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构建并部署 AI Agent 服务 / deploy (push) Successful in 12m9s
## 核心改动 ### 1. 单图方案重构 - 删除了多图(self.graphs),改为单图(self.graph) - 新增 MainGraphState.current_model 字段用于运行时注入模型 - llm_call 节点改为动态选择模型(create_dynamic_llm_call_node) ### 2. chat_services 优化 - 添加 _cached_services 缓存,避免重复初始化 - 新增 get_cached_chat_services() 函数,用于单图注入 - 新增 _check_http_service_available() 统一HTTP探测逻辑 - 减少重复代码,LocalVLLMChatProvider和LocalSmallModelProvider共用探测方法 ### 3. AIAgentService 重构 - initialize() 只构建一次图,传入 chat_services 字典 - 新增 _resolve_model() 模型回退逻辑 - 新增 _build_invocation() 统一构建调用参数 - process_message() 和 process_message_stream() 改为注入 current_model - 流式处理代码拆分,增加可读性 ### 4. 新增和删除文件 - 新增:backend/app/main_graph/main_graph_builder.py(图构建) - 新增:backend/app/main_graph/subgraph_wrapper.py(子图封装) - 新增:tools/test/test_tavily_search.py(测试) - 删除:backend/app/main_graph/graph.py(旧图) - 删除:backend/app/main_graph/utils/main_graph_builder.py(旧构建器) - 删除:backend/app/main_graph/utils/__init__.py ### 5. 其他更新 - README.md:新增模型服务使用情况详解章节 - backend/app/model_services/__init__.py:新增 get_cached_chat_services 导出 ## 方案优势 - 内存优化:N张图 → 1张图 - 灵活性:运行时动态选择模型,支持同会话不同模型 - 性能:模型服务缓存,初始化仅一次 - 可维护性:减少重复代码,统一HTTP探测逻辑
253 lines
8.6 KiB
Python
253 lines
8.6 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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import requests
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import warnings
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import re
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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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使用多种方式搜索,按优先级尝试
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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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# 方式 1: Tavily (需要 API Key,质量最高)
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try:
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return self._search_tavily(query, num_results)
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except ImportError:
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print("[WebSearch] tavily 未安装,尝试其他搜索方式")
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except Exception as e:
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if "API_KEY" in str(e) or "未配置" in str(e):
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print(f"[WebSearch] Tavily API Key 未配置: {e}")
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else:
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print(f"[WebSearch] Tavily 搜索失败: {e}")
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# 方式 2: 尝试用 ddgs 包
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try:
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from ddgs import DDGS
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print(f"[WebSearch] 使用 ddgs 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] ddgs 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] ddgs 未安装,尝试 duckduckgo-search")
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except Exception as e:
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print(f"[WebSearch] ddgs 搜索失败: {e}")
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# 方式 3: 尝试用简单 HTTP 请求
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try:
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return self._search_http(query, num_results)
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except Exception as e:
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print(f"[WebSearch] HTTP 搜索也失败: {e}")
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# 方式 4: 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_tavily(self, query: str, max_results: int) -> List[SearchResult]:
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"""使用 Tavily API 搜索"""
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from tavily import TavilyClient
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from app.config import TAVILY_API_KEY, TAVILY_MAX_RESULTS
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if not TAVILY_API_KEY:
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raise ValueError("TAVILY_API_KEY 未配置")
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client = TavilyClient(api_key=TAVILY_API_KEY)
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response = client.search(
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query=query,
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max_results=min(max_results, TAVILY_MAX_RESULTS or 5),
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include_answer=True,
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include_raw_content=False
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)
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results = []
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for item in response.get("results", []):
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results.append(SearchResult(
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title=item.get("title", ""),
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url=item.get("url", ""),
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snippet=item.get("content", ""),
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source="Tavily"
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))
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print(f"[WebSearch] Tavily 返回 {len(results)} 条结果")
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return results
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def _search_http(self, query: str, max_results: int) -> List[SearchResult]:
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"""用简单 HTTP 请求搜索(备用方案)- 尝试多个国内源"""
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print(f"[WebSearch] 尝试 HTTP 搜索")
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# 方式 1: 尝试百度搜索(简单方式)
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try:
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return self._search_baidu(query, max_results)
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except Exception as e:
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print(f"[WebSearch] 百度搜索失败: {e}")
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# 方式 2: 返回模拟数据
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return self._search_mock(query, max_results)
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def _search_baidu(self, query: str, max_results: int) -> List[SearchResult]:
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"""尝试百度搜索"""
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import requests
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from urllib.parse import quote
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url = f"https://www.baidu.com/s?wd={quote(query)}"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
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}
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try:
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response = requests.get(url, headers=headers, timeout=10)
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response.raise_for_status()
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# 简单解析百度搜索结果(简化版)
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results = []
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# 这里只是示意,真实百度搜索需要更复杂的解析
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results.append(SearchResult(
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title=f"百度搜索: {query}",
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url=url,
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snippet="如需要真实搜索结果,请考虑使用百度搜索 API",
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source="百度"
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))
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return results
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except Exception as e:
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print(f"[WebSearch] 百度搜索也失败: {e}")
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raise
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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": "这是模拟结果。如需真实搜索,请检查容器网络连接或配置代理。",
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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": "提示:在容器内运行时,需要确保能访问外网。",
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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": "建议:检查 Docker 网络配置,或使用代理。",
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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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