{"id":132436,"date":"2025-04-03T14:48:48","date_gmt":"2025-04-03T06:48:48","guid":{"rendered":"https:\/\/www.growthhk.cn\/?p=132436"},"modified":"2025-04-03T14:48:54","modified_gmt":"2025-04-03T06:48:54","slug":"%e6%9e%84%e5%bb%ba%e6%82%a8%e7%9a%84%e7%ac%ac%e4%b8%80%e4%b8%aa-ai-%e6%99%ba%e8%83%bd%e4%bd%93%e7%9a%84%e5%ae%8c%e6%95%b4%e6%8c%87%e5%8d%97%ef%bc%88%e6%af%94%e6%82%a8%e6%83%b3%e8%b1%a1%e7%9a%84","status":"publish","type":"post","link":"https:\/\/www.growthhk.cn\/cgo\/product\/132436.html","title":{"rendered":"\u6784\u5efa\u60a8\u7684\u7b2c\u4e00\u4e2a AI \u667a\u80fd\u4f53\u7684\u5b8c\u6574\u6307\u5357\uff08\u6bd4\u60a8\u60f3\u8c61\u7684\u8981\u5bb9\u6613\uff09"},"content":{"rendered":"\n

\u5728\u6784\u5efa\u6211\u7684\u7b2c\u4e00\u4e2a\u5546\u4e1a AI<\/a><\/span> \u667a\u80fd\u4f53<\/a><\/span>\u4e09\u4e2a\u6708\u540e\uff0c\u5728\u5ba2\u6237\u7aef\u6f14\u793a\u671f\u95f4\uff0c\u4e00\u5207\u90fd\u5d29\u6e83\u4e86\u3002<\/p>\n\n\n\n

\u672c\u5e94\u662f\u65e0\u7f1d\u7684\u81ea\u4e3b\u5de5\u4f5c\u6d41\u7a0b\u53d8\u6210\u4e86\u4e00\u4e2a\u53cd\u590d\u7684\u6f84\u6e05\u8bf7\u6c42\u548c\u4e0d\u4e00\u81f4\u7684\u51b3\u5b9a\u7684\u5c34\u5c2c\u5faa\u73af\u3002\u5ba2\u6237\u4ecd\u7136\u4fdd\u6301\u793c\u8c8c\uff0c\u4f46\u663e\u7136\u5f88\u5931\u671b\u3002<\/p>\n\n\n\n

\u4ed6\u4eec\u79bb\u5f00\u540e\uff0c\u6211\u82b1\u4e86\u51e0\u4e2a\u5c0f\u65f6\u5206\u6790\u5931\u8d25\uff0c\u53d1\u73b0\u6211\u4ece\u6839\u672c\u4e0a\u8bef\u89e3\u4e86\u667a\u80fd\u4f53\u67b6\u6784\u2014\u2014\u6211\u6784\u5efa\u4e86\u4e00\u4e2a\u8fc7\u4e8e\u590d\u6742\u7684\u7cfb\u7edf\uff0c\u51b3\u7b56\u8fb9\u754c\u5f88\u5dee\uff0c\u6ca1\u6709\u660e\u786e\u7684\u63a8\u7406\u8def\u5f84\u3002<\/p>\n\n\n\n

\u90a3\u6b21\u5931\u8d25\u6539\u53d8\u4e86\u6211\u7684\u65b9\u6cd5\uff0c\u5e76\u6210\u4e3a\u6211\u89e3\u91ca\u8fd9\u4e9b\u7cfb\u7edf\u7684\u57fa\u7840\u3002\u4e00\u65e6\u4f60\u7406\u89e3\u4e86\u6838\u5fc3\u539f\u5219\uff0c\u6784\u5efa\u6709\u6548\u7684\u667a\u80fd\u4f53\u5c31\u4f1a\u53d8\u5f97\u5f02\u5e38\u7b80\u5355\u3002<\/strong><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

AI \u667a\u80fd\u4f53\u7b80\u4ecb<\/strong><\/h2>\n\n\n\n

\u4e0e\u4ec5\u54cd\u5e94\u63d0\u793a\u7684\u804a\u5929\u673a\u5668\u4eba\u4e0d\u540c\uff0c\u667a\u80fd\u4f53\u4f1a\u4e3b\u52a8\u5e76\u81ea\u884c\u5b8c\u6210\u4efb\u52a1\u3002\u5b83\u4eec\u662f\u8ba9\u67d0\u4eba\u56de\u7b54\u60a8\u6709\u5173\u6570\u636e\u7684\u95ee\u9898\u4e0e\u8ba9\u67d0\u4eba\u5b9e\u9645\u4e3a\u60a8\u5206\u6790\u6570\u636e\u4e4b\u95f4\u7684\u533a\u522b\u3002<\/p>\n\n\n\n

\u4ece\u6a21\u578b\u5230\u667a\u80fd\u4f53<\/strong><\/h2>\n\n\n\n

\u5728\u667a\u80fd\u4f53\u4e4b\u524d\uff0c\u6211\u4eec\u5c06 AI \u89e3\u51b3\u65b9\u6848\u6784\u5efa\u4e3a\u72ec\u7acb\u7684\u3001\u4e92\u4e0d\u5173\u8054\u7684\u7ec4\u4ef6 \u2014 \u4e00\u4e2a\u6a21\u578b\u7528\u4e8e\u7406\u89e3\u6587\u672c\uff0c\u53e6\u4e00\u4e2a\u6a21\u578b\u7528\u4e8e\u751f\u6210\u4ee3\u7801\uff0c\u53e6\u4e00\u4e2a\u6a21\u578b\u7528\u4e8e\u5904\u7406\u56fe\u50cf\u3002<\/p>\n\n\n\n

\u8fd9\u79cd\u788e\u7247\u5316\u7684\u65b9\u6cd5<\/p>\n\n\n\n

    \n
  1. \u8feb\u4f7f\u7528\u6237\u624b\u52a8\u7ba1\u7406\u5de5\u4f5c\u6d41\u7a0b\uff1b<\/li>\n\n\n\n
  2. \u5bfc\u81f4\u5728\u4e0d\u540c\u7cfb\u7edf\u4e4b\u95f4\u79fb\u52a8\u65f6\u4e0a\u4e0b\u6587\u6d88\u5931\uff1b<\/li>\n\n\n\n
  3. \u9700\u8981\u4e3a\u6bcf\u4e2a\u6d41\u7a0b\u6b65\u9aa4\u6784\u5efa\u81ea\u5b9a\u4e49\u96c6\u6210\uff1b<\/li>\n<\/ol>\n\n\n\n

    \u667a\u80fd\u4f53\u6539\u53d8\u4e86\u8fd9\u79cd\u8303\u5f0f<\/strong>\u3002<\/p>\n\n\n\n

    \u4e0e\u5904\u7406\u5b64\u7acb\u4efb\u52a1\u7684\u4f20\u7edf\u6a21\u578b\u4e0d\u540c\uff0c\u667a\u80fd\u4f53\u7ba1\u7406\u5404\u79cd\u529f\u80fd\uff0c\u540c\u65f6\u4fdd\u6301\u5bf9\u6574\u4e2a\u4efb\u52a1\u7684\u6574\u4f53\u7406\u89e3\u3002<\/p>\n\n\n\n

    \u667a\u80fd\u4f53\u4e0d\u4ec5\u9075\u5faa\u6307\u793a\uff0c\u8fd8\u4f1a\u6839\u636e\u5728\u6b64\u8fc7\u7a0b\u4e2d\u5b66\u5230\u7684\u4fe1\u606f\u8fdb\u884c\u8c03\u6574\u5e76\u505a\u51fa\u6709\u5173\u540e\u7eed\u6b65\u9aa4\u7684\u660e\u667a\u51b3\u7b56\uff0c\u7c7b\u4f3c\u4e8e\u6211\u4eec\u4eba\u7c7b\u7684\u4f5c\u65b9\u5f0f\u3002<\/p>\n\n\n\n

    \u667a\u80fd\u4f53\u7684\u6838\u5fc3\u4f18\u52bf<\/strong><\/h2>\n\n\n\n

    \u8ba9\u6211\u4eec\u901a\u8fc7\u67e5\u770b\u7279\u5b9a\u4efb\u52a1\u6765\u4e86\u89e3\u667a\u80fd\u4f53\u7684\u80fd\u529b\u3002<\/p>\n\n\n\n

    \u4f20\u7edf AI \u5c06\u5176\u5206\u4e3a\u51e0\u4e2a\u5b64\u7acb\u7684\u6b65\u9aa4 \u2014 \u603b\u7ed3\u3001\u63d0\u53d6\u5173\u952e\u672f\u8bed\u3001\u5bf9\u5185\u5bb9\u8fdb\u884c\u5206\u7c7b\u548c\u751f\u6210\u89c1\u89e3 \u2014 \u6bcf\u4e2a\u6b65\u9aa4\u90fd\u9700\u8981\u660e\u786e\u7684\u4eba\u5de5\u534f\u8c03\u3002<\/p>\n\n\n\n

    \u9650\u5236\u4e0d\u4ec5\u5728\u4e8e\u6a21\u578b\u5b64\u7acb\u5de5\u4f5c\uff0c\u8fd8\u5728\u4e8e\u60a8\u5fc5\u987b\u624b\u52a8\u5bf9\u6574\u4e2a\u8fc7\u7a0b\u8fdb\u884c\u6392\u5e8f\uff0c\u663e\u5f0f\u7ba1\u7406\u6b65\u9aa4\u4e4b\u95f4\u7684\u77e5\u8bc6\u4f20\u9012\uff0c\u5e76\u6839\u636e\u4e2d\u95f4\u7ed3\u679c\u72ec\u7acb\u786e\u5b9a\u9700\u8981\u54ea\u4e9b\u5176\u4ed6\u4f5c\u3002<\/p>\n\n\n\n

    \u76f8\u6bd4\u4e4b\u4e0b**\uff0c\u57fa\u4e8e\u667a\u80fd\u4f53\u7684\u65b9\u6cd5\u53ef\u4ee5\u81ea\u4e3b\u6267\u884c\u6bcf\u4e2a\u6b65\u9aa4\uff0c\u800c\u4e0d\u4f1a\u5931\u53bb\u66f4\u5e7f\u6cdb\u76ee\u6807\u7684\u4e00\u9762**\u3002<\/p>\n\n\n\n

    \u667a\u80fd\u4f53\u667a\u80fd\u7684\u6784\u5efa\u5757<\/strong><\/h2>\n\n\n\n

    AI \u667a\u80fd\u4f53\u57fa\u4e8e\u4e09\u4e2a\u57fa\u672c\u539f\u5219<\/strong>\uff1a<\/p>\n\n\n\n

      \n
    1. \u72b6\u6001\u7ba1\u7406\uff1a<\/strong>\u00a0\u667a\u80fd\u4f53\u7684\u5de5\u4f5c\u8bb0\u5fc6\u8ddf\u8e2a\u4e0a\u4e0b\u6587\uff0c\u4e86\u89e3\u5b83\u6240\u5b66\u5230\u7684\u5185\u5bb9\u548c\u65e8\u5728\u5b8c\u6210\u7684\u4efb\u52a1\uff1b<\/li>\n\n\n\n
    2. \u51b3\u7b56\uff1a<\/strong>\u00a0\u667a\u80fd\u4f53\u6839\u636e\u5f53\u524d\u77e5\u8bc6\u786e\u5b9a\u54ea\u79cd\u65b9\u6cd5\u6709\u610f\u4e49\uff1b<\/li>\n\n\n\n
    3. \u5de5\u5177\u4f7f\u7528\uff1a<\/strong>\u00a0\u667a\u80fd\u4f53\u77e5\u9053\u54ea\u4e2a\u5de5\u5177\u89e3\u51b3\u4e86\u6bcf\u4e2a\u7279\u5b9a\u95ee\u9898\uff1b<\/li>\n<\/ol>\n\n\n\n

      \u4f7f\u7528 LangGraph \u6784\u5efa AI \u667a\u80fd\u4f53<\/strong><\/h2>\n\n\n\n

      \u73b0\u5728\u60a8\u5df2\u7ecf\u4e86\u89e3\u4e86\u4ec0\u4e48\u662f AI \u667a\u80fd\u4f53\u4ee5\u53ca\u5b83\u4eec\u4e3a\u4ec0\u4e48\u91cd\u8981\uff0c\u8ba9\u6211\u4eec\u4f7f\u7528 LangGraph\uff08LangChain \u7528\u4e8e\u6784\u5efa\u5f3a\u5927\u7684 AI \u667a\u80fd\u4f53\u7684\u6846\u67b6\uff09\u6784\u5efa\u4e00\u4e2a\u667a\u80fd\u4f53\u3002<\/p>\n\n\n\n

      \u6211\u771f\u6b63\u559c\u6b22 LangGraph \u7684\u5730\u65b9\u5728\u4e8e\uff0c\u5b83\u53ef\u4ee5\u8ba9\u60a8\u5c06\u667a\u80fd\u4f53\u7684\u601d\u7ef4\u548c\u884c\u52a8\u6620\u5c04\u4e3a\u56fe\u8868\u3002\u6bcf\u4e2a\u8282\u70b9\u4ee3\u8868\u4e00\u79cd\u80fd\u529b\uff08\u5982\u641c\u7d22 Web \u6216\u7f16\u5199\u4ee3\u7801\uff09\uff0c\u8282\u70b9\uff08\u8fb9\u7f18\uff09\u4e4b\u95f4\u7684\u8fde\u63a5\u63a7\u5236\u4fe1\u606f\u6d41\u3002<\/p>\n\n\n\n

      \u5f53\u6211\u5f00\u59cb\u6784\u5efa\u667a\u80fd\u4f53\u65f6\uff0c\u8fd9\u79cd\u65b9\u6cd5\u5bf9\u6211\u6765\u8bf4\u5f88\u6709\u610f\u4e49\uff0c\u56e0\u4e3a\u6211\u5b9e\u9645\u4e0a\u53ef\u4ee5\u53ef\u89c6\u5316\u6211\u7684\u667a\u80fd\u4f53\u601d\u7ef4\u8fc7\u7a0b\u3002<\/p>\n\n\n\n

      \u60a8\u7684\u7b2c\u4e00\u4e2a\u667a\u80fd\u4f53\uff1aMedium Articles Analyzer<\/strong><\/h2>\n\n\n\n

      \u8ba9\u6211\u4eec\u770b\u770b\u5982\u4f55\u4f7f\u7528 LangGraph \u521b\u5efa\u6587\u672c\u5206\u6790\u667a\u80fd\u4f53\u3002<\/p>\n\n\n\n

      \u8be5\u667a\u80fd\u4f53\u5c06\u9605\u8bfb\u6587\u7ae0\uff0c\u5f04\u6e05\u695a\u5b83\u4eec\u7684\u5185\u5bb9\uff0c\u63d0\u53d6\u91cd\u8981\u5143\u7d20\uff0c\u5e76\u63d0\u4f9b\u5e72\u51c0\u7684\u6458\u8981\u2014\u2014\u672c\u8d28\u4e0a\u662f\u60a8\u7684\u79c1\u4eba\u7814\u7a76\u52a9\u7406\u3002<\/p>\n\n\n\n

      \u8bbe\u7f6e\u73af\u5883<\/strong><\/p>\n\n\n\n

      \u9996\u5148\uff0c\u60a8\u9700\u8981\u8bbe\u7f6e\u60a8\u7684\u5f00\u53d1\u73af\u5883\u3002<\/p>\n\n\n\n

      \u7b2c 1 \u6b65 \u2014 \u521b\u5efa\u9879\u76ee\u76ee\u5f55\uff1a<\/strong><\/p>\n\n\n\n

      mkdir ai_agent_project cd ai_agent_project<\/pre>\n\n\n\n
      \u7b2c 2 \u6b65 \u2014 \u521b\u5efa\u5e76\u6fc0\u6d3b\u865a\u62df\u73af\u5883\uff1a<\/strong><\/p>\n\n\n\n
      On Windows\npython -m venv agent_env agent_env\\Scripts\\activate\nOn macOS\/Linux\npython3 -m venv agent_env source agent_env\/bin\/activate<\/pre>\n\n\n\n
      \u7b2c 3 \u6b65 \u2014 \u5b89\u88c5\u5fc5\u8981\u7684\u8f6f\u4ef6\u5305\uff1a<\/strong><\/p>\n\n\n\n
      pip install langgraph langchain langchain-openai python-dotenv<\/pre>\n\n\n\n
      \u7b2c 4 \u6b65 \u2014 \u8bbe\u7f6e\u60a8\u7684 OpenAI API\uff1a<\/strong><\/p>\n\n\n\n
      \u6211\u4f7f\u7528 GPT-4o mini \u4f5c\u4e3a\u6211\u4eec\u667a\u80fd\u4f53\u7684\u5927\u8111\uff0c\u4f46\u60a8\u53ef\u4ee5\u5c06\u5176\u4ea4\u6362\u4e3a\u60a8\u559c\u6b22\u7684\u4efb\u4f55LLM\u3002\u5982\u679c\u60a8\u6ca1\u6709 API \u5bc6\u94a5\uff1a<\/p>\n\n\n\n
        \n
      1. \u4f7f\u7528 OpenAI \u521b\u5efa\u5e10\u6237<\/a><\/li>\n\n\n\n
      2. \u5bfc\u822a\u5230 API \u5bc6\u94a5\u90e8\u5206<\/li>\n\n\n\n
      3. \u70b9\u51fb \u201cCreate new secret key\u201d<\/li>\n\n\n\n
      4. \u590d\u5236\u60a8\u7684 API \u5bc6\u94a5<\/li>\n<\/ol>\n\n\n\n
        \u7b2c 5 \u6b65 \u2014 \u521b\u5efa\u4e00\u4e2a .env \u6587\u4ef6<\/strong><\/p>\n\n\n\n
        On Windows\necho OPENAI_API_KEY=your-api-key-here > .env\nOn macOS\/Linux\necho \"OPENAI_API_KEY=your-api-key-here\" > .env<\/pre>\n\n\n\n
        \u5c06 ‘your-api-key-here’ \u66ff\u6362\u4e3a\u60a8\u7684 OpenAI API \u5bc6\u94a5\u3002<\/p>\n\n\n\n
        \u7b2c 6 \u6b65 \u2013 \u521b\u5efa\u540d\u4e3a test_setup.py<\/code><\/strong> \u7684\u6d4b\u8bd5\u6587\u4ef6<\/p>\n\n\n\n
        python\nimport os\nfrom dotenv import load_dotenv\nfrom langchain_openai import ChatOpenAI\nLoad environment variables\nload_dotenv()\nInitialize the ChatOpenAI instance\nllm = ChatOpenAI(model=\"gpt-4o-mini\")\nTest the setup\nresponse = llm.invoke(\"Hello! Are you working?\") print(response.content)<\/pre>\n\n\n\n
        \u7b2c 7 \u6b65 \u2014 \u8fd0\u884c\u6d4b\u8bd5\uff1a<\/strong><\/p>\n\n\n\n
        python test_setup.py<\/pre>\n\n\n\n
        \u5982\u679c\u60a8\u6536\u5230\u56de\u590d\uff0c\u606d\u559c\uff0c\u60a8\u7684\u73af\u5883\u5df2\u51c6\u5907\u597d\u6784\u5efa\u667a\u80fd\u4f53\uff01<\/p>\n\n\n\n
        \u521b\u5efa\u6211\u4eec\u7684\u7b2c\u4e00\u4e2a\u667a\u80fd\u4f53<\/strong><\/h2>\n\n\n\n
        \u6211\u4eec\u7684\u667a\u80fd\u4f53\u9700\u8981\u5185\u5b58\u6765\u8ddf\u8e2a\u5b83\u7684\u8fdb\u5ea6\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 TypedDict \u521b\u5efa\u5b83\uff1a<\/p>\n\n\n\n
        The original question or task\nclass State(TypedDict): text:\nTracks the agent's thinking and decisions\nstr classification:\nStores intermediate results from tools\nstr entities: List[str] summary: str<\/pre>\n\n\n\n
        \u8fd9\u79cd\u7ed3\u6784\u8ba9\u6211\u4eec\u7684\u667a\u80fd\u4f53\u8bb0\u4f4f\u60a8\u7684\u8bf7\u6c42\u3001\u8ddf\u8e2a\u5176\u63a8\u7406\u3001\u5b58\u50a8\u5de5\u5177\u6570\u636e\u5e76\u51c6\u5907\u6700\u7ec8\u7b54\u6848\u3002\u4f7f\u7528 TypeDict<\/code>\u63d0\u4f9b\u7c7b\u578b\u5b89\u5168\uff0c\u5982\u679c\u6211\u4eec\u5b58\u50a8\u7684\u6570\u636e\u7c7b\u578b\u4e0d\u6b63\u786e\uff0c\u5b83\u4f1a\u53d1\u51fa\u8b66\u544a\uff0c\u4ece\u800c\u7b80\u5316\u8c03\u8bd5\u3002<\/p>\n\n\n\n
        \u73b0\u5728\u6211\u4eec\u7684\u667a\u80fd\u4f53\u6709\u4e86\u5185\u5b58\uff0c\u8ba9\u6211\u4eec\u7ed9\u5b83\u4e00\u4e9b\u601d\u8003\u80fd\u529b\u5427\uff01<\/p>\n\n\n\n
        llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)<\/pre>\n\n\n\n
        \u8bbe\u7f6e Temperature=0 \u53ef\u786e\u4fdd\u6211\u4eec\u7684\u667a\u80fd\u4f53\u59cb\u7ec8\u9009\u62e9\u6700\u53ef\u80fd\u7684\u54cd\u5e94 \u2014 \u8fd9\u5bf9\u4e8e\u9075\u5faa\u7279\u5b9a\u63a8\u7406\u6a21\u5f0f\u7684\u667a\u80fd\u4f53\u81f3\u5173\u91cd\u8981\u3002\u4f5c\u4e3a\u590d\u4e60\uff0c\u6e29\u5ea6\u5145\u5f53 \u201c\u521b\u9020\u529b\u65cb\u94ae\u201d LLMs\uff1a<\/p>\n\n\n\n
        \u6e29\u5ea6 = 0\uff1a\u805a\u7126\u7684\u786e\u5b9a\u6027\u54cd\u5e94<\/p>\n\n\n\n
        \u6e29\u5ea6=1\uff1a\u66f4\u591a\u79cd\u7c7b\u3001\u66f4\u6709\u521b\u610f\u7684\u8f93\u51fa<\/p>\n\n\n\n
        \u6e29\u5ea6=2\uff1a\u72c2\u91ce\u7684\u3001\u6709\u65f6\u4e0d\u8fde\u8d2f\u7684\u60f3\u6cd5<\/p>\n\n\n\n
        \u5982\u679c\u60a8\u7684\u667a\u80fd\u4f53\u505a\u51fa\u5947\u602a\u7684\u51b3\u5b9a\uff0c\u8bf7\u5148\u68c0\u67e5\u60a8\u7684\u6e29\u5ea6\u8bbe\u7f6e\uff01<\/p>\n\n\n\n
        \u6dfb\u52a0\u667a\u80fd\u4f53\u7684\u529f\u80fd<\/strong><\/h2>\n\n\n\n
        \u73b0\u5728\uff0c\u6211\u4eec\u5c06\u4e3a\u667a\u80fd\u4f53\u6784\u5efa\u4e13\u95e8\u7684\u5de5\u5177\uff0c\u6bcf\u4e2a\u5de5\u5177\u5904\u7406\u7279\u5b9a\u7684\u4efb\u52a1\u7c7b\u578b\u3002<\/p>\n\n\n\n
        \u4e00\u3001\u6211\u4eec\u7684\u5206\u7c7b\u80fd\u529b\uff1a<\/p>\n\n\n\n
        def\nsummarize_node\n(state):\nCreate a template for the summarization prompt\nThis tells the model to summarize the input text in one sentence\nsummarization_prompt = PromptTemplate.from_template(\n\"\"\"Summarize the following text in one short sentence.\nText: {input}\nSummary:\"\"\"\n)\nCreate a chain by connecting the prompt template to the language model\nThe \"|\" operator pipes the output of the prompt into the model\nchain = summarization_prompt | llm\nExecute the chain with the input text from the state dictionary\nThis passes the text to be summarized to the model\nresponse = chain.invoke({\"input\": state[\"input\"]})\nReturn a dictionary with the summary extracted from the model's response\nThis will be merged into the agent's state\nreturn {\"summary\": response.content}<\/pre>\n\n\n\n
        \u6b64\u529f\u80fd\u5c06\u6587\u6863\u63d0\u70bc\u4e3a\u5176\u8981\u70b9\u7684\u7b80\u660e\u6458\u8981\u3002<\/p>\n\n\n\n
        \u8fd9\u4e9b\u6280\u80fd\u7ed3\u5408\u8d77\u6765\uff0c\u4f7f\u6211\u4eec\u7684\u667a\u80fd\u4f53\u80fd\u591f\u7406\u89e3\u5185\u5bb9\u7c7b\u578b\u3001\u8bc6\u522b\u5173\u952e\u4fe1\u606f\u5e76\u521b\u5efa\u6613\u4e8e\u7406\u89e3\u7684\u6458\u8981 \u2014 \u6bcf\u4e2a\u51fd\u6570\u90fd\u9075\u5faa\u76f8\u540c\u7684\u6a21\u5f0f\uff0c\u5373\u83b7\u53d6\u5f53\u524d\u72b6\u6001\u3001\u5904\u7406\u5f53\u524d\u72b6\u6001\u5e76\u5c06\u6709\u7528\u4fe1\u606f\u8fd4\u56de\u7ed9\u4e0b\u4e00\u4e2a\u51fd\u6570\u3002<\/p>\n\n\n\n
        \u5b8c\u6210\u667a\u80fd\u4f53\u7ed3\u6784<\/strong><\/h2>\n\n\n\n
        \u73b0\u5728\uff0c\u6211\u4eec\u5c06\u8fd9\u4e9b\u529f\u80fd\u8fde\u63a5\u5230\u4e00\u4e2a\u534f\u8c03\u7684\u5de5\u4f5c\u6d41\u4e2d\uff1a<\/p>\n\n\n\n
        workflow = StateGraph(State)\n\nAdd nodes to the graph\n\nworkflow.add_node(\"classification_node\", classification_node)\n\nworkflow.add_node(\"entity_extraction\", entity_extraction_node)\n\nworkflow.add_node(\"summarization\", summarization_node)\n\nAdd edges to the graph\n\nworkflow.set_entry_point(\"classification_node\") # Set the entry point of the graph\n\nworkflow.add_edge(\"classification_node\", \"entity_extraction\")\n\nworkflow.add_edge(\"entity_extraction\", \"summarization\")\n\nworkflow.add_edge(\"summarization\", END)\n\nCompile the graph\n\napp = workflow.compile()<\/pre>\n\n\n\n
        \u60a8\u5df2\u7ecf\u6784\u5efa\u4e86\u4e00\u4e2a\u667a\u80fd\u4f53\uff0c\u8be5\u667a\u80fd\u4f53\u6309\u534f\u8c03\u7684\u987a\u5e8f\u4ece\u5206\u7c7b\u5230\u5b9e\u4f53\u63d0\u53d6\u518d\u5230\u6458\u8981\uff0c\u4f7f\u5176\u80fd\u591f\u7406\u89e3\u6587\u672c\u7c7b\u578b\u3001\u8bc6\u522b\u91cd\u8981\u5b9e\u4f53\u3001\u521b\u5efa\u6458\u8981\uff0c\u7136\u540e\u5b8c\u6210\u8be5\u8fc7\u7a0b\u3002<\/p>\n\n\n\n
        \u667a\u80fd\u4f53\u5728\u884c\u52a8<\/strong><\/h2>\n\n\n\n
        \u73b0\u5728\uff0c\u8ba9\u6211\u4eec\u4f7f\u7528\u793a\u4f8b\u6587\u672c\u6d4b\u8bd5\u6211\u4eec\u7684\u667a\u80fd\u4f53\uff1a<\/p>\n\n\n\n
        Define a sample text about Anthropic's MCP to test our agent\n\nsample_text = \"\"\"\n\nAnthropic's MCP (Model Context Protocol) is an open-source powerhouse that lets your applications interact effortlessly with APIs across various systems.\n\n\"\"\"\n\nCreate the initial state with our sample text\n\nstate_input = {\"text\": sample_text}\n\nRun the agent's full workflow on our sample text\n\nresult = app.invoke(state_input)\n\nPrint each component of the result:\n\n- The classification category (News, Blog, Research, or Other)\n\nprint(\"Classification:\", result[\"classification\"])\n\n- The extracted entities (People, Organizations, Locations)\n\nprint(\"\\nEntities:\", result[\"entities\"])\n\n- The generated summary of the text\n\nprint(\"\\nSummary:\", result[\"summary\"])<\/pre>\n\n\n\n
        \u8fd0\u884c\u6b64\u4ee3\u7801\u4f1a\u901a\u8fc7\u6bcf\u4e2a\u529f\u80fd\u5904\u7406\u6587\u672c\uff1a<\/p>\n\n\n\n
        \u5206\u7c7b<\/strong>\uff1a \u6280\u672f<\/p>\n\n\n\n
        \u5b9e\u4f53<\/strong>\uff1a[‘Anthropic’\uff0c ‘MCP’\uff0c ‘Model Context Protocol’]<\/p>\n\n\n\n
        \u7b80\u4ecb<\/strong>\uff1a Anthropic \u7684 MCP \u662f\u4e00\u79cd\u5f00\u6e90\u534f\u8bae\uff0c\u652f\u6301\u4e0e\u5404\u79cd API \u7cfb\u7edf\u8fdb\u884c\u65e0\u7f1d\u5e94\u7528\u7a0b\u5e8f\u4ea4\u4e92\u3002<\/p>\n\n\n\n
        \u4ee4\u4eba\u5370\u8c61\u6df1\u523b\u7684\u4e0d\u4ec5\u4ec5\u662f\u6700\u7ec8\u7ed3\u679c\uff0c\u8fd8\u6709\u6bcf\u4e2a\u9636\u6bb5\u5982\u4f55\u5efa\u7acb\u5728\u524d\u4e00\u4e2a\u9636\u6bb5\u4e4b\u4e0a\u3002\u8fd9\u53cd\u6620\u4e86\u6211\u4eec\u81ea\u5df1\u7684\u9605\u8bfb\u8fc7\u7a0b\uff1a\u6211\u4eec\u9996\u5148\u786e\u5b9a\u5185\u5bb9\u7c7b\u578b\uff0c\u7136\u540e\u786e\u5b9a\u91cd\u8981\u7684\u540d\u79f0\u548c\u6982\u5ff5\uff0c\u6700\u540e\u521b\u5efa\u8fde\u63a5\u6240\u6709\u5185\u5bb9\u7684\u5fc3\u7406\u603b\u7ed3\u3002<\/p>\n\n\n\n
        \u8fd9\u79cd\u667a\u80fd\u4f53\u6784\u5efa\u65b9\u6cd5\u8fdc\u8fdc\u8d85\u51fa\u4e86\u6211\u4eec\u7684\u6280\u672f\u793a\u4f8b\u3002\u60a8\u53ef\u4ee5\u5c06\u7c7b\u4f3c\u7684\u8bbe\u7f6e\u7528\u4e8e\uff1a<\/p>\n\n\n\n
          \n
        1. \u4e2a\u4eba\u53d1\u5c55\u6587\u7ae0 \u2014 \u5bf9\u589e\u957f\u9886\u57df\u8fdb\u884c\u5206\u7c7b\uff0c\u63d0\u53d6\u53ef\u4f5c\u7684\u5efa\u8bae\uff0c\u5e76\u603b\u7ed3\u5173\u952e\u89c1\u89e3\uff1b<\/li>\n\n\n\n
        2. \u521d\u521b\u516c\u53f8\u521b\u59cb\u4eba\u7684\u6545\u4e8b \u2014 \u4e86\u89e3\u5546\u4e1a\u6a21\u5f0f<\/a><\/span>\u3001\u878d\u8d44\u6a21\u5f0f\u548c\u589e\u957f\u6218\u7565\uff1b<\/li>\n\n\n\n
        3. \u4ea7\u54c1\u8bc4\u8bba \u2014 \u8bc6\u522b\u529f\u80fd\u3001\u54c1\u724c\u548c\u5efa\u8bae\uff1b<\/li>\n<\/ol>\n\n\n\n
          AI \u667a\u80fd\u4f53\u7684\u5c40\u9650\u6027<\/strong><\/h2>\n\n\n\n
          \u6211\u4eec\u7684\u667a\u80fd\u4f53\u5728\u6211\u4eec\u8bbe\u8ba1\u7684\u8282\u70b9\u548c\u8fde\u63a5\u7684\u521a\u6027\u6846\u67b6\u5185\u5de5\u4f5c\u3002<\/p>\n\n\n\n
          \u8fd9\u79cd\u53ef\u9884\u6d4b\u7684\u9650\u5236\u4e86\u5b83\u7684\u9002\u5e94\u6027<\/strong>\u3002\u4e0e\u4eba\u7c7b\u4e0d\u540c\uff0c\u667a\u80fd\u4f53\u9075\u5faa\u56fa\u5b9a\u7684\u8def\u5f84\uff0c\u5728\u9762\u5bf9\u610f\u5916\u60c5\u51b5\u65f6\u65e0\u6cd5\u8c03\u6574\u3002<\/p>\n\n\n\n
          \u4e0a\u4e0b\u6587\u7406\u89e3<\/strong>\u662f\u53e6\u4e00\u4e2a\u9650\u5236\u3002\u8fd9\u4e2a\u667a\u80fd\u4f53\u53ef\u4ee5\u5904\u7406\u6587\u672c\uff0c\u4f46\u7f3a\u4e4f\u4eba\u7c7b\u81ea\u7136\u638c\u63e1\u7684\u66f4\u5e7f\u6cdb\u7684\u77e5\u8bc6\u548c\u6587\u5316\u7ec6\u5fae\u5dee\u522b\u3002\u667a\u80fd\u4f53\u5728\u63d0\u4f9b\u7684\u6587\u672c\u8303\u56f4\u5185\u8fd0\u4f5c\uff0c\u5c3d\u7ba1\u6dfb\u52a0\u4e92\u8054\u7f51\u641c\u7d22\u53ef\u4ee5\u5e2e\u52a9\u8865\u5145\u5176\u77e5\u8bc6\u3002<\/p>\n\n\n\n
          \u9ed1\u5323\u5b50\u95ee\u9898<\/strong>\u4e5f\u5b58\u5728\u4e8e\u667a\u80fd\u4f53\u7cfb\u7edf\u4e2d\u3002\u6211\u4eec\u770b\u5230\u8f93\u5165\u548c\u8f93\u51fa\uff0c\u4f46\u770b\u4e0d\u5230\u5185\u90e8\u51b3\u7b56\u3002\u50cf GPT-o1 \u6216 DeepSeek R1 \u8fd9\u6837\u7684\u63a8\u7406\u6a21\u578b\u901a\u8fc7\u5c55\u793a\u5b83\u4eec\u7684\u601d\u7ef4\u8fc7\u7a0b\u6765\u63d0\u4f9b\u66f4\u9ad8\u7684\u900f\u660e\u5ea6\uff0c\u5c3d\u7ba1\u6211\u4eec\u4ecd\u7136\u65e0\u6cd5\u5b8c\u5168\u63a7\u5236\u5185\u90e8\u53d1\u751f\u7684\u4e8b\u60c5\u3002<\/p>\n\n\n\n
          \u6700\u540e\uff0c\u8fd9\u4e9b\u7cfb\u7edf\u5e76\u975e\u5b8c\u5168\u81ea\u4e3b\uff0c\u9700\u8981\u4eba\u5de5\u76d1\u7763<\/strong>\uff0c\u5c24\u5176\u662f\u5728\u9a8c\u8bc1\u8f93\u51fa\u548c\u786e\u4fdd\u51c6\u786e\u6027\u65b9\u9762\u3002\u4e0e\u4efb\u4f55\u5176\u4ed6 AI \u7cfb\u7edf\u4e00\u6837\uff0c\u5c06 AI \u529f\u80fd\u4e0e\u4eba\u5de5\u76d1\u7763\u76f8\u7ed3\u5408\uff0c\u53ef\u4ee5\u83b7\u5f97\u6700\u4f73\u7ed3\u679c\u3002<\/p>\n\n\n\n
          \u4e86\u89e3\u8fd9\u4e9b\u9650\u5236\u6709\u52a9\u4e8e\u6211\u4eec\u6784\u5efa\u66f4\u597d\u7684\u7cfb\u7edf\uff0c\u5e76\u786e\u5207\u5730\u77e5\u9053\u4f55\u65f6\u9700\u8981\u4eba\u7c7b\u4ecb\u5165\u3002\u5c06 AI \u529f\u80fd\u4e0e\u4eba\u7c7b\u4e13\u4e1a\u77e5\u8bc6\u76f8\u7ed3\u5408\uff0c\u53ef\u4ee5\u83b7\u5f97\u6700\u4f73\u7ed3\u679c\u3002<\/p>\n\n\n\n
          <\/p>\n","protected":false},"excerpt":{"rendered":"
          \u624b\u628a\u624b\u6559\u4f60\u521b\u5efa\u60a8\u7684\u4e13\u5c5e AI \u667a\u80fd\u4f53<\/p>\n","protected":false},"author":2100,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[375,6842,6510],"special":[],"class_list":["post-132436","post","type-post","status-publish","format-standard","hentry","category-product","tag-ai","tag-ai-agents","tag-6510","entry"],"views":10513,"_links":{"self":[{"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/posts\/132436","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/users\/2100"}],"replies":[{"embeddable":true,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/comments?post=132436"}],"version-history":[{"count":1,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/posts\/132436\/revisions"}],"predecessor-version":[{"id":133154,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/posts\/132436\/revisions\/133154"}],"wp:attachment":[{"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/media?parent=132436"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/categories?post=132436"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/tags?post=132436"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/www.growthhk.cn\/wp-json\/wp\/v2\/special?post=132436"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}