len(search_results)} 条结果")
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return search_results
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except ImportError:
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print("[WebSearch] duckduckgo-search 未安装，尝试备用方案")
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except Exception as e:
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print(f"[WebSearch] DuckDuckGo 搜索失败: {e}")
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# 方法2: 尝试使用 requests 直接调用简单搜索API
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try:
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import requests
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print(f"[WebSearch] 使用备用搜索方案")
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# 使用百度搜索的简易接口（仅作演示）
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# 或者返回一些模拟的提示结果
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return self._search_mock(query, num_results)
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except Exception as e:
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print(f"[WebSearch] 备用方案也失败: {e}")
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# 方法3: 返回模拟数据作为最后兜底
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return self._search_mock(query, num_results)
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def _search_mock(self, query: str, max_results: Optional[int] = None) -> List[SearchResult]:
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"""模拟搜索结果（兜底方案）"""
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print(f"[WebSearch] 使用模拟搜索结果 (查询: {query})")
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# 根据查询内容生成更有意义的模拟结果
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mock_templates = [
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{
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"title": f"关于「{query}」的相关介绍",
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"snippet": "这是一个模拟的搜索结果。在实际部署中，需要确保网络连接正常，或者配置其他可用的搜索API。",
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"url": "https://example.com/about"
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},
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{
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"title": f"「{query}」 - 最新动态",
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"snippet": "搜索功能暂时使用模拟数据。请检查容器网络配置，或联系管理员配置可用的搜索服务。",
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"url": "https://example.com/latest"
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},
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{
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"title": f"了解更多关于「{query}」的内容",
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"snippet": "提示：如果需要真实的联网搜索，可以考虑使用 Bing Search API、Google Custom Search JSON API 或其他商用搜索服务。",
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"url": "https://example.com/more"
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}
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]
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num = max_results or self.max_results
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results = []
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for i, template in enumerate(mock_templates[:num]):
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results.append(SearchResult(
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title=template["title"],
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url=template["url"],
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snippet=template["snippet"],
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source="模拟数据"
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))
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return results
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def format_search_results(self, results: List[SearchResult]) -> str:
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"""
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格式化搜索结果（带引用溯源）
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Args:
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results: 搜索结果列表
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Returns:
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格式化后的 Markdown 文本
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"""
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if not results:
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return "未找到相关搜索结果"
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lines = []
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lines.append("## 🔍 联网搜索结果\n")
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for idx, result in enumerate(results, 1):
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lines.append(f"### [{idx}] {result.title}")
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lines.append(f"- 🔗 来源：[{result.url}]({result.url})")
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lines.append(f"- 📝 摘要：{result.snippet}")
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lines.append(f"- 📅 时间：{result.timestamp.strftime('%Y-%m-%d %H:%M:%S')}")
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lines.append("")
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# 添加引用溯源说明
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lines.append("---")
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lines.append("💡 **引用溯源说明**：")
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lines.append("- 以上搜索结果均标注了来源链接")
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lines.append("- 使用方括号数字标识引用（如 [1]、[2]）")
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lines.append("- 可通过链接追溯原始信息")
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return "\n".join(lines)
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# 单例实例
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_web_search_tool = None
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def get_web_search_tool() -> WebSearchTool:
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"""获取联网搜索工具单例"""
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global _web_search_tool
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if _web_search_tool is None:
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_web_search_tool = WebSearchTool()
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return _web_search_tool
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def web_search(query: str, max_results: int = 5) -> str:
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"""
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便捷函数：联网搜索并返回格式化结果
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Args:
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query: 搜索关键词
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max_results: 返回结果数量
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Returns:
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格式化后的搜索结果文本
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"""
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tool = get_web_search_tool()
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results = tool.search(query, max_results)
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return tool.format_search_results(results)
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