{"id":110947,"date":"2026-09-29T21:48:44","date_gmt":"2026-09-29T13:48:44","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/110947.html"},"modified":"2026-09-29T21:48:44","modified_gmt":"2026-09-29T13:48:44","slug":"langchain%e6%a1%86%e6%9e%b6%e5%ae%8c%e5%85%a8%e6%8c%87%e5%8d%97%ef%bc%88%e4%bb%8b%e7%bb%8d%e4%b8%8e%e4%bd%bf%e7%94%a8%ef%bc%89","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/110947.html","title":{"rendered":"LangChain\u6846\u67b6\u5b8c\u5168\u6307\u5357\uff08\u4ecb\u7ecd\u4e0e\u4f7f\u7528\uff09"},"content":{"rendered":"

LangChain \u6846\u67b6\u5b8c\u5168\u6307\u5357：\u4ece 1.0 \u91cd\u6784\u5230 Agent \u5b9e\u6218<\/h2>\n

\u4e00\u53e5\u8bdd\u603b\u7ed3：LangChain \u662f\u76ee\u524d\u6700\u6d41\u884c\u7684 LLM \u5e94\u7528\u5f00\u53d1\u6846\u67b6\u2014\u2014\u5b83\u4e0d\u8bad\u7ec3\u6a21\u578b，\u800c\u662f\u89e3\u51b3\u300c\u600e\u4e48\u628a\u5927\u6a21\u578b\u63a5\u8fdb\u771f\u5b9e\u8f6f\u4ef6\u300d\u8fd9\u4ef6\u4e8b：\u7edf\u4e00\u5404\u5bb6\u6a21\u578b\u7684\u8c03\u7528\u63a5\u53e3\u3001\u628a\u63d0\u793a\u8bcd\/\u5de5\u5177\/\u8bb0\u5fc6\/\u68c0\u7d22\u6807\u51c6\u5316\u6210\u53ef\u7ec4\u5408\u7684\u7ec4\u4ef6\u3001\u5e76\u63d0\u4f9b\u4e00\u5957 Agent \u8fd0\u884c\u65f6（\u5faa\u73af\u8c03\u7528\u6a21\u578b \u2192 \u6267\u884c\u5de5\u5177 \u2192 \u518d\u8c03\u7528）\u30022025 \u5e74 10 \u6708\u5b83\u53d1\u5e03\u4e86 1.0，\u628a\u6846\u67b6\u5927\u5e45\u6536\u7f29：\u65e7\u7684 LLMChain\u3001AgentExecutor \u5168\u90e8\u79fb\u51fa\u4e3b\u5305，\u65b0\u6838\u5fc3\u53ea\u5269\u4e00\u4e2a\u51fd\u6570 create_agent，\u5916\u52a0\u4e00\u5957\u4e2d\u95f4\u4ef6\u673a\u5236\u3002\u8fd9\u610f\u5473\u7740\u7f51\u4e0a 2024 \u5e74\u7684\u6559\u7a0b\u57fa\u672c\u5168\u90e8\u5931\u6548\u2014\u2014\u672c\u7bc7\u6309\u5f53\u524d langchain 1.4.2 \u7684\u5b9e\u9645\u63a5\u53e3\u5199，\u5e76\u4e13\u95e8\u7ed9\u4e86\u4e00\u8282\u300c\u8001\u6559\u7a0b\u6392\u9519\u5bf9\u7167\u8868\u300d\u3002<\/p>\n

\n

📋 \u76ee\u5f55<\/h3>\n
  • LangChain \u662f\u4ec0\u4e48，\u5b83\u5230\u5e95\u89e3\u51b3\u4ec0\u4e48\u95ee\u9898<\/li>\n
  • \u26a0\ufe0f \u6700\u91cd\u8981\u7684\u4e00\u4ef6\u4e8b：1.0 \u628a\u65e7\u6559\u7a0b\u5168\u5e9f\u4e86<\/li>\n
  • \u751f\u6001\u5168\u666f：\u4e00\u5f20\u56fe\u770b\u61c2\u4e03\u4e2a\u5305\u7684\u5206\u5de5<\/li>\n
  • \u6838\u5fc3\u6982\u5ff5：\u56db\u4e2a\u8bcd\u5403\u900f LangChain<\/li>\n
  • \u5b89\u88c5\u4e0e\u73af\u5883\u51c6\u5907（\u542b\u56fd\u5185 DeepSeek \u65b9\u6848）<\/li>\n
  • \u7b2c\u4e00\u4e2a Agent：10 \u884c\u4ee3\u7801\u8dd1\u901a<\/li>\n
  • \u9010\u9879\u62c6\u89e3：LangChain \u7684\u516d\u9879\u6838\u5fc3\u80fd\u529b<\/li>\n
  • LCEL \u4e0e Runnable：\u5e95\u5c42\u534f\u8bae<\/li>\n
  • RAG \u5b9e\u6218：\u4e09\u79cd\u67b6\u6784\u4e0e\u5b8c\u6574\u4ee3\u7801<\/li>\n
  • \u4ec0\u4e48\u65f6\u5019\u8be5\u7528 LangGraph<\/li>\n
  • LangSmith：\u53ef\u89c2\u6d4b\u6027\u4e0e\u8bc4\u6d4b<\/li>\n
  • \u5e38\u89c1\u95ee\u9898 FAQ（\u542b\u8001\u6559\u7a0b\u62a5\u9519\u6392\u67e5）<\/li>\n
  • \u603b\u7ed3<\/li>\n
    \n

    \u4e00\u3001LangChain \u662f\u4ec0\u4e48，\u5b83\u5230\u5e95\u89e3\u51b3\u4ec0\u4e48\u95ee\u9898<\/h3>\n

    1.1 \u4e00\u53e5\u8bdd\u5b9a\u4f4d<\/h4>\n

    LangChain \u4e0d\u8bad\u7ec3\u6a21\u578b，\u4e5f\u4e0d\u63d0\u4f9b\u6a21\u578b\u3002 \u5b83\u662f\u4e00\u5c42\u300c\u80f6\u6c34 + \u9aa8\u67b6\u300d，\u628a\u5927\u6a21\u578b\u548c\u4f60\u7684\u4ee3\u7801\u3001\u6570\u636e\u3001\u5de5\u5177\u8fde\u8d77\u6765\u3002<\/p>\n

    \u7528\u4e00\u53e5\u8bdd\u6982\u62ec\u5b83\u7684\u4ef7\u503c：\u8ba9\u4f60\u4e0d\u7528\u4e3a\u6bcf\u4e00\u4e2a\u6a21\u578b\u4f9b\u5e94\u5546\u3001\u6bcf\u4e00\u79cd\u6570\u636e\u6e90\u3001\u6bcf\u4e00\u5957\u91cd\u8bd5\/\u6d41\u5f0f\/\u65e5\u5fd7\u903b\u8f91\u91cd\u590d\u9020\u8f6e\u5b50\u3002<\/p>\n

    1.2 \u6ca1\u6709\u6846\u67b6\u65f6，\u4f60\u4f1a\u9047\u5230\u4ec0\u4e48\u95ee\u9898<\/h4>\n

    \u5047\u8bbe\u4f60\u60f3\u505a\u4e00\u4e2a\u300c\u4f01\u4e1a\u77e5\u8bc6\u5e93\u95ee\u7b54\u300d：<\/p>\n

    # \u76f4\u63a5\u7528\u5b98\u65b9 SDK \u7684\u5199\u6cd5（\u793a\u610f）<\/span>
    \nimport<\/span> openai<\/p>\n

    resp =<\/span> openai.<\/span>chat.<\/span>completions.<\/span>create(<\/span>
    \n model=<\/span>"gpt-4o"<\/span>,<\/span>
    \n messages=<\/span>[<\/span>{<\/span>"role"<\/span>:<\/span> "user"<\/span>,<\/span> "content"<\/span>:<\/span> f"\u6839\u636e\u4ee5\u4e0b\u8d44\u6599\u56de\u7b54\u95ee\u9898：\\\\n<\/span>{<\/span>context}<\/span><\/span>\\\\n\\\\n\u95ee\u9898：<\/span>{<\/span>question}<\/span><\/span>"<\/span><\/span>}<\/span>]<\/span>,<\/span>
    \n)<\/span>
    \nanswer =<\/span> resp.<\/span>choices[<\/span>0<\/span>]<\/span>.<\/span>message.<\/span>content<\/p>\n

    \u8fd9\u6bb5\u4ee3\u7801\u80fd\u8dd1\u3002\u4f46\u4e00\u65e6\u8981\u505a\u6210\u4ea7\u54c1，\u4f60\u4f1a\u7acb\u523b\u649e\u4e0a\u8fd9\u5806\u95ee\u9898：<\/p>\n\n\u95ee\u9898\u624b\u5199\u8981\u5904\u7406\u4ec0\u4e48<\/tr>\n\n\n\n\n\n\n\n\n\n
    \u6362\u6a21\u578b<\/td>\n\u6bcf\u5bb6 SDK \u7684\u8c03\u7528\u65b9\u5f0f\u3001\u53c2\u6570\u540d\u3001\u8fd4\u56de\u7ed3\u6784\u90fd\u4e0d\u540c，\u6362\u4e00\u5bb6\u8981\u91cd\u5199\u4e00\u904d<\/td>\n<\/tr>\n
    \u6d41\u5f0f\u8f93\u51fa<\/td>\n\u524d\u7aef\u8981\u4e00\u4e2a\u5b57\u4e00\u4e2a\u5b57\u51fa，\u5f97\u81ea\u5df1\u5904\u7406 SSE\u3001\u5206\u5757\u62fc\u63a5\u3001\u5f02\u5e38\u4e2d\u65ad<\/td>\n<\/tr>\n
    \u5e76\u53d1\u6279\u5904\u7406<\/td>\n100 \u6761\u6570\u636e\u8981\u5e76\u53d1\u8dd1，\u5f97\u81ea\u5df1\u5199 asyncio \/ \u7ebf\u7a0b\u6c60\u548c\u9650\u6d41<\/td>\n<\/tr>\n
    \u5de5\u5177\u8c03\u7528<\/td>\n\u6a21\u578b\u8981\u8c03\u7528\u5916\u90e8 API，\u5f97\u81ea\u5df1\u5199 JSON Schema\u3001\u89e3\u6790\u5de5\u5177\u8c03\u7528\u3001\u5904\u7406\u5931\u8d25\u91cd\u8bd5<\/td>\n<\/tr>\n
    \u591a\u8f6e\u8bb0\u5fc6<\/td>\n\u4f1a\u8bdd\u5386\u53f2\u8981\u81ea\u5df1\u5b58\u3001\u81ea\u5df1\u88c1\u526a\u3001\u81ea\u5df1\u63a7\u5236 token \u9884\u7b97<\/td>\n<\/tr>\n
    RAG \u68c0\u7d22<\/td>\n\u6587\u6863\u5207\u5206\u3001\u5411\u91cf\u5316\u3001\u5165\u5e93\u3001\u53ec\u56de\u3001\u91cd\u6392，\u6bcf\u6b65\u90fd\u662f\u4e00\u5957\u72ec\u7acb\u903b\u8f91<\/td>\n<\/tr>\n
    \u53ef\u89c2\u6d4b\u6027<\/td>\n\u4e00\u6b21\u8bf7\u6c42\u7ecf\u8fc7 7 \u4e2a\u6b65\u9aa4，\u51fa\u9519\u4e86\u6839\u672c\u4e0d\u77e5\u9053\u6b7b\u5728\u54ea<\/td>\n<\/tr>\n
    \u91cd\u8bd5\u4e0e\u964d\u7ea7<\/td>\n\u4e3b\u6a21\u578b\u6302\u4e86\u8981\u5207\u5907\u7528\u6a21\u578b，\u8981\u81ea\u5df1\u5199 fallback<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    LangChain \u7684\u505a\u6cd5\u662f\u628a\u8fd9\u4e9b\u62bd\u8c61\u6210\u7edf\u4e00\u7684\u300c\u7ec4\u4ef6\u534f\u8bae\u300d：<\/p>\n

    #mermaid-svg-j7u0AQx2w870s6N3{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-j7u0AQx2w870s6N3 .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-j7u0AQx2w870s6N3 .error-icon{fill:#552222;}#mermaid-svg-j7u0AQx2w870s6N3 .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-j7u0AQx2w870s6N3 .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-j7u0AQx2w870s6N3 .marker{fill:#333333;stroke:#333333;}#mermaid-svg-j7u0AQx2w870s6N3 .marker.cross{stroke:#333333;}#mermaid-svg-j7u0AQx2w870s6N3 svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-j7u0AQx2w870s6N3 p{margin:0;}#mermaid-svg-j7u0AQx2w870s6N3 .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-j7u0AQx2w870s6N3 .cluster-label text{fill:#333;}#mermaid-svg-j7u0AQx2w870s6N3 .cluster-label span{color:#333;}#mermaid-svg-j7u0AQx2w870s6N3 .cluster-label span p{background-color:transparent;}#mermaid-svg-j7u0AQx2w870s6N3 .label text,#mermaid-svg-j7u0AQx2w870s6N3 span{fill:#333;color:#333;}#mermaid-svg-j7u0AQx2w870s6N3 .node rect,#mermaid-svg-j7u0AQx2w870s6N3 .node circle,#mermaid-svg-j7u0AQx2w870s6N3 .node ellipse,#mermaid-svg-j7u0AQx2w870s6N3 .node polygon,#mermaid-svg-j7u0AQx2w870s6N3 .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-j7u0AQx2w870s6N3 .rough-node .label text,#mermaid-svg-j7u0AQx2w870s6N3 .node .label text,#mermaid-svg-j7u0AQx2w870s6N3 .image-shape .label,#mermaid-svg-j7u0AQx2w870s6N3 .icon-shape .label{text-anchor:middle;}#mermaid-svg-j7u0AQx2w870s6N3 .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-j7u0AQx2w870s6N3 .rough-node .label,#mermaid-svg-j7u0AQx2w870s6N3 .node .label,#mermaid-svg-j7u0AQx2w870s6N3 .image-shape .label,#mermaid-svg-j7u0AQx2w870s6N3 .icon-shape .label{text-align:center;}#mermaid-svg-j7u0AQx2w870s6N3 .node.clickable{cursor:pointer;}#mermaid-svg-j7u0AQx2w870s6N3 .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-j7u0AQx2w870s6N3 .arrowheadPath{fill:#333333;}#mermaid-svg-j7u0AQx2w870s6N3 .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-j7u0AQx2w870s6N3 .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-j7u0AQx2w870s6N3 .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-j7u0AQx2w870s6N3 .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-j7u0AQx2w870s6N3 .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-j7u0AQx2w870s6N3 .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-j7u0AQx2w870s6N3 .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-j7u0AQx2w870s6N3 .cluster text{fill:#333;}#mermaid-svg-j7u0AQx2w870s6N3 .cluster span{color:#333;}#mermaid-svg-j7u0AQx2w870s6N3 div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-j7u0AQx2w870s6N3 .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-j7u0AQx2w870s6N3 rect.text{fill:none;stroke-width:0;}#mermaid-svg-j7u0AQx2w870s6N3 .icon-shape,#mermaid-svg-j7u0AQx2w870s6N3 .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-j7u0AQx2w870s6N3 .icon-shape p,#mermaid-svg-j7u0AQx2w870s6N3 .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-j7u0AQx2w870s6N3 .icon-shape .label rect,#mermaid-svg-j7u0AQx2w870s6N3 .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-j7u0AQx2w870s6N3 .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-j7u0AQx2w870s6N3 .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-j7u0AQx2w870s6N3 :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u4f60\u7684\u4e1a\u52a1\u4ee3\u7801<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    LangChain \u7edf\u4e00\u63a5\u53e3<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    OpenAI<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    Anthropic<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    DeepSeek<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    Ollama \u672c\u5730<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    Chroma \/ FAISS<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    PostgreSQL \/ Milvus<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u5de5\u5177 \/ API \/ MCP<\/p>\n

    <\/span><\/p>\n

    \u6362\u6a21\u578b = \u6539\u4e00\u4e2a\u5b57\u7b26\u4e32\u3002\u52a0\u68c0\u7d22 = \u52a0\u4e00\u4e2a\u7ec4\u4ef6\u3002\u8fd9\u5957\u62bd\u8c61\u5c31\u662f\u5b83\u7684\u6838\u5fc3\u5356\u70b9\u3002<\/p>\n

    1.3 \u8bda\u5b9e\u7684\u8fb9\u754c：\u4ec0\u4e48\u65f6\u5019\u4e0d\u8be5\u7528 LangChain<\/h4>\n

    \u8fd9\u70b9\u5f88\u591a\u6559\u7a0b\u4e0d\u8bf4，\u4f46\u5f88\u91cd\u8981：<\/p>\n\n\u4f60\u7684\u573a\u666f\u5efa\u8bae<\/tr>\n\n\n\n\n\n\n
    \u53ea\u8c03\u7528\u4e00\u6b21 LLM，\u56fa\u5b9a prompt<\/td>\n\u274c \u76f4\u63a5\u7528\u5b98\u65b9 SDK\u3002LangChain \u53ea\u4f1a\u589e\u52a0\u62bd\u8c61\u5c42\u548c\u5fc3\u667a\u8d1f\u62c5<\/td>\n<\/tr>\n
    \u56fa\u5b9a\u7684 2\u20134 \u6b65\u6d41\u6c34\u7ebf（\u68c0\u7d22 \u2192 \u63d0\u793a \u2192 \u6a21\u578b）<\/td>\n\u2705 LCEL \u5f88\u5408\u9002<\/td>\n<\/tr>\n
    Agent \u5faa\u73af\u3001\u5de5\u5177\u8c03\u7528\u3001\u9700\u8981\u4eba\u5de5\u5ba1\u6279<\/td>\n\u2705\u2705 \u8fd9\u6b63\u662f LangChain \/ LangGraph \u7684\u4e3b\u573a<\/td>\n<\/tr>\n
    \u6781\u81f4\u6027\u80fd\u3001\u4e0d\u9700\u8981\u4efb\u4f55\u89c2\u6d4b<\/td>\n\u274c \u76f4\u63a5\u8c03 SDK \u66f4\u5feb<\/td>\n<\/tr>\n
    \u9700\u8981\u6781\u590d\u6742\u7684\u81ea\u5b9a\u4e49\u72b6\u6001\u673a<\/td>\n\u2705 \u7528 LangGraph（LangChain \u7684\u5e95\u5c42\u7f16\u6392\u6846\u67b6）<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    🎯 \u4e00\u53e5\u8bdd\u5224\u65ad\u6807\u51c6：\u5982\u679c\u4f60\u5728\u5199\u300c\u80f6\u6c34\u4ee3\u7801\u300d\u8d85\u8fc7 50 \u884c，LangChain \u5c31\u503c\u4e86；\u5982\u679c\u53ea\u662f\u5355\u6b21 API \u8c03\u7528，\u5b83\u53ea\u4f1a\u788d\u4e8b\u3002<\/p>\n

    1.4 \u5173\u952e\u4fe1\u606f\u4e00\u89c8（\u6570\u636e\u622a\u81f3 2026-09）<\/h4>\n\n\u9879\u76ee\u5185\u5bb9<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n
    \u5f53\u524d\u7248\u672c<\/td>\nlangchain 1.4.2（2026-09-19 \u53d1\u5e03）<\/td>\n<\/tr>\n
    \u6838\u5fc3\u5e93<\/td>\nlangchain-core 1.6.0（2026-08-19）<\/td>\n<\/tr>\n
    \u7f16\u6392\u6846\u67b6<\/td>\nlanggraph 1.2.12（2026-09-21）<\/td>\n<\/tr>\n
    1.0 GA \u65f6\u95f4<\/td>\n2025-10-22（\u4e0e LangGraph 1.0 \u540c\u65e5）<\/td>\n<\/tr>\n
    Python \u8981\u6c42<\/td>\n3.10 \u2013 3.14<\/td>\n<\/tr>\n
    \u5f00\u6e90\u534f\u8bae<\/td>\nMIT<\/td>\n<\/tr>\n
    GitHub Stars<\/td>\nlangchain \u7ea6 147k；langgraph \u7ea6 42.3k<\/td>\n<\/tr>\n
    \u751f\u6001\u89c4\u6a21<\/td>\n\u6570\u767e\u4e2a\u96c6\u6210\u5305（\u6a21\u578b \/ \u5411\u91cf\u5e93 \/ \u52a0\u8f7d\u5668 \/ \u5de5\u5177）<\/td>\n<\/tr>\n
    \u5546\u4e1a\u4ea7\u54c1<\/td>\nLangSmith（\u53ef\u89c2\u6d4b\u6027）\u3001LangGraph Platform（\u90e8\u7f72）<\/td>\n<\/tr>\n
    \u5b98\u65b9\u8bfe\u7a0b<\/td>\nLangChain Academy（\u514d\u8d39）<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n

    \u4e8c\u3001\u26a0\ufe0f \u6700\u91cd\u8981\u7684\u4e00\u4ef6\u4e8b：1.0 \u628a\u65e7\u6559\u7a0b\u5168\u5e9f\u4e86<\/h3>\n

    \u5982\u679c\u4f60\u5728\u7f51\u4e0a\u641c\u5230 2024 \u5e74\u7684 LangChain \u6559\u7a0b，\u7167\u6284\u4f1a\u76f4\u63a5\u62a5 ImportError\u2014\u2014\u4e0d\u662f\u4f60\u7684\u73af\u5883\u95ee\u9898，\u662f API \u771f\u7684\u5220\u4e86\u3002<\/p>\n

    2.1 \u53d1\u751f\u4e86\u4ec0\u4e48<\/h4>\n

    #mermaid-svg-5XRgcu1cT5wZEHDD{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-5XRgcu1cT5wZEHDD .error-icon{fill:#552222;}#mermaid-svg-5XRgcu1cT5wZEHDD .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-5XRgcu1cT5wZEHDD .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-5XRgcu1cT5wZEHDD .marker{fill:#333333;stroke:#333333;}#mermaid-svg-5XRgcu1cT5wZEHDD .marker.cross{stroke:#333333;}#mermaid-svg-5XRgcu1cT5wZEHDD svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-5XRgcu1cT5wZEHDD p{margin:0;}#mermaid-svg-5XRgcu1cT5wZEHDD .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD .cluster-label text{fill:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD .cluster-label span{color:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD .cluster-label span p{background-color:transparent;}#mermaid-svg-5XRgcu1cT5wZEHDD .label text,#mermaid-svg-5XRgcu1cT5wZEHDD span{fill:#333;color:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD .node rect,#mermaid-svg-5XRgcu1cT5wZEHDD .node circle,#mermaid-svg-5XRgcu1cT5wZEHDD .node ellipse,#mermaid-svg-5XRgcu1cT5wZEHDD .node polygon,#mermaid-svg-5XRgcu1cT5wZEHDD .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-5XRgcu1cT5wZEHDD .rough-node .label text,#mermaid-svg-5XRgcu1cT5wZEHDD .node .label text,#mermaid-svg-5XRgcu1cT5wZEHDD .image-shape .label,#mermaid-svg-5XRgcu1cT5wZEHDD .icon-shape .label{text-anchor:middle;}#mermaid-svg-5XRgcu1cT5wZEHDD .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-5XRgcu1cT5wZEHDD .rough-node .label,#mermaid-svg-5XRgcu1cT5wZEHDD .node .label,#mermaid-svg-5XRgcu1cT5wZEHDD .image-shape .label,#mermaid-svg-5XRgcu1cT5wZEHDD .icon-shape .label{text-align:center;}#mermaid-svg-5XRgcu1cT5wZEHDD .node.clickable{cursor:pointer;}#mermaid-svg-5XRgcu1cT5wZEHDD .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-5XRgcu1cT5wZEHDD .arrowheadPath{fill:#333333;}#mermaid-svg-5XRgcu1cT5wZEHDD .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-5XRgcu1cT5wZEHDD .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-5XRgcu1cT5wZEHDD .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-5XRgcu1cT5wZEHDD .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-5XRgcu1cT5wZEHDD .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-5XRgcu1cT5wZEHDD .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-5XRgcu1cT5wZEHDD .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-5XRgcu1cT5wZEHDD .cluster text{fill:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD .cluster span{color:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-5XRgcu1cT5wZEHDD .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-5XRgcu1cT5wZEHDD rect.text{fill:none;stroke-width:0;}#mermaid-svg-5XRgcu1cT5wZEHDD .icon-shape,#mermaid-svg-5XRgcu1cT5wZEHDD .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-5XRgcu1cT5wZEHDD .icon-shape p,#mermaid-svg-5XRgcu1cT5wZEHDD .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-5XRgcu1cT5wZEHDD .icon-shape .label rect,#mermaid-svg-5XRgcu1cT5wZEHDD .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-5XRgcu1cT5wZEHDD .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-5XRgcu1cT5wZEHDD .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-5XRgcu1cT5wZEHDD :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    0.x \u65f6\u4ee32022-2025\u5305\u7f57\u4e07\u8c61\u7684 chain \u52a8\u7269\u56ed<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    2025-10-22LangChain 1.0 GA\u5927\u5e45\u6536\u7f29 + \u7a33\u5b9a\u627f\u8bfa<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u4e3b\u5305\u53ea\u7559\u56db\u4ef6\u4e8bagents \/ models \/ messages \/ tools<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u5176\u4f59\u5168\u90e8\u642c\u5230langchain-classic<\/p>\n

    <\/span><\/p>\n

    \u4e24\u4ef6\u4e8b\u6bd4\u7248\u672c\u53f7\u91cd\u8981\u5f97\u591a：<\/p>\n

    \u2460 \u8303\u56f4\u6536\u7f29（Scope Cut） langchain \u4e3b\u5305\u4e0d\u518d\u5c1d\u8bd5\u5bb9\u7eb3\u8fc7\u53bb\u4e09\u5e74\u6240\u6709\u7684 chain \u6a21\u5f0f，\u53ea\u4fdd\u7559\u56db\u4ef6\u4e8b：agents\u3001models\u3001messages\u3001tools\u3002\u6240\u6709\u65e7\u4e1c\u897f\u2014\u2014LLMChain\u3001\u5404\u79cd pre-built chains\u3001AgentExecutor\u2014\u2014\u642c\u5230\u4e86\u4e00\u4e2a\u5b57\u9762\u5c31\u53eb classic \u7684\u5305\u91cc：<\/p>\n

    # \u65e7\u4ee3\u7801\u7684\u65b0\u5730\u5740<\/span>
    \nfrom<\/span> langchain_classic.<\/span>chains import<\/span> LLMChain<\/p>\n

    \u8fd9\u4e2a\u547d\u540d\u5f88\u8bda\u5b9e：\u6846\u67b6\u5728\u544a\u8bc9\u4f60，\u8fd9\u662f\u535a\u7269\u9986\u5c55\u533a\u3002<\/p>\n

    \u2461 \u7a33\u5b9a\u6027\u627f\u8bfa（Stability Promise） 1.0 \u627f\u8bfa \u5728 2.0 \u4e4b\u524d\u4e0d\u505a\u7834\u574f\u6027\u53d8\u66f4\u3002\u542c\u8d77\u6765\u5f88\u65e0\u804a，\u4f46\u5bf9\u4e00\u4e2a\u300c\u6bcf\u9694\u51e0\u4e2a\u6708\u5c31\u641e\u5d29\u4e00\u6b21\u6559\u7a0b\u300d\u7684\u5e93\u6765\u8bf4，\u8fd9\u53ef\u80fd\u662f\u8fd9\u6b21\u53d1\u5e03\u91cc\u6700\u5927\u7684\u529f\u80fd\u3002<\/p>\n

    2.2 \u4e3a\u4ec0\u4e48\u6536\u7f29：2023 \u7684\u95ee\u9898\u548c 2026 \u7684\u95ee\u9898\u4e0d\u4e00\u6837<\/h4>\n\n\u5e74\u4efd\u90a3\u65f6\u7684\u95ee\u9898\u90a3\u65f6\u7684\u7b54\u6848<\/tr>\n\n\n\n
    2023<\/td>\n\u300c\u6211\u600e\u4e48\u628a\u63d0\u793a\u8bcd\u62fc\u8d77\u6765？\u300d<\/td>\nChains<\/td>\n<\/tr>\n
    2026<\/td>\n\u300c\u6211\u600e\u4e48\u8ba9\u6a21\u578b\u5728\u5de5\u5177\u5faa\u73af\u91cc\u5b89\u5168\u5730\u8dd1\u8d77\u6765？\u300d<\/td>\nAgents<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Agents \u8d62\u4e86，\u5305\u7ed3\u6784\u73b0\u5728\u76f4\u63a5\u627f\u8ba4\u4e86\u8fd9\u4e00\u70b9\u3002<\/p>\n

    2.3 \u65b0\u65e7\u5bf9\u7167\u8868（\u901f\u67e5）<\/h4>\n\n\u4f60\u60f3\u505a\u4ec0\u4e48\u8001\u5199\u6cd5（0.x）\u65b0\u5199\u6cd5（1.x）<\/tr>\n\n\n\n\n\n\n\n\n\n
    \u8c03\u7528\u6a21\u578b<\/td>\nChatOpenAI(…)<\/td>\ninit_chat_model("openai:gpt-5.5")<\/td>\n<\/tr>\n
    \u62fc\u63d0\u793a + \u8c03\u7528<\/td>\nLLMChain(llm=…, prompt=…)<\/td>\nprompt | model | parser<\/td>\n<\/tr>\n
    \u6784\u5efa Agent<\/td>\ninitialize_agent(…) \/ AgentExecutor<\/td>\ncreate_agent(…)<\/td>\n<\/tr>\n
    ReAct Agent<\/td>\nlanggraph.prebuilt.create_react_agent<\/td>\n\u5df2\u5f03\u7528 \u2192 create_agent<\/td>\n<\/tr>\n
    \u52a0\u8bb0\u5fc6<\/td>\nConversationChain \/ ConversationBufferMemory<\/td>\ncheckpointer \/ RunnableWithMessageHistory<\/td>\n<\/tr>\n
    \u65e7 chain \u5bfc\u5165<\/td>\nfrom langchain.chains import …<\/td>\nfrom langchain_classic.chains import …<\/td>\n<\/tr>\n
    \u6587\u672c\u5207\u5206<\/td>\nfrom langchain.text_splitter import …<\/td>\nfrom langchain_text_splitters import …<\/td>\n<\/tr>\n
    Chroma<\/td>\nfrom langchain_community.vectorstores import Chroma<\/td>\nfrom langchain_chroma import Chroma<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n

    \u4e09\u3001\u751f\u6001\u5168\u666f：\u4e00\u5f20\u56fe\u770b\u61c2\u4e03\u4e2a\u5305\u7684\u5206\u5de5<\/h3>\n

    \u8fd9\u662f\u7406\u89e3 LangChain \u6700\u5bb9\u6613\u88ab\u7ed5\u6655\u7684\u5730\u65b9\u2014\u2014\u5b83\u4e0d\u662f\u4e00\u4e2a\u5305，\u662f\u4e00\u65cf\u5305\u3002<\/p>\n

    #mermaid-svg-29xA3rNaDeSTS5OD{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-29xA3rNaDeSTS5OD .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-29xA3rNaDeSTS5OD .error-icon{fill:#552222;}#mermaid-svg-29xA3rNaDeSTS5OD .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-29xA3rNaDeSTS5OD .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-29xA3rNaDeSTS5OD .marker{fill:#333333;stroke:#333333;}#mermaid-svg-29xA3rNaDeSTS5OD .marker.cross{stroke:#333333;}#mermaid-svg-29xA3rNaDeSTS5OD svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-29xA3rNaDeSTS5OD p{margin:0;}#mermaid-svg-29xA3rNaDeSTS5OD .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-29xA3rNaDeSTS5OD .cluster-label text{fill:#333;}#mermaid-svg-29xA3rNaDeSTS5OD .cluster-label span{color:#333;}#mermaid-svg-29xA3rNaDeSTS5OD .cluster-label span p{background-color:transparent;}#mermaid-svg-29xA3rNaDeSTS5OD .label text,#mermaid-svg-29xA3rNaDeSTS5OD span{fill:#333;color:#333;}#mermaid-svg-29xA3rNaDeSTS5OD .node rect,#mermaid-svg-29xA3rNaDeSTS5OD .node circle,#mermaid-svg-29xA3rNaDeSTS5OD .node ellipse,#mermaid-svg-29xA3rNaDeSTS5OD .node polygon,#mermaid-svg-29xA3rNaDeSTS5OD .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-29xA3rNaDeSTS5OD .rough-node .label text,#mermaid-svg-29xA3rNaDeSTS5OD .node .label text,#mermaid-svg-29xA3rNaDeSTS5OD .image-shape .label,#mermaid-svg-29xA3rNaDeSTS5OD .icon-shape .label{text-anchor:middle;}#mermaid-svg-29xA3rNaDeSTS5OD .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-29xA3rNaDeSTS5OD .rough-node .label,#mermaid-svg-29xA3rNaDeSTS5OD .node .label,#mermaid-svg-29xA3rNaDeSTS5OD .image-shape .label,#mermaid-svg-29xA3rNaDeSTS5OD .icon-shape .label{text-align:center;}#mermaid-svg-29xA3rNaDeSTS5OD .node.clickable{cursor:pointer;}#mermaid-svg-29xA3rNaDeSTS5OD .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-29xA3rNaDeSTS5OD .arrowheadPath{fill:#333333;}#mermaid-svg-29xA3rNaDeSTS5OD .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-29xA3rNaDeSTS5OD .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-29xA3rNaDeSTS5OD .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-29xA3rNaDeSTS5OD .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-29xA3rNaDeSTS5OD .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-29xA3rNaDeSTS5OD .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-29xA3rNaDeSTS5OD .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-29xA3rNaDeSTS5OD .cluster text{fill:#333;}#mermaid-svg-29xA3rNaDeSTS5OD .cluster span{color:#333;}#mermaid-svg-29xA3rNaDeSTS5OD div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-29xA3rNaDeSTS5OD .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-29xA3rNaDeSTS5OD rect.text{fill:none;stroke-width:0;}#mermaid-svg-29xA3rNaDeSTS5OD .icon-shape,#mermaid-svg-29xA3rNaDeSTS5OD .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-29xA3rNaDeSTS5OD .icon-shape p,#mermaid-svg-29xA3rNaDeSTS5OD .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-29xA3rNaDeSTS5OD .icon-shape .label rect,#mermaid-svg-29xA3rNaDeSTS5OD .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-29xA3rNaDeSTS5OD .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-29xA3rNaDeSTS5OD .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-29xA3rNaDeSTS5OD :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

    <\/p>\n

    \u65c1\u8def<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u5e95\u5ea7<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u96c6\u6210\u5c42（\u6309\u9700\u5b89\u88c5）<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u9ad8\u5c42（\u5f00\u7bb1\u5373\u7528）<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u4f60\u7684\u5e94\u7528<\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u4e1a\u52a1\u4ee3\u7801<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchaincreate_agent + models + messages + tools<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langgraphStateGraph \/ \u7f16\u6392 \/ \u8fd0\u884c\u65f6<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-openai<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-anthropic<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-deepseek<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-ollama<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-chroma \/ -postgres \/ -milvus …<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-coreRunnable \/ LCEL \/ MessagePrompt \/ OutputParser \/ \u62bd\u8c61\u63a5\u53e3<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    langchain-classic\u65e7\u7684 chains（\u535a\u7269\u9986）<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    LangSmith\u53ef\u89c2\u6d4b\u6027 \/ \u8bc4\u6d4b（\u5546\u4e1a）<\/p>\n

    <\/span><\/p>\n\n\u5305\u540d\u4f5c\u7528\u4ec0\u4e48\u65f6\u5019\u88c5<\/tr>\n\n\n\n\n\n\n\n\n\n
    langchain-core<\/td>\n\u5e95\u5ea7\u3002Runnable \u534f\u8bae\u3001LCEL\u3001\u6d88\u606f\u7c7b\u578b\u3001\u63d0\u793a\u8bcd\u6a21\u677f\u3001\u8f93\u51fa\u89e3\u6790\u5668\u3001\u62bd\u8c61\u63a5\u53e3<\/td>\n\u88ab\u4f9d\u8d56，\u81ea\u52a8\u88c5<\/td>\n<\/tr>\n
    langchain<\/td>\n\u4e3b\u5305\u3002create_agent\u3001\u6a21\u578b\/\u6d88\u606f\/\u5de5\u5177\u7684\u6838\u5fc3\u6784\u5efa\u6a21\u5757<\/td>\n\u505a Agent \u5c31\u88c5<\/td>\n<\/tr>\n
    langgraph<\/td>\n\u7f16\u6392\u6846\u67b6\u4e0e\u8fd0\u884c\u65f6\u3002\u72b6\u6001\u56fe\u3001\u6301\u4e45\u5316\u3001\u6d41\u5f0f\u3001\u4eba\u5de5\u5e72\u9884<\/td>\n\u9700\u8981\u590d\u6742\u6d41\u7a0b\u65f6<\/td>\n<\/tr>\n
    langchain-<provider><\/td>\n\u96c6\u6210\u5305\u3002\u5404\u6a21\u578b\/\u5411\u91cf\u5e93\u7684\u5177\u4f53\u5b9e\u73b0<\/td>\n\u7528\u5230\u54ea\u4e2a\u88c5\u54ea\u4e2a<\/td>\n<\/tr>\n
    langchain-classic<\/td>\n\u65e7\u7248\u9057\u7559\u3002LLMChain \u7b49<\/td>\n\u53ea\u5728\u7ef4\u62a4\u8001\u9879\u76ee\u65f6\u88c5<\/td>\n<\/tr>\n
    langchain-text-splitters<\/td>\n\u6587\u672c\u5207\u5206\u5668<\/td>\n\u505a RAG \u65f6\u88c5<\/td>\n<\/tr>\n
    langchain-community<\/td>\n\u793e\u533a\u96c6\u6210（\u5927\u91cf\u6587\u6863\u52a0\u8f7d\u5668\u7b49）<\/td>\n\u6309\u9700<\/td>\n<\/tr>\n
    LangSmith<\/td>\n\u8ffd\u8e2a \/ \u8bc4\u6d4b \/ \u63d0\u793a\u8bcd\u7ba1\u7406<\/td>\n\u53ef\u9009，\u5546\u4e1a\u670d\u52a1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    💡 \u5173\u952e\u7406\u89e3：create_agent \u5e95\u5c42\u8dd1\u5728 LangGraph \u4e0a\u3002 \u8fd9\u610f\u5473\u7740\u4f60\u4e0d\u9700\u8981\u4f1a LangGraph，\u5c31\u80fd\u767d\u62ff\u5b83\u7684：\u6301\u4e45\u5316\u3001\u6d41\u5f0f\u5904\u7406\u3001\u4eba\u5de5\u5e72\u9884\u3001\u65f6\u95f4\u65c5\u884c\u3002 \u8fd9\u4e5f\u89e3\u91ca\u4e86\u4e3a\u4ec0\u4e48 langgraph \u4f1a\u51fa\u73b0\u5728\u4f9d\u8d56\u91cc\u2014\u2014\u9ad8\u5c42 API \u7684\u6536\u76ca，\u6765\u81ea\u5e95\u5c42\u8fd0\u884c\u65f6\u7684\u80fd\u529b\u3002<\/p>\n

    3.1 \u5b98\u65b9\u63a8\u8350\u7684\u300c\u5206\u5c42\u4f7f\u7528\u300d\u8def\u5f84<\/h4>\n

    \u5b98\u65b9\u660e\u786e\u8bf4\u8fc7：\u5148\u7528\u9ad8\u5c42 API，\u9700\u8981\u65f6\u518d\u4e0b\u6c89\u2014\u2014\u8fd9\u4e0d\u662f\u6743\u5b9c\u4e4b\u8ba1，\u8fd9\u662f\u8bbe\u8ba1\u610f\u56fe\u3002<\/p>\n

    #mermaid-svg-bcX5mh4ECX7ZMoBk{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-bcX5mh4ECX7ZMoBk .error-icon{fill:#552222;}#mermaid-svg-bcX5mh4ECX7ZMoBk .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-bcX5mh4ECX7ZMoBk .marker{fill:#333333;stroke:#333333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .marker.cross{stroke:#333333;}#mermaid-svg-bcX5mh4ECX7ZMoBk svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-bcX5mh4ECX7ZMoBk p{margin:0;}#mermaid-svg-bcX5mh4ECX7ZMoBk .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .cluster-label text{fill:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .cluster-label span{color:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .cluster-label span p{background-color:transparent;}#mermaid-svg-bcX5mh4ECX7ZMoBk .label text,#mermaid-svg-bcX5mh4ECX7ZMoBk span{fill:#333;color:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .node rect,#mermaid-svg-bcX5mh4ECX7ZMoBk .node circle,#mermaid-svg-bcX5mh4ECX7ZMoBk .node ellipse,#mermaid-svg-bcX5mh4ECX7ZMoBk .node polygon,#mermaid-svg-bcX5mh4ECX7ZMoBk .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .rough-node .label text,#mermaid-svg-bcX5mh4ECX7ZMoBk .node .label text,#mermaid-svg-bcX5mh4ECX7ZMoBk .image-shape .label,#mermaid-svg-bcX5mh4ECX7ZMoBk .icon-shape .label{text-anchor:middle;}#mermaid-svg-bcX5mh4ECX7ZMoBk .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .rough-node .label,#mermaid-svg-bcX5mh4ECX7ZMoBk .node .label,#mermaid-svg-bcX5mh4ECX7ZMoBk .image-shape .label,#mermaid-svg-bcX5mh4ECX7ZMoBk .icon-shape .label{text-align:center;}#mermaid-svg-bcX5mh4ECX7ZMoBk .node.clickable{cursor:pointer;}#mermaid-svg-bcX5mh4ECX7ZMoBk .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .arrowheadPath{fill:#333333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-bcX5mh4ECX7ZMoBk .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-bcX5mh4ECX7ZMoBk .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-bcX5mh4ECX7ZMoBk .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-bcX5mh4ECX7ZMoBk .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .cluster text{fill:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk .cluster span{color:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-bcX5mh4ECX7ZMoBk .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-bcX5mh4ECX7ZMoBk rect.text{fill:none;stroke-width:0;}#mermaid-svg-bcX5mh4ECX7ZMoBk .icon-shape,#mermaid-svg-bcX5mh4ECX7ZMoBk .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-bcX5mh4ECX7ZMoBk .icon-shape p,#mermaid-svg-bcX5mh4ECX7ZMoBk .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-bcX5mh4ECX7ZMoBk .icon-shape .label rect,#mermaid-svg-bcX5mh4ECX7ZMoBk .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-bcX5mh4ECX7ZMoBk .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-bcX5mh4ECX7ZMoBk .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-bcX5mh4ECX7ZMoBk :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u7b2c\u4e00\u6b65create_agent（10 \u884c\u8dd1\u901a）<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u7b2c\u4e8c\u6b65\u52a0 middleware（\u6cbb\u7406\/\u5ba1\u6279\/\u6458\u8981）<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u7b2c\u4e09\u6b65\u663e\u5f0f LangGraph \u56fe（\u81ea\u5b9a\u4e49\u72b6\u6001\u8f6c\u79fb\/\u957f\u65f6\u4efb\u52a1）<\/p>\n

    <\/span><\/p>\n

    \n

    \u56db\u3001\u6838\u5fc3\u6982\u5ff5：\u56db\u4e2a\u8bcd\u5403\u900f LangChain<\/h3>\n

    4.1 Model（\u6a21\u578b）：\u7528\u5b57\u7b26\u4e32\u63cf\u8ff0\u6a21\u578b<\/h4>\n

    1.0 \u6700\u91cd\u8981\u7684\u4fbf\u5229\u4e4b\u4e00：\u7528 provider:model \u5b57\u7b26\u4e32\u6307\u5b9a\u6a21\u578b\u3002<\/p>\n

    from<\/span> langchain.<\/span>chat_models import<\/span> init_chat_model<\/p>\n

    model =<\/span> init_chat_model(<\/span>"openai:gpt-5.5"<\/span>,<\/span> temperature=<\/span>0.5<\/span>)<\/span>
    \n# \u6362 Claude \u5c31\u6539\u8fd9\u4e00\u884c<\/span>
    \nmodel =<\/span> init_chat_model(<\/span>"anthropic:claude-sonnet-4-6"<\/span>)<\/span>
    \n# \u6362 DeepSeek（\u56fd\u5185\u5e38\u7528）<\/span>
    \nmodel =<\/span> init_chat_model(<\/span>"deepseek:deepseek-chat"<\/span>)<\/span>
    \n# \u6362\u672c\u5730 Ollama<\/span>
    \nmodel =<\/span> init_chat_model(<\/span>"ollama:llama3.1"<\/span>)<\/span><\/p>\n

    \u8fd9\u4e2a\u8bbe\u8ba1\u6700\u5b9e\u9645\u7684\u597d\u5904：\u62ff\u672c\u5730\u5c0f\u6a21\u578b\u8bd5\u4f60\u7684 Agent，\u53ea\u9700\u8981\u6539\u4e00\u884c\u5b57\u7b26\u4e32\u3002<\/p>\n

    4.2 Message（\u6d88\u606f）：\u7edf\u4e00\u7684\u5bf9\u8bdd\u8f7d\u4f53<\/h4>\n

    \u6240\u6709\u6a21\u578b\u4ea4\u4e92\u90fd\u5f52\u7ed3\u4e3a\u6d88\u606f\u5217\u8868\u30021.0 \u65b0\u589e\u7684 content_blocks \u5c5e\u6027\u662f\u5173\u952e\u6539\u8fdb\u2014\u2014\u8de8\u4f9b\u5e94\u5546\u7edf\u4e00\u8bfb\u53d6\u63a8\u7406\u8fc7\u7a0b\u3001\u5f15\u7528\u3001\u5de5\u5177\u8c03\u7528：<\/p>\n

    response =<\/span> model.<\/span>invoke(<\/span>"\u6cd5\u56fd\u9996\u90fd\u662f\u4ec0\u4e48？"<\/span>)<\/span><\/p>\n

    for<\/span> block in<\/span> response.<\/span>content_blocks:<\/span>
    \n if<\/span> block[<\/span>"type"<\/span>]<\/span> ==<\/span> "reasoning"<\/span>:<\/span>
    \n print<\/span>(<\/span>"\u6a21\u578b\u63a8\u7406:"<\/span>,<\/span> block[<\/span>"reasoning"<\/span>]<\/span>)<\/span>
    \n elif<\/span> block[<\/span>"type"<\/span>]<\/span> ==<\/span> "text"<\/span>:<\/span>
    \n print<\/span>(<\/span>"\u56de\u7b54:"<\/span>,<\/span> block[<\/span>"text"<\/span>]<\/span>)<\/span>
    \n elif<\/span> block[<\/span>"type"<\/span>]<\/span> ==<\/span> "tool_call"<\/span>:<\/span>
    \n print<\/span>(<\/span>"\u5de5\u5177\u8c03\u7528:"<\/span>,<\/span> block[<\/span>"name"<\/span>]<\/span>,<\/span> block[<\/span>"args"<\/span>]<\/span>)<\/span><\/p>\n

    \u26a0\ufe0f \u76ee\u524d content_blocks \u652f\u6301\u8fd9\u4e9b\u96c6\u6210：langchain-anthropic\u3001langchain-aws\u3001langchain-openai\u3001langchain-google-genai\u3001langchain-ollama\u3002<\/p>\n

    4.3 Tool（\u5de5\u5177）：\u4e00\u4e2a\u88c5\u9970\u5668\u5c31\u591f\u4e86<\/h4>\n

    \u5728 LangChain \u91cc，\u5de5\u5177\u5c31\u662f\u300c\u4e00\u4e2a\u5e26\u597d\u7684 docstring \u7684\u666e\u901a Python \u51fd\u6570\u300d\u3002<\/p>\n

    from<\/span> langchain.<\/span>tools import<\/span> tool<\/p>\n

    @tool<\/span>
    \ndef<\/span> get_weather<\/span>(<\/span>city:<\/span> str<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
    \n """Get weather for a given city."""<\/span>
    \n return<\/span> f"It's always sunny in <\/span>{<\/span>city}<\/span><\/span>!"<\/span><\/span><\/p>\n

    🎯 \u4e3a\u4ec0\u4e48 docstring \u8fd9\u4e48\u91cd\u8981？ \u5b98\u65b9\u6587\u6863\u5199\u5f97\u5f88\u76f4\u767d：\u5de5\u5177\u7684\u540d\u5b57\u3001\u63cf\u8ff0\u3001\u53c2\u6570\u540d，\u4f1a\u76f4\u63a5\u53d8\u6210\u6a21\u578b\u63d0\u793a\u8bcd\u7684\u4e00\u90e8\u5206\u3002 \u4e5f\u5c31\u662f\u8bf4\u2014\u2014\u4f60\u5199\u7ed9\u6a21\u578b\u7684\u300c\u8bf4\u660e\u4e66\u300d\u8d28\u91cf，\u51b3\u5b9a\u4e86\u5b83\u4f1a\u4e0d\u4f1a\u6b63\u786e\u8c03\u7528\u8fd9\u4e2a\u5de5\u5177\u3002 \u8fd9\u4e0d\u662f\u6ce8\u91ca，\u8fd9\u662f prompt\u3002<\/p>\n

    4.4 Agent（\u667a\u80fd\u4f53）：\u4e00\u4e2a\u5faa\u73af<\/h4>\n

    create_agent \u7684\u5185\u90e8\u5176\u5b9e\u975e\u5e38\u7b80\u5355，\u5c31\u4e00\u4e2a\u5faa\u73af：<\/p>\n

    #mermaid-svg-mydZxusiuwXXafg5{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-mydZxusiuwXXafg5 .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-mydZxusiuwXXafg5 .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-mydZxusiuwXXafg5 .error-icon{fill:#552222;}#mermaid-svg-mydZxusiuwXXafg5 .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-mydZxusiuwXXafg5 .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-mydZxusiuwXXafg5 .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-mydZxusiuwXXafg5 .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-mydZxusiuwXXafg5 .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-mydZxusiuwXXafg5 .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-mydZxusiuwXXafg5 .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-mydZxusiuwXXafg5 .marker{fill:#333333;stroke:#333333;}#mermaid-svg-mydZxusiuwXXafg5 .marker.cross{stroke:#333333;}#mermaid-svg-mydZxusiuwXXafg5 svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-mydZxusiuwXXafg5 p{margin:0;}#mermaid-svg-mydZxusiuwXXafg5 .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-mydZxusiuwXXafg5 .cluster-label text{fill:#333;}#mermaid-svg-mydZxusiuwXXafg5 .cluster-label span{color:#333;}#mermaid-svg-mydZxusiuwXXafg5 .cluster-label span p{background-color:transparent;}#mermaid-svg-mydZxusiuwXXafg5 .label text,#mermaid-svg-mydZxusiuwXXafg5 span{fill:#333;color:#333;}#mermaid-svg-mydZxusiuwXXafg5 .node rect,#mermaid-svg-mydZxusiuwXXafg5 .node circle,#mermaid-svg-mydZxusiuwXXafg5 .node ellipse,#mermaid-svg-mydZxusiuwXXafg5 .node polygon,#mermaid-svg-mydZxusiuwXXafg5 .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-mydZxusiuwXXafg5 .rough-node .label text,#mermaid-svg-mydZxusiuwXXafg5 .node .label text,#mermaid-svg-mydZxusiuwXXafg5 .image-shape .label,#mermaid-svg-mydZxusiuwXXafg5 .icon-shape .label{text-anchor:middle;}#mermaid-svg-mydZxusiuwXXafg5 .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-mydZxusiuwXXafg5 .rough-node .label,#mermaid-svg-mydZxusiuwXXafg5 .node .label,#mermaid-svg-mydZxusiuwXXafg5 .image-shape .label,#mermaid-svg-mydZxusiuwXXafg5 .icon-shape .label{text-align:center;}#mermaid-svg-mydZxusiuwXXafg5 .node.clickable{cursor:pointer;}#mermaid-svg-mydZxusiuwXXafg5 .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-mydZxusiuwXXafg5 .arrowheadPath{fill:#333333;}#mermaid-svg-mydZxusiuwXXafg5 .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-mydZxusiuwXXafg5 .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-mydZxusiuwXXafg5 .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-mydZxusiuwXXafg5 .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-mydZxusiuwXXafg5 .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-mydZxusiuwXXafg5 .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-mydZxusiuwXXafg5 .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-mydZxusiuwXXafg5 .cluster text{fill:#333;}#mermaid-svg-mydZxusiuwXXafg5 .cluster span{color:#333;}#mermaid-svg-mydZxusiuwXXafg5 div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-mydZxusiuwXXafg5 .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-mydZxusiuwXXafg5 rect.text{fill:none;stroke-width:0;}#mermaid-svg-mydZxusiuwXXafg5 .icon-shape,#mermaid-svg-mydZxusiuwXXafg5 .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-mydZxusiuwXXafg5 .icon-shape p,#mermaid-svg-mydZxusiuwXXafg5 .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-mydZxusiuwXXafg5 .icon-shape .label rect,#mermaid-svg-mydZxusiuwXXafg5 .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-mydZxusiuwXXafg5 .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-mydZxusiuwXXafg5 .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-mydZxusiuwXXafg5 :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u6709<\/p>\n

    <\/span><\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u6ca1\u6709<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u7528\u6237\u6d88\u606f<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u8c03\u7528\u6a21\u578b<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u6a21\u578b\u8f93\u51fa\u6709\u5de5\u5177\u8c03\u7528\u5417？<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u6267\u884c\u5de5\u5177\u7ed3\u679c\u4f5c\u4e3a tool message \u8ffd\u52a0<\/p>\n

    <\/span><\/p>\n

    <\/p>\n

    \u8f93\u51fa\u6700\u7ec8\u56de\u7b54<\/p>\n

    <\/span><\/p>\n

    \u5c31\u8fd9\u6837\u3002 \u6ca1\u6709\u9b54\u6cd5\u3002\u6240\u8c13\u300cAgent\u300d，\u672c\u8d28\u5c31\u662f**\u300c\u6a21\u578b\u81ea\u5df1\u51b3\u5b9a\u4e0b\u4e00\u6b65\u505a\u4ec0\u4e48\u300d\u7684 while \u5faa\u73af**\u3002<\/p>\n

    \n

    \u4e94\u3001\u5b89\u88c5\u4e0e\u73af\u5883\u51c6\u5907<\/h3>\n

    5.1 \u5b89\u88c5<\/h4>\n

    # \u63a8\u8350\u7528 uv（\u5b98\u65b9\u63a8\u8350）<\/span>
    \nuv python pin 3.11<\/span>
    \nuv add<\/span> langchain<\/p>\n

    # \u6216\u8005\u7528 pip<\/span>
    \npip install<\/span> -U<\/span> langchain<\/p>\n

    \u6309\u9700\u5b89\u88c5\u96c6\u6210\u5305：<\/p>\n

    # \u56fd\u5185\u5e38\u7528：DeepSeek（\u6027\u4ef7\u6bd4\u9ad8\u3001\u4e2d\u6587\u5f3a\u3001\u517c\u5bb9 OpenAI \u63a5\u53e3）<\/span>
    \npip install<\/span> langchain-deepseek<\/p>\n

    # \u5e38\u89c1\u7ec4\u5408<\/span>
    \npip install<\/span> langchain-openai # OpenAI<\/span>
    \npip install<\/span> langchain-anthropic # Claude<\/span>
    \npip install<\/span> langchain-ollama # \u672c\u5730\u6a21\u578b<\/span>
    \npip install<\/span> langchain-chroma # Chroma \u5411\u91cf\u5e93<\/span>
    \npip install<\/span> langchain-text-splitters # \u6587\u672c\u5207\u5206\u5668（RAG \u7528）<\/span><\/p>\n

    \u6ce8\u610f langchain \u81ea\u5e26\u4e00\u5806\u53ef\u9009\u4f9d\u8d56\u7ec4（PyPI \u4e0a\u5217\u51fa\u7684 extras）： anthropic\u3001aws\u3001azure-ai\u3001baseten\u3001community\u3001deepseek\u3001fireworks\u3001google-genai\u3001google-vertexai\u3001groq\u3001huggingface\u3001mcp\u3001meta\u3001mistralai\u3001ollama\u3001openai\u3001perplexity\u3001together\u3001xai<\/p>\n

    \u6240\u4ee5\u4f60\u4e5f\u53ef\u4ee5\u8fd9\u6837\u88c5：<\/p>\n

    pip install<\/span> "langchain[openai,deepseek]"<\/span><\/p>\n

    5.2 \u914d\u7f6e API Key<\/h4>\n

    \u6c38\u8fdc\u4e0d\u8981\u628a Key \u5199\u6b7b\u5728\u4ee3\u7801\u91cc\u3002 \u7528\u4e00\u4e2a .env \u6587\u4ef6：<\/p>\n

    # .env<\/span>
    \nDEEPSEEK_API_KEY<\/span>=<\/span>sk-your-key-here
    \n# OPENAI_API_KEY=sk-…<\/span>
    \n# ANTHROPIC_API_KEY=sk-…<\/span><\/p>\n

    from<\/span> dotenv import<\/span> load_dotenv
    \nload_dotenv(<\/span>)<\/span> # \u81ea\u52a8\u8bfb\u53d6 .env \u4e2d\u7684\u73af\u5883\u53d8\u91cf<\/span><\/p>\n

    SDK \u4f1a\u81ea\u52a8\u4ece\u73af\u5883\u53d8\u91cf\u8bfb\u53d6\u5bf9\u5e94\u7684 Key\u2014\u2014ChatDeepSeek \u4f1a\u81ea\u52a8\u8bfb DEEPSEEK_API_KEY，\u5e76\u81ea\u52a8\u4f7f\u7528 api.deepseek.com \u4f5c\u4e3a base_url，\u4e0d\u9700\u8981\u4f60\u624b\u5199 base_url\u3002<\/p>\n

    5.3 \u56fd\u5185\u5f00\u53d1\u8005\u7684\u63a8\u8350\u914d\u7f6e<\/h4>\n\n\u9879\u5efa\u8bae<\/tr>\n\n\n\n\n\n\n
    \u6a21\u578b<\/td>\nDeepSeek（\u4fbf\u5b9c + \u4e2d\u6587\u5f3a + \u517c\u5bb9 OpenAI \u534f\u8bae）<\/td>\n<\/tr>\n
    \u52a0\u8f7d\u5668\/\u5411\u91cf\u5e93<\/td>\nChroma（\u672c\u5730\u3001\u96f6\u90e8\u7f72）\u6216 pgvector（\u5df2\u6709 PostgreSQL \u7684\u8bdd）<\/td>\n<\/tr>\n
    Embedding<\/td>\n\u4f18\u5148\u56fd\u5185\u5382\u5546\u7684 embedding \u63a5\u53e3；\u672c\u5730\u53ef\u7528 Ollama + nomic-embed-text<\/td>\n<\/tr>\n
    \u7f51\u7edc<\/td>\n\u82e5\u76f4\u8fde\u4e0d\u7a33，\u8003\u8651\u56fd\u5185\u4e91\u5382\u5546\u7684 OpenAI \u517c\u5bb9\u7aef\u70b9<\/td>\n<\/tr>\n
    LangSmith<\/td>\n\u6d77\u5916\u670d\u52a1，\u8de8\u5883\u6570\u636e\u4f20\u8f93\u9700\u81ea\u884c\u8bc4\u4f30\u5408\u89c4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n

    \u516d\u3001\u7b2c\u4e00\u4e2a Agent：10 \u884c\u4ee3\u7801\u8dd1\u901a<\/h3>\n

    \u8fd9\u662f\u5b98\u65b9 quickstart \u7684\u5f62\u72b6，\u5f53\u524d\u63a5\u53e3\u4e0b\u8fd9\u5c31\u662f\u5b8c\u6574\u53ef\u8dd1\u7684\u4ee3\u7801：<\/p>\n

    from<\/span> langchain.<\/span>agents import<\/span> create_agent<\/p>\n

    def<\/span> get_weather<\/span>(<\/span>city:<\/span> str<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
    \n """Get weather for a given city."""<\/span>
    \n return<\/span> f"It's always sunny in <\/span>{<\/span>city}<\/span><\/span>!"<\/span><\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n model=<\/span>"openai:gpt-5.5"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>get_weather]<\/span>,<\/span>
    \n system_prompt=<\/span>"You are a helpful assistant"<\/span>,<\/span>
    \n)<\/span><\/p>\n

    result =<\/span> agent.<\/span>invoke(<\/span>
    \n {<\/span>"messages"<\/span>:<\/span> [<\/span>{<\/span>"role"<\/span>:<\/span> "user"<\/span>,<\/span> "content"<\/span>:<\/span> "What's the weather in San Francisco?"<\/span>}<\/span>]<\/span>}<\/span>
    \n)<\/span>
    \nprint<\/span>(<\/span>result[<\/span>"messages"<\/span>]<\/span>[<\/span>–<\/span>1<\/span>]<\/span>.<\/span>content_blocks)<\/span><\/p>\n

    \u8dd1\u4e4b\u524d\u6709\u4e00\u4ef6\u4ee3\u7801\u672c\u8eab\u4e0d\u4f1a\u63d0\u9192\u4f60\u7684\u4e8b：\u5148\u5bfc\u51fa\u4f60\u6240\u7528\u4f9b\u5e94\u5546\u7684 API Key（OPENAI_API_KEY \/ ANTHROPIC_API_KEY \/ DEEPSEEK_API_KEY\u2026\u2026），\u5426\u5219 Agent \u6ca1\u6709\u51ed\u636e\u53ef\u7528\u3002<\/p>\n

    create_agent \u5c31\u662f\u5168\u90e8\u3002 \u4f60\u4ea4\u7ed9\u5b83\u4e09\u6837\u4e1c\u897f：<\/p>\n\n\u53c2\u6570\u8bf4\u660e<\/tr>\n\n\n\n\n
    model<\/td>\n\u300c\u4f9b\u5e94\u5546:\u6a21\u578b\u540d\u300d\u5b57\u7b26\u4e32，\u6216\u4e00\u4e2a\u6a21\u578b\u5bf9\u8c61<\/td>\n<\/tr>\n
    tools<\/td>\n\u4e00\u4e32\u666e\u901a Python \u51fd\u6570（\u53ef\u4ee5\u662f\u88f8\u51fd\u6570，\u4e5f\u53ef\u4ee5\u662f @tool \u5305\u88c5\u7684）<\/td>\n<\/tr>\n
    system_prompt<\/td>\n\u7cfb\u7edf\u63d0\u793a\u8bcd<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u6362\u6210 DeepSeek \u7248\u672c（\u56fd\u5185\u8bfb\u8005\u53ef\u76f4\u63a5\u7528）：<\/p>\n

    from<\/span> dotenv import<\/span> load_dotenv
    \nfrom<\/span> langchain.<\/span>agents import<\/span> create_agent<\/p>\n

    load_dotenv(<\/span>)<\/span><\/p>\n

    def<\/span> get_weather<\/span>(<\/span>city:<\/span> str<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
    \n """\u67e5\u8be2\u6307\u5b9a\u57ce\u5e02\u7684\u5929\u6c14\u3002"""<\/span>
    \n return<\/span> f"<\/span>{<\/span>city}<\/span><\/span> \u4eca\u5929\u6674，25\u2103\u3002"<\/span><\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n model=<\/span>"deepseek:deepseek-chat"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>get_weather]<\/span>,<\/span>
    \n system_prompt=<\/span>"\u4f60\u662f\u4e00\u4e2a\u4e50\u4e8e\u52a9\u4eba\u7684\u4e2d\u6587\u52a9\u624b\u3002"<\/span>,<\/span>
    \n)<\/span><\/p>\n

    result =<\/span> agent.<\/span>invoke(<\/span>{<\/span>"messages"<\/span>:<\/span> [<\/span>{<\/span>"role"<\/span>:<\/span> "user"<\/span>,<\/span> "content"<\/span>:<\/span> "\u5317\u4eac\u5929\u6c14\u600e\u4e48\u6837？"<\/span>}<\/span>]<\/span>}<\/span>)<\/span>
    \nprint<\/span>(<\/span>result[<\/span>"messages"<\/span>]<\/span>[<\/span>–<\/span>1<\/span>]<\/span>.<\/span>content_blocks)<\/span><\/p>\n

    \n

    \u4e03\u3001\u9010\u9879\u62c6\u89e3：LangChain \u7684\u516d\u9879\u6838\u5fc3\u80fd\u529b<\/h3>\n

    7.1 \u6a21\u578b\u8c03\u7528：init_chat_model<\/h4>\n

    from<\/span> langchain.<\/span>chat_models import<\/span> init_chat_model<\/p>\n

    model =<\/span> init_chat_model(<\/span>
    \n "deepseek:deepseek-chat"<\/span>,<\/span>
    \n temperature=<\/span>0.5<\/span>,<\/span>
    \n timeout=<\/span>300<\/span>,<\/span>
    \n max_tokens=<\/span>25000<\/span>,<\/span>
    \n)<\/span><\/p>\n

    \u4e24\u79cd\u6539\u53c2\u6570\u7684\u59ff\u52bf：<\/p>\n\n\u65b9\u5f0f\u5199\u6cd5\u7279\u70b9<\/tr>\n\n\n\n
    bind()<\/td>\nmodel.bind(temperature=2).invoke(messages)<\/td>\n\u4e00\u6b21\u8c03\u7528\u4e34\u65f6\u6539\u53c2\u6570，\u6700\u76f4\u63a5<\/td>\n<\/tr>\n
    configurable_fields<\/td>\ninit_chat_model(…, configurable_fields=("model","temperature"))<\/td>\n\u8fd0\u884c\u65f6\u901a\u8fc7 config \u5207\u6362，\u66f4\u7075\u6d3b<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    # \u7528\u6cd5\u793a\u4f8b：\u8fd0\u884c\u65f6\u5207\u6362 model \u4e0e temperature<\/span>
    \nconfigurable_model =<\/span> init_chat_model(<\/span>
    \n "deepseek:deepseek-chat"<\/span>,<\/span>
    \n configurable_fields=<\/span>(<\/span>"model"<\/span>,<\/span> "model_provider"<\/span>,<\/span> "temperature"<\/span>)<\/span>,<\/span>
    \n)<\/span><\/p>\n

    result =<\/span> configurable_model.<\/span>invoke(<\/span>
    \n messages,<\/span>
    \n config=<\/span>{<\/span>"configurable"<\/span>:<\/span> {<\/span>"temperature"<\/span>:<\/span> 1<\/span>}<\/span>}<\/span>,<\/span>
    \n)<\/span><\/p>\n

    \u591a\u8f6e\u5bf9\u8bdd\u5c31\u662f\u4f20\u6d88\u606f\u5217\u8868：<\/p>\n

    from<\/span> langchain.<\/span>messages import<\/span> HumanMessage,<\/span> SystemMessage<\/p>\n

    messages =<\/span> [<\/span>
    \n SystemMessage(<\/span>content=<\/span>"\u4f60\u662f\u4e00\u4e2a\u4e50\u4e8e\u52a9\u4eba\u7684\u4e2d\u6587\u52a9\u624b"<\/span>)<\/span>,<\/span>
    \n HumanMessage(<\/span>content=<\/span>"1+1 \u7b49\u4e8e\u51e0？"<\/span>)<\/span>,<\/span>
    \n]<\/span>
    \nprint<\/span>(<\/span>model.<\/span>invoke(<\/span>messages)<\/span>.<\/span>content)<\/span><\/p>\n

    7.2 \u5de5\u5177：@tool \u8be6\u89e3<\/h4>\n

    from<\/span> langchain.<\/span>tools import<\/span> tool<\/p>\n

    @tool<\/span>
    \ndef<\/span> search_flights<\/span>(<\/span>origin:<\/span> str<\/span>,<\/span> destination:<\/span> str<\/span>,<\/span> date:<\/span> str<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
    \n """\u67e5\u8be2\u6307\u5b9a\u65e5\u671f\u4ece\u51fa\u53d1\u5730\u5230\u76ee\u7684\u5730\u7684\u822a\u73ed\u3002<\/p>\n

    Args:
    \n origin: \u51fa\u53d1\u57ce\u5e02，\u5982 "\u5317\u4eac"
    \n destination: \u76ee\u7684\u57ce\u5e02，\u5982 "\u4e0a\u6d77"
    \n date: \u65e5\u671f，\u683c\u5f0f YYYY-MM-DD
    \n """<\/span>
    \n return<\/span> "CA1501 08:00-10:15 \u00a51200"<\/span><\/p>\n

    \u4e09\u6761\u786c\u89c4\u5219：<\/p>\n

  • \u51fd\u6570\u540d = \u5de5\u5177\u540d，\u6a21\u578b\u9760\u5b83\u8c03\u7528\u3002\u7528 search_flights \u800c\u4e0d\u662f func1\u3002<\/li>\n
  • docstring = \u5de5\u5177\u63cf\u8ff0，\u76f4\u63a5\u8fdb prompt\u3002\u5199\u6e05\u695a\u300c\u4ec0\u4e48\u65f6\u5019\u8be5\u7528\u300d\u6bd4\u5199\u6e05\u695a\u300c\u5b83\u80fd\u505a\u4ec0\u4e48\u300d\u66f4\u91cd\u8981\u3002<\/li>\n
  • \u7c7b\u578b\u6ce8\u89e3\u662f\u5fc5\u9700\u7684，LangChain \u9760\u5b83\u751f\u6210\u53c2\u6570\u7684 JSON Schema\u3002Pydantic \u6a21\u578b\u4e5f\u53ef\u4ee5\u7528\u3002<\/li>\n

    @tool \u8fd8\u652f\u6301\u901a\u8fc7 ToolRuntime \u53c2\u6570\u505a\u8fd0\u884c\u65f6\u6ce8\u5165（\u6bd4\u5982\u628a\u7528\u6237 ID\u3001\u6570\u636e\u5e93\u8fde\u63a5\u4f20\u8fdb\u5de5\u5177，\u800c\u4e0d\u8ba9\u6a21\u578b\u770b\u5230\u8fd9\u4e9b\u53c2\u6570）\u3002<\/p>\n

    7.3 \u7ed3\u6784\u5316\u8f93\u51fa<\/h4>\n

    Agent \u4e5f\u80fd\u76f4\u63a5\u5410\u7ed3\u6784\u5316\u6570\u636e\u2014\u2014\u800c\u4e14\u662f\u96c6\u6210\u5728\u4e3b\u5faa\u73af\u91cc\u7684，\u4e0d\u9700\u8981\u989d\u5916\u4e00\u6b21 LLM \u8c03\u7528：<\/p>\n

    from<\/span> langchain.<\/span>agents import<\/span> create_agent
    \nfrom<\/span> langchain.<\/span>agents.<\/span>structured_output import<\/span> ToolStrategy
    \nfrom<\/span> pydantic import<\/span> BaseModel<\/p>\n

    class<\/span> Weather<\/span>(<\/span>BaseModel)<\/span>:<\/span>
    \n temperature:<\/span> float<\/span>
    \n condition:<\/span> str<\/span><\/p>\n

    def<\/span> weather_tool<\/span>(<\/span>city:<\/span> str<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
    \n """\u67e5\u8be2\u57ce\u5e02\u5929\u6c14\u3002"""<\/span>
    \n return<\/span> f"<\/span>{<\/span>city}<\/span><\/span> \u5929\u6c14\u6674，70\u00b0F"<\/span><\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n "openai:gpt-4o-mini"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>weather_tool]<\/span>,<\/span>
    \n response_format=<\/span>ToolStrategy(<\/span>Weather)<\/span>,<\/span>
    \n)<\/span><\/p>\n

    result =<\/span> agent.<\/span>invoke(<\/span>{<\/span>"messages"<\/span>:<\/span> [<\/span>{<\/span>"role"<\/span>:<\/span> "user"<\/span>,<\/span> "content"<\/span>:<\/span> "\u65e7\u91d1\u5c71\u5929\u6c14\u5982\u4f55？"<\/span>}<\/span>]<\/span>}<\/span>)<\/span>
    \nprint<\/span>(<\/span>result[<\/span>"structured_response"<\/span>]<\/span>)<\/span><\/p>\n

    💡 1.0 \u7684\u4e09\u70b9\u6539\u8fdb：\u2460 \u7ed3\u6784\u5316\u8f93\u51fa\u5728\u4e3b\u5faa\u73af\u5185\u751f\u6210，\u65e0\u9700\u989d\u5916 LLM \u8c03\u7528；\u2461 \u6a21\u578b\u53ef\u9009\u62e9\u8c03\u7528\u5de5\u5177\u6216\u4f7f\u7528\u63d0\u4f9b\u5546\u4fa7\u7684\u7ed3\u6784\u5316\u8f93\u51fa；\u2462 \u76f4\u63a5\u7701\u94b1\u3002<\/p>\n

    7.4 \u4e2d\u95f4\u4ef6（Middleware）：1.0 \u771f\u6b63\u7684\u4eae\u70b9 \u2b50<\/h4>\n

    create_agent \u62ff\u5230\u4e86\u53d1\u5e03\u516c\u544a\u7684\u5168\u90e8\u6ce8\u610f\u529b，\u4f46\u65e5\u5e38\u5f00\u53d1\u4e2d\u66f4\u91cd\u8981\u7684\u662f\u4e2d\u95f4\u4ef6\u3002<\/p>\n

    \u5728 1.0 \u4e4b\u524d，\u60f3\u63a7\u5236 Agent \u5faa\u73af\u7684\u300c\u4e2d\u95f4\u8fc7\u7a0b\u300d，\u4f60\u8981\u4e48\u7528 callback handlers，\u8981\u4e48\u7ee7\u627f\u5b50\u7c7b，\u8981\u4e48 fork \u4e00\u4e2a prebuilt graph\u2014\u2014\u5927\u591a\u6570\u6559\u7a0b\u5e72\u8106\u8df3\u8fc7\u4e86\u8fd9\u4e2a\u95ee\u9898\u3002<\/p>\n

    \u73b0\u5728\u6709\u4e86\u660e\u786e\u7684\u300c\u7f1d\u300d，\u800c\u4e14\u547d\u540d\u5c31\u5199\u660e\u4e86\u5b83\u5207\u5728\u54ea\u91cc：<\/p>\n\nHook\u6267\u884c\u65f6\u673a\u5178\u578b\u7528\u4f8b<\/tr>\n\n\n\n\n\n\n\n
    before_agent<\/td>\n\u8c03\u7528 Agent \u524d<\/td>\n\u52a0\u8f7d\u8bb0\u5fc6\u3001\u6821\u9a8c\u8f93\u5165<\/td>\n<\/tr>\n
    before_model<\/td>\n\u6bcf\u6b21 LLM \u8c03\u7528\u524d<\/td>\n\u66f4\u65b0\u63d0\u793a\u8bcd\u3001\u4fee\u526a\u6d88\u606f\u3001\u63a7\u5236\u9884\u7b97<\/td>\n<\/tr>\n
    wrap_model_call<\/td>\n\u5305\u88f9\u6bcf\u6b21 LLM \u8c03\u7528<\/td>\n\u62e6\u622a\u5e76\u4fee\u6539\u8bf7\u6c42\/\u54cd\u5e94<\/td>\n<\/tr>\n
    wrap_tool_call<\/td>\n\u5305\u88f9\u6bcf\u6b21\u5de5\u5177\u8c03\u7528<\/td>\n\u62e6\u622a\u5e76\u4fee\u6539\u5de5\u5177\u6267\u884c<\/td>\n<\/tr>\n
    after_model<\/td>\n\u6bcf\u6b21 LLM \u54cd\u5e94\u540e<\/td>\n\u6821\u9a8c\u8f93\u51fa\u3001\u5e94\u7528\u5b89\u5168\u62a4\u680f<\/td>\n<\/tr>\n
    after_agent<\/td>\nAgent \u5b8c\u6210\u540e<\/td>\n\u4fdd\u5b58\u7ed3\u679c\u3001\u6e05\u7406\u8d44\u6e90<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u5185\u7f6e\u4e2d\u95f4\u4ef6（\u5f00\u7bb1\u5373\u7528，\u8986\u76d6\u4e86\u6700\u5e38\u89c1\u7684\u4e09\u7c7b\u9700\u6c42）：<\/p>\n

    from<\/span> langchain.<\/span>agents import<\/span> create_agent
    \nfrom<\/span> langchain.<\/span>agents.<\/span>middleware import<\/span> (<\/span>
    \n PIIMiddleware,<\/span>
    \n SummarizationMiddleware,<\/span>
    \n HumanInTheLoopMiddleware,<\/span>
    \n)<\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n model=<\/span>"anthropic:claude-sonnet-4-5"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>read_email,<\/span> send_email]<\/span>,<\/span>
    \n middleware=<\/span>[<\/span>
    \n # \u2460 \u53d1\u9001\u7ed9\u6a21\u578b\u524d\u5c4f\u853d\u654f\u611f\u4fe1\u606f<\/span>
    \n PIIMiddleware(<\/span>patterns=<\/span>[<\/span>"email"<\/span>,<\/span> "phone"<\/span>,<\/span> "ssn"<\/span>]<\/span>)<\/span>,<\/span>
    \n # \u2461 \u5bf9\u8bdd\u8fc7\u957f\u65f6\u81ea\u52a8\u6458\u8981，\u63a7\u5236 token \u9884\u7b97<\/span>
    \n SummarizationMiddleware(<\/span>
    \n model=<\/span>"anthropic:claude-sonnet-4-5"<\/span>,<\/span>
    \n max_tokens_before_summary=<\/span>500<\/span>,<\/span>
    \n )<\/span>,<\/span>
    \n # \u2462 \u654f\u611f\u5de5\u5177\u8c03\u7528\u9700\u4eba\u5de5\u5ba1\u6279<\/span>
    \n HumanInTheLoopMiddleware(<\/span>
    \n interrupt_on=<\/span>{<\/span>
    \n "send_email"<\/span>:<\/span> {<\/span>"allowed_decisions"<\/span>:<\/span> [<\/span>"approve"<\/span>,<\/span> "edit"<\/span>,<\/span> "reject"<\/span>]<\/span>}<\/span>
    \n }<\/span>
    \n )<\/span>,<\/span>
    \n ]<\/span>,<\/span>
    \n)<\/span><\/p>\n

    \u81ea\u5b9a\u4e49\u4e2d\u95f4\u4ef6（\u5199\u6210\u7c7b，\u5b9e\u73b0 wrap_model_call）：<\/p>\n

    from<\/span> dataclasses import<\/span> dataclass
    \nfrom<\/span> typing import<\/span> Callable<\/p>\n

    from<\/span> langchain.<\/span>agents import<\/span> create_agent
    \nfrom<\/span> langchain.<\/span>agents.<\/span>middleware import<\/span> AgentMiddleware,<\/span> ModelRequest
    \nfrom<\/span> langchain.<\/span>agents.<\/span>middleware.<\/span>types import<\/span> ModelResponse
    \nfrom<\/span> langchain_openai import<\/span> ChatOpenAI<\/p>\n

    @dataclass<\/span>
    \nclass<\/span> Context<\/span>:<\/span>
    \n user_expertise:<\/span> str<\/span> =<\/span> "beginner"<\/span><\/p>\n

    class<\/span> ExpertiseBasedToolMiddleware<\/span>(<\/span>AgentMiddleware)<\/span>:<\/span>
    \n """\u6309\u7528\u6237\u4e13\u4e1a\u5ea6\u52a8\u6001\u6362\u6a21\u578b\u3001\u6362\u5de5\u5177\u96c6"""<\/span><\/p>\n

    def<\/span> wrap_model_call<\/span>(<\/span>
    \n self,<\/span>
    \n request:<\/span> ModelRequest,<\/span>
    \n handler:<\/span> Callable[<\/span>[<\/span>ModelRequest]<\/span>,<\/span> ModelResponse]<\/span>,<\/span>
    \n )<\/span> –<\/span>><\/span> ModelResponse:<\/span>
    \n user_level =<\/span> request.<\/span>runtime.<\/span>context.<\/span>user_expertise<\/p>\n

    if<\/span> user_level ==<\/span> "expert"<\/span>:<\/span>
    \n request.<\/span>model =<\/span> ChatOpenAI(<\/span>model=<\/span>"openai:gpt-5"<\/span>)<\/span>
    \n request.<\/span>tools =<\/span> [<\/span>advanced_search,<\/span> data_analysis]<\/span>
    \n else<\/span>:<\/span>
    \n request.<\/span>model =<\/span> ChatOpenAI(<\/span>model=<\/span>"openai:gpt-5-nano"<\/span>)<\/span>
    \n request.<\/span>tools =<\/span> [<\/span>simple_search,<\/span> basic_calculator]<\/span><\/p>\n

    return<\/span> handler(<\/span>request)<\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n model=<\/span>"anthropic:claude-sonnet-4-5"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>simple_search,<\/span> advanced_search,<\/span> basic_calculator,<\/span> data_analysis]<\/span>,<\/span>
    \n middleware=<\/span>[<\/span>ExpertiseBasedToolMiddleware(<\/span>)<\/span>]<\/span>,<\/span>
    \n context_schema=<\/span>Context,<\/span>
    \n)<\/span><\/p>\n

    🎯 \u8fd9\u4e2a\u6a21\u5f0f\u7684\u5a01\u529b：\u65b0\u624b\u7528\u4fbf\u5b9c\u7684\u5c0f\u6a21\u578b + \u7b80\u5355\u5de5\u5177，\u4e13\u5bb6\u7528\u65d7\u8230\u6a21\u578b + \u9ad8\u7ea7\u5de5\u5177\u3002 \u4e00\u5957\u4ee3\u7801，\u4e24\u79cd\u6210\u672c\u66f2\u7ebf\u3002\u8fd9\u9053\u4ee5\u524d\u8981 fork \u6e90\u7801\u624d\u80fd\u505a\u7684\u9898，\u73b0\u5728\u662f\u4e00\u4e2a\u7c7b\u3002<\/p>\n

    7.5 \u8bb0\u5fc6\u4e0e\u6301\u4e45\u5316<\/h4>\n

    \u56e0\u4e3a create_agent \u8dd1\u5728 LangGraph \u4e0a，\u6301\u4e45\u5316\u662f\u767d\u62ff\u7684：<\/p>\n

    from<\/span> langgraph.<\/span>checkpoint.<\/span>memory import<\/span> InMemorySaver<\/p>\n

    checkpointer =<\/span> InMemorySaver(<\/span>)<\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n model=<\/span>"deepseek:deepseek-chat"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>get_weather]<\/span>,<\/span>
    \n checkpointer=<\/span>checkpointer,<\/span> # \u2190 \u52a0\u4e0a\u8fd9\u884c\u5c31\u6709\u4e86\u8bb0\u5fc6<\/span>
    \n)<\/span><\/p>\n

    # \u7528 thread_id \u533a\u5206\u4f1a\u8bdd<\/span>
    \nconfig =<\/span> {<\/span>"configurable"<\/span>:<\/span> {<\/span>"thread_id"<\/span>:<\/span> "user-001"<\/span>}<\/span>}<\/span><\/p>\n

    agent.<\/span>invoke(<\/span>{<\/span>"messages"<\/span>:<\/span> [<\/span>{<\/span>"role"<\/span>:<\/span> "user"<\/span>,<\/span> "content"<\/span>:<\/span> "\u6211\u53eb\u5c0f\u660e"<\/span>}<\/span>]<\/span>}<\/span>,<\/span> config)<\/span>
    \nresult =<\/span> agent.<\/span>invoke(<\/span>{<\/span>"messages"<\/span>:<\/span> [<\/span>{<\/span>"role"<\/span>:<\/span> "user"<\/span>,<\/span> "content"<\/span>:<\/span> "\u6211\u53eb\u4ec0\u4e48？"<\/span>}<\/span>]<\/span>}<\/span>,<\/span> config)<\/span>
    \nprint<\/span>(<\/span>result[<\/span>"messages"<\/span>]<\/span>[<\/span>–<\/span>1<\/span>]<\/span>.<\/span>content)<\/span> # \u4f1a\u8bb0\u5f97\u4f60\u53eb\u5c0f\u660e<\/span><\/p>\n

    \u26a0\ufe0f InMemorySaver \u53ea\u9002\u5408\u5f00\u53d1\u2014\u2014\u8fdb\u7a0b\u4e00\u91cd\u542f\u5c31\u6ca1\u4e86\u3002\u751f\u4ea7\u73af\u5883\u5fc5\u987b\u6362\u6210\u6301\u4e45\u5316 checkpointer（\u5b58\u5230\u6570\u636e\u5e93）\u3002<\/p>\n

    \u4ece LangGraph \u81ea\u52a8\u7ee7\u627f\u7684\u56db\u4e2a\u80fd\u529b：<\/p>\n\n\u80fd\u529b\u8bf4\u660e<\/tr>\n\n\n\n\n\n
    \u6301\u4e45\u5316<\/td>\n\u4f1a\u8bdd\u95f4\u5bf9\u8bdd\u81ea\u52a8\u4fdd\u5b58<\/td>\n<\/tr>\n
    \u6d41\u5f0f\u5904\u7406<\/td>\n\u5b9e\u65f6\u4f20\u8f93 token\u3001\u5de5\u5177\u8c03\u7528\u4e0e\u63a8\u7406\u8f68\u8ff9<\/td>\n<\/tr>\n
    \u4eba\u5de5\u5e72\u9884<\/td>\n\u654f\u611f\u64cd\u4f5c\u524d\u6682\u505c Agent \u7b49\u5ba1\u6279<\/td>\n<\/tr>\n
    \u65f6\u95f4\u65c5\u884c<\/td>\n\u56de\u6eaf\u5bf9\u8bdd\u5386\u53f2，\u63a2\u7d22\u4e0d\u540c\u5206\u652f<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n

    \u516b\u3001LCEL \u4e0e Runnable：\u5e95\u5c42\u534f\u8bae<\/h3>\n

    langchain-core \u91cc\u6700\u6838\u5fc3\u7684\u4e1c\u897f\u662f Runnable \u534f\u8bae\u3002\u5b83\u5b9a\u4e49\u4e86\u300c\u4efb\u4f55\u4e00\u4e2a\u53ef\u7ec4\u5408\u7684\u5de5\u4f5c\u5355\u5143\u300d\u5fc5\u987b\u63d0\u4f9b\u7684\u63a5\u53e3：<\/p>\n

    from<\/span> langchain_core.<\/span>runnables import<\/span> Runnable<\/p>\n

    class<\/span> MyRunnable<\/span>(<\/span>Runnable[<\/span>str<\/span>,<\/span> str<\/span>]<\/span>)<\/span>:<\/span>
    \n def<\/span> invoke<\/span>(<\/span>self,<\/span> input<\/span>:<\/span> str<\/span>,<\/span> config=<\/span>None<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span> .<\/span>.<\/span>.<\/span>
    \n async<\/span> def<\/span> ainvoke<\/span>(<\/span>self,<\/span> input<\/span>:<\/span> str<\/span>,<\/span> config=<\/span>None<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span> .<\/span>.<\/span>.<\/span>
    \n def<\/span> stream<\/span>(<\/span>self,<\/span> input<\/span>:<\/span> str<\/span>,<\/span> config=<\/span>None<\/span>)<\/span>:<\/span> .<\/span>.<\/span>.<\/span>
    \n async<\/span> def<\/span> astream<\/span>(<\/span>self,<\/span> input<\/span>:<\/span> str<\/span>,<\/span> config=<\/span>None<\/span>)<\/span>:<\/span> .<\/span>.<\/span>.<\/span>
    \n def<\/span> batch<\/span>(<\/span>self,<\/span> inputs:<\/span> list<\/span>[<\/span>str<\/span>]<\/span>,<\/span> config=<\/span>None<\/span>)<\/span> –<\/span>><\/span> list<\/span>[<\/span>str<\/span>]<\/span>:<\/span> .<\/span>.<\/span>.<\/span><\/p>\n

    \u5185\u7f6e\u7684 Runnable \u5305\u62ec：\u6bcf\u4e2a\u804a\u5929\u6a21\u578b\u3001\u6bcf\u4e2a\u8f93\u51fa\u89e3\u6790\u5668\u3001\u6bcf\u4e2a\u63d0\u793a\u8bcd\u6a21\u677f\u3001\u6bcf\u4e2a\u68c0\u7d22\u5668\u3001\u6bcf\u4e2a\u5de5\u5177\u3002<\/p>\n

    LCEL（LangChain Expression Language）\u5c31\u662f\u7528 | \u628a\u5b83\u4eec\u4e32\u8d77\u6765：<\/p>\n

    from<\/span> langchain_core.<\/span>prompts import<\/span> ChatPromptTemplate
    \nfrom<\/span> langchain_core.<\/span>output_parsers import<\/span> StrOutputParser
    \nfrom<\/span> langchain_openai import<\/span> ChatOpenAI<\/p>\n

    model =<\/span> ChatOpenAI(<\/span>model=<\/span>"gpt-4o"<\/span>)<\/span>
    \nprompt =<\/span> ChatPromptTemplate.<\/span>from_template(<\/span>"\u7528\u4e00\u53e5\u8bdd\u89e3\u91ca {topic}\u3002"<\/span>)<\/span>
    \nparser =<\/span> StrOutputParser(<\/span>)<\/span><\/p>\n

    chain =<\/span> prompt |<\/span> model |<\/span> parser<\/p>\n

    result =<\/span> chain.<\/span>invoke(<\/span>{<\/span>"topic"<\/span>:<\/span> "\u5149\u5408\u4f5c\u7528"<\/span>}<\/span>)<\/span> # \u963b\u585e\u5f0f，\u8fd4\u56de\u5b8c\u6574\u7ed3\u679c<\/span>
    \n# chain.stream({"topic": "\u5149\u5408\u4f5c\u7528"}) # \u6d41\u5f0f，\u9010\u5757\u8fd4\u56de<\/span>
    \n# chain.batch([{"topic": "A"}, {"topic": "B"}]) # \u6279\u91cf<\/span>
    \n# await chain.ainvoke(…) # \u5f02\u6b65<\/span><\/p>\n

    \u5b98\u65b9\u8bbe\u8ba1\u76ee\u6807：\u4e00\u6b21\u5b9a\u4e49\u7ec4\u5408，batch \/ async \/ stream \u4e0d\u7528\u91cd\u5199\u4ee3\u7801\u3002<\/p>\n

    8.1 \u4e09\u4e2a\u5fc5\u987b\u77e5\u9053\u7684\u7ec6\u8282<\/h4>\n

    \u2460 | \u662f\u60f0\u6027\u7684\u3002 prompt | model | parser \u53ea\u662f\u5b9a\u4e49，\u4e0d\u4f1a\u6267\u884c\u3002\u4e0d\u8c03\u7528 .invoke() \/ .stream() \/ .batch() \/ .astream()，\u4ec0\u4e48\u90fd\u4e0d\u4f1a\u53d1\u751f\u3002\u4ee3\u7801\u300c\u8dd1\u4e86\u4f46\u6ca1\u53cd\u5e94\u300d，\u5148\u68c0\u67e5\u662f\u4e0d\u662f\u5fd8\u4e86\u8c03\u3002<\/p>\n

    \u2461 \u7ec4\u5408\u7c7b\u578b<\/p>\n\n\u5199\u6cd5\u5f97\u5230\u7684\u7c7b\u578b\u8bed\u4e49<\/tr>\n\n\n\n
    a | b | c<\/td>\nRunnableSequence<\/td>\n\u4e32\u884c，\u524d\u4e00\u4e2a\u7684\u8f93\u51fa\u662f\u540e\u4e00\u4e2a\u7684\u8f93\u5165<\/td>\n<\/tr>\n
    {"x": a, "y": b}<\/td>\nRunnableParallel<\/td>\n\u5e76\u884c fan-out，\u540c\u4e00\u4efd\u8f93\u5165\u5582\u7ed9\u591a\u4e2a\u5206\u652f<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    RAG \u7684\u7ecf\u5178\u7ec4\u5408（\u4e00\u773c\u5c31\u80fd\u770b\u51fa\u6765\u5b83\u5728\u5e72\u561b）：<\/p>\n

    rag =<\/span> (<\/span>
    \n {<\/span>"context"<\/span>:<\/span> retriever |<\/span> format_docs,<\/span> "question"<\/span>:<\/span> RunnablePassthrough(<\/span>)<\/span>}<\/span>
    \n |<\/span> prompt
    \n |<\/span> model
    \n |<\/span> StrOutputParser(<\/span>)<\/span>
    \n)<\/span><\/p>\n

    \u2462 \u6d41\u5f0f\u548c\u5e76\u53d1\u7684\u4e24\u4e2a\u5751<\/p>\n\n\u73b0\u8c61\u539f\u56e0\u89e3\u6cd5<\/tr>\n\n\n\n
    stream() \u53ea\u51fa\u6700\u540e\u4e00\u5927\u6bb5<\/td>\n\u4e2d\u95f4\u67d0\u6b65\u7528\u4e86 .invoke \u800c\u975e .stream，\u6216\u67d0\u4e2a\u975e LLM \u7684 Runnable \u6ca1\u5b9e\u73b0 stream<\/td>\n\u7528 astream_events(input, version="v2") \u770b\u54ea\u4e2a\u73af\u8282\u6ca1\u6709 on_chat_model_stream \u4e8b\u4ef6<\/td>\n<\/tr>\n
    batch \u6bd4 for \u5faa\u73af\u8fd8\u6162<\/td>\n\u5e76\u53d1\u5ea6\u6ca1\u4e0a\u53bb<\/td>\nchain.batch(inputs, config={"max_concurrency": 8})<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u751f\u4ea7\u73af\u5883\u8fd8\u8981\u52a0：<\/p>\n

    # \u964d\u7ea7：\u4e3b\u6a21\u578b\u6302\u4e86\u81ea\u52a8\u5207\u5907\u7528<\/span>
    \nmodel_with_fallback =<\/span> model.<\/span>with_fallbacks(<\/span>[<\/span>backup_model]<\/span>)<\/span><\/p>\n

    # \u91cd\u8bd5<\/span>
    \nfrom<\/span> tenacity import<\/span> stop_after_attempt
    \nreliable =<\/span> model.<\/span>with_retry(<\/span>stop_after_attempt=<\/span>3<\/span>)<\/span><\/p>\n

    # \u8ffd\u8e2a（LangSmith \u9760 config \u4f20\u64ad）<\/span>
    \nchain.<\/span>invoke(<\/span>{<\/span>"q"<\/span>:<\/span> "…"<\/span>}<\/span>,<\/span> config=<\/span>{<\/span>"tags"<\/span>:<\/span> [<\/span>"prod"<\/span>,<\/span> "faq"<\/span>]<\/span>,<\/span> "metadata"<\/span>:<\/span> {<\/span>"user_id"<\/span>:<\/span> "u1"<\/span>}<\/span>}<\/span>)<\/span><\/p>\n

    \n

    \u4e5d\u3001RAG \u5b9e\u6218：\u4e09\u79cd\u67b6\u6784\u4e0e\u5b8c\u6574\u4ee3\u7801<\/h3>\n

    RAG（\u68c0\u7d22\u589e\u5f3a\u751f\u6210）\u662f LangChain \u6700\u4e3b\u6d41\u7684\u843d\u5730\u573a\u666f\u3002\u5b83\u89e3\u51b3 LLM \u7684\u4e24\u4e2a\u786c\u4f24：\u4e0a\u4e0b\u6587\u6709\u9650\u3001\u77e5\u8bc6\u9759\u6001（\u8bad\u7ec3\u6570\u636e\u51bb\u7ed3\u5728\u67d0\u4e2a\u65f6\u95f4\u70b9）\u3002<\/p>\n

    9.1 \u4e09\u79cd RAG \u67b6\u6784\u600e\u4e48\u9009<\/h4>\n

    \u5b98\u65b9\u628a RAG \u5206\u6210\u4e09\u7c7b，\u9009\u62e9\u7684\u5173\u952e\u662f\u300c\u4f60\u9700\u8981\u591a\u5c11\u53ef\u63a7\u6027\u300d：<\/p>\n\n\u67b6\u6784\u8bf4\u660e\u63a7\u5236\u529b\u7075\u6d3b\u6027\u5ef6\u8fdf\u5178\u578b\u573a\u666f<\/tr>\n\n\n\n\n
    2-Step RAG<\/td>\n\u68c0\u7d22\u603b\u662f\u53d1\u751f\u5728\u751f\u6210\u4e4b\u524d<\/td>\n\u2705 \u9ad8<\/td>\n\u274c \u4f4e<\/td>\n\u26a1 \u5feb\u4e14\u53ef\u9884\u6d4b<\/td>\nFAQ\u3001\u6587\u6863\u673a\u5668\u4eba<\/td>\n<\/tr>\n
    Agentic RAG<\/td>\nAgent \u81ea\u5df1\u51b3\u5b9a\u4f55\u65f6\u3001\u5982\u4f55\u68c0\u7d22<\/td>\n\u274c \u4f4e<\/td>\n\u2705 \u9ad8<\/td>\n\u23f3 \u53ef\u53d8<\/td>\n\u80fd\u8bbf\u95ee\u591a\u4e2a\u5de5\u5177\u7684\u7814\u7a76\u52a9\u624b<\/td>\n<\/tr>\n
    Hybrid RAG<\/td>\n\u4e24\u8005\u7ed3\u5408，\u52a0\u6821\u9a8c\u6b65\u9aa4<\/td>\n\u2696\ufe0f \u4e2d<\/td>\n\u2696\ufe0f \u4e2d<\/td>\n\u23f3 \u53ef\u53d8<\/td>\n\u9700\u8981\u8d28\u91cf\u6821\u9a8c\u7684\u9886\u57df\u95ee\u7b54<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    💡 \u5ef6\u8fdf\u8fd9\u70b9\u5f88\u5173\u952e：2-Step RAG \u7684\u6700\u5927 LLM \u8c03\u7528\u6b21\u6570\u662f\u5df2\u77e5\u4e14\u6709\u4e0a\u9650\u7684，\u6240\u4ee5\u5ef6\u8fdf\u66f4\u53ef\u9884\u6d4b\u3002<\/p>\n

    9.2 \u6709\u73b0\u6210\u77e5\u8bc6\u5e93\u7684\u8bdd，\u4e0d\u8981\u91cd\u5efa<\/h4>\n

    \u5b98\u65b9\u7279\u522b\u63d0\u9192：\u5982\u679c\u4f60\u5df2\u7ecf\u6709\u77e5\u8bc6\u5e93（SQL\u3001\u6587\u6863\u5e93\u3001CRM\u3001\u5185\u90e8\u6587\u6863\u7cfb\u7edf），\u4e0d\u9700\u8981\u91cd\u5efa\u5b83\u3002 \u76f4\u63a5：<\/p>\n

  • \u5f53\u6210\u5de5\u5177\u63a5\u7ed9 Agent（Agentic RAG）<\/li>\n
  • \u67e5\u8be2\u540e\u628a\u7ed3\u679c\u4f5c\u4e3a context \u5582\u7ed9 LLM（2-Step RAG）<\/li>\n

    9.3 \u5b8c\u6574\u4ee3\u7801：2-Step RAG<\/h4>\n

    """\u6700\u5c0f\u53ef\u8fd0\u884c\u7684 RAG \u793a\u4f8b"""<\/span>
    \nfrom<\/span> dotenv import<\/span> load_dotenv
    \nfrom<\/span> langchain_community.<\/span>document_loaders import<\/span> PyPDFLoader,<\/span> TextLoader,<\/span> DirectoryLoader
    \nfrom<\/span> langchain_text_splitters import<\/span> RecursiveCharacterTextSplitter
    \nfrom<\/span> langchain_chroma import<\/span> Chroma
    \nfrom<\/span> langchain_openai import<\/span> ChatOpenAI,<\/span> OpenAIEmbeddings
    \nfrom<\/span> langchain_core.<\/span>prompts import<\/span> ChatPromptTemplate
    \nfrom<\/span> langchain_core.<\/span>output_parsers import<\/span> StrOutputParser
    \nfrom<\/span> langchain_core.<\/span>runnables import<\/span> RunnablePassthrough<\/p>\n

    load_dotenv(<\/span>)<\/span><\/p>\n

    # ———- \u2460 \u52a0\u8f7d\u6587\u6863 ———-<\/span>
    \nloader =<\/span> PyPDFLoader(<\/span>"docs\/manual.pdf"<\/span>)<\/span>
    \ndocs =<\/span> loader.<\/span>load(<\/span>)<\/span><\/p>\n

    # \u4e5f\u53ef\u4ee5\u7528\u76ee\u5f55\u52a0\u8f7d\u5668\u6279\u91cf\u8bfb Markdown<\/span>
    \n# loader = DirectoryLoader(".\/knowledge_base", glob="**\/*.md", loader_cls=TextLoader)<\/span>
    \n# docs = loader.load()<\/span><\/p>\n

    # ———- \u2461 \u5207\u5206 ———-<\/span>
    \nsplitter =<\/span> RecursiveCharacterTextSplitter(<\/span>
    \n chunk_size=<\/span>1000<\/span>,<\/span>
    \n chunk_overlap=<\/span>200<\/span>,<\/span>
    \n separators=<\/span>[<\/span>"\\\\n\\\\n"<\/span>,<\/span> "\\\\n"<\/span>,<\/span> "\u3002"<\/span>,<\/span> "！"<\/span>,<\/span> "？"<\/span>,<\/span> "."<\/span>,<\/span> " "<\/span>,<\/span> ""<\/span>]<\/span>,<\/span>
    \n)<\/span>
    \nchunks =<\/span> splitter.<\/span>split_documents(<\/span>docs)<\/span>
    \nprint<\/span>(<\/span>f"\u5207\u5206\u51fa <\/span>{<\/span>len<\/span>(<\/span>chunks)<\/span>}<\/span><\/span> \u4e2a\u5757"<\/span><\/span>)<\/span><\/p>\n

    # ———- \u2462 \u5411\u91cf\u5316 + \u5165\u5e93 ———-<\/span>
    \nembeddings =<\/span> OpenAIEmbeddings(<\/span>model=<\/span>"text-embedding-3-small"<\/span>)<\/span>
    \nvectorstore =<\/span> Chroma.<\/span>from_documents(<\/span>
    \n documents=<\/span>chunks,<\/span>
    \n embedding=<\/span>embeddings,<\/span>
    \n persist_directory=<\/span>".\/chroma_db"<\/span>,<\/span>
    \n)<\/span><\/p>\n

    # ———- \u2463 \u6784\u9020\u68c0\u7d22\u5668 ———-<\/span>
    \nretriever =<\/span> vectorstore.<\/span>as_retriever(<\/span>
    \n search_type=<\/span>"mmr"<\/span>,<\/span> # \u7528 MMR \u517c\u987e\u76f8\u5173\u6027\u4e0e\u591a\u6837\u6027<\/span>
    \n search_kwargs=<\/span>{<\/span>"k"<\/span>:<\/span> 5<\/span>,<\/span> "fetch_k"<\/span>:<\/span> 20<\/span>}<\/span>,<\/span>
    \n)<\/span><\/p>\n

    # ———- \u2464 \u7ec4\u88c5 RAG \u94fe ———-<\/span>
    \nprompt =<\/span> ChatPromptTemplate.<\/span>from_template(<\/span>
    \n """\u4f60\u662f\u4e00\u4e2a\u4e25\u8c28\u7684\u52a9\u624b\u3002\u8bf7**\u53ea**\u6839\u636e\u4e0b\u9762\u63d0\u4f9b\u7684\u8d44\u6599\u56de\u7b54\u95ee\u9898\u3002
    \n\u5982\u679c\u8d44\u6599\u4e2d\u4e0d\u542b\u7b54\u6848，\u76f4\u63a5\u8bf4\u300c\u8d44\u6599\u4e2d\u6ca1\u6709\u76f8\u5173\u4fe1\u606f\u300d，\u4e0d\u8981\u7f16\u9020\u3002<\/p>\n

    \u8d44\u6599：
    \n{context}<\/p>\n

    \u95ee\u9898：{question}<\/p>\n

    \u56de\u7b54："""<\/span>
    \n)<\/span><\/p>\n

    model =<\/span> ChatOpenAI(<\/span>model=<\/span>"gpt-4o-mini"<\/span>,<\/span> temperature=<\/span>0<\/span>)<\/span><\/p>\n

    def<\/span> format_docs<\/span>(<\/span>docs)<\/span>:<\/span>
    \n return<\/span> "\\\\n\\\\n—\\\\n\\\\n"<\/span>.<\/span>join(<\/span>
    \n f"[\u6765\u6e90: <\/span>{<\/span>d.<\/span>metadata.<\/span>get(<\/span>'source'<\/span>,<\/span> '\u672a\u77e5'<\/span>)<\/span>}<\/span><\/span>]\\\\n<\/span>{<\/span>d.<\/span>page_content}<\/span><\/span>"<\/span><\/span>
    \n for<\/span> d in<\/span> docs
    \n )<\/span><\/p>\n

    rag_chain =<\/span> (<\/span>
    \n {<\/span>"context"<\/span>:<\/span> retriever |<\/span> format_docs,<\/span> "question"<\/span>:<\/span> RunnablePassthrough(<\/span>)<\/span>}<\/span>
    \n |<\/span> prompt
    \n |<\/span> model
    \n |<\/span> StrOutputParser(<\/span>)<\/span>
    \n)<\/span><\/p>\n

    # ———- \u2465 \u63d0\u95ee ———-<\/span>
    \nanswer =<\/span> rag_chain.<\/span>invoke(<\/span>"\u6587\u6863\u91cc\u8bb2\u4e86\u54ea\u4e9b\u6838\u5fc3\u6982\u5ff5？"<\/span>)<\/span>
    \nprint<\/span>(<\/span>answer)<\/span><\/p>\n

    9.4 \u5b8c\u6574\u4ee3\u7801：Agentic RAG<\/h4>\n

    \u7ed9 Agent \u4e00\u4e2a\u300c\u80fd\u53d6\u5916\u90e8\u77e5\u8bc6\u300d\u7684\u5de5\u5177\u5373\u53ef：<\/p>\n

    import<\/span> requests
    \nfrom<\/span> langchain.<\/span>tools import<\/span> tool
    \nfrom<\/span> langchain.<\/span>agents import<\/span> create_agent<\/p>\n

    @tool<\/span>
    \ndef<\/span> fetch_url<\/span>(<\/span>url:<\/span> str<\/span>)<\/span> –<\/span>><\/span> str<\/span>:<\/span>
    \n """Fetch text content from a URL"""<\/span>
    \n response =<\/span> requests.<\/span>get(<\/span>url,<\/span> timeout=<\/span>10.0<\/span>)<\/span>
    \n response.<\/span>raise_for_status(<\/span>)<\/span>
    \n return<\/span> response.<\/span>text<\/p>\n

    system_prompt =<\/span> """\\\\
    \n\u9700\u8981\u4ece\u7f51\u9875\u83b7\u53d6\u4fe1\u606f\u65f6\u8bf7\u4f7f\u7528 fetch_url；\u56de\u7b54\u65f6\u5f15\u7528\u76f8\u5173\u539f\u6587\u7247\u6bb5\u3002
    \n"""<\/span><\/p>\n

    agent =<\/span> create_agent(<\/span>
    \n model=<\/span>"claude-sonnet-4-6"<\/span>,<\/span>
    \n tools=<\/span>[<\/span>fetch_url]<\/span>,<\/span> # \u2190 \u4e00\u4e2a\u68c0\u7d22\u5de5\u5177\u5c31\u591f\u5f00\u542f RAG \u884c\u4e3a<\/span>
    \n system_prompt=<\/span>system_prompt,<\/span>
    \n)<\/span><\/p>\n

    🎯 \u6ce8\u610f\u8fd9\u53e5\u5b98\u65b9\u539f\u8bdd：\u300c\u4e00\u4e2a Agent \u8981\u5b9e\u73b0 RAG \u884c\u4e3a，\u552f\u4e00\u9700\u8981\u7684\u5c31\u662f\u8bbf\u95ee\u4e00\u4e2a\u6216\u591a\u4e2a\u80fd\u53d6\u5916\u90e8\u77e5\u8bc6\u7684\u5de5\u5177\u3002\u300d \u4e5f\u5c31\u662f\u8bf4，Agentic RAG \u4e0d\u9700\u8981\u4efb\u4f55\u4e13\u95e8\u7684 RAG \u4ee3\u7801\u2014\u2014RAG \u9000\u5316\u6210\u300c\u7ed9 Agent \u4e00\u4e2a\u68c0\u7d22\u5de5\u5177\u300d\u8fd9\u4e00\u4e2a\u52a8\u4f5c\u3002<\/p>\n

    9.5 \u8c03\u53c2\u7ecf\u9a8c<\/h4>\n\n\u53c2\u6570\u5efa\u8bae\u539f\u56e0<\/tr>\n\n\n\n\n\n\n
    chunk_size<\/td>\n256\u2013512 token（\u4e2d\u6587\u7ea6 300\u2013600 \u5b57）<\/td>\n\u592a\u5927 \u2192 \u8bed\u4e49\u88ab\u566a\u58f0\u7a00\u91ca；\u592a\u5c0f \u2192 \u4e22\u5931\u5fc5\u8981\u4e0a\u4e0b\u6587<\/td>\n<\/tr>\n
    chunk_overlap<\/td>\nchunk_size \u7684 10\u201320%<\/td>\n\u907f\u514d\u53e5\u5b50\u6b63\u597d\u88ab\u5207\u65ad\u5728\u8fb9\u754c<\/td>\n<\/tr>\n
    search_type<\/td>\n"mmr" \u4f18\u4e8e\u9ed8\u8ba4 similarity<\/td>\n\u7eaf top-k \u5e38\u53ec\u56de 5 \u6761\u5185\u5bb9\u96f7\u540c\u7684\u5757；MMR \u517c\u987e\u76f8\u5173\u6027 + \u591a\u6837\u6027<\/td>\n<\/tr>\n
    separators<\/td>\n\u4e2d\u6587\u8981\u52a0 \u3002！？<\/td>\n\u9ed8\u8ba4\u5206\u9694\u7b26\u662f\u82f1\u6587\u6807\u70b9，\u4e2d\u6587\u4f1a\u5207\u5f97\u5f88\u96be\u770b<\/td>\n<\/tr>\n
    \u7ed3\u6784\u5316\u6587\u6863<\/td>\n\u7528 MarkdownHeaderTextSplitter \/ HTMLHeaderTextSplitter<\/td>\n\u5c0a\u91cd\u6587\u6863\u7ed3\u6784，\u80fd\u663e\u8457\u63d0\u5347\u68c0\u7d22\u7cbe\u5ea6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n

    \u5341\u3001\u4ec0\u4e48\u65f6\u5019\u8be5\u7528 LangGraph<\/h3>\n

    create_agent \u8986\u76d6\u4e0d\u4e86\u7684\u573a\u666f，\u5c31\u662f\u8981\u4e0b\u6c89\u5230 LangGraph \u7684\u65f6\u5019\u3002<\/p>\n\n\u9700\u6c42\u7528 create_agent\u7528 LangGraph<\/tr>\n\n\n\n\n\n\n\n\n
    \u6807\u51c6\u5de5\u5177\u5faa\u73af<\/td>\n\u2705<\/td>\n\u2014<\/td>\n<\/tr>\n
    \u81ea\u5b9a\u4e49\u72b6\u6001\u8f6c\u79fb\u3001\u6761\u4ef6\u5206\u652f<\/td>\n\u274c<\/td>\n\u2705<\/td>\n<\/tr>\n
    \u6301\u4e45\u5316 checkpoints（\u751f\u4ea7\u7ea7）<\/td>\n\u26a0\ufe0f \u57fa\u7840\u591f\u7528<\/td>\n\u2705 \u5b8c\u5168\u63a7\u5236<\/td>\n<\/tr>\n
    \u590d\u6742\u8def\u7531 \/ \u957f\u65f6\u8fd0\u884c\u5faa\u73af<\/td>\n\u274c<\/td>\n\u2705<\/td>\n<\/tr>\n
    \u7ec6\u7c92\u5ea6\u6267\u884c\u63a7\u5236（\u6bcf\u6b65\u8017\u65f6）<\/td>\n\u274c<\/td>\n\u2705<\/td>\n<\/tr>\n
    \u591a Agent \u534f\u540c<\/td>\n\u26a0\ufe0f \u90e8\u5206<\/td>\n\u2705<\/td>\n<\/tr>\n
    \u4eba\u5de5\u5ba1\u6279\u3001\u91cd\u8bd5\u3001\u62a4\u680f<\/td>\n\u2705 \u7528 middleware \u5c31\u884c<\/td>\n\u2705<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    💡 \u91cd\u8981\u6f84\u6e05：\u4eba\u5de5\u5ba1\u6279\u3001\u91cd\u8bd5\u3001\u62a4\u680f，\u4ee5\u53ca\u4e00\u90e8\u5206\u591a Agent \u4ea4\u63a5，\u7528\u9ad8\u5c42 middleware \u548c interrupt \u5c31\u80fd\u5b9e\u73b0，\u4e0d\u9700\u8981\u5b9a\u4e49\u56fe\u3002 \u300c\u5148\u7528\u9ad8\u5c42，\u9700\u8981\u65f6\u518d\u4e0b\u6c89\u300d\u662f\u5b98\u65b9\u6307\u5b9a\u7684\u8def\u5f84，\u4e0d\u662f\u7ed5\u8def\u3002<\/p>\n

    LangGraph \u7684\u5b9a\u4f4d：\u5b83\u662f\u4e00\u4e2a\u4f4e\u5c42\u7f16\u6392\u6846\u67b6\u4e0e\u8fd0\u884c\u65f6，\u7528\u4e8e\u6784\u5efa\u957f\u65f6\u95f4\u8fd0\u884c\u3001\u6709\u72b6\u6001\u7684 Agent\u3002\u5b83\u53d7 Pregel \u548c Apache Beam \u542f\u53d1，\u516c\u5f00\u63a5\u53e3\u501f\u9274\u4e86 NetworkX\u3002<\/p>\n

    \u5b83\u89e3\u51b3\u7684\u6b63\u662f LangChain \u649e\u5230\u7684\u5929\u82b1\u677f：<\/p>\n

      \n
    • \u539f AgentExecutor \u8fc7\u4e8e\u72ec\u65ad\u3001\u96be\u4ee5\u5b9a\u5236<\/li>\n
    • \u7ec4\u5408\u591a\u4e2a Agent \u9700\u8981\u5404\u79cd workaround<\/li>\n
    • \u8de8\u8f6e\u6b21\u7684\u72b6\u6001\u662f\u4f60\u81ea\u5df1\u7684\u95ee\u9898<\/li>\n<\/ul>\n

      \u8fd9\u5c31\u662f\u56e2\u961f\u4e3a\u4ec0\u4e48\u8981\u9020 LangGraph，\u5e76\u628a\u6240\u6709\u4e25\u8083\u7684 Agent \u5de5\u4f5c\u90fd\u6307\u5411\u90a3\u91cc\u3002<\/p>\n

      \u7528 LangGraph \u5199\u4e00\u4e2a\u6700\u5c0f\u56fe（\u793a\u610f）：<\/p>\n

      from<\/span> langgraph.<\/span>graph import<\/span> StateGraph,<\/span> MessagesState
      \nfrom<\/span> langgraph.<\/span>checkpoint.<\/span>memory import<\/span> InMemorySaver<\/p>\n

      builder =<\/span> StateGraph(<\/span>MessagesState)<\/span><\/p>\n

      builder.<\/span>add_node(<\/span>"agent"<\/span>,<\/span> call_model)<\/span>
      \nbuilder.<\/span>add_node(<\/span>"tools"<\/span>,<\/span> tool_node)<\/span><\/p>\n

      builder.<\/span>add_edge(<\/span>"__start__"<\/span>,<\/span> "agent"<\/span>)<\/span>
      \nbuilder.<\/span>add_conditional_edges(<\/span>"agent"<\/span>,<\/span> should_continue,<\/span> {<\/span>"tools"<\/span>:<\/span> "tools"<\/span>,<\/span> "end"<\/span>:<\/span> "__end__"<\/span>}<\/span>)<\/span>
      \nbuilder.<\/span>add_edge(<\/span>"tools"<\/span>,<\/span> "agent"<\/span>)<\/span> # \u2190 \u8fd9\u91cc\u5f62\u6210\u4e86\u5faa\u73af<\/span><\/p>\n

      graph =<\/span> builder.<\/span>compile<\/span>(<\/span>checkpointer=<\/span>InMemorySaver(<\/span>)<\/span>)<\/span><\/p>\n

      LangGraph \u5df2\u7ecf\u88ab Klarna\u3001Replit\u3001Elastic \u7b49\u516c\u53f8\u7528\u4e8e\u751f\u4ea7\u3002<\/p>\n

      \n

      \u5341\u4e00\u3001LangSmith：\u53ef\u89c2\u6d4b\u6027\u4e0e\u8bc4\u6d4b<\/h3>\n

      \u6ca1\u6709\u8ffd\u8e2a，\u8c03\u591a\u6b65 Agent \u5c31\u50cf\u5728\u6ca1\u6709\u65e5\u5fd7\u7684\u60c5\u51b5\u4e0b\u8c03\u5206\u5e03\u5f0f\u7cfb\u7edf\u2014\u2014\u80fd\u505a，\u4f46\u6ca1\u5fc5\u8981\u7684\u96be\u3002<\/p>\n

      LangSmith \u662f\u4e00\u4e2a\u6258\u7ba1\u5e73\u53f0，\u63d0\u4f9b：\u8ffd\u8e2a（tracing）\u3001\u8bc4\u6d4b（evaluation）\u3001\u63d0\u793a\u8bcd\u7ba1\u7406\u3001\u76d1\u63a7\u3002<\/p>\n

      \u5b83\u628a LangChain \u5185\u7f6e\u7684 callbacks \u548c\u57cb\u70b9，\u5305\u88c5\u6210\u7edf\u4e00\u7684\u754c\u9762\u3002 \u4e00\u6761 trace \u53ef\u4ee5\u628a\u591a\u6b21\u6a21\u578b\u8c03\u7528\u3001\u5de5\u5177\u8c03\u7528\u3001\u68c0\u7d22\u6b65\u9aa4\u3001\u4e2d\u95f4\u4ef6\u6267\u884c\u3001\u4e2d\u95f4\u8f93\u51fa\u5f52\u5e76\u6210\u4e00\u6761\u53ef\u8c03\u8bd5\u7684\u8bb0\u5f55\u3002<\/p>\n

      #mermaid-svg-iw7GoGbhtZgXMHca{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-iw7GoGbhtZgXMHca .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-iw7GoGbhtZgXMHca .error-icon{fill:#552222;}#mermaid-svg-iw7GoGbhtZgXMHca .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-iw7GoGbhtZgXMHca .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-iw7GoGbhtZgXMHca .marker{fill:#333333;stroke:#333333;}#mermaid-svg-iw7GoGbhtZgXMHca .marker.cross{stroke:#333333;}#mermaid-svg-iw7GoGbhtZgXMHca svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-iw7GoGbhtZgXMHca p{margin:0;}#mermaid-svg-iw7GoGbhtZgXMHca .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-iw7GoGbhtZgXMHca .cluster-label text{fill:#333;}#mermaid-svg-iw7GoGbhtZgXMHca .cluster-label span{color:#333;}#mermaid-svg-iw7GoGbhtZgXMHca .cluster-label span p{background-color:transparent;}#mermaid-svg-iw7GoGbhtZgXMHca .label text,#mermaid-svg-iw7GoGbhtZgXMHca span{fill:#333;color:#333;}#mermaid-svg-iw7GoGbhtZgXMHca .node rect,#mermaid-svg-iw7GoGbhtZgXMHca .node circle,#mermaid-svg-iw7GoGbhtZgXMHca .node ellipse,#mermaid-svg-iw7GoGbhtZgXMHca .node polygon,#mermaid-svg-iw7GoGbhtZgXMHca .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-iw7GoGbhtZgXMHca .rough-node .label text,#mermaid-svg-iw7GoGbhtZgXMHca .node .label text,#mermaid-svg-iw7GoGbhtZgXMHca .image-shape .label,#mermaid-svg-iw7GoGbhtZgXMHca .icon-shape .label{text-anchor:middle;}#mermaid-svg-iw7GoGbhtZgXMHca .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-iw7GoGbhtZgXMHca .rough-node .label,#mermaid-svg-iw7GoGbhtZgXMHca .node .label,#mermaid-svg-iw7GoGbhtZgXMHca .image-shape .label,#mermaid-svg-iw7GoGbhtZgXMHca .icon-shape .label{text-align:center;}#mermaid-svg-iw7GoGbhtZgXMHca .node.clickable{cursor:pointer;}#mermaid-svg-iw7GoGbhtZgXMHca .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-iw7GoGbhtZgXMHca .arrowheadPath{fill:#333333;}#mermaid-svg-iw7GoGbhtZgXMHca .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-iw7GoGbhtZgXMHca .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-iw7GoGbhtZgXMHca .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-iw7GoGbhtZgXMHca .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-iw7GoGbhtZgXMHca .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-iw7GoGbhtZgXMHca .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-iw7GoGbhtZgXMHca .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-iw7GoGbhtZgXMHca .cluster text{fill:#333;}#mermaid-svg-iw7GoGbhtZgXMHca .cluster span{color:#333;}#mermaid-svg-iw7GoGbhtZgXMHca div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-iw7GoGbhtZgXMHca .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-iw7GoGbhtZgXMHca rect.text{fill:none;stroke-width:0;}#mermaid-svg-iw7GoGbhtZgXMHca .icon-shape,#mermaid-svg-iw7GoGbhtZgXMHca .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-iw7GoGbhtZgXMHca .icon-shape p,#mermaid-svg-iw7GoGbhtZgXMHca .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-iw7GoGbhtZgXMHca .icon-shape .label rect,#mermaid-svg-iw7GoGbhtZgXMHca .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-iw7GoGbhtZgXMHca .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-iw7GoGbhtZgXMHca .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-iw7GoGbhtZgXMHca :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

      <\/span><\/p>\n

      <\/span><\/p>\n

      <\/span><\/p>\n

      <\/span><\/p>\n

      <\/span><\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u4e00\u6b21\u7528\u6237\u8bf7\u6c42<\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u4e2d\u95f4\u4ef6<\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u6a21\u578b\u8c03\u7528 1<\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u5de5\u5177\u8c03\u7528<\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u68c0\u7d22<\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u6a21\u578b\u8c03\u7528 2<\/p>\n

      <\/span><\/p>\n

      <\/p>\n

      \u4e00\u6761\u5b8c\u6574 Trace<\/p>\n

      <\/span><\/p>\n

      \u4e09\u4e2a\u4e3b\u8981\u80fd\u529b：<\/p>\n\n\u80fd\u529b\u8bf4\u660e<\/tr>\n\n\n\n\n
      Tracing<\/td>\n\u7aef\u5230\u7aef\u770b\u5230\u6bcf\u4e00\u6b65\u7684\u8f93\u5165\u8f93\u51fa\u3001\u8017\u65f6\u3001token<\/td>\n<\/tr>\n
      Prompt \u7248\u672c\u7ba1\u7406<\/td>\n\u6bd4\u8f83\u6539\u52a8\u3001\u56de\u6eda\u5230\u65e7\u7248\u672c<\/td>\n<\/tr>\n
      \u8bc4\u6d4b<\/td>\n\u5728\u6570\u636e\u96c6\u4e0a\u8dd1\u8bc4\u6d4b，\u5bf9\u53d1\u5e03\u505a\u57fa\u51c6\u3001\u68c0\u6d4b\u56de\u5f52<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u987a\u5e26\u4e00\u63d0：LangSmith \u8fd8\u80fd\u5728\u53ef\u7528\u4fe1\u606f\u8db3\u591f\u65f6，\u6309 trace \/ \u6a21\u578b \/ \u4f1a\u8bdd \/ \u6253\u6807\u7528\u6237\u4f30\u7b97\u6a21\u578b\u6210\u672c\u3002<\/p>\n

      11.1 \u4f46\u8981\u8bf4\u6e05\u695a\u5b83\u7684\u8fb9\u754c<\/h4>\n

      \u2460 \u5b83\u4e0d\u662f\u5546\u4e1a\u667a\u80fd\u7cfb\u7edf\u3002 \u5b83\u4e0d\u4f1a\u66ff\u4ee3\u4f60\u7684\u8ba1\u8d39\u6570\u636e\u5e93\u3001\u8d22\u52a1\u8f6f\u4ef6\u6216\u8425\u6536\u770b\u677f\u3002\u8425\u6536\u3001\u57fa\u7840\u8bbe\u65bd\u6210\u672c\u3001\u5ba2\u6237\u7ea7\u6bdb\u5229\u2014\u2014\u8fd9\u4e9b\u4ecd\u7136\u8981\u4f60\u81ea\u5df1\u7684\u8d26\u5355\u4e0e\u5206\u6790\u7ba1\u9053\u3002<\/p>\n

      \u2461 \u5b83\u4e0d\u662f MIT \u534f\u8bae\u7684\u3002 LangSmith Cloud \u662f\u4e13\u6709\u5546\u4e1a\u670d\u52a1\u3002\u4f01\u4e1a\u5ba2\u6237\u6709 BYOC \u548c\u5b8c\u5168\u81ea\u6258\u7ba1\u9009\u9879（\u542b\u6570\u636e\u9a7b\u7559\u3001\u79c1\u6709\u7f51\u7edc\u3001\u6c14\u9699\u73af\u5883）\u3002<\/p>\n

      \u2462 \u5b83\u4e0d\u662f\u5fc5\u987b\u7684\u3002 \u4f60\u53ef\u4ee5\u7528\u7ed3\u6784\u5316\u65e5\u5fd7\u3001OpenTelemetry\u3001\u81ea\u5efa\u7cfb\u7edf，\u6216\u8fd9\u4e9b\u66ff\u4ee3\u54c1：Langfuse\u3001Helicone\u3001Arize Phoenix（\u7528\u4e4b\u524d\u8bf7\u81ea\u884c\u6838\u5bf9\u5404\u81ea\u7684\u8bb8\u53ef\u8bc1）\u3002<\/p>\n

      🎯 \u5224\u65ad\u6807\u51c6：\u5f53\u300c\u65e0\u6cd5\u89e3\u91ca\u7684\u5931\u8d25\u300d\u7684\u4ee3\u4ef7，\u8d85\u8fc7\u300c\u5f15\u5165\u53e6\u4e00\u4e2a\u6258\u7ba1\u670d\u52a1\u300d\u7684\u4ee3\u4ef7\u65f6，LangSmith \u5c31\u503c\u4e86\u3002<\/p>\n

      \n

      \u5341\u4e8c\u3001\u5e38\u89c1\u95ee\u9898 FAQ<\/h3>\n

      \u8001\u6559\u7a0b\u62a5\u9519\u6392\u67e5（\u6700\u5e38\u88ab\u95ee\u7684\u4e00\u7c7b）<\/h4>\n

      Q1：ImportError: cannot import name 'LLMChain' from 'langchain.chains' \u2192 LLMChain \u5df2\u79fb\u51fa\u4e3b\u5305\u3002\u8fc1\u79fb\u5230 LCEL（\u63a8\u8350），\u6216\u6539\u4ece\u9057\u7559\u5305\u5bfc\u5165：<\/p>\n

      from<\/span> langchain_classic.<\/span>chains import<\/span> LLMChain # \u9700\u8981 pip install langchain-classic<\/span><\/p>\n

      Q2：ImportError: cannot import name 'create_react_agent' \u2192 langgraph.prebuilt.create_react_agent \u5df2\u5f03\u7528\u3002\u6539\u7528：<\/p>\n

      from<\/span> langchain.<\/span>agents import<\/span> create_agent<\/p>\n

      Q3：AgentExecutor \u76f8\u5173\u4ee3\u7801\u5168\u62a5\u9519 \u2192 \u5df2\u5f03\u7528\u3002\u65b0\u9879\u76ee\u8bf7\u76f4\u63a5\u7528 create_agent，\u6216\u76f4\u63a5\u4e0a LangGraph\u3002<\/p>\n

      Q4：No module named 'langchain.text_splitter' \u2192 \u5207\u5206\u5668\u5df2\u72ec\u7acb\u6210\u5305：<\/p>\n

      from<\/span> langchain_text_splitters import<\/span> RecursiveCharacterTextSplitter # pip install langchain-text-splitters<\/span><\/p>\n

      Q5：No module named 'langchain_community' \/ Chroma \u5bfc\u5165\u5931\u8d25 \u2192 \u6309\u9700\u5b89\u88c5\u5bf9\u5e94\u96c6\u6210\u5305，\u5e76\u4f18\u5148\u7528\u4e13\u7528\u5305：<\/p>\n

      pip install<\/span> langchain-chroma<\/p>\n

      from<\/span> langchain_chroma import<\/span> Chroma # \u66ff\u4ee3 langchain_community.vectorstores.Chroma<\/span><\/p>\n

      Q6：ConversationChain \/ ConversationBufferMemory \u627e\u4e0d\u5230 \u2192 \u7528 checkpointer \u6216 RunnableWithMessageHistory \u66ff\u4ee3\u30021.0 \u7684\u63a8\u8350\u505a\u6cd5\u5c31\u662f\u7ed9 create_agent \u4f20 checkpointer\u3002<\/p>\n

      Q7：AttributeError: 'ChatOpenAI' object has no attribute 'chain' \u2192 0.x \u65f6\u4ee3\u7684 .chain() \u5199\u6cd5\u5df2\u4e0d\u5b58\u5728\u3002\u6539\u7528 | \u7ec4\u5408\u3002<\/p>\n

      \n

      \u6982\u5ff5\u4e0e\u4f7f\u7528\u7c7b<\/h4>\n

      Q8：create_agent \u548c LangGraph \u662f\u4ec0\u4e48\u5173\u7cfb？\u5fc5\u987b\u5b66 LangGraph \u5417？ \u2192 create_agent \u5e95\u5c42\u5c31\u662f LangGraph\u3002\u57fa\u7840\u7528\u6cd5\u5b8c\u5168\u4e0d\u9700\u8981\u5b66 LangGraph，\u4f46\u4f60\u4f1a\u767d\u62ff\u5b83\u7684\u6301\u4e45\u5316\u3001\u6d41\u5f0f\u3001\u4eba\u5de5\u5e72\u9884\u3001\u65f6\u95f4\u65c5\u884c\u3002\u9700\u8981\u590d\u6742\u7f16\u6392\u65f6\u518d\u4e0b\u6c89\u3002<\/p>\n

      Q9：model="anthropic:claude-sonnet-4-6" \u8fd9\u79cd\u5b57\u7b26\u4e32\u662f\u600e\u4e48\u8bc6\u522b\u7684？ \u2192 LangChain \u6309 provider:model \u524d\u7f00\u81ea\u52a8\u8def\u7531\u5230\u5bf9\u5e94\u96c6\u6210\u5305\u3002\u524d\u63d0\u662f\u5bf9\u5e94\u5305\u5df2\u5b89\u88c5（\u5982 langchain-anthropic），\u4e14 API Key \u5728\u73af\u5883\u53d8\u91cf\u91cc\u3002\u7528 langchain[anthropic] \u4e00\u6b21\u88c5\u597d\u3002<\/p>\n

      Q10：chain = prompt | model | parser \u4e3a\u4ec0\u4e48\u8dd1\u8d77\u6765\u6ca1\u53cd\u5e94？ \u2192 | \u662f\u60f0\u6027\u7684，\u53ea\u662f\u5b9a\u4e49，\u4e0d\u6267\u884c\u3002 \u5fc5\u987b\u8c03\u7528 .invoke() \/ .stream() \/ .batch() \/ .astream() \u4e4b\u4e00\u3002\u8fd9\u662f\u6700\u9ad8\u9891\u7684\u8bef\u89e3\u3002<\/p>\n

      Q11：.batch() \u4e3a\u4ec0\u4e48\u6bd4 for \u5faa\u73af\u8fd8\u6162？ \u2192 .batch() \u9ed8\u8ba4\u4e0d\u662f\u4f60\u60f3\u8c61\u7684\u5e76\u884c\u3002 \u9700\u8981\u663e\u5f0f\u63d0\u9ad8\u5e76\u53d1\u5ea6：<\/p>\n

      chain.<\/span>batch(<\/span>inputs,<\/span> config=<\/span>{<\/span>"max_concurrency"<\/span>:<\/span> 8<\/span>}<\/span>)<\/span><\/p>\n

      \u8981\u771f\u6b63\u7684\u5f02\u6b65\u5e76\u884c，\u7528 .abatch()\u3002<\/p>\n

      Q12：\u6d41\u5f0f\u8f93\u51fa\u4e3a\u4ec0\u4e48\u53ea\u51fa\u6700\u540e\u4e00\u5927\u6bb5？ \u2192 \u4e2d\u95f4\u67d0\u4e00\u73af\u6ca1\u6709\u6d41\u5f0f\u3002\u5e38\u89c1\u539f\u56e0：\u67d0\u6b65\u7528\u4e86 .invoke()，\u6216\u67d0\u4e2a\u81ea\u5b9a\u4e49 Runnable \u6ca1\u5b9e\u73b0 stream\u3002\u7528 astream_events(…, version="v2") \u770b\u54ea\u4e2a\u73af\u8282\u7f3a\u5c11 on_chat_model_stream \u4e8b\u4ef6，\u8fd9\u662f\u751f\u4ea7\u8c03\u8bd5\u7684\u9996\u9009\u624b\u6bb5\u3002<\/p>\n

      Q13：\u600e\u4e48\u77e5\u9053\u8be5\u7528 create_agent \u8fd8\u662f LangGraph？ \u2192 \u4e00\u53e5\u8bdd：\u6807\u51c6\u5de5\u5177\u5faa\u73af\u7528 create_agent；\u4e00\u65e6\u4f60\u9700\u8981\u300c\u81ea\u5b9a\u4e49\u72b6\u6001 + \u6761\u4ef6\u8df3\u8f6c + \u957f\u65f6\u4efb\u52a1\u300d，\u5c31\u4e0b\u6c89\u5230 LangGraph\u3002<\/p>\n

      Q14：LangChain \u4f1a\u4e0d\u4f1a\u53c8\u641e\u7834\u574f\u6027\u66f4\u65b0？ \u2192 1.0 \u627f\u8bfa\u5728 2.0 \u4e4b\u524d\u4e0d\u505a\u7834\u574f\u6027\u53d8\u66f4\u3002 \u8fd9\u4e5f\u610f\u5473\u7740\u4f60\u73b0\u5728\u5b66\u7684 1.x \u6838\u5fc3 API \u80fd\u7a33\u5b9a\u7528\u4e00\u6bb5\u65f6\u95f4\u2014\u2014\u8fd9\u5bf9\u4e00\u4e2a\u4ee5\u524d\u6bcf\u9694\u51e0\u4e2a\u6708\u5c31\u5d29\u4e00\u6b21\u6559\u7a0b\u7684\u5e93\u6765\u8bf4，\u662f\u6700\u5927\u7684\u6539\u8fdb\u3002<\/p>\n

      Q15：\u6211\u53ef\u4ee5\u53ea\u88c5 langchain-core \u5417？ \u2192 \u53ef\u4ee5\u3002\u5982\u679c\u4f60\u53ea\u60f3\u7528 LCEL \/ Runnable \/ \u6d88\u606f\u7c7b\u578b，\u4e0d\u6d89\u53ca Agent，\u88c5 langchain-core + \u5bf9\u5e94\u7684\u96c6\u6210\u5305\u5373\u53ef\u3002langchain-core \u73b0\u5728\u8fd8\u62c6\u51fa\u4e86 langchain-protocol \u7b49\u66f4\u7ec6\u7684\u5305，\u4f9d\u8d56\u7ed3\u6784\u5728\u6301\u7eed\u7ec6\u5316\u3002<\/p>\n

      \n

      \u5341\u4e09\u3001\u603b\u7ed3<\/h3>\n

      \u4e09\u53e5\u8bdd\u6982\u62ec LangChain \u7684\u73b0\u72b6<\/h4>\n
    • \u5b83\u5df2\u7ecf\u4e0d\u662f\u4e00\u4e2a\u300c\u94fe\u5f0f\u8c03\u7528\u5de5\u5177\u5e93\u300d，\u800c\u662f\u4e00\u4e2a\u300cAgent \u6846\u67b6\u300d\u3002 1.0 \u7684\u8303\u56f4\u6536\u7f29\u4e0d\u662f\u51cf\u6cd5，\u662f\u5b9a\u4f4d\u6f84\u6e05\u2014\u20142023 \u5e74\u8981\u89e3\u51b3\u300c\u600e\u4e48\u62fc\u63d0\u793a\u8bcd\u300d，2026 \u5e74\u8981\u89e3\u51b3\u300c\u600e\u4e48\u8ba9\u6a21\u578b\u5728\u5de5\u5177\u5faa\u73af\u91cc\u5b89\u5168\u5730\u8dd1\u300d\u3002<\/li>\n
    • \u6838\u5fc3\u53ea\u6709\u4e00\u4e2a\u51fd\u6570 create_agent，\u5916\u52a0\u4e00\u5957 middleware\u3002 \u524d\u8005\u8ba9\u4f60 10 \u884c\u8dd1\u901a，\u540e\u8005\u8ba9\u4f60\u5728 Agent \u5faa\u73af\u7684\u516d\u4e2a\u300c\u7f1d\u300d\u4e0a\u505a\u6cbb\u7406\u3002<\/li>\n
    • \u5b83\u5728\u5411 LangGraph \u5206\u5c42：\u9ad8\u5c42\u5f00\u7bb1\u5373\u7528，\u4f4e\u5c42\u5b8c\u5168\u53ef\u63a7\u3002 \u5b98\u65b9\u660e\u786e\u8bf4\u300c\u5148\u7528\u9ad8\u5c42，\u9700\u8981\u65f6\u518d\u4e0b\u6c89\u300d\u662f\u8bbe\u8ba1\u610f\u56fe，\u4e0d\u662f\u6743\u5b9c\u4e4b\u8ba1\u3002<\/li>\n

      \u2705 \u5e94\u8be5\u505a\u7684<\/h4>\n
    • \u65b0\u9879\u76ee\u76f4\u63a5\u4e0a langchain >= 1.4，\u4e0d\u8981\u4ece 0.x \u5f00\u59cb<\/li>\n
    • \u7528 init_chat_model("provider:model") \u83b7\u5f97\u6700\u5927\u7684\u6362\u6a21\u578b\u7075\u6d3b\u6027<\/li>\n
    • \u628a\u5de5\u5177\u7684 docstring \u5f53\u6210 prompt \u6765\u5199\u2014\u2014\u5b83\u4f1a\u76f4\u63a5\u8fdb\u6a21\u578b\u7684\u63d0\u793a\u8bcd<\/li>\n
    • \u751f\u4ea7\u548c\u5f00\u53d1\u7528\u4e0d\u540c\u7684 checkpointer：InMemorySaver \u53ea\u662f\u73a9\u5177，\u751f\u4ea7\u5fc5\u987b\u6301\u4e45\u5316<\/li>\n
    • \u4f18\u5148\u7528 middleware \u89e3\u51b3\u95ee\u9898，\u4e0d\u8981\u6025\u7740 fork \u6216\u5199\u81ea\u5b9a\u4e49\u56fe<\/li>\n
    • \u7ed9 LCEL \u94fe\u914d\u4e0a astream_events \u8c03\u8bd5，\u5426\u5219\u6d41\u5f0f\u95ee\u9898\u4f1a\u8ba9\u4f60\u6000\u7591\u4eba\u751f<\/li>\n
    • \u4e0a\u7ebf\u524d\u5148\u95ee\u81ea\u5df1：\u771f\u7684\u9700\u8981 LangChain \u5417？ \u5355\u6b21\u8c03\u7528\u7528\u5b98\u65b9 SDK \u66f4\u597d<\/li>\n

      \u274c \u4e0d\u8981\u505a\u7684<\/h4>\n
    • \u4e0d\u8981\u7167\u6284 2024 \u5e74\u7684\u6559\u7a0b\u2014\u2014LLMChain\u3001AgentExecutor\u3001create_react_agent \u90fd\u5df2\u5e9f\u5f03\u6216\u79fb\u51fa<\/li>\n
    • \u4e0d\u8981\u628a langchain \u5f53\u6210\u4e00\u4e2a\u5305\u2014\u2014\u5b83\u662f core + \u4e3b\u5305 + \u51e0\u5341\u4e2a\u96c6\u6210\u5305<\/li>\n
    • \u4e0d\u8981\u5728\u751f\u4ea7\u7528 InMemorySaver<\/li>\n
    • \u4e0d\u8981\u5fd8\u4e86\u8c03\u7528 .invoke() \u5c31\u5f00\u59cb\u6000\u7591\u73af\u5883<\/li>\n
    • \u4e0d\u8981\u4e3a\u4e86\u300c\u7528\u6846\u67b6\u300d\u800c\u7528\u6846\u67b6\u2014\u2014\u80f6\u6c34\u4ee3\u7801\u4e0d\u5230 50 \u884c，\u88f8 SDK \u66f4\u6e05\u723d<\/li>\n
    • \u4e0d\u8981\u5047\u8bbe .batch() \u4e00\u5b9a\u5e76\u884c，\u663e\u5f0f\u8bbe\u7f6e max_concurrency<\/li>\n

      🎯 \u6700\u540e\u4e00\u53e5<\/h4>\n

      LangChain \u7684\u4ef7\u503c\u4e0d\u5728\u4e8e\u5b83\u300c\u80fd\u505a\u4ec0\u4e48\u300d，\u800c\u5728\u4e8e\u5b83\u300c\u5e2e\u4f60\u7701\u6389\u4e86\u4ec0\u4e48\u300d\u3002 \u5b83\u7701\u6389\u7684\u662f：\u4e3a\u6bcf\u79cd\u6a21\u578b\u91cd\u5199\u8c03\u7528\u4ee3\u7801\u3001\u81ea\u5df1\u5b9e\u73b0\u6d41\u5f0f\u4e0e\u5e76\u53d1\u3001\u81ea\u5df1\u642d\u5de5\u5177\u8c03\u7528\u534f\u8bae\u3001\u81ea\u5df1\u8bbe\u8ba1 Agent \u5faa\u73af\u3001\u81ea\u5df1\u62fc\u53ef\u89c2\u6d4b\u6027\u3002\u8fd9\u4e9b\u4e8b\u4f60\u90fd\u80fd\u81ea\u5df1\u505a，\u4f46\u505a\u5b8c\u4e4b\u540e\u4f60\u4f1a\u53d1\u73b0，\u4f60\u5199\u7684\u5c31\u662f\u4e00\u4e2a\u66f4\u5dee\u7684 LangChain\u3002 \u2014\u2014\u800c\u5b83\u7684\u8fb9\u754c\u540c\u6837\u6e05\u6670：\u5355\u6b21\u8c03\u7528\u522b\u7528\u5b83，\u8d85\u590d\u6742\u72b6\u6001\u673a\u7528 LangGraph\u3002<\/p>\n

      \n

      📚 \u53c2\u8003\u8d44\u6599\u4e0e\u6570\u636e\u8bf4\u660e<\/h3>\n
        \n
      • \u5b98\u65b9\u6587\u6863：https:\/\/docs.langchain.com\/oss\/python\/langchain\/overview<\/li>\n
      • API Reference：https:\/\/reference.langchain.com\/python\/langchain\/langchain\/<\/li>\n
      • LangChain v1 \u65b0\u7279\u6027（\u4e2d\u6587）：https:\/\/langchain-doc.cn\/v1\/python\/langchain\/releases\/langchain-v1.html<\/li>\n
      • \u5b98\u65b9 Quickstart：https:\/\/docs.langchain.com\/oss\/python\/langchain\/quickstart<\/li>\n
      • LangGraph \u6587\u6863：https:\/\/docs.langchain.com\/oss\/python\/langgraph\/overview<\/li>\n
      • Retrieval \/ RAG \u6587\u6863：https:\/\/docs.langchain.com\/oss\/python\/langchain\/retrieval<\/li>\n
      • PyPI：langchain \/ langchain-core \/ langgraph<\/li>\n
      • GitHub：https:\/\/github.com\/langchain-ai\/langchain\u3001https:\/\/github.com\/langchain-ai\/langgraph<\/li>\n
      • \u5b98\u65b9\u514d\u8d39\u8bfe\u7a0b：LangChain Academy https:\/\/academy.langchain.com\/<\/li>\n<\/ul>\n

        \u7248\u672c\u4e0e\u6570\u636e\u8bf4\u660e：\u672c\u6587\u7248\u672c\u53f7\u3001\u4f9d\u8d56\u4fe1\u606f\u4e0e Star \u6570\u53d6\u81ea PyPI \u4e0e GitHub \u4e8e 2026-09-21 \u81f3 2026-09-26 \u7684\u6570\u636e： langchain 1.4.2（2026-09-19）\u3001langchain-core 1.6.0（2026-08-19）\u3001langgraph 1.2.12（2026-09-21）\u3002 LangChain \u5904\u4e8e\u5feb\u901f\u8fed\u4ee3\u671f，\u672c\u6587\u4ee3\u7801\u57fa\u4e8e 1.x \u63a5\u53e3\u7f16\u5199，\u4f46\u90e8\u5206\u96c6\u6210\u5305\u7684\u5bfc\u5165\u8def\u5f84\u53ef\u80fd\u968f\u7248\u672c\u5fae\u8c03，\u843d\u5730\u524d\u8bf7\u4ee5\u5b98\u65b9\u6587\u6863\u4e3a\u51c6\u3002\u793a\u4f8b\u4e2d\u7684\u6a21\u578b\u540d（\u5982 gpt-5.5\u3001claude-sonnet-4-6）\u6765\u81ea\u5b98\u65b9\u6587\u6863\u793a\u4f8b，\u8bf7\u66ff\u6362\u4e3a\u4f60\u8d26\u53f7\u5b9e\u9645\u53ef\u7528\u7684\u6a21\u578b\u3002<\/p>\n

        \n

        \u5982\u679c\u8fd9\u7bc7\u6307\u5357\u5bf9\u4f60\u6709\u5e2e\u52a9，\u6b22\u8fce\u70b9\u8d5e + \u6536\u85cf\u3002\u9700\u8981\u7684\u8bdd\u6211\u53ef\u4ee5\u7ee7\u7eed\u62c6\u89e3 LangGraph \u72b6\u6001\u7ba1\u7406\u5b9e\u6218\u3001LangChain + MCP \u5de5\u5177\u63a5\u5165，\u6216\u8005 \u57fa\u4e8e LangChain \u7684\u672c\u5730\u77e5\u8bc6\u5e93\u5b8c\u6574\u9879\u76ee\u2014\u2014\u8bc4\u8bba\u533a\u544a\u8bc9\u6211\u4f60\u60f3\u5148\u770b\u54ea\u4e2a\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

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