{"id":111524,"date":"2026-10-01T10:58:20","date_gmt":"2026-10-01T02:58:20","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/111524.html"},"modified":"2026-10-01T10:58:20","modified_gmt":"2026-10-01T02:58:20","slug":"bentoml-openllm-l3%e9%9d%99%e6%80%81%e8%af%84%e6%b5%8b%ef%bc%9a41%e4%b8%aa%e6%96%87%e4%bb%b6%e3%80%817-8%e9%80%9a%e8%bf%87%ef%bc%8c%e4%b8%80%e4%b8%aa%e8%96%84%e7%bd%91%e5%85%b3","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/111524.html","title":{"rendered":"BentoML OpenLLM L3\u9759\u6001\u8bc4\u6d4b\uff1a41\u4e2a\u6587\u4ef6\u30017\/8\u901a\u8fc7\uff0c\u4e00\u4e2a\u201c\u8584\u7f51\u5173\u201d\u7684\u5de5\u7a0b\u62a4\u57ce\u6cb3\u4e0e\u9009\u578b\u8fb9\u754c"},"content":{"rendered":"

BentoML OpenLLM L3\u9759\u6001\u8bc4\u6d4b：41\u4e2a\u6587\u4ef6\u30017\/8\u901a\u8fc7，\u4e00\u4e2a\u201c\u8584\u7f51\u5173\u201d\u7684\u5de5\u7a0b\u62a4\u57ce\u6cb3\u4e0e\u9009\u578b\u8fb9\u754c<\/h2>\n

\u8bc4\u6d4b\u7f16\u53f7：L3-OSB-20260922-03
\n\u8bc4\u6d4b\u5bf9\u8c61：bentoml\/OpenLLM @ ec2355ce
\n\u9879\u76ee\u5b9a\u4f4d：\u7edf\u4e00LLM\u63a8\u7406\u670d\u52a1\u7f51\u5173（\u4e00\u6761\u547d\u4ee4\u628a\u5f00\u6e90LLM\u4ee5OpenAI\u517c\u5bb9API\u5f62\u5f0f\u81ea\u6258\u7ba1）
\n\u6570\u636e\u6307\u6807：41\u4e2a\u6811\u6587\u4ef6 | 18\u4e2a\u9650\u5b9a\u68c0\u51fa | 7\/8\u68c0\u67e5\u9879\u901a\u8fc7 | \u8bc1\u636e\u8986\u76d6\u7387100%
\n\u534f\u8bae：Apache-2.0（\u5bbd\u677e\u8bb8\u53ef，\u5546\u7528\u53cb\u597d）
\n\u661f\u6807\u6570：12,535 | \u6700\u65b0\u7248\u672c：v0.6.30（2025-04-21）
\n\u4f5c\u8005：Valhalla Matrix\u6cbb\u7406\u5b9e\u9a8c\u5ba4<\/p>\n

\u6458\u8981：L3\u72ec\u7acb\u8bc4\u6d4b\u62a5\u544a\u663e\u793a，OpenLLM\u5728\u56fa\u5b9acommit ec2355ce\u4e0b\u7684bounded\u5feb\u7167\u5168\u6838\u9a8c\u901a\u8fc7，7\u9879\u68c0\u67e5PASS，\u8bc1\u636e\u8986\u76d6\u7387100%，\u98ce\u9669\u59ff\u6001baseline\u3002\u552f\u4e00\u672a\u901a\u8fc7\u7684\u68c0\u67e5\u9879\u662ftest_surface_present\u2014\u2014\u572830\u6587\u4ef6\u9884\u7b97\u5185\u672a\u547d\u4e2d\u6d4b\u8bd5\u9762\u3002\u4f46\u8fd9\u6070\u6070\u53cd\u6620\u4e86OpenLLM\u7684\u5de5\u7a0b\u672c\u8d28：\u5b83\u662f\u4e00\u4e2a\u201c\u8584\u7f51\u5173\u201d，\u800c\u975e\u4e00\u4e2a\u201c\u539a\u6846\u67b6\u201d \u300241\u4e2a\u6811\u6587\u4ef6\u7684\u6781\u7b80\u4f53\u91cf\u3001accelerator_spec.py\/venv.py\/model.py\u7684\u6e05\u6670\u5206\u5c42，\u8bf4\u660eOpenLLM\u7684\u8bbe\u8ba1\u54f2\u5b66\u662f\u628a\u201c\u63a8\u7406\u201d\u4ea4\u7ed9vLLM\u7b49\u4e13\u4e1a\u540e\u7aef，\u628a\u201c\u670d\u52a1\u5316\u201d\u548c\u201cOpenAI\u517c\u5bb9\u201d\u505a\u8584\u505a\u900f\u3002\u672c\u6587\u4eceL3\u8bc4\u6d4b\u62a5\u544a\u51fa\u53d1，\u7ed3\u5408OpenLLM\u7684\u9002\u914d\u5668-\u73af\u5883-\u6a21\u578b\u4e09\u5c42\u67b6\u6784\u3001\u4e0evLLM\/Ollama\u7684\u7ade\u54c1\u5b9a\u4f4d\u5dee\u5f02\u3001\u4ee5\u53ca\u5176\u201c\u8bca\u65ad\u903b\u8f91\u201d\u7684\u4e0d\u53ef\u590d\u5236\u6027，\u62c6\u89e3\u8fd9\u4e2a\u201c\u4e0d\u505a\u63a8\u7406\u5f15\u64ce\u7684\u63a8\u7406\u7f51\u5173\u201d\u7684\u771f\u5b9e\u4ef7\u503c\u4e0e\u9009\u578b\u8fb9\u754c\u3002\u6838\u5fc3\u5224\u65ad：OpenLLM\u7684\u4ef7\u503c\u4e0d\u5728\u4e8e\u201c\u81ea\u5df1\u6709\u591a\u5f3a\u201d，\u800c\u5728\u4e8e\u5b83\u628a\u201c\u5207\u6362\u63a8\u7406\u540e\u7aef\u201d\u8fd9\u4ef6\u4e8b\u7684\u6210\u672c\u964d\u5230\u4e86\u6700\u4f4e\u2014\u2014\u4f46\u8fd9\u4e2a\u4ef7\u503c\u7684\u524d\u63d0\u662f，\u4f60\u6e05\u695a\u81ea\u5df1\u9700\u8981\u7684\u53ea\u662f\u4e00\u4e2a\u7f51\u5173，\u800c\u975e\u4e00\u4e2a\u5b8c\u6574\u7684\u63a8\u7406\u5f15\u64ce\u3002\u5176\u771f\u6b63\u7684\u5de5\u7a0b\u62a4\u57ce\u6cb3，\u662f\u5b83\u7ecf\u8fc7\u5927\u91cf\u9879\u76ee\u9a8c\u8bc1\u7684\u201c\u540e\u7aef\u9002\u914d\u8bca\u65ad\u903b\u8f91\u201d，\u800c\u975e\u8868\u9762\u7684\u914d\u7f6e\u6587\u4ef6\u3002<\/p>\n

\u4e00\u3001L3\u8bc4\u6d4b\u62a5\u544a\u89e3\u8bfb：7\/8\u80cc\u540e\u7684\u201c\u6d4b\u8bd5\u9762\u7f3a\u5931\u201d\u4fe1\u53f7<\/h3>\n

\u5148\u770b\u672c\u6b21\u8bc4\u6d4b\u7684\u6838\u5fc3\u6570\u636e：<\/p>\n\n\u6307\u6807\u89c2\u6d4b\u503c<\/tr>\n\n\n\n\n\n\n\n
\u6811\u6587\u4ef6\u603b\u6570<\/td>\n41<\/td>\n<\/tr>\n
\u9650\u5b9a\u68c0\u51fa<\/td>\n18<\/td>\n<\/tr>\n
\u8d85\u8303\u56f4\u8ddf\u8e2a\u6587\u4ef6<\/td>\n23<\/td>\n<\/tr>\n
\u68c0\u67e5\u901a\u8fc7<\/td>\n7\/8<\/td>\n<\/tr>\n
\u8bc1\u636e\u8986\u76d6\u7387<\/td>\n100%<\/td>\n<\/tr>\n
\u98ce\u9669\u59ff\u6001<\/td>\nbaseline<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u552f\u4e00\u672a\u901a\u8fc7\u7684\u68c0\u67e5\u9879\u662ftest_surface_present\u2014\u2014\u62a5\u544a\u660e\u786e\u6807\u6ce8\u201c\u6d4b\u8bd5\u9762\u6587\u4ef6\u5728bounded\u9762\u5185\u672a\u547d\u4e2d\u201d\u3002\u5728\u4e4b\u524d\u7684L3\u8bc4\u6d4b\u4e2d，AutoGen\u4ee51,837\u4e2a\u6811\u6587\u4ef6\u30017\u4e2a\u6d4b\u8bd5\u6587\u4ef6\u547d\u4e2d\u7684\u6210\u7ee9\u901a\u8fc7\u4e86test_surface_present\u3002OpenLLM\u7684\u60c5\u51b5\u5b8c\u5168\u4e0d\u540c：41\u4e2a\u6811\u6587\u4ef6\u7684\u6781\u5c0f\u4f53\u91cf，\u610f\u5473\u774030\u6587\u4ef6\u7684bounded\u9884\u7b97\u5df2\u7ecf\u8986\u76d6\u4e8673%\u7684\u4ed3\u5e93，\u4f46\u6d4b\u8bd5\u6587\u4ef6\u6070\u597d\u4e0d\u5728\u88ab\u62bd\u6837\u768418\u4e2a\u6587\u4ef6\u4e4b\u5185\u3002<\/p>\n

\u8fd9\u4e2a\u4fe1\u53f7\u6709\u4e24\u79cd\u53ef\u80fd\u7684\u89e3\u8bfb：<\/p>\n

\u89e3\u8bfb\u4e00：\u4ed3\u5e93\u786e\u5b9e\u7f3a\u5c11\u6d4b\u8bd5\u3002 \u5982\u679cOpenLLM\u7684\u6d4b\u8bd5\u6587\u4ef6\u5206\u6563\u5728tests\/\u76ee\u5f55\u4e0b\u4f46\u672a\u88abbounded\u9762\u5305\u542b，\u8bf4\u660e\u6d4b\u8bd5\u9762\u5728\u4ed3\u5e93\u4e2d\u7684\u201c\u53ef\u89c1\u5ea6\u201d\u4e0d\u9ad8\u3002\u5bf9\u4e8e\u4e00\u4e2a\u5b9a\u4f4d\u4e3a\u201c\u751f\u4ea7\u7ea7\u63a8\u7406\u670d\u52a1\u201d\u7684\u9879\u76ee，\u6d4b\u8bd5\u9762\u7684\u7f3a\u5931\u662f\u4e00\u4e2a\u9700\u8981\u5173\u6ce8\u7684\u5de5\u7a0b\u4fe1\u53f7\u3002<\/p>\n

\u89e3\u8bfb\u4e8c：\u6d4b\u8bd5\u9762\u88ab\u8d85\u8303\u56f4\u6392\u9664\u3002 \u62a5\u544a\u663e\u793a\u201c\u8d85\u8303\u56f4\u8ddf\u8e2a\u6587\u4ef6：23\u4e2a\u201d，\u8fd9\u4e9b\u6587\u4ef6\u4e0d\u5728bounded\u9762\u5185\u3002\u5982\u679c\u6d4b\u8bd5\u6587\u4ef6\u5c5e\u4e8e\u8fd923\u4e2a\u8d85\u8303\u56f4\u6587\u4ef6，\u90a3\u4e48test_surface_present\u7684\u672a\u901a\u8fc7\u662f\u62bd\u6837\u7b56\u7565\u7684\u7ed3\u679c，\u800c\u975e\u4ed3\u5e93\u7684\u771f\u5b9e\u72b6\u6001\u3002<\/p>\n

\u65e0\u8bba\u54ea\u79cd\u89e3\u8bfb，\u7ed3\u8bba\u662f\u4e00\u81f4\u7684：\u5728\u672c\u6b21bounded\u9762\u5185，OpenLLM\u7684\u6d4b\u8bd5\u8bc1\u636e\u4e0d\u8db3\u4ee5\u652f\u6491\u201c\u53ef\u6d4b\u8bd5\u6027\u5df2\u89c2\u6d4b\u201d\u7684\u5224\u65ad\u3002 \u6280\u672f\u51b3\u7b56\u8005\u9700\u8981\u81ea\u884c\u8865\u5145\u6d4b\u8bd5\u6267\u884c\u9a8c\u8bc1\u3002<\/p>\n

\u4e8c\u300141\u4e2a\u6587\u4ef6\u7684\u201c\u8584\u7f51\u5173\u201d\u67b6\u6784：\u4e0d\u505a\u63a8\u7406，\u53ea\u505a\u9002\u914d<\/h3>\n

OpenLLM\u6700\u6838\u5fc3\u7684\u67b6\u6784\u51b3\u7b56\u662f：\u5b83\u81ea\u8eab\u4e0d\u63d0\u4f9b\u63a8\u7406\u5f15\u64ce，\u800c\u662f\u4f5c\u4e3a\u9002\u914d\u5c42，\u652f\u6301\u5bf9\u63a5vLLM\u3001Transformers\u3001llama.cpp\u7b49\u591a\u79cd\u63a8\u7406\u540e\u7aef\u3002<\/p>\n

\u8fd9\u4e2a\u51b3\u7b56\u7684\u5de5\u7a0b\u542b\u4e49\u662f\u6df1\u8fdc\u7684\u3002\u4eceL3\u62a5\u544a\u7684\u8bed\u4e49\u6837\u672c\u53ef\u4ee5\u770b\u5230，src\/openllm\/\u4e0b\u7684\u6838\u5fc3\u6587\u4ef6\u5448\u73b0\u51fa\u6e05\u6670\u7684\u9002\u914d\u5668-\u73af\u5883-\u6a21\u578b\u5206\u5c42：<\/p>\n\n\u6587\u4ef6\u804c\u8d23\u5206\u5c42\u5f52\u5c5e<\/tr>\n\n\n\n\n\n
accelerator_spec.py<\/td>\nGPU\/\u52a0\u901f\u5668\u89c4\u683c\u5b9a\u4e49\u4e0e\u68c0\u6d4b<\/td>\n\u73af\u5883\u5c42<\/td>\n<\/tr>\n
venv.py<\/td>\n\u865a\u62df\u73af\u5883\u7ba1\u7406\u4e0e\u4f9d\u8d56\u89e3\u6790<\/td>\n\u73af\u5883\u5c42<\/td>\n<\/tr>\n
model.py<\/td>\n\u6a21\u578b\u52a0\u8f7d\u3001\u9002\u914d\u5668\u63a5\u53e3\u3001\u540e\u7aef\u5207\u6362<\/td>\n\u6a21\u578b\u5c42<\/td>\n<\/tr>\n
__main__.py<\/td>\nCLI\u5165\u53e3\u4e0e\u670d\u52a1\u542f\u52a8<\/td>\n\u7f51\u5173\u5c42<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u8fd9\u4e2a\u5206\u5c42\u7684\u5de5\u7a0b\u903b\u8f91\u662f：<\/p>\n

    \n
  • \u7f51\u5173\u5c42\u8d1f\u8d23\u63a5\u6536OpenAI\u517c\u5bb9\u7684API\u8bf7\u6c42，\u5c06\u5176\u8f6c\u6362\u4e3a\u7edf\u4e00\u7684\u5185\u90e8\u5206\u5e03\u5f0f\u6d88\u606f\u683c\u5f0f<\/li>\n
  • \u6a21\u578b\u5c42\u8d1f\u8d23\u5c06\u6d88\u606f\u8def\u7531\u5230\u5177\u4f53\u7684\u63a8\u7406\u540e\u7aef（vLLM \/ Transformers \/ llama.cpp），\u5e76\u5904\u7406\u6a21\u578b\u52a0\u8f7d\u548c\u5378\u8f7d<\/li>\n
  • \u73af\u5883\u5c42\u8d1f\u8d23\u68c0\u6d4b\u786c\u4ef6\u52a0\u901f\u5668\u3001\u7ba1\u7406\u865a\u62df\u73af\u5883\u4f9d\u8d56，\u786e\u4fdd\u540e\u7aef\u5728\u6b63\u786e\u7684\u73af\u5883\u4e2d\u8fd0\u884c<\/li>\n<\/ul>\n

    OpenLLM\u4e0d\u505a\u7684\u4e8b：\u5b83\u4e0d\u5b9e\u73b0\u6ce8\u610f\u529b\u7b97\u6cd5，\u4e0d\u7ba1\u7406KV\u7f13\u5b58，\u4e0d\u8c03\u5ea6\u6279\u5904\u7406\u3002\u8fd9\u4e9b\u5168\u90e8\u59d4\u6258\u7ed9\u540e\u7aef\u3002\u5b83\u505a\u7684\u4e8b：\u628a\u201c\u542f\u52a8\u4e00\u4e2a\u5f00\u6e90LLM\u7684OpenAI\u517c\u5bb9API\u670d\u52a1\u201d\u8fd9\u4ef6\u4e8b，\u4ece\u201c\u9700\u8981\u5199Dockerfile + \u914d\u7f6eFastAPI + \u5904\u7406\u8ba4\u8bc1 + \u7ba1\u7406\u6a21\u578b\u751f\u547d\u5468\u671f\u201d\u7b80\u5316\u4e3a\u4e00\u6761\u547d\u4ee4\u3002\u771f\u6b63\u7684\u5de5\u7a0b\u62a4\u57ce\u6cb3，\u5e76\u975e\u8fd9\u4e9b\u8868\u9762\u7684\u914d\u7f6e\u6587\u4ef6，\u800c\u662f\u5176\u7ecf\u8fc7\u5927\u91cf\u9879\u76ee\u9a8c\u8bc1\u7684\u201c\u540e\u7aef\u9002\u914d\u8bca\u65ad\u903b\u8f91\u201d\u2014\u2014\u4f8b\u5982，\u5982\u4f55\u81ea\u52a8\u68c0\u6d4bGPU\u7b97\u529b\u3001\u5982\u4f55\u6839\u636eCUDA\u7248\u672c\u9009\u62e9\u517c\u5bb9\u7684vLLM\u7248\u672c\u3001\u5982\u4f55\u5728\u4e0d\u540c\u786c\u4ef6\u4e0a\u4f18\u96c5\u964d\u7ea7\u3002\u8fd9\u5957\u8bca\u65ad\u903b\u8f91\u662fOpenLLM\u56e2\u961f\u5728\u771f\u5b9e\u90e8\u7f72\u4e2d\u79ef\u7d2f\u7684\u9690\u6027\u77e5\u8bc6，\u65e0\u6cd5\u901a\u8fc7\u590d\u5236\u51e0\u884cYAML\u914d\u7f6e\u6765\u83b7\u5f97\u3002<\/p>\n

    2.1 \u4e0evLLM\u7684\u672c\u8d28\u533a\u522b<\/h4>\n

    \u8fd9\u4e2a\u5b9a\u4f4d\u4e0evLLM\u5f62\u6210\u4e86\u9c9c\u660e\u7684\u5bf9\u6bd4\u3002vLLM\u7684\u67b6\u6784\u76ee\u6807\u6781\u4e3a\u805a\u7126：\u6253\u9020\u541e\u5410\u91cf\u6700\u9ad8\u7684\u5206\u5e03\u5f0f\u63a8\u7406\u5f15\u64ce\u3002 \u5b83\u7684\u6838\u5fc3\u521b\u65b0\u5728\u4e8ePagedAttention\u7b97\u6cd5\u548c\u9ad8\u6548\u7684\u5185\u5b58\u7ba1\u7406，\u67b6\u6784\u56f4\u7ed5\u201c\u5982\u4f55\u8ba9GPU\u7684\u6bcf\u4e2aCUDA Core\u66f4\u5fd9，\u8ba9\u663e\u5b58\u5229\u7528\u66f4\u9ad8\u6548\u201d\u5c55\u5f00\u3002<\/p>\n

    OpenLLM\u7684\u67b6\u6784\u76ee\u6807\u5219\u662f\u201c\u7edf\u4e00\u5165\u53e3\u201d ：\u8ba9\u5f00\u53d1\u8005\u4e0d\u9700\u8981\u5173\u5fc3\u5e95\u5c42\u7528\u7684\u662fvLLM\u8fd8\u662fTransformers，\u53ea\u9700\u8981\u901a\u8fc7\u7edf\u4e00\u7684CLI\u548cAPI\u4e0e\u6a21\u578b\u4ea4\u4e92\u3002\u4e24\u8005\u7684\u5173\u7cfb\u4e0d\u662f\u7ade\u4e89，\u800c\u662f\u5c42\u6b21\u5173\u7cfb\u2014\u2014OpenLLM\u53ef\u4ee5\u5c06vLLM\u4f5c\u4e3a\u540e\u7aef\u8c03\u7528\u3002\u4ecev0.5\u7248\u672c\u5f00\u59cb，OpenLLM\u5df2\u5c06\u540e\u7aef\u7b80\u5316\u4e3a\u4ec5\u652f\u6301vLLM，\u56e0\u4e3a\u201cvLLM\u662f\u5728\u4e91GPU\u4e0a\u670d\u52a1LLM\u6700\u5408\u9002\u3001\u6700\u53ef\u9760\u7684\u540e\u7aef\u201d\u3002<\/p>\n

    2.2 \u4e0eOllama\u7684\u672c\u8d28\u533a\u522b<\/h4>\n

    Ollama\u91c7\u7528\u8f7b\u91cf\u7ea7\u3001\u4e00\u4f53\u5316\u8bbe\u8ba1\u54f2\u5b66，\u5c06\u6a21\u578b\u52a0\u8f7d\u3001\u63a8\u7406\u670d\u52a1\u3001API\u63a5\u53e3\u3001\u547d\u4ee4\u884c\u4ea4\u4e92\u9ad8\u5ea6\u96c6\u6210\u5728\u4e00\u4e2a\u5b88\u62a4\u8fdb\u7a0b\u4e2d\u3002\u5b83\u5185\u7f6e\u57fa\u4e8ellama.cpp\u4f18\u5316\u7684\u63a8\u7406\u5f15\u64ce，\u6df1\u5ea6\u96c6\u6210GGUF\u683c\u5f0f，\u5728CPU\/Apple Silicon\u4e0a\u8868\u73b0\u4f18\u5f02\u3002<\/p>\n

    OpenLLM\u5219\u662f\u4e00\u4e2a\u201c\u751f\u4ea7\u7ea7\u62bd\u8c61\u201d ：\u5b83\u4e0d\u7ed1\u5b9a\u5355\u4e00\u63a8\u7406\u5f15\u64ce，\u4e0d\u5185\u7f6e\u6a21\u578b\u683c\u5f0f，\u800c\u662f\u628a\u63a8\u7406\u80fd\u529b\u62bd\u8c61\u4e3a\u53ef\u63d2\u62d4\u7684\u540e\u7aef\u7ec4\u4ef6\u3002\u8fd9\u610f\u5473\u7740OpenLLM\u5728NVIDIA GPU\u7684\u9ad8\u5e76\u53d1\u573a\u666f\u4e0b，\u82e5\u4e0d\u4e3b\u52a8\u914d\u7f6evLLM\u540e\u7aef，\u5176\u541e\u5410\u91cf\u4e0d\u53ca\u539f\u751fvLLM；\u4f46\u5728\u9700\u8981\u7075\u6d3b\u5207\u6362\u540e\u7aef\u3001\u591a\u6a21\u578b\u7ba1\u7406\u7684\u4f01\u4e1a\u573a\u666f\u4e2d，OpenLLM\u7684\u9002\u914d\u5c42\u4ef7\u503c\u5c31\u4f1a\u663e\u73b0\u3002Ollama\u7684\u6781\u81f4\u5f00\u53d1\u8005\u4f53\u9a8c\u4e0eOpenLLM\u7684\u4f01\u4e1a\u7ea7\u7ba1\u7406\u80fd\u529b，\u4ee3\u8868\u4e86\u4e24\u79cd\u622a\u7136\u4e0d\u540c\u7684\u5de5\u7a0b\u54f2\u5b66\u3002<\/p>\n

    \u4e09\u3001\u6027\u80fd\u771f\u76f8：OpenLLM\u7684\u5ef6\u8fdf\u4f18\u52bf\u4e0e\u541e\u5410\u91cf\u8fb9\u754c<\/h3>\n

    3.1 \u5ef6\u8fdf\u4f18\u5316：BentoML\u68c0\u67e5\u70b9\u7684\u52a0\u8f7d\u4f18\u52bf<\/h4>\n

    \u6839\u636eIEEE\u53d1\u8868\u7684\u5bf9\u6bd4\u7814\u7a76，OpenLLM\u7684BentoML\u68c0\u67e5\u70b9\u52a0\u8f7d\u901f\u5ea6\u5728\u6240\u6709\u6a21\u578b\u5927\u5c0f\u548c\u67b6\u6784\u4e2d\u90fd\u662f\u6700\u5feb\u7684，\u72ec\u7acb\u4e8e\u6a21\u578b\u89c4\u6a21\u3002\u8bbe\u7f6e\u4e00\u4e2a\u6a21\u578b\u7528\u4e8eOpenLLM\u7684\u65f6\u95f4\u5728\u6240\u6709\u60c5\u51b5\u4e0b\u90fd\u4e0d\u52300.1\u79d2\u3002\u8fd9\u5f97\u76ca\u4e8eOpenLLM\u5bf9\u5ef6\u8fdf\u4f18\u5316\u7684\u4e13\u6ce8\u2014\u2014\u5b83\u7684\u8bbe\u8ba1\u76ee\u6807\u4e0d\u662f\u6700\u5927\u5316\u541e\u5410\u91cf，\u800c\u662f\u6700\u5c0f\u5316\u201c\u4ece\u8bf7\u6c42\u5230\u9996token\u201d\u7684\u5ef6\u8fdf\u3002<\/p>\n

    3.2 \u541e\u5410\u91cf\u7684\u8fb9\u754c：\u9700\u8981vLLM\u540e\u7aef\u652f\u6491<\/h4>\n

    OpenLLM\u7684\u6027\u80fd\u5929\u82b1\u677f\u53d6\u51b3\u4e8e\u540e\u7aef\u9009\u62e9：<\/p>\n\n\u540e\u7aef\u9002\u7528\u573a\u666f\u541e\u5410\u91cf\u8868\u73b0<\/tr>\n\n\n\n\n
    vLLM<\/td>\nNVIDIA GPU（\u7b97\u529b\u22658.0）\u3001\u9ad8\u5e76\u53d1\u751f\u4ea7<\/td>\n\u6700\u4f18，PagedAttention + \u8fde\u7eed\u6279\u5904\u7406<\/td>\n<\/tr>\n
    Transformers<\/td>\n\u7075\u6d3b\u9002\u914d\u591a\u786c\u4ef6\u3001\u539f\u578b\u9a8c\u8bc1<\/td>\n\u4e2d\u7b49，\u65e0\u4e13\u7528\u4f18\u5316<\/td>\n<\/tr>\n
    llama.cpp<\/td>\nCPU\/Apple Silicon\u3001\u91cf\u5316\u6a21\u578b<\/td>\n\u4f4e\u5e76\u53d1\u573a\u666f\u4e0b\u53ef\u63a5\u53d7<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u5173\u952e\u4e8b\u5b9e：OpenLLM\u57282025\u5e745\u6708\u6b63\u5f0f\u5f03\u7528\u4e86PyTorch\u540e\u7aef，\u8f6c\u800c\u63a8\u8350\u7528\u6237\u5728\u751f\u4ea7\u73af\u5883\u4f7f\u7528vLLM\u540e\u7aef\u3002\u8fd9\u610f\u5473\u7740OpenLLM\u7684\u201c\u9002\u914d\u5c42\u201d\u4ef7\u503c\u5728\u5b9e\u8df5\u4e2d\u88ab\u5927\u5e45\u6536\u7a84\u2014\u2014\u5b83\u5b9e\u9645\u4e0a\u662f\u4e00\u4e2a\u201cvLLM\u7684OpenAI\u517c\u5bb9\u5305\u88c5\u5668 + \u591a\u540e\u7aef\u5207\u6362\u80fd\u529b\u201d\u3002<\/p>\n

    3.3 \u4e0evLLM\u539f\u751f\u7684\u6027\u80fd\u5dee\u8ddd<\/h4>\n

    \u5982\u679c\u76f4\u63a5\u4f7f\u7528vLLM，\u4f60\u53ef\u4ee5\u83b7\u5f97\u6700\u76f4\u63a5\u7684\u6027\u80fd\u4f18\u5316\u8def\u5f84\u3002OpenLLM\u5728vLLM\u4e4b\u4e0a\u589e\u52a0\u4e86\u4e00\u5c42\u62bd\u8c61，\u8fd9\u5c42\u62bd\u8c61\u5e26\u6765\u4e86：<\/p>\n

      \n
    • \u7edf\u4e00\u7684CLI\u548cAPI：\u4e0d\u9700\u8981\u4e3a\u6bcf\u4e2a\u6a21\u578b\u5199Dockerfile\u548cFastAPI\u914d\u7f6e<\/li>\n
    • \u591a\u540e\u7aef\u5207\u6362\u80fd\u529b：\u53ef\u4ee5\u5728\u4e0d\u4fee\u6539\u4e0a\u5c42\u4ee3\u7801\u7684\u60c5\u51b5\u4e0b\u5207\u6362\u63a8\u7406\u5f15\u64ce<\/li>\n
    • \u6a21\u578b\u4ed3\u5e93\u62bd\u8c61：\u901a\u8fc7bentoml\/openllm-models\u7edf\u4e00\u7ba1\u7406\u6a21\u578b\u540d\u79f0\u89e3\u6790<\/li>\n<\/ul>\n

      \u4ee3\u4ef7\u662f：\u6bcf\u589e\u52a0\u4e00\u5c42\u62bd\u8c61，\u5c31\u4f1a\u589e\u52a0\u4e00\u5b9a\u7684\u5ef6\u8fdf\u548c\u8d44\u6e90\u5f00\u9500\u3002\u5bf9\u4e8e\u8ffd\u6c42\u6781\u81f4\u541e\u5410\u91cf\u7684\u573a\u666f，\u539f\u751fvLLM\u53ef\u80fd\u662f\u66f4\u76f4\u63a5\u7684\u9009\u62e9\u3002<\/p>\n

      \u56db\u3001L3\u8bc4\u6d4b\u65b9\u6cd5\u8bba：bounded\u5feb\u7167\u7684\u4e25\u8c28\u6027\u4e0e\u8fb9\u754c<\/h3>\n

      L3\u8bc4\u6d4b\u7684\u4e25\u8c28\u6027\u503c\u5f97\u5355\u72ec\u8ba8\u8bba，\u56e0\u4e3a\u5b83\u5b9a\u4e49\u4e86\u6574\u4efd\u62a5\u544a\u7684\u8bc1\u636e\u8fb9\u754c\u3002<\/p>\n

      4.1 \u4e94\u5927\u6280\u672f\u652f\u67f1<\/h4>\n

      \u6839\u636eValhalla\u9759\u6001\u5de5\u7a0b\u5ba1\u9605\u6846\u67b6\u7684\u516c\u5f00\u65b9\u6cd5\u8bba，L3\u8bc4\u6d4b\u4f9d\u8d56\u4e94\u4e2a\u786c\u6027\u6280\u672f\u652f\u67f1：<\/p>\n\n\u652f\u67f1\u6280\u672f\u5185\u6db5\u5728OpenLLM\u8bc4\u6d4b\u4e2d\u7684\u4f53\u73b0<\/tr>\n\n\n\n\n\n\n
      \u5feb\u7167\u9501\u5b9a<\/td>\n\u57fa\u4e8e\u552f\u4e00Git Commit SHA，\u675c\u7edd\u7248\u672c\u6f02\u79fb<\/td>\nec2355ce1a75176164c451cbb7592b3046531540<\/td>\n<\/tr>\n
      \u53ea\u8bfb\u9759\u6001<\/td>\n\u7981\u6b62\u7f16\u8bd1\u3001\u6267\u884c\u3001\u90e8\u7f72\u3001\u8fd0\u884c\u6d4b\u8bd5<\/td>\n\u672a\u6267\u884c\u4efb\u4f55OpenLLM\u4ee3\u7801<\/td>\n<\/tr>\n
      \u8bc1\u636e\u9a71\u52a8<\/td>\n\u6bcf\u4e00\u6761\u7ed3\u8bba\u5fc5\u987b\u5173\u8054\u5230\u5177\u4f53\u6587\u4ef6\u8def\u5f84<\/td>\naccelerator_spec.py\u3001venv.py\u3001model.py<\/td>\n<\/tr>\n
      \u5206\u5c42\u5f52\u56e0<\/td>\n\u533a\u5206\u751f\u4ea7\u4ee3\u7801\u3001\u6d4b\u8bd5\u5939\u5177\u3001\u5f00\u53d1\u811a\u672c\u7684\u98ce\u9669\u6743\u91cd<\/td>\n\u4ec5\u62bd\u6837root_contract\/ci_workflow\/production_source<\/td>\n<\/tr>\n
      SAST\u89c4\u5219\u5f15\u64ce<\/td>\n\u5185\u7f6e\u5b9a\u5236\u5316\u89c4\u5219\u96c6\u8fdb\u884c\u6a21\u5f0f\u5339\u914d<\/td>\nsemantic_clean_gate\u901a\u8fc7<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      4.2 bounded_verified\u7684\u7cbe\u786e\u542b\u4e49<\/h4>\n

      \u62a5\u544a\u4e2d\u53cd\u590d\u51fa\u73b0\u7684bounded_verified\u9700\u8981\u7cbe\u786e\u7406\u89e3：\u5b83\u58f0\u660e\u7684\u662f\u201c\u6240\u58f0\u660e\u7684bounded\u8303\u56f4（18\u4e2a\u6587\u4ef6）\u5b8c\u6574\u6838\u9a8c\u201d，\u800c\u975e\u201c\u5168\u4ed341\u4e2a\u6587\u4ef6\u5b8c\u6574\u9a8c\u8bc1\u201d \u3002<\/p>\n

      \u8fd9\u4e2a\u533a\u5206\u5728\u6280\u672f\u5c3d\u8c03\u4e2d\u81f3\u5173\u91cd\u8981\u3002\u5f53\u62a5\u544a\u8bf4\u201c\u8bc1\u636e\u8986\u76d6\u7387100%\u201d\u65f6，\u5b83\u8861\u91cf\u7684\u662fbounded\u9762\u5185\u7684\u6838\u9a8c\u5b8c\u6574\u5ea6，\u800c\u975e\u4ed3\u5e93\u7684\u5168\u5c40\u8986\u76d6\u5ea6\u3002\u5bf9\u4e8e41\u4e2a\u6587\u4ef6\u7684OpenLLM，18\u4e2a\u6587\u4ef6\u7684\u62bd\u6837\u5df2\u7ecf\u8986\u76d6\u4e8644%\u7684\u4ed3\u5e93；\u4f46\u5bf9\u4e8eAutoGen\u76841,837\u4e2a\u6587\u4ef6，30\u4e2a\u6587\u4ef6\u7684\u62bd\u6837\u4ec5\u8986\u76d61.6%\u3002<\/p>\n

      \u8fd9\u4e2a\u5dee\u5f02\u610f\u5473\u7740：\u5bf9\u4e8eOpenLLM\u8fd9\u6837\u7684\u5c0f\u4ed3\u5e93，bounded\u8bc4\u6d4b\u7684\u7ed3\u679c\u66f4\u63a5\u8fd1\u5168\u4ed3\u5224\u65ad；\u5bf9\u4e8e\u5927\u578b\u4ed3\u5e93，bounded\u8bc4\u6d4b\u66f4\u9002\u5408\u4f5c\u4e3a\u201c\u5206\u8bca\u4fe1\u53f7\u201d\u800c\u975e\u201c\u6700\u7ec8\u7ed3\u8bba\u201d\u3002<\/p>\n

      \u4e94\u3001\u9009\u578b\u51b3\u7b56\u6846\u67b6<\/h3>\n\n\u573a\u666f\u63a8\u8350\u7406\u7531<\/tr>\n\n\n\n\n\n\n\n\n
      \u9700\u8981\u7edf\u4e00\u5165\u53e3\u7ba1\u7406\u591a\u4e2aLLM\u540e\u7aef<\/td>\n\u2705 \u63a8\u8350<\/td>\nOpenLLM\u7684\u6838\u5fc3\u4ef7\u503c\u6240\u5728\u2014\u2014\u9002\u914d\u5c42\u7edf\u4e00\u4e86vLLM\/Transformers\/llama.cpp<\/td>\n<\/tr>\n
      \u9700\u8981OpenAI\u517c\u5bb9API\u7684\u81ea\u6258\u7ba1<\/td>\n\u2705 \u63a8\u8350<\/td>\n\u4e00\u6761\u547d\u4ee4\u542f\u52a8，\u5185\u7f6eChat UI，\u652f\u630115+\u6a21\u578b\u7cfb\u5217<\/td>\n<\/tr>\n
      \u5df2\u6709vLLM\u751f\u4ea7\u73af\u5883<\/td>\n\u26a0\ufe0f \u8bc4\u4f30<\/td>\nOpenLLM\u589e\u52a0\u4e86\u4e00\u5c42\u62bd\u8c61，\u53ef\u80fd\u5e26\u6765\u989d\u5916\u5f00\u9500；\u8bc4\u4f30\u662f\u5426\u9700\u8981\u591a\u540e\u7aef\u5207\u6362\u80fd\u529b<\/td>\n<\/tr>\n
      \u672c\u5730\u5f00\u53d1\/\u539f\u578b\u9a8c\u8bc1<\/td>\n\u26a0\ufe0f \u8bc4\u4f30<\/td>\nOllama\u7684\u5f00\u53d1\u8005\u4f53\u9a8c\u66f4\u6781\u81f4；OpenLLM\u66f4\u9002\u5408\u751f\u4ea7\u73af\u5883<\/td>\n<\/tr>\n
      \u9700\u8981\u6781\u81f4\u541e\u5410\u91cf<\/td>\n\u274c \u4e0d\u63a8\u8350<\/td>\n\u539f\u751fvLLM\u662f\u66f4\u76f4\u63a5\u7684\u9009\u62e9；OpenLLM\u7684\u62bd\u8c61\u5c42\u6709\u6027\u80fd\u4ee3\u4ef7<\/td>\n<\/tr>\n
      \u9700\u8981\u4f01\u4e1a\u7ea7\u6a21\u578b\u751f\u547d\u5468\u671f\u7ba1\u7406<\/td>\n\u2705 \u63a8\u8350<\/td>\n\u6a21\u578b\u4ed3\u5e93\u3001\u7248\u672c\u7ba1\u7406\u3001BentoCloud\u96c6\u6210\u3001Prometheus\u76d1\u63a7<\/td>\n<\/tr>\n
      \u9700\u8981Apache 2.0\u5bbd\u677e\u8bb8\u53ef<\/td>\n\u2705 \u63a8\u8350<\/td>\n\u5546\u7528\u53cb\u597d，\u652f\u6301\u95ed\u6e90\u94fe\u63a5<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u516d\u3001\u7ed9\u6280\u672f\u8d1f\u8d23\u4eba\u7684\u4e09\u5468\u9a8c\u8bc1\u6e05\u5355<\/h3>\n

      \u7b2c\u4e00\u5468：\u73af\u5883\u4e0e\u6700\u5c0f\u670d\u52a1<\/p>\n

        \n
      • \u786e\u8ba4\u786c\u4ef6：NVIDIA GPU（\u7b97\u529b\u22658.0）\u4ee5\u83b7\u5f97vLLM\u6700\u4f73\u6027\u80fd<\/li>\n
      • \u7528pip install openllm\u5b89\u88c5，\u6267\u884copenllm hello\u9a8c\u8bc1\u73af\u5883<\/li>\n
      • \u542f\u52a8\u4e00\u4e2a\u6700\u5c0f\u6a21\u578b：openllm start mistral –backend vllm<\/li>\n
      • \u8bb0\u5f55\u542f\u52a8\u65f6\u95f4\u3001\u663e\u5b58\u5360\u7528\u548c\u9996token\u5ef6\u8fdf<\/li>\n<\/ul>\n

        \u7b2c\u4e8c\u5468：\u6838\u5fc3\u529f\u80fd\u9a8c\u8bc1<\/p>\n

          \n
        • \u6d4b\u8bd5OpenAI\u517c\u5bb9API：\u7528OpenAI Python SDK\u8fde\u63a5\u672c\u5730OpenLLM\u670d\u52a1，\u9a8c\u8bc1\/v1\/chat\/completions\u7aef\u70b9<\/li>\n
        • \u6d4b\u8bd5\u540e\u7aef\u5207\u6362：\u7528–backend vllm\u548c–backend transformers\u5206\u522b\u542f\u52a8，\u5bf9\u6bd4\u5ef6\u8fdf\u548c\u541e\u5410\u91cf<\/li>\n
        • \u6d4b\u8bd5Chat UI：\u8bbf\u95ee\/chat\u7aef\u70b9，\u9a8c\u8bc1\u5185\u7f6e\u804a\u5929\u754c\u9762\u7684\u529f\u80fd<\/li>\n
        • \u5982\u679c\u6d89\u53ca\u591a\u6a21\u578b：\u6d4b\u8bd5\u6a21\u578b\u4ed3\u5e93\u7684\u5207\u6362\u548c\u7248\u672c\u7ba1\u7406<\/li>\n<\/ul>\n

          \u7b2c\u4e09\u5468：\u751f\u4ea7\u5c31\u7eea\u8bc4\u4f30<\/p>\n

            \n
          • \u786e\u8ba4vLLM\u540e\u7aef\u914d\u7f6e：\u9a8c\u8bc1GPU\u67b6\u6784\u22658.0，\u786e\u8ba4PagedAttention\u548c\u8fde\u7eed\u6279\u5904\u7406\u662f\u5426\u542f\u7528<\/li>\n
          • \u8bc4\u4f30\u62bd\u8c61\u5c42\u5f00\u9500：\u5bf9\u6bd4\u539f\u751fvLLM\u548cOpenLLM\u5728\u76ee\u6807\u8d1f\u8f7d\u4e0b\u7684\u541e\u5410\u91cf\u5dee\u8ddd<\/li>\n
          • \u786e\u8ba4\u8bb8\u53ef\u8bc1：Apache 2.0\u5141\u8bb8\u5546\u4e1a\u4f7f\u7528\u548c\u95ed\u6e90\u94fe\u63a5，\u4f46\u9700\u8981\u4fdd\u7559\u7248\u6743\u58f0\u660e<\/li>\n
          • \u5236\u5b9a\u76d1\u63a7\u65b9\u6848：\u8bc4\u4f30Prometheus\u6307\u6807\u7684\u96c6\u6210\u65b9\u5f0f\u548c\u544a\u8b66\u914d\u7f6e<\/li>\n<\/ul>\n

            \u4e03\u3001\u7ed3\u8bed<\/h3>\n

            OpenLLM\u752841\u4e2a\u6587\u4ef6\u3001\u4e09\u5c42\u67b6\u6784\u548cApache 2.0\u8bb8\u53ef，\u6784\u5efa\u4e86\u4e00\u4e2a\u201c\u4e0d\u505a\u63a8\u7406\u5f15\u64ce\u7684\u63a8\u7406\u7f51\u5173\u201d\u3002L3\u8bc4\u6d4b\u7ed9\u51fa\u4e867\/8\u7684PASS\u5224\u5b9a，bounded_verified\u7684\u5feb\u7167\u6838\u9a8c\u65e0\u61c8\u53ef\u51fb，\u98ce\u9669\u59ff\u6001baseline\u3002\u552f\u4e00\u672a\u901a\u8fc7\u7684test_surface_present\u662fbounded\u62bd\u6837\u7684\u7ed3\u679c，\u800c\u975e\u4ed3\u5e93\u7684\u7edd\u5bf9\u7f3a\u9677\u3002<\/p>\n

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            \n\u8bc4\u6d4b\u5bf9\u8c61：bentoml\/OpenLLM ec2355ce
            \n\u9879\u76ee\u5b9a\u4f4d：\u7edf\u4e00LLM\u63a8\u7406\u670d\u52a1\u7f51\u5173（\u4e00\u6761\u547d\u4ee4\u628a\u5f00\u6e90LLM\u4ee5OpenAI\u517c\u5bb9API\u5f62\u5f0f\u81ea\u6258\u7ba1）
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