{"id":113204,"date":"2026-10-05T18:25:29","date_gmt":"2026-10-05T10:25:29","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/113204.html"},"modified":"2026-10-05T18:25:29","modified_gmt":"2026-10-05T10:25:29","slug":"%e7%88%ac%e8%99%abagent%ef%bc%9a%e6%89%a7%e8%a1%8c%e5%bc%8fai%e8%87%aa%e5%8a%a8%e9%87%87%e9%9b%86%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/113204.html","title":{"rendered":"\u722c\u866bAgent\uff1a\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e"},"content":{"rendered":"

\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/h2>\n

\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e<\/p>\n

📝 \u672c\u7ae0\u5b66\u4e60\u76ee\u6807：\u672c\u7ae0\u5c55\u793a\u884c\u4e1a\u5b9e\u6218\u6848\u4f8b，\u5e2e\u52a9\u8bfb\u8005\u5c06\u7406\u8bba\u5e94\u7528\u4e8e\u5b9e\u8df5\u3002\u901a\u8fc7\u672c\u7ae0\u5b66\u4e60，\u4f60\u5c06\u5168\u9762\u638c\u63e1"\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e"\u8fd9\u4e00\u6838\u5fc3\u4e3b\u9898\u3002<\/p>\n

\n

\u4e00\u3001\u5f15\u8a00：\u4e3a\u4ec0\u4e48\u8fd9\u4e2a\u8bdd\u9898\u5982\u6b64\u91cd\u8981<\/h3>\n

\u5728AI Agent\u5feb\u901f\u53d1\u5c55\u7684\u4eca\u5929，\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u5df2\u7ecf\u6210\u4e3a\u6bcf\u4e2a\u5f00\u53d1\u8005\u548c\u7814\u7a76\u8005\u5fc5\u987b\u4e86\u89e3\u7684\u6838\u5fc3\u77e5\u8bc6\u3002\u65e0\u8bba\u4f60\u662f\u6280\u672f\u80cc\u666f\u8fd8\u662f\u975e\u6280\u672f\u80cc\u666f，\u7406\u89e3\u8fd9\u4e00\u6982\u5ff5\u90fd\u5c06\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u628a\u63e1AI\u65f6\u4ee3\u7684\u673a\u9047\u3002<\/p>\n

1.1 \u80cc\u666f\u4e0e\u610f\u4e49<\/h4>\n

💡 \u6838\u5fc3\u8ba4\u77e5：AI Agent\u6b63\u5728\u4ece"\u5bf9\u8bdd\u5de5\u5177"\u8fdb\u5316\u4e3a"\u6267\u884c\u5f15\u64ce"，\u80fd\u591f\u4e3b\u52a8\u5b8c\u6210\u4efb\u52a1\u3001\u8c03\u7528\u5de5\u5177\u3001\u4e0e\u5916\u90e8\u4e16\u754c\u4ea4\u4e92\u3002\u8fd9\u4e00\u53d8\u9769\u6b63\u5728\u6df1\u523b\u6539\u53d8\u6211\u4eec\u7684\u5de5\u4f5c\u548c\u751f\u6d3b\u65b9\u5f0f\u3002<\/p>\n

\u4ece2023\u5e74AutoGPT\u7684\u6a2a\u7a7a\u51fa\u4e16，\u5230\u5982\u4eca\u767e\u82b1\u9f50\u653e\u7684Agent\u751f\u6001，\u77ed\u77ed\u4e00\u5e74\u591a\u65f6\u95f4，\u6267\u884c\u5f0fAI\u5df2\u7ecf\u4ece\u6982\u5ff5\u8d70\u5411\u843d\u5730\u3002\u6839\u636e\u6700\u65b0\u7edf\u8ba1，\u5168\u7403AI Agent\u5e02\u573a\u89c4\u6a21\u5df2\u7a81\u7834\u767e\u4ebf\u7f8e\u5143，\u5e74\u589e\u957f\u7387\u8d85\u8fc7100%\u3002\u8fd9\u4e00\u6570\u5b57\u80cc\u540e，\u662f\u65e0\u6570\u4f01\u4e1a\u548c\u4e2a\u4eba\u6b63\u5728\u7ecf\u5386\u7684\u667a\u80fd\u5316\u8f6c\u578b\u3002<\/p>\n

1.2 \u672c\u7ae0\u7ed3\u6784\u6982\u89c8<\/h4>\n

\u4e3a\u4e86\u5e2e\u52a9\u8bfb\u8005\u7cfb\u7edf\u6027\u5730\u638c\u63e1\u672c\u7ae0\u5185\u5bb9，\u6211\u5c06\u4ece\u4ee5\u4e0b\u51e0\u4e2a\u7ef4\u5ea6\u5c55\u5f00：<\/p>\n

📊 \u7406\u8bba\u57fa\u7840 \u2192 \u6838\u5fc3\u6982\u5ff5 \u2192 \u6280\u672f\u539f\u7406 \u2192 \u5b9e\u8df5\u5e94\u7528 \u2192 \u6848\u4f8b\u5206\u6790 \u2192 \u603b\u7ed3\u5c55\u671b<\/p>\n

\n

\u4e8c\u3001\u6838\u5fc3\u6982\u5ff5\u89e3\u6790<\/h3>\n

2.1 \u57fa\u672c\u5b9a\u4e49<\/h4>\n

\u8ba9\u6211\u4eec\u9996\u5148\u660e\u786e\u51e0\u4e2a\u6838\u5fc3\u6982\u5ff5：<\/p>\n

\u6982\u5ff5\u4e00：\u57fa\u7840\u5b9a\u4e49<\/p>\n

\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u662f\u6307\u5728AI Agent\u9886\u57df\u4e2d，\u4e0e\u8be5\u4e3b\u9898\u76f8\u5173\u7684\u6838\u5fc3\u6280\u672f\u6216\u5e94\u7528\u3002\u5b83\u6d89\u53ca\u591a\u4e2a\u5b66\u79d1\u4ea4\u53c9，\u5305\u62ec\u4eba\u5de5\u667a\u80fd\u3001\u8f6f\u4ef6\u5de5\u7a0b\u3001\u7cfb\u7edf\u67b6\u6784\u7b49\u3002<\/p>\n

\u6982\u5ff5\u4e8c：\u6280\u672f\u5185\u6db5<\/p>\n

\u4ece\u6280\u672f\u89d2\u5ea6\u770b，\u8fd9\u4e00\u6982\u5ff5\u5305\u542b\u4ee5\u4e0b\u51e0\u4e2a\u5c42\u9762：<\/p>\n\n\u7ef4\u5ea6\u8bf4\u660e\u91cd\u8981\u7a0b\u5ea6<\/tr>\n\n\n\n\n\n
\u7406\u8bba\u57fa\u7840<\/td>\n\u652f\u6491\u8be5\u6280\u672f\u7684\u7b97\u6cd5\u548c\u67b6\u6784\u539f\u7406<\/td>\n\u2b50\u2b50\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n
\u5de5\u7a0b\u5b9e\u73b0<\/td>\n\u5c06\u7406\u8bba\u8f6c\u5316\u4e3a\u53ef\u8fd0\u884c\u7cfb\u7edf\u7684\u8fc7\u7a0b<\/td>\n\u2b50\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n
\u5e94\u7528\u573a\u666f<\/td>\n\u6280\u672f\u53ef\u4ee5\u89e3\u51b3\u7684\u5b9e\u9645\u95ee\u9898<\/td>\n\u2b50\u2b50\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n
\u53d1\u5c55\u8d8b\u52bf<\/td>\n\u6280\u672f\u7684\u672a\u6765\u6f14\u8fdb\u65b9\u5411<\/td>\n\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

2.2 \u5173\u952e\u672f\u8bed\u89e3\u91ca<\/h4>\n

\u26a0\ufe0f \u6ce8\u610f：\u4ee5\u4e0b\u672f\u8bed\u662f\u7406\u89e3\u672c\u7ae0\u5185\u5bb9\u7684\u57fa\u7840，\u8bf7\u52a1\u5fc5\u638c\u63e1\u3002<\/p>\n

\u672f\u8bed1：\u6838\u5fc3\u6982\u5ff5<\/p>\n

\u8fd9\u662f\u7406\u89e3\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u7684\u5173\u952e\u3002\u7b80\u5355\u6765\u8bf4，\u5b83\u6307\u7684\u662f\u5728AI Agent\u6267\u884c\u8fc7\u7a0b\u4e2d，\u5b9e\u73b0\u7279\u5b9a\u529f\u80fd\u7684\u65b9\u6cd5\u548c\u673a\u5236\u3002<\/p>\n

\u672f\u8bed2：\u6280\u672f\u6307\u6807<\/p>\n

\u5728\u8bc4\u4f30\u76f8\u5173\u6280\u672f\u65f6，\u6211\u4eec\u901a\u5e38\u5173\u6ce8\u4ee5\u4e0b\u6307\u6807：<\/p>\n

    \n
  • \u6267\u884c\u6548\u7387：\u5b8c\u6210\u4efb\u52a1\u6240\u9700\u7684\u65f6\u95f4\u548c\u8d44\u6e90<\/li>\n
  • \u51c6\u786e\u7387：\u6267\u884c\u7ed3\u679c\u7684\u6b63\u786e\u7a0b\u5ea6<\/li>\n
  • \u7a33\u5b9a\u6027：\u5728\u4e0d\u540c\u6761\u4ef6\u4e0b\u7684\u8868\u73b0\u4e00\u81f4\u6027<\/li>\n
  • \u53ef\u6269\u5c55\u6027：\u9002\u5e94\u66f4\u5927\u89c4\u6a21\u9700\u6c42\u7684\u80fd\u529b<\/li>\n<\/ul>\n

    2.3 \u4e0e\u76f8\u5173\u6982\u5ff5\u7684\u533a\u522b<\/h4>\n

    💡 \u6280\u5de7：\u7406\u89e3\u6982\u5ff5\u4e4b\u95f4\u7684\u533a\u522b，\u6709\u52a9\u4e8e\u5efa\u7acb\u6e05\u6670\u7684\u77e5\u8bc6\u4f53\u7cfb\u3002<\/p>\n\n\u6982\u5ff5\u5b9a\u4e49\u4e0e\u672c\u7ae0\u4e3b\u9898\u7684\u5173\u7cfb<\/tr>\n\n\n\n\n
    \u4f20\u7edfAI<\/td>\n\u88ab\u52a8\u54cd\u5e94\u5f0f\u7cfb\u7edf<\/td>\n\u662fAI Agent\u7684\u6f14\u8fdb\u57fa\u7840<\/td>\n<\/tr>\n
    \u6267\u884c\u5f0fAI<\/td>\n\u4e3b\u52a8\u5b8c\u6210\u4efb\u52a1<\/td>\n\u662f\u672c\u7ae0\u4e3b\u9898\u7684\u6838\u5fc3\u7279\u5f81<\/td>\n<\/tr>\n
    \u5de5\u5177\u8c03\u7528<\/td>\n\u8c03\u7528\u5916\u90e8\u80fd\u529b<\/td>\n\u662f\u6267\u884c\u7684\u5177\u4f53\u624b\u6bb5<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n

    \u4e09\u3001\u6280\u672f\u539f\u7406\u6df1\u5165<\/h3>\n

    3.1 \u5e95\u5c42\u67b6\u6784<\/h4>\n

    🔧 \u6280\u672f\u6df1\u5ea6：\u672c\u8282\u5c06\u6df1\u5165\u63a2\u8ba8\u6280\u672f\u5b9e\u73b0\u7ec6\u8282\u3002<\/p>\n

    \u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u7684\u5e95\u5c42\u67b6\u6784\u53ef\u4ee5\u6982\u62ec\u4e3a\u4ee5\u4e0b\u51e0\u4e2a\u5c42\u6b21：<\/p>\n

    \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510
    \n\u2502 \u5e94\u7528\u5c42 (Application) \u2502
    \n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524
    \n\u2502 Agent\u5c42 (\u667a\u80fd\u4f53) \u2502
    \n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524
    \n\u2502 \u5de5\u5177\u5c42 (Tools) \u2502
    \n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524
    \n\u2502 \u6a21\u578b\u5c42 (LLM) \u2502
    \n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524
    \n\u2502 \u57fa\u7840\u8bbe\u65bd\u5c42 (Infrastructure) \u2502
    \n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<\/p>\n

    \u5404\u5c42\u8be6\u89e3：<\/p>\n

    \u2460 \u5e94\u7528\u5c42<\/p>\n

    \u5e94\u7528\u5c42\u662f\u7528\u6237\u76f4\u63a5\u4ea4\u4e92\u7684\u754c\u9762，\u8d1f\u8d23\u63a5\u6536\u7528\u6237\u6307\u4ee4\u5e76\u5c55\u793a\u6267\u884c\u7ed3\u679c\u3002\u8bbe\u8ba1\u826f\u597d\u7684\u5e94\u7528\u5c42\u5e94\u8be5\u5177\u5907：<\/p>\n

      \n
    • \u6e05\u6670\u7684\u4efb\u52a1\u8f93\u5165\u754c\u9762<\/li>\n
    • \u5b9e\u65f6\u7684\u6267\u884c\u72b6\u6001\u5c55\u793a<\/li>\n
    • \u5b8c\u5584\u7684\u7ed3\u679c\u53cd\u9988\u673a\u5236<\/li>\n<\/ul>\n

      \u2461 Agent\u5c42<\/p>\n

      Agent\u5c42\u662f\u6838\u5fc3\u667a\u80fd\u4f53，\u8d1f\u8d23：<\/p>\n

        \n
      • \u7406\u89e3\u7528\u6237\u610f\u56fe<\/li>\n
      • \u89c4\u5212\u6267\u884c\u6b65\u9aa4<\/li>\n
      • \u534f\u8c03\u5de5\u5177\u8c03\u7528<\/li>\n
      • \u5904\u7406\u6267\u884c\u7ed3\u679c<\/li>\n<\/ul>\n

        \u2462 \u5de5\u5177\u5c42<\/p>\n

        \u5de5\u5177\u5c42\u63d0\u4f9b\u5177\u4f53\u6267\u884c\u80fd\u529b：<\/p>\n

          \n
        • \u6587\u4ef6\u64cd\u4f5c\u5de5\u5177<\/li>\n
        • \u7f51\u7edc\u8bf7\u6c42\u5de5\u5177<\/li>\n
        • \u6570\u636e\u5904\u7406\u5de5\u5177<\/li>\n
        • \u5916\u90e8API\u5de5\u5177<\/li>\n<\/ul>\n

          3.2 \u6838\u5fc3\u7b97\u6cd5<\/h4>\n

          📊 \u7b97\u6cd5\u8be6\u89e3：\u4ee5\u4e0b\u662f\u652f\u6491\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u7684\u6838\u5fc3\u7b97\u6cd5\u3002<\/p>\n

          \u7b97\u6cd5\u4e00：\u57fa\u7840\u6267\u884c\u7b97\u6cd5<\/p>\n

          # \u793a\u4f8b\u4ee3\u7801：AI Agent\u57fa\u7840\u6267\u884c\u6846\u67b6<\/span>
          \nclass<\/span> AIAgent<\/span>:<\/span>
          \n """AI Agent\u6267\u884c\u6846\u67b6"""<\/span><\/p>\n

          def<\/span> __init__<\/span>(<\/span>self,<\/span> llm,<\/span> tools=<\/span>None<\/span>)<\/span>:<\/span>
          \n self.<\/span>llm =<\/span> llm # \u5927\u6a21\u578b<\/span>
          \n self.<\/span>tools =<\/span> tools or<\/span> [<\/span>]<\/span> # \u53ef\u7528\u5de5\u5177\u5217\u8868<\/span>
          \n self.<\/span>memory =<\/span> [<\/span>]<\/span> # \u6267\u884c\u8bb0\u5fc6<\/span><\/p>\n

          def<\/span> execute<\/span>(<\/span>self,<\/span> task)<\/span>:<\/span>
          \n """\u6267\u884c\u4efb\u52a1\u7684\u4e3b\u5165\u53e3"""<\/span>
          \n # \u7b2c\u4e00\u6b65：\u7406\u89e3\u4efb\u52a1<\/span>
          \n understanding =<\/span> self.<\/span>_understand(<\/span>task)<\/span><\/p>\n

          # \u7b2c\u4e8c\u6b65：\u89c4\u5212\u6b65\u9aa4<\/span>
          \n plan =<\/span> self.<\/span>_plan(<\/span>understanding)<\/span><\/p>\n

          # \u7b2c\u4e09\u6b65：\u6267\u884c\u6b65\u9aa4<\/span>
          \n results =<\/span> [<\/span>]<\/span>
          \n for<\/span> step in<\/span> plan:<\/span>
          \n result =<\/span> self.<\/span>_execute_step(<\/span>step)<\/span>
          \n results.<\/span>append(<\/span>result)<\/span><\/p>\n

          # \u68c0\u67e5\u662f\u5426\u9700\u8981\u8c03\u6574<\/span>
          \n if<\/span> not<\/span> self.<\/span>_verify(<\/span>result)<\/span>:<\/span>
          \n plan =<\/span> self.<\/span>_replan(<\/span>step,<\/span> result)<\/span><\/p>\n

          # \u7b2c\u56db\u6b65：\u603b\u7ed3\u8f93\u51fa<\/span>
          \n output =<\/span> self.<\/span>_summarize(<\/span>results)<\/span><\/p>\n

          return<\/span> output<\/p>\n

          def<\/span> _understand<\/span>(<\/span>self,<\/span> task)<\/span>:<\/span>
          \n """\u7406\u89e3\u4efb\u52a1\u610f\u56fe"""<\/span>
          \n prompt =<\/span> f"\u5206\u6790\u4ee5\u4e0b\u4efb\u52a1\u7684\u6838\u5fc3\u76ee\u6807：<\/span>{<\/span>task}<\/span><\/span>"<\/span><\/span>
          \n return<\/span> self.<\/span>llm.<\/span>generate(<\/span>prompt)<\/span><\/p>\n

          def<\/span> _plan<\/span>(<\/span>self,<\/span> understanding)<\/span>:<\/span>
          \n """\u89c4\u5212\u6267\u884c\u6b65\u9aa4"""<\/span>
          \n prompt =<\/span> f"\u4e3a\u4ee5\u4e0b\u76ee\u6807\u5236\u5b9a\u6267\u884c\u8ba1\u5212：<\/span>{<\/span>understanding}<\/span><\/span>"<\/span><\/span>
          \n plan_text =<\/span> self.<\/span>llm.<\/span>generate(<\/span>prompt)<\/span>
          \n return<\/span> self.<\/span>_parse_plan(<\/span>plan_text)<\/span><\/p>\n

          def<\/span> _execute_step<\/span>(<\/span>self,<\/span> step)<\/span>:<\/span>
          \n """\u6267\u884c\u5355\u4e2a\u6b65\u9aa4"""<\/span>
          \n # \u9009\u62e9\u5408\u9002\u7684\u5de5\u5177<\/span>
          \n tool =<\/span> self.<\/span>_select_tool(<\/span>step)<\/span><\/p>\n

          # \u6267\u884c\u5de5\u5177\u8c03\u7528<\/span>
          \n result =<\/span> tool.<\/span>execute(<\/span>step)<\/span><\/p>\n

          # \u8bb0\u5f55\u5230\u8bb0\u5fc6<\/span>
          \n self.<\/span>memory.<\/span>append(<\/span>{<\/span>
          \n 'step'<\/span>:<\/span> step,<\/span>
          \n 'tool'<\/span>:<\/span> tool.<\/span>name,<\/span>
          \n 'result'<\/span>:<\/span> result
          \n }<\/span>)<\/span><\/p>\n

          return<\/span> result<\/p>\n

          def<\/span> _verify<\/span>(<\/span>self,<\/span> result)<\/span>:<\/span>
          \n """\u9a8c\u8bc1\u6267\u884c\u7ed3\u679c"""<\/span>
          \n return<\/span> result.<\/span>get(<\/span>'success'<\/span>,<\/span> False<\/span>)<\/span><\/p>\n

          def<\/span> _replan<\/span>(<\/span>self,<\/span> failed_step,<\/span> result)<\/span>:<\/span>
          \n """\u91cd\u65b0\u89c4\u5212"""<\/span>
          \n prompt =<\/span> f"\u6b65\u9aa4'<\/span>{<\/span>failed_step}<\/span><\/span>'\u6267\u884c\u5931\u8d25，\u7ed3\u679c：<\/span>{<\/span>result}<\/span><\/span>，\u8bf7\u8c03\u6574\u8ba1\u5212"<\/span><\/span>
          \n new_plan =<\/span> self.<\/span>llm.<\/span>generate(<\/span>prompt)<\/span>
          \n return<\/span> self.<\/span>_parse_plan(<\/span>new_plan)<\/span>
          \n def<\/span> _summarize<\/span>(<\/span>self,<\/span> results)<\/span>:<\/span>
          \n """\u603b\u7ed3\u6267\u884c\u7ed3\u679c"""<\/span>
          \n prompt =<\/span> f"\u603b\u7ed3\u4ee5\u4e0b\u6267\u884c\u7ed3\u679c：<\/span>{<\/span>results}<\/span><\/span>"<\/span><\/span>
          \n return<\/span> self.<\/span>llm.<\/span>generate(<\/span>prompt)<\/span><\/p>\n

          def<\/span> _parse_plan<\/span>(<\/span>self,<\/span> plan_text)<\/span>:<\/span>
          \n """\u89e3\u6790\u8ba1\u5212\u6587\u672c\u4e3a\u6b65\u9aa4\u5217\u8868"""<\/span>
          \n return<\/span> [<\/span>line.<\/span>strip(<\/span>)<\/span> for<\/span> line in<\/span> plan_text.<\/span>split(<\/span>'\\\\n'<\/span>)<\/span> if<\/span> line.<\/span>strip(<\/span>)<\/span>]<\/span><\/p>\n

          def<\/span> _select_tool<\/span>(<\/span>self,<\/span> step)<\/span>:<\/span>
          \n """\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177"""<\/span>
          \n for<\/span> tool in<\/span> self.<\/span>tools:<\/span>
          \n if<\/span> tool.<\/span>can_handle(<\/span>step)<\/span>:<\/span>
          \n return<\/span> tool
          \n return<\/span> DefaultTool(<\/span>)<\/span><\/p>\n

          # \u4f7f\u7528\u793a\u4f8b<\/span>
          \nagent =<\/span> AIAgent(<\/span>llm=<\/span>MockLLM(<\/span>)<\/span>,<\/span> tools=<\/span>[<\/span>FileTool(<\/span>)<\/span>,<\/span> WebTool(<\/span>)<\/span>]<\/span>)<\/span>
          \nresult =<\/span> agent.<\/span>execute(<\/span>"\u5e2e\u6211\u6574\u7406\u684c\u9762\u7684\u6240\u6709PDF\u6587\u4ef6"<\/span>)<\/span>
          \nprint<\/span>(<\/span>result)<\/span><\/p>\n

          \u7b97\u6cd5\u4e8c：ReAct\u6267\u884c\u5faa\u73af<\/p>\n

          # ReAct: \u601d\u8003-\u884c\u52a8-\u89c2\u5bdf\u5faa\u73af<\/span>
          \nclass<\/span> ReActAgent<\/span>:<\/span>
          \n """\u57fa\u4e8eReAct\u8303\u5f0f\u7684AI Agent"""<\/span><\/p>\n

          def<\/span> __init__<\/span>(<\/span>self,<\/span> llm,<\/span> tools)<\/span>:<\/span>
          \n self.<\/span>llm =<\/span> llm
          \n self.<\/span>tools =<\/span> {<\/span>tool.<\/span>name:<\/span> tool for<\/span> tool in<\/span> tools}<\/span>
          \n self.<\/span>max_iterations =<\/span> 10<\/span><\/p>\n

          def<\/span> run<\/span>(<\/span>self,<\/span> task)<\/span>:<\/span>
          \n """\u8fd0\u884cReAct\u5faa\u73af"""<\/span>
          \n context =<\/span> f"\u4efb\u52a1：<\/span>{<\/span>task}<\/span><\/span>\\\\n"<\/span><\/span><\/p>\n

          for<\/span> i in<\/span> range<\/span>(<\/span>self.<\/span>max_iterations)<\/span>:<\/span>
          \n # \u601d\u8003\u9636\u6bb5<\/span>
          \n thought =<\/span> self.<\/span>_think(<\/span>context)<\/span>
          \n print<\/span>(<\/span>f"[\u601d\u8003] <\/span>{<\/span>thought}<\/span><\/span>"<\/span><\/span>)<\/span><\/p>\n

          # \u5224\u65ad\u662f\u5426\u5b8c\u6210<\/span>
          \n if<\/span> "\u4efb\u52a1\u5b8c\u6210"<\/span> in<\/span> thought or<\/span> "Final Answer:"<\/span> in<\/span> thought:<\/span>
          \n return<\/span> self.<\/span>_extract_answer(<\/span>thought)<\/span><\/p>\n

          # \u884c\u52a8\u9636\u6bb5<\/span>
          \n action,<\/span> action_input =<\/span> self.<\/span>_decide_action(<\/span>thought)<\/span>
          \n print<\/span>(<\/span>f"[\u884c\u52a8] <\/span>{<\/span>action}<\/span><\/span>(<\/span>{<\/span>action_input}<\/span><\/span>)"<\/span><\/span>)<\/span><\/p>\n

          # \u89c2\u5bdf\u9636\u6bb5<\/span>
          \n observation =<\/span> self.<\/span>_observe(<\/span>action,<\/span> action_input)<\/span>
          \n print<\/span>(<\/span>f"[\u89c2\u5bdf] <\/span>{<\/span>observation}<\/span><\/span>"<\/span><\/span>)<\/span><\/p>\n

          # \u66f4\u65b0\u4e0a\u4e0b\u6587<\/span>
          \n context +=<\/span> f"\\\\n\u601d\u8003：<\/span>{<\/span>thought}<\/span><\/span>\\\\n\u884c\u52a8：<\/span>{<\/span>action}<\/span><\/span>(<\/span>{<\/span>action_input}<\/span><\/span>)\\\\n\u89c2\u5bdf：<\/span>{<\/span>observation}<\/span><\/span>"<\/span><\/span><\/p>\n

          return<\/span> "\u8fbe\u5230\u6700\u5927\u8fed\u4ee3\u6b21\u6570，\u4efb\u52a1\u672a\u5b8c\u6210"<\/span><\/p>\n

          def<\/span> _think<\/span>(<\/span>self,<\/span> context)<\/span>:<\/span>
          \n """\u601d\u8003\u4e0b\u4e00\u6b65"""<\/span>
          \n prompt =<\/span> f"""
          \n <\/span>{<\/span>context}<\/span><\/span><\/p>\n

          \u8bf7\u601d\u8003\u4e0b\u4e00\u6b65\u5e94\u8be5\u505a\u4ec0\u4e48\u3002\u5982\u679c\u4efb\u52a1\u5df2\u5b8c\u6210，\u8bf7\u56de\u7b54"\u4efb\u52a1\u5b8c\u6210：[\u7ed3\u679c]"
          \n """<\/span><\/span>
          \n return<\/span> self.<\/span>llm.<\/span>generate(<\/span>prompt)<\/span><\/p>\n

          def<\/span> _decide_action<\/span>(<\/span>self,<\/span> thought)<\/span>:<\/span>
          \n """\u51b3\u5b9a\u6267\u884c\u4ec0\u4e48\u884c\u52a8"""<\/span>
          \n prompt =<\/span> f"\u6839\u636e\u601d\u8003'<\/span>{<\/span>thought}<\/span><\/span>'，\u9009\u62e9\u8981\u6267\u884c\u7684\u5de5\u5177\u548c\u53c2\u6570"<\/span><\/span>
          \n response =<\/span> self.<\/span>llm.<\/span>generate(<\/span>prompt)<\/span>
          \n # \u89e3\u6790\u8fd4\u56de\u7684\u5de5\u5177\u540d\u548c\u53c2\u6570<\/span>
          \n return<\/span> self.<\/span>_parse_action(<\/span>response)<\/span><\/p>\n

          def<\/span> _observe<\/span>(<\/span>self,<\/span> action,<\/span> action_input)<\/span>:<\/span>
          \n """\u6267\u884c\u884c\u52a8\u5e76\u89c2\u5bdf\u7ed3\u679c"""<\/span>
          \n if<\/span> action in<\/span> self.<\/span>tools:<\/span>
          \n return<\/span> self.<\/span>tools[<\/span>action]<\/span>.<\/span>execute(<\/span>action_input)<\/span>
          \n return<\/span> f"\u672a\u77e5\u5de5\u5177：<\/span>{<\/span>action}<\/span><\/span>"<\/span><\/span><\/p>\n

          def<\/span> _extract_answer<\/span>(<\/span>self,<\/span> thought)<\/span>:<\/span>
          \n """\u63d0\u53d6\u6700\u7ec8\u7b54\u6848"""<\/span>
          \n return<\/span> thought.<\/span>split(<\/span>"\u4efb\u52a1\u5b8c\u6210："<\/span>)<\/span>[<\/span>–<\/span>1<\/span>]<\/span>.<\/span>strip(<\/span>)<\/span><\/p>\n

          def<\/span> _parse_action<\/span>(<\/span>self,<\/span> response)<\/span>:<\/span>
          \n """\u89e3\u6790\u884c\u52a8\u54cd\u5e94"""<\/span>
          \n # \u7b80\u5316\u89e3\u6790\u903b\u8f91<\/span>
          \n lines =<\/span> response.<\/span>strip(<\/span>)<\/span>.<\/span>split(<\/span>'\\\\n'<\/span>)<\/span>
          \n action =<\/span> "default"<\/span>
          \n action_input =<\/span> ""<\/span>
          \n for<\/span> line in<\/span> lines:<\/span>
          \n if<\/span> "\u5de5\u5177："<\/span> in<\/span> line or<\/span> "tool:"<\/span> in<\/span> line.<\/span>lower(<\/span>)<\/span>:<\/span>
          \n action =<\/span> line.<\/span>split(<\/span>"："<\/span>)<\/span>[<\/span>–<\/span>1<\/span>]<\/span>.<\/span>strip(<\/span>)<\/span>
          \n if<\/span> "\u53c2\u6570："<\/span> in<\/span> line or<\/span> "input:"<\/span> in<\/span> line.<\/span>lower(<\/span>)<\/span>:<\/span>
          \n action_input =<\/span> line.<\/span>split(<\/span>"："<\/span>)<\/span>[<\/span>–<\/span>1<\/span>]<\/span>.<\/span>strip(<\/span>)<\/span>
          \n return<\/span> action,<\/span> action_input<\/p>\n

          # \u5de5\u5177\u57fa\u7c7b<\/span>
          \nclass<\/span> Tool<\/span>:<\/span>
          \n name =<\/span> "base_tool"<\/span><\/p>\n

          def<\/span> execute<\/span>(<\/span>self,<\/span> input_data)<\/span>:<\/span>
          \n raise<\/span> NotImplementedError<\/p>\n

          def<\/span> can_handle<\/span>(<\/span>self,<\/span> task)<\/span>:<\/span>
          \n return<\/span> False<\/span><\/p>\n

          class<\/span> FileTool<\/span>(<\/span>Tool)<\/span>:<\/span>
          \n name =<\/span> "file_tool"<\/span><\/p>\n

          def<\/span> execute<\/span>(<\/span>self,<\/span> input_data)<\/span>:<\/span>
          \n return<\/span> f"\u6587\u4ef6\u64cd\u4f5c\u5b8c\u6210：<\/span>{<\/span>input_data}<\/span><\/span>"<\/span><\/span><\/p>\n

          def<\/span> can_handle<\/span>(<\/span>self,<\/span> task)<\/span>:<\/span>
          \n return<\/span> "\u6587\u4ef6"<\/span> in<\/span> task or<\/span> "file"<\/span> in<\/span> task.<\/span>lower(<\/span>)<\/span><\/p>\n

          class<\/span> WebTool<\/span>(<\/span>Tool)<\/span>:<\/span>
          \n name =<\/span> "web_tool"<\/span><\/p>\n

          def<\/span> execute<\/span>(<\/span>self,<\/span> input_data)<\/span>:<\/span>
          \n return<\/span> f"\u7f51\u7edc\u8bf7\u6c42\u5b8c\u6210：<\/span>{<\/span>input_data}<\/span><\/span>"<\/span><\/span><\/p>\n

          def<\/span> can_handle<\/span>(<\/span>self,<\/span> task)<\/span>:<\/span>
          \n return<\/span> "\u641c\u7d22"<\/span> in<\/span> task or<\/span> "\u7f51\u9875"<\/span> in<\/span> task or<\/span> "web"<\/span> in<\/span> task.<\/span>lower(<\/span>)<\/span><\/p>\n

          class<\/span> DefaultTool<\/span>(<\/span>Tool)<\/span>:<\/span>
          \n name =<\/span> "default"<\/span><\/p>\n

          def<\/span> execute<\/span>(<\/span>self,<\/span> input_data)<\/span>:<\/span>
          \n return<\/span> f"\u9ed8\u8ba4\u5904\u7406：<\/span>{<\/span>input_data}<\/span><\/span>"<\/span><\/span><\/p>\n

          # Mock LLM for demo<\/span>
          \nclass<\/span> MockLLM<\/span>:<\/span>
          \n def<\/span> generate<\/span>(<\/span>self,<\/span> prompt)<\/span>:<\/span>
          \n if<\/span> "\u601d\u8003"<\/span> in<\/span> prompt:<\/span>
          \n return<\/span> "\u6211\u9700\u8981\u5148\u641c\u7d22\u76f8\u5173\u4fe1\u606f"<\/span>
          \n elif<\/span> "\u9009\u62e9"<\/span> in<\/span> prompt:<\/span>
          \n return<\/span> "\u5de5\u5177：web_tool\\\\n\u53c2\u6570：\u641c\u7d22AI Agent"<\/span>
          \n return<\/span> "\u5904\u7406\u5b8c\u6210"<\/span><\/p>\n

          3.3 \u6280\u672f\u6f14\u8fdb\u5386\u7a0b<\/h4>\n

          📈 \u53d1\u5c55\u8109\u7edc：\u4e86\u89e3\u6280\u672f\u6f14\u8fdb\u6709\u52a9\u4e8e\u628a\u63e1\u672a\u6765\u65b9\u5411\u3002<\/p>\n\n\u9636\u6bb5\u65f6\u95f4\u5173\u952e\u7a81\u7834\u4ee3\u8868\u6027\u9879\u76ee<\/tr>\n\n\n\n\n\n
          \u840c\u82bd\u671f<\/td>\n2022<\/td>\n\u5927\u6a21\u578b\u5177\u5907\u5de5\u5177\u8c03\u7528\u80fd\u529b<\/td>\nGPT-3.5<\/td>\n<\/tr>\n
          \u7206\u53d1\u671f<\/td>\n2023<\/td>\n\u81ea\u4e3b\u6267\u884cAgent\u8bde\u751f<\/td>\nAutoGPT\u3001BabyAGI<\/td>\n<\/tr>\n
          \u53d1\u5c55\u671f<\/td>\n2024<\/td>\n\u591aAgent\u534f\u4f5c\u6210\u719f<\/td>\nMetaGPT\u3001AutoGen<\/td>\n<\/tr>\n
          \u5e94\u7528\u671f<\/td>\n2025<\/td>\n\u884c\u4e1a\u843d\u5730\u52a0\u901f<\/td>\n\u5404\u7c7b\u5782\u76f4Agent<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
          \n

          \u56db\u3001\u5b9e\u8df5\u5e94\u7528\u6307\u5357<\/h3>\n

          4.1 \u5e94\u7528\u573a\u666f\u5206\u6790<\/h4>\n

          \u2705 \u6838\u5fc3\u573a\u666f：\u4ee5\u4e0b\u662f\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u7684\u4e3b\u8981\u5e94\u7528\u573a\u666f\u3002<\/p>\n

          \u573a\u666f\u4e00：\u4f01\u4e1a\u81ea\u52a8\u5316<\/p>\n

          \u5728\u4f01\u4e1a\u73af\u5883\u4e2d，AI Agent\u4e3b\u8981\u5e94\u7528\u4e8e：<\/p>\n\n\u5e94\u7528\u9886\u57df\u5177\u4f53\u7528\u9014\u6548\u679c\u8bc4\u4f30<\/tr>\n\n\n\n\n\n
          \u6587\u6863\u5904\u7406<\/td>\n\u81ea\u52a8\u6574\u7406\u3001\u5206\u7c7b\u3001\u63d0\u53d6<\/td>\n\u6548\u7387\u63d0\u534780%<\/td>\n<\/tr>\n
          \u6570\u636e\u5206\u6790<\/td>\n\u81ea\u52a8\u751f\u6210\u62a5\u8868\u3001\u6d1e\u5bdf<\/td>\n\u6548\u7387\u63d0\u534770%<\/td>\n<\/tr>\n
          \u5ba2\u6237\u670d\u52a1<\/td>\n\u81ea\u52a8\u56de\u7b54\u3001\u5de5\u5355\u5904\u7406<\/td>\n\u54cd\u5e94\u65f6\u95f4\u964d\u4f4e90%<\/td>\n<\/tr>\n
          \u6d41\u7a0b\u81ea\u52a8\u5316<\/td>\n\u5ba1\u6279\u3001\u901a\u77e5\u3001\u5f52\u6863<\/td>\n\u4eba\u529b\u8282\u770160%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

          \u573a\u666f\u4e8c：\u4e2a\u4eba\u6548\u7387<\/p>\n

          \u5bf9\u4e8e\u4e2a\u4eba\u7528\u6237，\u4e3b\u8981\u5e94\u7528\u573a\u666f\u5305\u62ec：<\/p>\n

            \n
          • 📝 \u5199\u4f5c\u8f85\u52a9：\u5927\u7eb2\u751f\u6210\u3001\u5185\u5bb9\u6269\u5199\u3001\u6da6\u8272\u4fee\u6539<\/li>\n
          • 💼 \u5de5\u4f5c\u6548\u7387：\u90ae\u4ef6\u5904\u7406\u3001\u4f1a\u8bae\u7eaa\u8981\u3001\u4efb\u52a1\u7ba1\u7406<\/li>\n
          • 🎨 \u521b\u610f\u5de5\u4f5c：\u7075\u611f\u6fc0\u53d1\u3001\u65b9\u6848\u751f\u6210\u3001\u7d20\u6750\u6574\u7406<\/li>\n
          • 📊 \u4fe1\u606f\u5904\u7406：\u6587\u6863\u603b\u7ed3\u3001\u6570\u636e\u6e05\u6d17\u3001\u77e5\u8bc6\u7ba1\u7406<\/li>\n<\/ul>\n

            4.2 \u5b9e\u65bd\u6b65\u9aa4\u8be6\u89e3<\/h4>\n

            🔧 \u64cd\u4f5c\u6307\u5357：\u4ee5\u4e0b\u662f\u5b8c\u6574\u7684\u5b9e\u65bd\u6b65\u9aa4\u3002<\/p>\n

            \u6b65\u9aa4\u4e00：\u9700\u6c42\u5206\u6790<\/p>\n

            \u5728\u5f00\u59cb\u4e4b\u524d，\u9700\u8981\u660e\u786e\u4ee5\u4e0b\u95ee\u9898：<\/p>\n

            \u2460 \u8981\u89e3\u51b3\u4ec0\u4e48\u95ee\u9898？
            \n\u2461 \u73b0\u6709\u6d41\u7a0b\u662f\u600e\u6837\u7684？
            \n\u2462 AI Agent\u80fd\u505a\u4ec0\u4e48？
            \n\u2463 \u9884\u671f\u6548\u679c\u662f\u4ec0\u4e48？<\/p>\n

            \u6b65\u9aa4\u4e8c：\u65b9\u6848\u8bbe\u8ba1<\/p>\n

            \u57fa\u4e8e\u9700\u6c42\u5206\u6790，\u8bbe\u8ba1\u5b9e\u65bd\u65b9\u6848：<\/p>\n

            ## AI Agent\u65b9\u6848\u8bbe\u8ba1\u6a21\u677f<\/p>\n

            ### 1. \u9879\u76ee\u6982\u8ff0
            \n– \u9879\u76ee\u540d\u79f0
            \n– \u4e1a\u52a1\u76ee\u6807
            \n– \u6210\u529f\u6307\u6807<\/p>\n

            ### 2. Agent\u8bbe\u8ba1
            \n– \u89d2\u8272\u5b9a\u4e49
            \n– \u80fd\u529b\u8fb9\u754c
            \n– \u5de5\u5177\u914d\u7f6e<\/p>\n

            ### 3. \u6280\u672f\u65b9\u6848
            \n– \u6a21\u578b\u9009\u62e9
            \n– \u67b6\u6784\u8bbe\u8ba1
            \n– \u63a5\u53e3\u8bbe\u8ba1<\/p>\n

            ### 4. \u5b9e\u65bd\u8ba1\u5212
            \n– \u9636\u6bb5\u5212\u5206
            \n– \u91cc\u7a0b\u7891
            \n– \u8d44\u6e90\u914d\u7f6e<\/p>\n

            ### 5. \u98ce\u9669\u63a7\u5236
            \n– \u98ce\u9669\u8bc6\u522b
            \n– \u5e94\u5bf9\u63aa\u65bd
            \n– \u56de\u6eda\u65b9\u6848<\/p>\n

            \u6b65\u9aa4\u4e09：\u5f00\u53d1\u5b9e\u65bd<\/p>\n

            \u5f00\u53d1\u9636\u6bb5\u7684\u5173\u952e\u4efb\u52a1：<\/p>\n\n\u4efb\u52a1\u63cf\u8ff0\u8d1f\u8d23\u4eba\u65f6\u95f4<\/tr>\n\n\n\n\n\n\n
            \u73af\u5883\u642d\u5efa<\/td>\n\u914d\u7f6e\u5f00\u53d1\u73af\u5883<\/td>\n\u5f00\u53d1\u5de5\u7a0b\u5e08<\/td>\n1\u5929<\/td>\n<\/tr>\n
            Agent\u5f00\u53d1<\/td>\n\u6838\u5fc3\u903b\u8f91\u5b9e\u73b0<\/td>\nAI\u5de5\u7a0b\u5e08<\/td>\n3\u5929<\/td>\n<\/tr>\n
            \u5de5\u5177\u5f00\u53d1<\/td>\n\u81ea\u5b9a\u4e49\u5de5\u5177\u5f00\u53d1<\/td>\n\u5f00\u53d1\u5de5\u7a0b\u5e08<\/td>\n2\u5929<\/td>\n<\/tr>\n
            \u6d4b\u8bd5\u8054\u8c03<\/td>\n\u7cfb\u7edf\u6d4b\u8bd5<\/td>\n\u6d4b\u8bd5\u5de5\u7a0b\u5e08<\/td>\n2\u5929<\/td>\n<\/tr>\n
            \u90e8\u7f72\u4e0a\u7ebf<\/td>\n\u751f\u4ea7\u73af\u5883\u90e8\u7f72<\/td>\n\u8fd0\u7ef4\u5de5\u7a0b\u5e08<\/td>\n1\u5929<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

            \u6b65\u9aa4\u56db：\u4e0a\u7ebf\u8fd0\u7ef4<\/p>\n

            \u4e0a\u7ebf\u540e\u7684\u8fd0\u7ef4\u8981\u70b9：<\/p>\n

            \u26a0\ufe0f \u91cd\u8981\u63d0\u9192：<\/p>\n

              \n
            • \u5efa\u7acb\u76d1\u63a7\u544a\u8b66\u673a\u5236<\/li>\n
            • \u5236\u5b9a\u6545\u969c\u54cd\u5e94\u6d41\u7a0b<\/li>\n
            • \u5b9a\u671f\u8fdb\u884c\u6027\u80fd\u4f18\u5316<\/li>\n
            • \u6301\u7eed\u6536\u96c6\u7528\u6237\u53cd\u9988<\/li>\n<\/ul>\n

              4.3 \u6700\u4f73\u5b9e\u8df5\u5206\u4eab<\/h4>\n

              💡 \u7ecf\u9a8c\u603b\u7ed3：\u4ee5\u4e0b\u662f\u6765\u81ea\u4e00\u7ebf\u5b9e\u8df5\u7684\u7ecf\u9a8c\u5206\u4eab\u3002<\/p>\n

              \u6700\u4f73\u5b9e\u8df5\u4e00：\u4ece\u5c0f\u573a\u666f\u5f00\u59cb<\/p>\n

              \u4e0d\u8981\u4e00\u5f00\u59cb\u5c31\u8ffd\u6c42\u5927\u800c\u5168，\u5efa\u8bae：<\/p>\n

              \u2460 \u9009\u62e9\u4e00\u4e2a\u660e\u786e\u7684\u5c0f\u573a\u666f
              \n\u2461 \u5feb\u901f\u9a8c\u8bc1\u53ef\u884c\u6027
              \n\u2462 \u6536\u96c6\u53cd\u9988\u8fed\u4ee3\u4f18\u5316
              \n\u2463 \u9010\u6b65\u6269\u5c55\u5e94\u7528\u8303\u56f4<\/p>\n

              \u6700\u4f73\u5b9e\u8df5\u4e8c：\u91cd\u89c6\u63d0\u793a\u8bcd\u8bbe\u8ba1<\/p>\n

              \u63d0\u793a\u8bcd\u662fAgent\u7684"\u7075\u9b42"，\u9700\u8981：<\/p>\n

                \n
              • \u6e05\u6670\u5b9a\u4e49\u89d2\u8272\u548c\u80fd\u529b<\/li>\n
              • \u660e\u786e\u4efb\u52a1\u8fb9\u754c<\/li>\n
              • \u63d0\u4f9b\u5145\u5206\u7684\u793a\u4f8b<\/li>\n
              • \u6301\u7eed\u4f18\u5316\u8fed\u4ee3<\/li>\n<\/ul>\n

                \u6700\u4f73\u5b9e\u8df5\u4e09：\u5efa\u7acb\u8bc4\u4f30\u4f53\u7cfb<\/p>\n

                \u79d1\u5b66\u7684\u8bc4\u4f30\u4f53\u7cfb\u5305\u62ec：<\/p>\n\n\u7ef4\u5ea6\u6307\u6807\u76ee\u6807\u503c<\/tr>\n\n\n\n\n\n
                \u6267\u884c\u6210\u529f\u7387<\/td>\n\u5b8c\u6210\u7387<\/td>\n>90%<\/td>\n<\/tr>\n
                \u6267\u884c\u6548\u7387<\/td>\n\u5e73\u5747\u8017\u65f6<\/td>\n<30\u79d2<\/td>\n<\/tr>\n
                \u7ed3\u679c\u8d28\u91cf<\/td>\n\u7528\u6237\u6ee1\u610f\u5ea6<\/td>\n>85%<\/td>\n<\/tr>\n
                \u7a33\u5b9a\u6027<\/td>\n\u53ef\u7528\u6027<\/td>\n>99%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
                \n

                \u4e94\u3001\u6848\u4f8b\u5206\u6790<\/h3>\n

                5.1 \u6210\u529f\u6848\u4f8b<\/h4>\n

                📊 \u6848\u4f8b\u4e00：\u67d0\u516c\u53f8\u6587\u6863\u5904\u7406Agent<\/p>\n

                \u80cc\u666f\u4ecb\u7ecd<\/p>\n

                \u67d0\u79d1\u6280\u516c\u53f8\u6bcf\u5929\u4ea7\u751f\u5927\u91cf\u6280\u672f\u6587\u6863，\u9700\u8981\u4eba\u5de5\u6574\u7406\u5206\u7c7b，\u6548\u7387\u4f4e\u4e0b\u3002<\/p>\n

                \u89e3\u51b3\u65b9\u6848<\/p>\n

                \u5f00\u53d1\u6587\u6863\u5904\u7406Agent：<\/p>\n

                # \u6587\u6863\u5904\u7406Agent\u793a\u4f8b<\/span>
                \nclass<\/span> DocumentAgent<\/span>:<\/span>
                \n """\u6587\u6863\u5904\u7406\u667a\u80fd\u4f53"""<\/span><\/p>\n

                def<\/span> __init__<\/span>(<\/span>self,<\/span> llm)<\/span>:<\/span>
                \n self.<\/span>llm =<\/span> llm
                \n self.<\/span>tools =<\/span> [<\/span>
                \n FileReaderTool(<\/span>)<\/span>,<\/span>
                \n ClassifierTool(<\/span>)<\/span>,<\/span>
                \n SummarizerTool(<\/span>)<\/span>,<\/span>
                \n IndexerTool(<\/span>)<\/span>
                \n ]<\/span><\/p>\n

                def<\/span> process_documents<\/span>(<\/span>self,<\/span> folder_path)<\/span>:<\/span>
                \n """\u5904\u7406\u6587\u4ef6\u5939\u4e2d\u7684\u6240\u6709\u6587\u6863"""<\/span>
                \n results =<\/span> [<\/span>]<\/span><\/p>\n

                # 1. \u8bfb\u53d6\u6240\u6709\u6587\u6863<\/span>
                \n docs =<\/span> self.<\/span>tools[<\/span>0<\/span>]<\/span>.<\/span>read_folder(<\/span>folder_path)<\/span><\/p>\n

                for<\/span> doc in<\/span> docs:<\/span>
                \n # 2. \u5206\u7c7b<\/span>
                \n category =<\/span> self.<\/span>tools[<\/span>1<\/span>]<\/span>.<\/span>classify(<\/span>doc)<\/span><\/p>\n

                # 3. \u603b\u7ed3<\/span>
                \n summary =<\/span> self.<\/span>tools[<\/span>2<\/span>]<\/span>.<\/span>summarize(<\/span>doc)<\/span><\/p>\n

                # 4. \u7d22\u5f15<\/span>
                \n self.<\/span>tools[<\/span>3<\/span>]<\/span>.<\/span>index(<\/span>doc,<\/span> category,<\/span> summary)<\/span><\/p>\n

                results.<\/span>append(<\/span>{<\/span>
                \n 'file'<\/span>:<\/span> doc.<\/span>name,<\/span>
                \n 'category'<\/span>:<\/span> category,<\/span>
                \n 'summary'<\/span>:<\/span> summary
                \n }<\/span>)<\/span><\/p>\n

                return<\/span> results<\/p>\n

                # \u4f7f\u7528\u793a\u4f8b<\/span>
                \nagent =<\/span> DocumentAgent(<\/span>llm=<\/span>GPT4(<\/span>)<\/span>)<\/span>
                \nresults =<\/span> agent.<\/span>process_documents(<\/span>"\/data\/documents"<\/span>)<\/span><\/p>\n

                \u5b9e\u65bd\u6548\u679c<\/p>\n\n\u6307\u6807\u5b9e\u65bd\u524d\u5b9e\u65bd\u540e\u63d0\u5347\u5e45\u5ea6<\/tr>\n\n\n\n\n
                \u5904\u7406\u65f6\u95f4<\/td>\n4\u5c0f\u65f6\/\u5929<\/td>\n30\u5206\u949f\/\u5929<\/td>\n87%<\/td>\n<\/tr>\n
                \u5206\u7c7b\u51c6\u786e\u7387<\/td>\n70%<\/td>\n95%<\/td>\n36%<\/td>\n<\/tr>\n
                \u4eba\u529b\u6295\u5165<\/td>\n2\u4eba<\/td>\n0.5\u4eba<\/td>\n75%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                5.2 \u5931\u8d25\u6559\u8bad<\/h4>\n

                \u274c \u6848\u4f8b\u4e8c：\u67d0\u4f01\u4e1a\u8fc7\u5ea6\u81ea\u52a8\u5316\u9879\u76ee<\/p>\n

                \u95ee\u9898\u5206\u6790<\/p>\n

                \u67d0\u4f01\u4e1a\u8bd5\u56fe\u7528Agent\u81ea\u52a8\u5316\u6240\u6709\u6d41\u7a0b，\u7ed3\u679c\u5931\u8d25\u3002\u4e3b\u8981\u539f\u56e0：<\/p>\n

                \u2460 \u7f3a\u4e4f\u660e\u786e\u7684\u573a\u666f\u754c\u5b9a
                \n\u2461 Agent\u80fd\u529b\u8fb9\u754c\u4e0d\u6e05\u6670
                \n\u2462 \u6ca1\u6709\u5efa\u7acb\u515c\u5e95\u673a\u5236
                \n\u2463 \u7528\u6237\u671f\u671b\u8fc7\u9ad8<\/p>\n

                \u7ecf\u9a8c\u6559\u8bad<\/p>\n

                \u26a0\ufe0f \u8b66\u793a：<\/p>\n

                  \n
                • \u4e0d\u8981\u4e3a\u4e86AI\u800cAI<\/li>\n
                • \u660e\u786eAgent\u7684\u80fd\u529b\u8fb9\u754c<\/li>\n
                • \u5efa\u7acb\u4eba\u5de5\u515c\u5e95\u673a\u5236<\/li>\n
                • \u8bbe\u5b9a\u5408\u7406\u9884\u671f<\/li>\n<\/ul>\n
                  \n

                  \u516d\u3001\u5e38\u89c1\u95ee\u9898\u89e3\u7b54<\/h3>\n

                  6.1 \u6280\u672f\u95ee\u9898<\/h4>\n

                  Q1：\u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b？<\/p>\n

                  💡 \u5efa\u8bae：<\/p>\n\n\u573a\u666f\u63a8\u8350\u6a21\u578b\u7406\u7531<\/tr>\n\n\n\n\n\n
                  \u7b80\u5355\u4efb\u52a1<\/td>\nGPT-3.5\/\u56fd\u4ea7\u5c0f\u6a21\u578b<\/td>\n\u6210\u672c\u4f4e\u3001\u901f\u5ea6\u5feb<\/td>\n<\/tr>\n
                  \u590d\u6742\u63a8\u7406<\/td>\nGPT-4\/Claude<\/td>\n\u63a8\u7406\u80fd\u529b\u5f3a<\/td>\n<\/tr>\n
                  \u4ee3\u7801\u4efb\u52a1<\/td>\nGPT-4\/Claude<\/td>\n\u4ee3\u7801\u80fd\u529b\u5f3a<\/td>\n<\/tr>\n
                  \u672c\u5730\u90e8\u7f72<\/td>\nLLaMA\/Qwen<\/td>\n\u6570\u636e\u5b89\u5168<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                  Q2：\u5982\u4f55\u8bc4\u4f30Agent\u6548\u679c？<\/p>\n

                  \u5efa\u8bae\u5efa\u7acb\u591a\u7ef4\u8bc4\u4f30\u4f53\u7cfb：<\/p>\n

                  # Agent\u8bc4\u4f30\u6846\u67b6<\/span>
                  \ndef<\/span> evaluate_agent<\/span>(<\/span>agent,<\/span> test_cases)<\/span>:<\/span>
                  \n """\u8bc4\u4f30Agent\u6027\u80fd"""<\/span>
                  \n metrics =<\/span> {<\/span>
                  \n 'success_rate'<\/span>:<\/span> 0<\/span>,<\/span>
                  \n 'avg_time'<\/span>:<\/span> 0<\/span>,<\/span>
                  \n 'avg_steps'<\/span>:<\/span> 0<\/span>,<\/span>
                  \n 'user_satisfaction'<\/span>:<\/span> 0<\/span>
                  \n }<\/span><\/p>\n

                  results =<\/span> [<\/span>]<\/span>
                  \n for<\/span> case<\/span> in<\/span> test_cases:<\/span>
                  \n start_time =<\/span> time.<\/span>time(<\/span>)<\/span>
                  \n result =<\/span> agent.<\/span>execute(<\/span>case<\/span>[<\/span>'task'<\/span>]<\/span>)<\/span>
                  \n end_time =<\/span> time.<\/span>time(<\/span>)<\/span><\/p>\n

                  results.<\/span>append(<\/span>{<\/span>
                  \n 'success'<\/span>:<\/span> result ==<\/span> case<\/span>[<\/span>'expected'<\/span>]<\/span>,<\/span>
                  \n 'time'<\/span>:<\/span> end_time –<\/span> start_time,<\/span>
                  \n 'steps'<\/span>:<\/span> len<\/span>(<\/span>agent.<\/span>memory)<\/span>,<\/span>
                  \n 'quality'<\/span>:<\/span> rate_quality(<\/span>result,<\/span> case<\/span>[<\/span>'expected'<\/span>]<\/span>)<\/span>
                  \n }<\/span>)<\/span><\/p>\n

                  # \u8ba1\u7b97\u6307\u6807<\/span>
                  \n metrics[<\/span>'success_rate'<\/span>]<\/span> =<\/span> sum<\/span>(<\/span>r[<\/span>'success'<\/span>]<\/span> for<\/span> r in<\/span> results)<\/span> \/<\/span> len<\/span>(<\/span>results)<\/span>
                  \n metrics[<\/span>'avg_time'<\/span>]<\/span> =<\/span> sum<\/span>(<\/span>r[<\/span>'time'<\/span>]<\/span> for<\/span> r in<\/span> results)<\/span> \/<\/span> len<\/span>(<\/span>results)<\/span>
                  \n metrics[<\/span>'avg_steps'<\/span>]<\/span> =<\/span> sum<\/span>(<\/span>r[<\/span>'steps'<\/span>]<\/span> for<\/span> r in<\/span> results)<\/span> \/<\/span> len<\/span>(<\/span>results)<\/span>
                  \n metrics[<\/span>'user_satisfaction'<\/span>]<\/span> =<\/span> sum<\/span>(<\/span>r[<\/span>'quality'<\/span>]<\/span> for<\/span> r in<\/span> results)<\/span> \/<\/span> len<\/span>(<\/span>results)<\/span><\/p>\n

                  return<\/span> metrics<\/p>\n

                  6.2 \u5e94\u7528\u95ee\u9898<\/h4>\n

                  Q3：\u5982\u4f55\u63a7\u5236\u6210\u672c？<\/p>\n

                  💡 \u6210\u672c\u4f18\u5316\u7b56\u7565：<\/p>\n

                  \u2460 \u9009\u62e9\u5408\u9002\u89c4\u6a21\u7684\u6a21\u578b
                  \n\u2461 \u4f18\u5316\u63d0\u793a\u8bcd\u51cf\u5c11token\u6d88\u8017
                  \n\u2462 \u4f7f\u7528\u7f13\u5b58\u907f\u514d\u91cd\u590d\u8c03\u7528
                  \n\u2463 \u6279\u91cf\u5904\u7406\u63d0\u5347\u6548\u7387<\/p>\n

                  Q4：\u5982\u4f55\u4fdd\u8bc1\u5b89\u5168？<\/p>\n

                  \u26a0\ufe0f \u5b89\u5168\u8981\u70b9：<\/p>\n

                    \n
                  • \u8f93\u5165\u8fc7\u6ee4\u9632\u6b62\u6ce8\u5165<\/li>\n
                  • \u6743\u9650\u6700\u5c0f\u5316\u539f\u5219<\/li>\n
                  • \u654f\u611f\u64cd\u4f5c\u9700\u786e\u8ba4<\/li>\n
                  • \u5b8c\u6574\u5ba1\u8ba1\u65e5\u5fd7<\/li>\n<\/ul>\n
                    \n

                    \u4e03\u3001\u672a\u6765\u53d1\u5c55\u8d8b\u52bf<\/h3>\n

                    7.1 \u6280\u672f\u8d8b\u52bf<\/h4>\n

                    📈 \u53d1\u5c55\u65b9\u5411：<\/p>\n\n\u8d8b\u52bf\u63cf\u8ff0\u9884\u8ba1\u65f6\u95f4<\/tr>\n\n\n\n\n\n
                    \u591a\u6a21\u6001Agent<\/td>\n\u56fe\u6587\u97f3\u89c6\u9891\u7edf\u4e00\u5904\u7406<\/td>\n1-2\u5e74<\/td>\n<\/tr>\n
                    \u7aef\u4fa7\u90e8\u7f72<\/td>\n\u672c\u5730\u5316\u8fd0\u884cAgent<\/td>\n2-3\u5e74<\/td>\n<\/tr>\n
                    \u81ea\u4e3bAgent<\/td>\n\u65e0\u9700\u5e72\u9884\u5168\u81ea\u52a8<\/td>\n3-5\u5e74<\/td>\n<\/tr>\n
                    AGI\u63a2\u7d22<\/td>\n\u901a\u7528\u4eba\u5de5\u667a\u80fd<\/td>\n5-10\u5e74<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                    7.2 \u5e94\u7528\u8d8b\u52bf<\/h4>\n

                    \u2705 \u6838\u5fc3\u5224\u65ad：<\/p>\n

                    \u672a\u67653-5\u5e74，AI Agent\u5c06\u5728\u4ee5\u4e0b\u9886\u57df\u4ea7\u751f\u6df1\u8fdc\u5f71\u54cd：<\/p>\n

                    \u2460 \u4f01\u4e1a\u670d\u52a1：\u6210\u4e3a\u6807\u914d\u5de5\u5177
                    \n\u2461 \u4e2a\u4eba\u52a9\u7406：\u5168\u573a\u666f\u8986\u76d6
                    \n\u2462 \u4e13\u4e1a\u9886\u57df：\u6df1\u5ea6\u884c\u4e1a\u5e94\u7528
                    \n\u2463 \u521b\u610f\u5de5\u4f5c：\u4eba\u673a\u534f\u4f5c\u4e3b\u6d41<\/p>\n

                    7.3 \u804c\u4e1a\u53d1\u5c55<\/h4>\n

                    💡 \u804c\u4e1a\u5efa\u8bae：<\/p>\n

                    \u5bf9\u4e8e\u60f3\u8981\u8fdb\u5165\u8fd9\u4e00\u9886\u57df\u7684\u8bfb\u8005，\u5efa\u8bae：<\/p>\n\n\u9636\u6bb5\u5b66\u4e60\u91cd\u70b9\u65f6\u95f4\u6295\u5165<\/tr>\n\n\n\n\n\n
                    \u5165\u95e8\u671f<\/td>\n\u57fa\u7840\u6982\u5ff5\u3001\u5de5\u5177\u4f7f\u7528<\/td>\n1-2\u4e2a\u6708<\/td>\n<\/tr>\n
                    \u8fdb\u9636\u671f<\/td>\n\u539f\u7406\u7406\u89e3\u3001\u9879\u76ee\u5b9e\u8df5<\/td>\n2-4\u4e2a\u6708<\/td>\n<\/tr>\n
                    \u4e13\u4e1a\u671f<\/td>\n\u67b6\u6784\u8bbe\u8ba1\u3001\u4f18\u5316\u8c03\u4f18<\/td>\n4-8\u4e2a\u6708<\/td>\n<\/tr>\n
                    \u4e13\u5bb6\u671f<\/td>\n\u521b\u65b0\u7814\u7a76\u3001\u56e2\u961f\u9886\u5bfc<\/td>\n1\u5e74\u4ee5\u4e0a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
                    \n

                    \u516b\u3001\u672c\u7ae0\u5c0f\u7ed3<\/h3>\n

                    8.1 \u6838\u5fc3\u8981\u70b9\u56de\u987e<\/h4>\n

                    \u2705 \u672c\u7ae0\u6838\u5fc3\u5185\u5bb9：<\/p>\n

                    \u2460 \u6982\u5ff5\u7406\u89e3：\u660e\u786e\u4e86\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u7684\u57fa\u672c\u5b9a\u4e49\u548c\u6838\u5fc3\u6982\u5ff5<\/p>\n

                    \u2461 \u6280\u672f\u539f\u7406：\u6df1\u5165\u63a2\u8ba8\u4e86\u5e95\u5c42\u67b6\u6784\u548c\u6838\u5fc3\u7b97\u6cd5<\/p>\n

                    \u2462 \u5b9e\u8df5\u5e94\u7528：\u63d0\u4f9b\u4e86\u8be6\u7ec6\u7684\u5b9e\u65bd\u6307\u5357\u548c\u6700\u4f73\u5b9e\u8df5<\/p>\n

                    \u2463 \u6848\u4f8b\u5206\u6790：\u901a\u8fc7\u771f\u5b9e\u6848\u4f8b\u52a0\u6df1\u7406\u89e3<\/p>\n

                    \u2464 \u95ee\u9898\u89e3\u7b54：\u89e3\u7b54\u4e86\u5e38\u89c1\u7684\u6280\u672f\u548c\u5e94\u7528\u95ee\u9898<\/p>\n

                    \u2465 \u8d8b\u52bf\u5c55\u671b：\u5206\u6790\u4e86\u672a\u6765\u53d1\u5c55\u65b9\u5411<\/p>\n

                    8.2 \u5b66\u4e60\u5efa\u8bae<\/h4>\n

                    💡 \u7ed9\u8bfb\u8005\u7684\u5efa\u8bae：<\/p>\n

                    \u2460 \u7406\u8bba\u4e0e\u5b9e\u8df5\u7ed3\u5408：\u5728\u7406\u89e3\u6982\u5ff5\u7684\u57fa\u7840\u4e0a，\u52a8\u624b\u5b9e\u8df5
                    \n\u2461 \u5faa\u5e8f\u6e10\u8fdb：\u4ece\u7b80\u5355\u573a\u666f\u5f00\u59cb，\u9010\u6b65\u6df1\u5165
                    \n\u2462 \u6301\u7eed\u5b66\u4e60：\u6280\u672f\u53d1\u5c55\u8fc5\u901f，\u4fdd\u6301\u5b66\u4e60\u70ed\u60c5
                    \n\u2463 \u4ea4\u6d41\u5206\u4eab：\u52a0\u5165\u793e\u533a，\u4e0e\u540c\u884c\u4ea4\u6d41<\/p>\n

                    8.3 \u4e0b\u4e00\u7ae0\u9884\u544a<\/h4>\n

                    \u4e0b\u4e00\u7ae0\u5c06\u7ee7\u7eed\u63a2\u8ba8\u76f8\u5173\u4e3b\u9898，\u5e2e\u52a9\u8bfb\u8005\u5efa\u7acb\u5b8c\u6574\u7684\u77e5\u8bc6\u4f53\u7cfb\u3002\u5efa\u8bae\u8bfb\u8005\u5728\u638c\u63e1\u672c\u7ae0\u5185\u5bb9\u540e，\u7ee7\u7eed\u6df1\u5165\u5b66\u4e60\u540e\u7eed\u7ae0\u8282\u3002<\/p>\n

                    \n

                    \u4e5d\u3001\u8bfe\u540e\u7ec3\u4e60<\/h3>\n

                    \u7ec3\u4e60\u4e00：\u6982\u5ff5\u7406\u89e3<\/h4>\n

                    \u8bf7\u7528\u81ea\u5df1\u7684\u8bdd\u89e3\u91ca\u722c\u866bAgent：\u6267\u884c\u5f0fAI\u81ea\u52a8\u91c7\u96c6\u6570\u636e\u7684\u6838\u5fc3\u6982\u5ff5，\u5e76\u4e3e\u4f8b\u8bf4\u660e\u5176\u5e94\u7528\u573a\u666f\u3002<\/p>\n

                    \u7ec3\u4e60\u4e8c：\u5b9e\u8df5\u64cd\u4f5c<\/h4>\n

                    \u6839\u636e\u672c\u7ae0\u5185\u5bb9，\u5c1d\u8bd5\u5b8c\u6210\u4ee5\u4e0b\u4efb\u52a1：<\/p>\n

                    \u2460 \u642d\u5efa\u4e00\u4e2a\u7b80\u5355\u7684Agent\u73af\u5883
                    \n\u2461 \u5b9e\u73b0\u4e00\u4e2a\u57fa\u7840\u6267\u884c\u529f\u80fd
                    \n\u2462 \u6d4b\u8bd5\u5e76\u8bb0\u5f55\u7ed3\u679c<\/p>\n

                    \u7ec3\u4e60\u4e09：\u6848\u4f8b\u5206\u6790<\/h4>\n

                    \u9009\u62e9\u4e00\u4e2a\u4f60\u719f\u6089\u7684\u573a\u666f，\u5206\u6790\u5982\u4f55\u5e94\u7528\u672c\u7ae0\u6240\u5b66\u77e5\u8bc6\u89e3\u51b3\u5b9e\u9645\u95ee\u9898\u3002<\/p>\n

                    \n

                    \u5341\u3001\u53c2\u8003\u8d44\u6599<\/h3>\n

                    10.1 \u63a8\u8350\u9605\u8bfb<\/h4>\n

                    📄 \u7ecf\u5178\u8bba\u6587：<\/p>\n

                      \n
                    • ReAct: Synergizing Reasoning and Acting in Language Models (2023)<\/li>\n
                    • Toolformer: Language Models Can Teach Themselves to Use Tools (2023)<\/li>\n
                    • AutoGPT: An Autonomous GPT-4 Experiment (2023)<\/li>\n<\/ul>\n

                      📚 \u63a8\u8350\u4e66\u7c4d：<\/p>\n

                        \n
                      • \u300a\u6784\u5efaAI\u5e94\u7528\u300b<\/li>\n
                      • \u300a\u5927\u6a21\u578b\u5e94\u7528\u5f00\u53d1\u5b9e\u6218\u300b<\/li>\n
                      • \u300aAI Agent\u8bbe\u8ba1\u4e0e\u5b9e\u73b0\u300b<\/li>\n<\/ul>\n

                        10.2 \u5728\u7ebf\u8d44\u6e90<\/h4>\n

                        🔗 \u5b66\u4e60\u5e73\u53f0：<\/p>\n

                          \n
                        • LangChain\u6587\u6863: https:\/\/python.langchain.com<\/li>\n
                        • AutoGPT: https:\/\/github.com\/Significant-Gravitas\/AutoGPT<\/li>\n
                        • Hugging Face: https:\/\/huggingface.co<\/li>\n<\/ul>\n

                          10.3 \u793e\u533a\u4ea4\u6d41<\/h4>\n

                          💬 \u793e\u533a\u63a8\u8350：<\/p>\n

                            \n
                          • GitHub\u5f00\u6e90\u793e\u533a<\/li>\n
                          • Discord AI\u793e\u533a<\/li>\n
                          • \u77e5\u4e4eAI\u8bdd\u9898<\/li>\n
                          • \u5fae\u4fe1\u6280\u672f\u7fa4<\/li>\n<\/ul>\n
                            \n

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