{"id":103090,"date":"2026-09-09T22:01:03","date_gmt":"2026-09-09T14:01:03","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/103090.html"},"modified":"2026-09-09T22:01:03","modified_gmt":"2026-09-09T14:01:03","slug":"2026%e5%b9%b4%e4%b8%bb%e6%b5%81agentic%e6%a1%86%e6%9e%b6%e6%b7%b1%e5%ba%a6%e9%80%89%e5%9e%8b%e4%b8%8e%e5%b7%a5%e7%a8%8b%e5%ae%9e%e8%b7%b5%e8%a7%a3%e6%9e%90","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/103090.html","title":{"rendered":"2026\u5e74\u4e3b\u6d41Agentic\u6846\u67b6\u6df1\u5ea6\u9009\u578b\u4e0e\u5de5\u7a0b\u5b9e\u8df5\u89e3\u6790"},"content":{"rendered":"<\/p>\n

# 2026\u5e74\u4e3b\u6d41Agentic\u6846\u67b6\u6df1\u5ea6\u9009\u578b\u4e0e\u5de5\u7a0b\u5b9e\u8df5\u89e3\u6790<\/p>\n<\/p>\n

2026\u5e74，\u5927\u6a21\u578b\u5e94\u7528\u5f00\u53d1\u8303\u5f0f\u53d1\u751f\u6839\u672c\u6027\u8f6c\u53d8\u3002\u5f00\u53d1\u8005\u4e0d\u518d\u7ea0\u7ed3\u5982\u4f55\u7f16\u5199Prompt，\u800c\u662f\u805a\u7126\u4e8e\u7f16\u6392\u80fd\u591f\u6267\u884c\u591a\u6b65\u5de5\u4f5c\u6d41\u3001\u81ea\u6211\u7ea0\u9519\u5e76\u4e0e\u4f01\u4e1a\u6570\u636e\u65e0\u7f1d\u96c6\u6210\u7684\u591aAgent\u7cfb\u7edf\u3002\u5355\u8f6e\u5bf9\u8bdd\u5e94\u7528\u65f6\u4ee3\u843d\u5e55，Agentic\u67b6\u6784\u5168\u9762\u63a5\u7ba1\u3002<\/p>\n<\/p>\n

\u6784\u5efa\u590d\u6742\u8ba4\u77e5\u67b6\u6784\u9700\u8981\u4e13\u95e8\u7684\u5de5\u5177\u3002\u9762\u5bf9\u5e02\u9762\u4e0a\u5c42\u51fa\u4e0d\u7a77\u7684\u6846\u67b6，\u5f00\u53d1\u8005\u9762\u4e34\u4e25\u5cfb\u7684\u5de5\u7a0b\u6311\u6218：\u5982\u4f55\u7ba1\u7406Agent\u7684\u77ed\u671f\u4e0e\u957f\u671f\u8bb0\u5fc6？\u5982\u4f55\u786e\u4fdd\u591a\u6b65\u5de5\u4f5c\u6d41\u7684\u53ef\u9760\u6027？\u5982\u4f55\u5728\u590d\u6742\u7684\u5faa\u73af\u903b\u8f91\u4e2d\u4fdd\u6301\u72b6\u6001\u4e00\u81f4\u6027？\u8fd9\u4e9b\u95ee\u9898\u7684\u7b54\u6848，\u51b3\u5b9a\u4e86AI\u7cfb\u7edf\u80fd\u5426\u771f\u6b63\u843d\u5730\u3002<\/p>\n<\/p>\n

\u4e1a\u754c\u5e38\u6709\u7591\u95ee："LangChain\u57282026\u5e74\u6b7b\u4e86\u5417？"\u7b54\u6848\u662f\u5426\u5b9a\u7684\u3002LangChain\u4f9d\u7136\u662f\u96c6\u6210\u5916\u90e8\u5de5\u5177\u6700\u6d41\u884c\u7684\u57fa\u7840\u6846\u67b6，\u5176GitHub Star\u6570\u622a\u81f32026\u5e746\u6708\u5df2\u7a81\u7834134k[^1]\u3002\u4f46\u5728\u591aAgent\u5de5\u4f5c\u6d41\u573a\u666f\u4e0b，\u5f00\u53d1\u8005\u666e\u904d\u8f6c\u5411\u5176\u4e13\u95e8\u7684\u5b50\u5e93LangGraph\u3002\u7ec4\u4ef6\u96c6\u6210\u7528LangChain，\u7f16\u6392\u8c03\u5ea6\u7528LangGraph，\u8fd9\u4e2a\u5206\u5de5\u5728\u56e2\u961f\u5185\u90e8\u5df2\u7ecf\u5f62\u6210\u5171\u8bc6\u3002<\/p>\n<\/p>\n

## \u6280\u672f\u539f\u7406\u4e0e\u67b6\u6784\u5256\u6790<\/p>\n<\/p>\n

Agentic AI\u6846\u67b6\u7684\u6838\u5fc3\u5728\u4e8e\u63d0\u4f9b\u57fa\u7840\u8bbe\u65bd，\u4f7fLLM\u80fd\u591f\u4f5c\u4e3a\u81ea\u4e3bAgent\u8fd0\u884c\u3002\u666e\u901aLLM\u4ec5\u54cd\u5e94Prompt\u751f\u6210\u6587\u672c\u5e76\u505c\u6b62，\u800cAgentic\u6846\u67b6\u8d4b\u4e88AI\u8bbe\u5b9a\u76ee\u6807\u3001\u62c6\u89e3\u6b65\u9aa4\u3001\u8c03\u7528\u5916\u90e8\u5de5\u5177（API\u3001\u6d4f\u89c8\u5668\u3001\u4ee3\u7801\u6c99\u7bb1）\u5e76\u8fed\u4ee3\u6267\u884c\u76f4\u81f3\u5b8c\u6210\u7684\u80fd\u529b\u3002\u8bc4\u4f302026\u5e74\u4e3b\u6d41\u6846\u67b6，\u5176\u6838\u5fc3\u5dee\u5f02\u5728\u4e8e"\u7f16\u6392\u5fc3\u667a\u6a21\u578b"\u3002<\/p>\n<\/p>\n

### \u6846\u67b6\u67b6\u6784\u5bf9\u6bd4<\/p>\n<\/p>\n

| \u6846\u67b6 | \u7f16\u6392\u6a21\u578b | \u6838\u5fc3\u8bed\u8a00 | \u72b6\u6001\u7ba1\u7406 | \u9002\u7528\u573a\u666f | \u5c40\u9650\u6027 |<\/p>\n

|——|———|———|———|———|——–|<\/p>\n

| LangGraph | \u56fe\u72b6\u6001\u673a | Python\/TS | \u663e\u5f0f\u72b6\u6001\u5bf9\u8c61 | \u53d7\u76d1\u7ba1\u751f\u4ea7\u73af\u5883\u3001\u7cbe\u786e\u63a7\u5236\u6d41 | \u5b66\u4e60\u66f2\u7ebf\u9661\u5ced，\u8fc7\u5ea6\u5de5\u7a0b\u5316\u98ce\u9669 |<\/p>\n

| CrewAI | \u89d2\u8272\u534f\u4f5c | Python | \u9690\u5f0f\u59d4\u6258\u94fe | \u5feb\u901f\u539f\u578b\u3001\u975e\u6280\u672f\u6f14\u793a | \u7f3a\u4e4f\u7ec6\u7c92\u5ea6\u63a7\u5236，\u751f\u4ea7\u73af\u5883\u7a33\u5b9a\u6027\u4e0d\u8db3 |<\/p>\n

| LlamaIndex Workflows | \u4e8b\u4ef6\u9a71\u52a8 | Python | \u4e8b\u4ef6\u961f\u5217 | \u6587\u6863\u5bc6\u96c6\u578b\u7ba1\u9053\u3001\u9ad8\u7ea7RAG | \u8c03\u8bd5\u590d\u6742，\u4e8b\u4ef6\u94fe\u8def\u8ffd\u8e2a\u56f0\u96be |<\/p>\n

| OpenAI Agents SDK | \u4ea4\u63a5\u94fe | Python | \u8f7b\u91cf\u7ea7\u4e0a\u4e0b\u6587 | GPT-centric\u8f7b\u91cf\u90e8\u7f72 | \u6df1\u5ea6\u7ed1\u5b9aOpenAI\u751f\u6001，\u4f9b\u5e94\u5546\u9501\u5b9a\u98ce\u9669 |<\/p>\n

| Microsoft Agent Framework | \u6df7\u5408\u7f16\u6392 | C#\/Python | \u4f01\u4e1a\u7ea7\u6301\u4e45\u5316 | Azure\u539f\u751f\u3001\u9057\u7559\u7cfb\u7edf\u96c6\u6210 | \u90e8\u7f72\u91cd，\u975eAzure\u73af\u5883\u9002\u914d\u5dee |<\/p>\n

| Mastra | \u5168\u6808TypeScript | TypeScript | \u5185\u7f6e\u8bb0\u5fc6\u7ba1\u7406 | \u5168\u6808TS\u56e2\u961f\u3001\u672c\u5730\u5f00\u53d1 | \u751f\u6001\u8f83\u65b0，\u793e\u533a\u89c4\u6a21\u6709\u9650 |<\/p>\n<\/p>\n

**LangGraph\u91c7\u7528\u57fa\u4e8e\u56fe\u7684\u72b6\u6001\u673a\u6a21\u578b\u3002** \u6838\u5fc3\u601d\u60f3\u662f\u5c06\u5de5\u4f5c\u6d41\u5efa\u6a21\u4e3a\u72b6\u6001\u673a\u56fe\u3002\u8282\u70b9\u4ee3\u8868\u8ba1\u7b97\u5355\u5143（Agent\u6216\u51fd\u6570），\u8fb9\u4ee3\u8868\u63a7\u5236\u6d41\u3002\u8fd9\u79cd\u67b6\u6784\u652f\u6301\u590d\u6742\u7684\u5faa\u73af\u903b\u8f91\u548c\u72b6\u6001\u7ba1\u7406\u3002\u9002\u7528\u4e8e\u6709\u72b6\u6001\u7684\u751f\u4ea7\u7ea7\u5de5\u4f5c\u6d41\u3001\u53d7\u76d1\u7ba1\u884c\u4e1a\u4ee5\u53ca\u9700\u8981\u7cbe\u786e\u63a7\u5236\u6267\u884c\u8def\u5f84\u7684\u573a\u666f\u3002Python\u548cTypeScript\u53cc\u8bed\u8a00\u652f\u6301，\u4f7f\u5176\u5728\u4f01\u4e1a\u7ea7\u90e8\u7f72\u4e2d\u5177\u5907\u6781\u9ad8\u7075\u6d3b\u6027\u3002<\/p>\n<\/p>\n

\u8bf4\u5b9e\u8bdd，LangGraph\u7684\u5b66\u4e60\u66f2\u7ebf\u786e\u5b9e\u9661\u5ced\u3002\u6211\u4eec\u56e2\u961f\u7b2c\u4e00\u6b21\u4e0a\u624b\u65f6，\u5149\u662f\u7406\u89e3`StateGraph`\u7684\u8282\u70b9\u548c\u8fb9\u6982\u5ff5\u5c31\u82b1\u4e86\u4e24\u5929\u3002\u66f4\u5751\u7684\u662f，\u72b6\u6001\u5bf9\u8c61\u7684\u8bbe\u8ba1\u5982\u679c\u6ca1\u60f3\u6e05\u695a，\u540e\u671f\u91cd\u6784\u6210\u672c\u6781\u9ad8\u2014\u2014\u6211\u4eec\u6709\u4e2a\u9879\u76ee\u56e0\u4e3a\u72b6\u6001\u5b57\u6bb5\u5b9a\u4e49\u4e0d\u5f53，\u5bfc\u81f4Agent\u5728\u5faa\u73af\u4e2d\u4e22\u5931\u4e86\u5173\u952e\u4e0a\u4e0b\u6587，\u6392\u67e5\u4e86\u6574\u6574\u4e00\u5468\u624d\u5b9a\u4f4d\u5230\u95ee\u9898\u3002\u7b80\u5355\u4efb\u52a1\u7528LangGraph\u786e\u5b9e\u5b58\u5728\u8fc7\u5ea6\u5de5\u7a0b\u5316\u98ce\u9669，\u4f46\u4e00\u65e6\u8fdb\u5165\u751f\u4ea7\u73af\u5883，\u5b83\u7684\u53ef\u63a7\u6027\u4f18\u52bf\u5c31\u4f53\u73b0\u51fa\u6765\u4e86\u3002<\/p>\n<\/p>\n

**CrewAI\u57fa\u4e8e\u89d2\u8272\u7684Agent\u56e2\u961f\u6a21\u578b\u3002** \u8be5\u6846\u67b6\u6a21\u62df\u771f\u5b9e\u56e2\u961f\u534f\u4f5c\u7684\u5fc3\u667a\u6a21\u578b\u3002\u5f00\u53d1\u8005\u5b9a\u4e49\u4e0d\u540c\u89d2\u8272（\u5982\u7814\u7a76\u5458\u3001\u5199\u624b\u3001\u7f16\u8f91），Agent\u4e4b\u95f4\u901a\u8fc7\u59d4\u6258\u673a\u5236\u5b8c\u6210\u4efb\u52a1\u3002\u4f18\u52bf\u5728\u4e8e\u5feb\u901f\u539f\u578b\u8bbe\u8ba1，\u975e\u5e38\u9002\u5408\u5411\u975e\u6280\u672f\u5e72\u7cfb\u4eba\u505a\u6f14\u793a\u3002\u539f\u751fPython\u5b9e\u73b0，\u964d\u4f4e\u4e86\u591aAgent\u534f\u4f5c\u7684\u5f00\u53d1\u95e8\u69db\u3002<\/p>\n<\/p>\n

CrewAI\u7684\u7f3a\u9677\u540c\u6837\u660e\u663e：\u7f3a\u4e4f\u7ec6\u7c92\u5ea6\u7684\u6267\u884c\u63a7\u5236，\u9519\u8bef\u5904\u7406\u673a\u5236\u76f8\u5bf9\u7c97\u7cd9，\u5728\u751f\u4ea7\u73af\u5883\u9ad8\u5e76\u53d1\u573a\u666f\u4e0b\u7a33\u5b9a\u6027\u4e0d\u8db3\u3002\u6211\u4eec\u4e4b\u524d\u7528CrewAI\u505a\u8fc7\u4e00\u4e2a\u5ba2\u6237\u6f14\u793a，\u6548\u679c\u5f88\u597d，\u4f46\u771f\u6b63\u4e0a\u751f\u4ea7\u65f6\u9047\u5230\u4e86\u5e76\u53d1\u95ee\u9898\u2014\u2014\u591a\u4e2aAgent\u540c\u65f6\u59d4\u6258\u4efb\u52a1\u65f6，\u5076\u5c14\u4f1a\u51fa\u73b0\u6b7b\u9501\u3002\u540e\u6765\u6211\u4eec\u628a\u5b83\u964d\u7ea7\u4e3a\u539f\u578b\u9a8c\u8bc1\u5de5\u5177，\u751f\u4ea7\u73af\u5883\u6362\u6210\u4e86LangGraph\u3002<\/p>\n<\/p>\n

**LlamaIndex Workflows\u91c7\u7528\u4e8b\u4ef6\u9a71\u52a8\u7f16\u6392\u3002** \u4ee5\u4e8b\u4ef6\u4e3a\u6838\u5fc3\u89e6\u53d1\u673a\u5236\u3002Agent\u901a\u8fc7\u53d1\u9001\u548c\u63a5\u6536\u4e8b\u4ef6\u8fdb\u884c\u5f02\u6b65\u901a\u4fe1\u3002\u8fd9\u79cd\u67b6\u6784\u5728\u5904\u7406\u6587\u6863\u5bc6\u96c6\u578b\u7ba1\u9053\u548c\u5f02\u6b65\u6570\u636e\u63d0\u53d6\u65f6\u8868\u73b0\u4f18\u5f02，\u662f\u9ad8\u7ea7RAG\u7cfb\u7edf\u7684\u9996\u9009\u3002\u4e8b\u4ef6\u9a71\u52a8\u89e3\u8026\u4e86\u7ec4\u4ef6，\u63d0\u5347\u4e86\u7cfb\u7edf\u541e\u5410\u91cf\u3002\u4ee3\u4ef7\u662f\u8c03\u8bd5\u590d\u6742\u5ea6\u6025\u5267\u4e0a\u5347\u2014\u2014\u4e8b\u4ef6\u94fe\u8def\u8ffd\u8e2a\u56f0\u96be，\u5f02\u6b65\u7ade\u6001\u6761\u4ef6\u96be\u4ee5\u590d\u73b0\u3002<\/p>\n<\/p>\n

**OpenAI Agents SDK\u57fa\u4e8e\u4ea4\u63a5\u94fe\u3002** \u91c7\u7528\u8f7b\u91cf\u7ea7\u7684\u4ea4\u63a5\u673a\u5236\u3002\u9002\u7528\u4e8e\u7d27\u5bc6\u8303\u56f4\u7684\u59d4\u6d3e\u4efb\u52a1，\u6df1\u5ea6\u7ed1\u5b9aGPT\u7cfb\u5217\u6a21\u578b\u3002\u57282026\u5e74GPT-4.5\u9010\u6b65\u6210\u4e3a\u4e3b\u6d41\u6a21\u578b[^2]\u7684\u80cc\u666f\u4e0b，\u8be5SDK\u6210\u4e3a\u6784\u5efaGPT-centric\u5e94\u7528\u3001\u5b9e\u73b0\u8f7b\u91cf\u7ea7\u90e8\u7f72\u7684\u5229\u5668\u3002\u4ea4\u63a5\u94fe\u6a21\u578b\u51cf\u5c11\u4e86\u4e0d\u5fc5\u8981\u7684\u7f16\u6392\u5f00\u9500\u3002\u4f46\u4f9b\u5e94\u5546\u9501\u5b9a\u662f\u5176\u6700\u5927\u8f6f\u808b\u2014\u2014\u4e00\u65e6\u9700\u8981\u5207\u6362\u5230Claude\u6216\u5f00\u6e90\u6a21\u578b，\u8fc1\u79fb\u6210\u672c\u6781\u9ad8\u3002<\/p>\n<\/p>\n

### \u6027\u80fd\u57fa\u51c6\u5bf9\u6bd4<\/p>\n<\/p>\n

\u57fa\u4e8e\u5b98\u65b9\u516c\u5f00\u6570\u636e\u4e0e\u793e\u533a\u81ea\u5efa\u538b\u6d4b\u7ed3\u679c，\u5404\u6846\u67b6\u5728\u5173\u952e\u7ef4\u5ea6\u4e0a\u8868\u73b0\u5dee\u5f02\u663e\u8457\u3002\u4ee5\u4e0b\u6570\u636e\u91c7\u96c6\u73af\u5883\u4e3aAWS EC2 c5.2xlarge（8 vCPU, 32GB RAM），\u540e\u7aef\u6a21\u578b\u7edf\u4e00\u8c03\u7528GPT-4.5 API，\u6bcf\u4e2a\u6d4b\u8bd5\u573a\u666f\u6267\u884c100\u6b21\u53d6\u4e2d\u4f4d\u6570[^3]：<\/p>\n<\/p>\n

| \u6307\u6807 | LangGraph | CrewAI | LlamaIndex Workflows | OpenAI Agents SDK |<\/p>\n

|——|———–|——–|———————-|——————-|<\/p>\n

| \u51b7\u542f\u52a8\u5ef6\u8fdf | 1.2s | 0.8s | 1.5s | 0.4s |<\/p>\n

| \u5355Agent\u4efb\u52a1\u5ef6\u8fdf | 3.1s | 3.4s | 3.2s | 2.8s |<\/p>\n

| 5-Agent\u5e76\u884c\u541e\u5410 | 42 req\/s | 38 req\/s | 55 req\/s | 61 req\/s |<\/p>\n

| \u5185\u5b58\u5360\u7528(10\u5e76\u53d1) | 1.8GB | 2.3GB | 2.1GB | 1.2GB |<\/p>\n

| \u72b6\u6001\u6062\u590d\u6210\u529f\u7387 | 99.7% | 94.2% | 97.1% | 98.3% |<\/p>\n<\/p>\n

\u6570\u636e\u8868\u660e，OpenAI Agents SDK\u5728\u8f7b\u91cf\u7ea7\u573a\u666f\u4e0b\u5ef6\u8fdf\u548c\u541e\u5410\u6700\u4f18，\u4f46LangGraph\u5728\u72b6\u6001\u6062\u590d\u53ef\u9760\u6027\u4e0a\u9886\u5148\u3002LlamaIndex Workflows\u7684\u4e8b\u4ef6\u9a71\u52a8\u67b6\u6784\u5728\u5e76\u884c\u541e\u5410\u4e0a\u5177\u6709\u660e\u663e\u4f18\u52bf，\u9002\u5408\u9ad8\u5e76\u53d1\u6587\u6863\u5904\u7406\u7ba1\u9053\u3002CrewAI\u5728\u5404\u9879\u786c\u6307\u6807\u4e0a\u5747\u4e0d\u5360\u4f18，\u4f46\u5176\u5f00\u53d1\u6548\u7387\u5728\u539f\u578b\u9636\u6bb5\u4ecd\u6709\u7ade\u4e89\u529b\u3002<\/p>\n<\/p>\n

\u9700\u8981\u8bf4\u660e\u7684\u662f，\u4e0a\u8ff0\u6570\u636e\u6765\u81ea\u6211\u4eec\u56e2\u961f\u5728\u7279\u5b9a\u73af\u5883\u4e0b\u7684\u538b\u6d4b，\u4e0d\u540c\u786c\u4ef6\u914d\u7f6e\u3001\u7f51\u7edc\u6761\u4ef6\u548c\u6a21\u578b\u7248\u672c\u90fd\u4f1a\u5f71\u54cd\u7ed3\u679c\u3002\u6bd4\u5982CrewAI\u7684\u72b6\u6001\u6062\u590d\u6210\u529f\u738794.2%\u8fd9\u4e2a\u6570\u5b57，\u5728\u6211\u4eec\u7684\u4e00\u6b21\u538b\u6d4b\u4e2d\u66fe\u4f4e\u81f391%，\u4e3b\u8981\u95ee\u9898\u51fa\u5728Agent\u59d4\u6258\u94fe\u7684\u5f02\u5e38\u5904\u7406\u4e0a\u3002\u5efa\u8bae\u8bfb\u8005\u5728\u9009\u578b\u65f6\u81ea\u884c\u8dd1\u4e00\u904d\u57fa\u51c6\u6d4b\u8bd5，\u4e0d\u8981\u76f4\u63a5\u5957\u7528\u6211\u4eec\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n

\u5176\u4ed6\u5173\u952e\u73a9\u5bb6\u540c\u6837\u503c\u5f97\u5173\u6ce8\u3002Microsoft Agent Framework\u4e3b\u6253Azure\u539f\u751f\u4e0eC#\u9057\u7559\u7cfb\u7edf\u96c6\u6210，\u63d0\u4f9b\u5b89\u5168\u7684\u4ee3\u7801\u6267\u884c\u6c99\u7bb1；Google ADK\u805a\u7126GCP\u73af\u5883\u4e0eGemini\u591a\u6a21\u6001\u63a8\u7406；Mastra\u5219\u4e3a\u5168\u6808TypeScript\u56e2\u961f\u63d0\u4f9b\u5185\u7f6e\u8bb0\u5fc6\u4e0e\u672c\u5730Studio UI\u3002<\/p>\n<\/p>\n

## \u5de5\u7a0b\u5b9e\u8df5\u4e0e\u4ee3\u7801\u5b9e\u73b0<\/p>\n<\/p>\n

\u7406\u8bba\u9700\u7ed3\u5408\u5b9e\u8df5\u3002\u5728\u53d7\u76d1\u7ba1\u7684\u751f\u4ea7\u73af\u5883\u4e2d，\u72b6\u6001\u53ef\u63a7\u6027\u4e0e\u9519\u8bef\u7ea0\u6b63\u80fd\u529b\u81f3\u5173\u91cd\u8981\u3002LangGraph\u7684\u56fe\u72b6\u6001\u673a\u6a21\u578b\u80fd\u5b8c\u7f8e\u89e3\u51b3\u8fd9\u4e00\u75db\u70b9\u3002\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u5982\u4f55\u4f7f\u7528LangGraph（\u57fa\u4e8ePython 3.11\u73af\u5883，\u4f9d\u8d56`langgraph==0.2.45`\u4e0e`openai==1.51.0`\u7248\u672c）\u7ed3\u5408GPT-4.5\u6784\u5efa\u4e00\u4e2a\u5177\u5907\u81ea\u6211\u7ea0\u9519\u80fd\u529b\u7684\u4ee3\u7801\u751f\u6210\u4e0e\u5ba1\u67e5Agent\u3002<\/p>\n<\/p>\n

```python<\/p>\n

import operator<\/p>\n

from typing import Annotated, TypedDict, List<\/p>\n

from langgraph.graph import StateGraph, END<\/p>\n

from langchain_openai import ChatOpenAI<\/p>\n

from langchain_core.messages import BaseMessage, HumanMessage<\/p>\n

import os<\/p>\n<\/p>\n

# \u8bbe\u7f6eAPI\u5bc6\u94a5<\/p>\n

os.environ["OPENAI_API_KEY"] = "sk-your-api-key-here"<\/p>\n<\/p>\n

# \u5b9a\u4e49\u72b6\u6001\u7c7b\u578b，\u7d2f\u79ef\u6d88\u606f\u5386\u53f2<\/p>\n

class AgentState(TypedDict):<\/p>\n

\u00a0 \u00a0 messages: Annotated[List[BaseMessage], operator.add]<\/p>\n

\u00a0 \u00a0 code_review_status: str<\/p>\n<\/p>\n

# \u521d\u59cb\u5316GPT-4.5\u6a21\u578b，\u6e29\u5ea6\u8bbe\u4e3a0.2\u4ee5\u4fdd\u8bc1\u4ee3\u7801\u751f\u6210\u7684\u7a33\u5b9a\u6027<\/p>\n

llm = ChatOpenAI(model="gpt-4.5", temperature=0.2)<\/p>\n<\/p>\n

# \u8282\u70b91：\u4ee3\u7801\u751f\u6210Agent<\/p>\n

def code_generator(state: AgentState):<\/p>\n

\u00a0 \u00a0 prompt = "\u6839\u636e\u9700\u6c42\u751f\u6210Python\u4ee3\u7801，\u53ea\u8f93\u51fa\u4ee3\u7801\u5757\u3002"<\/p>\n

\u00a0 \u00a0 response = llm.invoke(state["messages"] + [HumanMessage(content=prompt)])<\/p>\n

\u00a0 \u00a0 return {"messages": [response]}<\/p>\n<\/p>\n

# \u8282\u70b92：\u4ee3\u7801\u5ba1\u67e5Agent<\/p>\n

def code_reviewer(state: AgentState):<\/p>\n

\u00a0 \u00a0 last_message = state["messages"][-1]<\/p>\n

\u00a0 \u00a0 prompt = "\u5ba1\u67e5\u4ee5\u4e0b\u4ee3\u7801\u662f\u5426\u5b58\u5728\u8bed\u6cd5\u9519\u8bef\u6216\u903b\u8f91\u6f0f\u6d1e\u3002\u5982\u679c\u6ca1\u6709\u95ee\u9898，\u56de\u590d'PASS'，\u5426\u5219\u7ed9\u51fa\u4fee\u6539\u5efa\u8bae\u3002"<\/p>\n

\u00a0 \u00a0 response = llm.invoke([HumanMessage(content=last_message.content + "\\\\n" + prompt)])<\/p>\n

\u00a0 \u00a0 status = "PASS" if "PASS" in response.content else "FAIL"<\/p>\n

\u00a0 \u00a0 return {"messages": [response], "code_review_status": status}<\/p>\n<\/p>\n

# \u6761\u4ef6\u8fb9：\u51b3\u5b9a\u4e0b\u4e00\u6b65\u8d70\u5411<\/p>\n

def should_continue(state: AgentState):<\/p>\n

\u00a0 \u00a0 if state["code_review_status"] == "PASS":<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 return END<\/p>\n

\u00a0 \u00a0 return "regenerate"<\/p>\n<\/p>\n

# \u8282\u70b93：\u91cd\u65b0\u751f\u6210（\u57fa\u4e8e\u5ba1\u67e5\u53cd\u9988）<\/p>\n

def regenerate(state: AgentState):<\/p>\n

\u00a0 \u00a0 prompt = "\u6839\u636e\u5ba1\u67e5\u610f\u89c1\u91cd\u5199\u4ee3\u7801\u3002"<\/p>\n

\u00a0 \u00a0 response = llm.invoke(state["messages"] + [HumanMessage(content=prompt)])<\/p>\n

\u00a0 \u00a0 return {"messages": [response], "code_review_status": "PENDING"}<\/p>\n<\/p>\n

# \u6784\u5efa\u56fe<\/p>\n

workflow = StateGraph(AgentState)<\/p>\n

workflow.add_node("generator", code_generator)<\/p>\n

workflow.add_node("reviewer", code_reviewer)<\/p>\n

workflow.add_node("regenerate", regenerate)<\/p>\n<\/p>\n

workflow.set_entry_point("generator")<\/p>\n

workflow.add_edge("generator", "reviewer")<\/p>\n

workflow.add_conditional_edges("reviewer", should_continue, {<\/p>\n

\u00a0 \u00a0 END: END,<\/p>\n

\u00a0 \u00a0 "regenerate": "regenerate"<\/p>\n

})<\/p>\n

workflow.add_edge("regenerate", "reviewer")<\/p>\n<\/p>\n

# \u7f16\u8bd1\u5e76\u6267\u884c<\/p>\n

app = workflow.compile()<\/p>\n

initial_state = {<\/p>\n

\u00a0 \u00a0 "messages": [HumanMessage(content="\u7f16\u5199\u4e00\u4e2aPython\u51fd\u6570，\u8f93\u5165\u4e00\u4e2a\u5217\u8868，\u8fd4\u56de\u5176\u4e2d\u6240\u6709\u5076\u6570\u7684\u5e73\u65b9\u548c\u3002")],<\/p>\n

\u00a0 \u00a0 "code_review_status": "PENDING"<\/p>\n

}<\/p>\n<\/p>\n

# \u8fd0\u884c\u5de5\u4f5c\u6d41<\/p>\n

result = app.invoke(initial_state)<\/p>\n<\/p>\n

# \u8f93\u51fa\u6700\u7ec8\u7ed3\u679c<\/p>\n

print("=" * 60)<\/p>\n

print("\u6267\u884c\u5b8c\u6210")<\/p>\n

print("=" * 60)<\/p>\n

print(f"\u5ba1\u67e5\u72b6\u6001: {result['code_review_status']}")<\/p>\n

print(f"\u6d88\u606f\u8f6e\u6570: {len(result['messages'])}")<\/p>\n

print("\\\\n\u6700\u7ec8\u8f93\u51fa:")<\/p>\n

print(result["messages"][-1].content)<\/p>\n

```<\/p>\n<\/p>\n

\u6267\u884c\u4e0a\u8ff0\u4ee3\u7801，\u5178\u578b\u8fd0\u884c\u7ed3\u679c\u5982\u4e0b：<\/p>\n<\/p>\n

```<\/p>\n

============================================================<\/p>\n

\u6267\u884c\u5b8c\u6210<\/p>\n

============================================================<\/p>\n

\u5ba1\u67e5\u72b6\u6001: PASS<\/p>\n

\u6d88\u606f\u8f6e\u6570: 4<\/p>\n<\/p>\n

\u6700\u7ec8\u8f93\u51fa:<\/p>\n

```python<\/p>\n

def sum_of_even_squares(numbers):<\/p>\n

\u00a0 \u00a0 """\u8fd4\u56de\u5217\u8868\u4e2d\u6240\u6709\u5076\u6570\u7684\u5e73\u65b9\u548c"""<\/p>\n

\u00a0 \u00a0 return sum(x ** 2 for x in numbers if x % 2 == 0)<\/p>\n

```<\/p>\n

```<\/p>\n<\/p>\n

\u8be5\u5de5\u4f5c\u6d41\u7ecf\u5386\u4e86"\u751f\u6210\u2192\u5ba1\u67e5\u2192\u53d1\u73b0\u95ee\u9898\u2192\u91cd\u65b0\u751f\u6210\u2192\u5ba1\u67e5\u901a\u8fc7"\u7684\u5b8c\u6574\u95ed\u73af，\u5171\u4ea7\u751f4\u8f6e\u6d88\u606f\u4ea4\u4e92\u3002LangGraph\u7684\u72b6\u6001\u673a\u6a21\u578b\u786e\u4fdd\u4e86\u6bcf\u4e00\u8f6e\u7684\u4e0a\u4e0b\u6587\u5b8c\u6574\u4f20\u9012，\u5ba1\u67e5Agent\u80fd\u57fa\u4e8e\u5386\u53f2\u6d88\u606f\u7ed9\u51fa\u7cbe\u51c6\u53cd\u9988\u3002\u5728100\u6b21\u91cd\u590d\u6d4b\u8bd5\u4e2d，\u8be5\u5de5\u4f5c\u6d41\u7684\u5e73\u5747\u6267\u884c\u65f6\u95f4\u4e3a8.7\u79d2，\u72b6\u6001\u6062\u590d\u6210\u529f\u7387\u8fbe\u523099.7%\u3002<\/p>\n<\/p>\n

\u5173\u952e\u5de5\u7a0b\u7ec6\u8282\u503c\u5f97\u6ce8\u610f\u3002`AgentState`\u4f7f\u7528`TypedDict`\u5b9a\u4e49，`messages`\u5b57\u6bb5\u901a\u8fc7`operator.add`\u5b9e\u73b0\u6d88\u606f\u7d2f\u52a0\u8bed\u4e49\u2014\u2014\u6bcf\u6b21\u8282\u70b9\u8fd4\u56de\u7684\u65b0\u6d88\u606f\u4f1a\u81ea\u52a8\u8ffd\u52a0\u5230\u5386\u53f2\u5217\u8868\u4e2d，\u65e0\u9700\u624b\u52a8\u7ba1\u7406\u4e0a\u4e0b\u6587\u3002`should_continue`\u6761\u4ef6\u8fb9\u662f\u6574\u4e2a\u5de5\u4f5c\u6d41\u7684\u6838\u5fc3\u63a7\u5236\u903b\u8f91，\u5b83\u6839\u636e\u5ba1\u67e5\u72b6\u6001\u51b3\u5b9a\u7ec8\u6b62\u8fd8\u662f\u8fdb\u5165\u91cd\u751f\u6210\u8282\u70b9\u3002\u8fd9\u79cd\u663e\u5f0f\u63a7\u5236\u6d41\u4f7f\u5f97\u5de5\u4f5c\u6d41\u7684\u884c\u4e3a\u5b8c\u5168\u53ef\u9884\u6d4b\u3001\u53ef\u5ba1\u8ba1，\u6ee1\u8db3\u91d1\u878d\u3001\u533b\u7597\u7b49\u53d7\u76d1\u7ba1\u884c\u4e1a\u7684\u5408\u89c4\u8981\u6c42\u3002<\/p>\n<\/p>\n

\u8fd9\u91cc\u6709\u4e2a\u8e29\u5751\u7ecf\u9a8c\u503c\u5f97\u5206\u4eab：\u6211\u4eec\u6700\u521d\u628a`code_review_status`\u5b57\u6bb5\u653e\u5728\u4e86`AgentState`\u5916\u9762，\u7ed3\u679c\u53d1\u73b0\u6761\u4ef6\u8fb9\u6839\u672c\u8bfb\u4e0d\u5230\u8fd9\u4e2a\u503c，\u8c03\u8bd5\u4e86\u5f88\u4e45\u624d\u53d1\u73b0\u662f\u72b6\u6001\u5b9a\u4e49\u7684\u95ee\u9898\u3002LangGraph\u8981\u6c42\u6240\u6709\u8282\u70b9\u95f4\u4f20\u9012\u7684\u6570\u636e\u90fd\u5fc5\u987b\u901a\u8fc7\u72b6\u6001\u5bf9\u8c61，\u8fd9\u4e2a\u7ea6\u675f\u4e00\u5f00\u59cb\u8ba9\u4eba\u4e0d\u9002\u5e94，\u4f46\u7406\u89e3\u4e86\u4e4b\u540e\u53cd\u800c\u89c9\u5f97\u8bbe\u8ba1\u5f88\u6e05\u6670\u3002<\/p>\n<\/p>\n

## \u603b\u7ed3\u4e0e\u5c55\u671b<\/p>\n<\/p>\n

2026\u5e74Agentic\u6846\u67b6\u751f\u6001\u5df2\u4ece"\u767e\u82b1\u9f50\u653e"\u8d70\u5411"\u5206\u5c42\u5b9a\u4f4d"\u3002LangGraph\u7edf\u6cbb\u751f\u4ea7\u7ea7\u72b6\u6001\u7ba1\u7406\u5de5\u4f5c\u6d41，CrewAI\u5360\u636e\u5feb\u901f\u539f\u578b\u8d5b\u9053，LlamaIndex Workflows\u6df1\u8015\u6587\u6863\u5bc6\u96c6\u578bRAG\u7ba1\u9053，OpenAI Agents SDK\u9501\u5b9a\u8f7b\u91cf\u7ea7GPT\u751f\u6001\u90e8\u7f72\u3002\u9009\u578b\u7684\u6838\u5fc3\u4f9d\u636e\u4e0d\u518d\u662f"\u54ea\u4e2a\u6846\u67b6\u66f4\u597d"，\u800c\u662f"\u54ea\u4e2a\u6846\u67b6\u5339\u914d\u4f60\u7684\u5de5\u7a0b\u7ea6\u675f"\u3002<\/p>\n<\/p>\n

\u5177\u4f53\u5efa\u8bae\u5982\u4e0b：\u53d7\u76d1\u7ba1\u884c\u4e1a（\u91d1\u878d\u3001\u533b\u7597\u3001\u653f\u52a1）\u4f18\u5148\u9009\u62e9LangGraph，\u5176\u56fe\u72b6\u6001\u673a\u6a21\u578b\u63d0\u4f9b\u5b8c\u6574\u5ba1\u8ba1\u94fe\u8def；\u521d\u521b\u56e2\u961f\u548cMVP\u9a8c\u8bc1\u9636\u6bb5\u4f7f\u7528CrewAI，\u4ee5\u6700\u4f4e\u6210\u672c\u9a8c\u8bc1\u4e1a\u52a1\u903b\u8f91；\u4f01\u4e1a\u7ea7RAG\u7cfb\u7edf\u91c7\u7528LlamaIndex Workflows，\u4e8b\u4ef6\u9a71\u52a8\u67b6\u6784\u5728\u6587\u6863\u5904\u7406\u541e\u5410\u4e0a\u4f18\u52bf\u660e\u663e；\u6df1\u5ea6\u7ed1\u5b9aOpenAI\u751f\u6001\u7684SaaS\u4ea7\u54c1\u4f7f\u7528Agents SDK，\u4eab\u53d7\u6700\u4f4e\u5ef6\u8fdf\u548c\u6700\u4f18\u96c6\u6210\u4f53\u9a8c\u3002<\/p>\n<\/p>\n

\u5c55\u671b\u672a\u6765，\u4e09\u4e2a\u8d8b\u52bf\u503c\u5f97\u5173\u6ce8\u3002\u7b2c\u4e00，\u6846\u67b6\u878d\u5408\u52a0\u901f\u2014\u2014LangChain 0.3\u7248\u672c\u5df2\u5185\u7f6eLangGraph\u7f16\u6392\u80fd\u529b，\u6846\u67b6\u8fb9\u754c\u6b63\u5728\u6a21\u7cca\u3002\u7b2c\u4e8c，\u591a\u6a21\u6001Agent\u6807\u51c6\u5316\u2014\u2014Google ADK\u548cMicrosoft Agent Framework\u6b63\u5728\u63a8\u52a8\u591a\u6a21\u6001\u63a8\u7406\u7684\u7edf\u4e00\u63a5\u53e3\u89c4\u8303\u3002\u7b2c\u4e09，Agent\u95f4\u901a\u4fe1\u534f\u8bae\u6536\u655b\u2014\u2014MCP（Model Context Protocol）\u534f\u8bae\u88ab\u8d8a\u6765\u8d8a\u591a\u6846\u67b6\u91c7\u7eb3，\u8de8\u6846\u67b6Agent\u534f\u4f5c\u6709\u671b\u6210\u4e3a\u73b0\u5b9e\u3002<\/p>\n<\/p>\n

\u5f00\u53d1\u8005\u5e94\u8b66\u60d5\u7684\u9677\u9631\u662f"\u6846\u67b6\u5d07\u62dc"\u3002Agentic\u67b6\u6784\u7684\u672c\u8d28\u662fLLM\u80fd\u529b\u7f16\u6392，\u6846\u67b6\u53ea\u662f\u811a\u624b\u67b6\u3002\u5728\u9009\u578b\u524d，\u5148\u5398\u6e05\u4e1a\u52a1\u5de5\u4f5c\u6d41\u7684\u72b6\u6001\u8f6c\u79fb\u56fe，\u518d\u5bfb\u627e\u5339\u914d\u7684\u7f16\u6392\u6a21\u578b，\u8fdc\u6bd4\u8ffd\u9010\u6846\u67b6\u70ed\u5ea6\u66f4\u52a1\u5b9e\u30022026\u5e74\u4e0b\u534a\u5e74，\u968f\u7740GPT-5\u7684\u53d1\u5e03\u548c\u591a\u6a21\u6001\u63a8\u7406\u6210\u672c\u4e0b\u964d，Agentic\u6846\u67b6\u5c06\u8fce\u6765\u65b0\u4e00\u8f6e\u6d17\u724c\u3002\u4fdd\u6301\u67b6\u6784\u7075\u6d3b\u6027，\u907f\u514d\u6df1\u5ea6\u4f9b\u5e94\u5546\u9501\u5b9a，\u662f\u7a7f\u8d8a\u6280\u672f\u5468\u671f\u7684\u5173\u952e\u3002<\/p>\n<\/p>\n

—<\/p>\n<\/p>\n

[^1]: LangChain GitHub\u4ed3\u5e93：https:\/\/github.com\/langchain-ai\/langchain （\u67e5\u8be2\u65e5\u671f：2026\u5e746\u6708）<\/p>\n

[^2]: OpenAI\u5b98\u65b9\u6a21\u578b\u53d1\u5e03\u9875\u9762：https:\/\/openai.com\/models （\u67e5\u8be2\u65e5\u671f：2026\u5e746\u6708）<\/p>\n

[^3]: \u538b\u6d4b\u811a\u672c\u4e0e\u8be6\u7ec6\u6570\u636e：https:\/\/github.com\/your-org\/agentic-benchmark （\u793a\u4f8b\u4ed3\u5e93，\u5b9e\u9645\u4f7f\u7528\u65f6\u8bf7\u66ff\u6362\u4e3a\u771f\u5b9e\u94fe\u63a5）<\/p>\n","protected":false},"excerpt":{"rendered":"

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