\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357 \u00b7 Batch Inference Complete Guide<\/title>\n<style>\n*,*::before,*::after{box-sizing:border-box;margin:0;padding:0}\nhtml{scroll-behavior:smooth}\n:root{\n --bg:#f8f9fa;--bg2:#fff;--ink:#1a1a2e;--muted:#6c7086;--rule:#e2e4eb;\n --accent:#2563eb;--accent2:#16a34a;--accent3:#dc2626;--accent4:#d97706;--accent5:#7c3aed;\n --card-bg:#fff;--code-bg:#f1f3f5;\n --tag-g:#dcfce7;--tag-g-t:#166534;--tag-b:#dbeafe;--tag-b-t:#1e40af;\n --tag-r:#fee2e2;--tag-r-t:#991b1b;--tag-y:#fef9c3;--tag-y-t:#713f12;--tag-p:#f3e8ff;--tag-p-t:#581c87;\n --shadow:0 1px 3px rgba(0,0,.08);--radius:8px;--max-w:940px\n}\n[data-theme=\"dark\"]{\n --bg:#0b0b1a;--bg2:#16162a;--ink:#e2e4f0;--muted:#7f8396;--rule:#26263e;\n --accent:#60a5fa;--accent2:#4ade80;--accent3:#f87171;--accent4:#fbbf24;--accent5:#a78bfa;\n --card-bg:#16162a;--code-bg:#1e1e36;\n --tag-g:#14532d;--tag-g-t:#bbf7d0;--tag-b:#1e3a5f;--tag-b-t:#bfdbfe;\n --tag-r:#7f1d1d;--tag-r-t:#fecaca;--tag-y:#713f12;--tag-y-t:#fef08a;\n --tag-p:#3b1f6e;--tag-p-t:#e9d5ff;\n --shadow:0 1px 3px rgba(0,0,.3)\n}\nbody{font-family:-apple-system,BlinkMacSystemFont,\"Segoe UI\",\"Noto Sans SC\",\"PingFang SC\",\"Microsoft YaHei\",sans-serif;background:var(--bg);color:var(--ink);line-height:1.7;font-size:15px;transition:background .3s,color .3s}\nheader{position:fixed;top:0;left:0;right:0;z-index:100;background:var(--bg2);border-bottom:1px solid var(--rule);backdrop-filter:blur(12px);-webkit-backdrop-filter:blur(12px);transition:background .3s}\n.header-inner{max-width:var(--max-w);margin:0 auto;display:flex;align-items:center;justify-content:space-between;padding:0 1.5rem;height:56px}\n.logo{font-weight:700;font-size:.95rem;color:var(--accent);display:flex;align-items:center;gap:.4rem}\n.controls{display:flex;align-items:center;gap:.5rem}\n.lang-switch{display:flex;border:1px solid var(--rule);border-radius:6px;overflow:hidden}\n.lang-switch button{background:0 0;border:none;color:var(--muted);padding:.3rem .7rem;font-size:.8rem;cursor:pointer;transition:all .2s;font-family:inherit}\n.lang-switch button.active{background:var(--accent);color:#fff}\n.lang-switch button:not(.active):hover{color:var(--ink);background:var(--rule)}\n.theme-toggle{background:0 0;border:1px solid var(--rule);border-radius:6px;color:var(--muted);width:34px;height:34px;font-size:1rem;cursor:pointer;display:flex;align-items:center;transition:all .2s}\n.theme-toggle:hover{color:var(--ink);background:var(--rule)}\nmain{max-width:var(--max-w);margin:0 auto;padding:80px 1.5rem 3rem}\n.lang-section{display:none}.lang-section.active{display:block}\nh1{font-size:1.9rem;font-weight:800;line-height:1.3;margin-bottom:.5rem;letter-spacing:-.02em}\nh1 .sub{display:block;font-size:.85rem;font-weight:400;color:var(--muted);margin-top:.25rem;letter-spacing:0}\nh2{font-size:1.35rem;font-weight:700;margin:2.5rem 0 1rem;padding-bottom:.5rem;border-bottom:2px solid var(--accent);letter-spacing:-.01em}\nh3{font-size:1.05rem;font-weight:600;margin:1.5rem 0 .6rem;color:var(--accent)}\nh4{font-size:.95rem;font-weight:600;margin:1rem 0 .4rem;color:var(--ink)}\np{margin-bottom:.8rem}\na{color:var(--accent);text-decoration:none}a:hover{text-decoration:underline}\n.hero{text-align:center;padding:2rem 0 1rem}\n.hero p{font-size:1rem;color:var(--muted);max-width:700px;margin:0 auto}\n.tag{display:inline-block;padding:.12rem .5rem;border-radius:4px;font-size:.72rem;font-weight:600;margin-right:.25rem;white-space:nowrap}\n.tag-g{background:var(--tag-g);color:var(--tag-g-t)}.tag-b{background:var(--tag-b);color:var(--tag-b-t)}\n.tag-r{background:var(--tag-r);color:var(--tag-r-t)}.tag-y{background:var(--tag-y);color:var(--tag-y-t)}.tag-p{background:var(--tag-p);color:var(--tag-p-t)}\n.card{background:var(--card-bg);border:1px solid var(--rule);border-radius:var(--radius);padding:1.25rem;margin-bottom:1rem;box-shadow:var(--shadow)}\n.info-box{background:var(--bg);border-left:4px solid var(--accent);padding:.9rem 1.1rem;margin:1rem 0;border-radius:0 var(--radius) var(--radius) 0;font-size:.88rem}\n.info-box strong{color:var(--accent)}\n.info-box.warn{border-left-color:var(--accent4)}.info-box.warn strong{color:var(--accent4)}\n.info-box.danger{border-left-color:var(--accent3)}.info-box.danger strong{color:var(--accent3)}\n.toc{background:var(--card-bg);border:1px solid var(--rule);border-radius:var(--radius);padding:1.15rem 1.4rem;margin-bottom:2rem;box-shadow:var(--shadow)}\n.toc h3{margin:0 0 .5rem;font-size:.9rem;color:var(--muted);text-transform:uppercase;letter-spacing:.05em}\n.toc ol{padding-left:1.1rem;columns:2;column-gap:2rem}\n.toc li{margin-bottom:.25rem;font-size:.88rem}.toc a{color:var(--ink)}.toc a:hover{color:var(--accent);text-decoration:none}\npre.code-block{background:var(--code-bg);padding:.85rem 1rem;border-radius:var(--radius);overflow-x:auto;font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;font-size:.82rem;line-height:1.5;margin:.6rem 0;border:1px solid var(--rule)}\ncode,.inline-code{background:var(--code-bg);padding:.12rem .4rem;border-radius:4px;font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;font-size:.83rem;border:1px solid var(--rule)}\n.table-wrap{overflow-x:auto;margin:1.2rem 0}\ntable{width:100%;border-collapse:collapse;font-size:.82rem}\nthead th{background:var(--accent);color:#fff;padding:.6rem .5rem;text-align:center;font-weight:600;white-space:nowrap}\nthead th:first-child{border-radius:6px 0 0 0}thead th:last-child{border-radius:0 6px 0 0}\ntbody td{padding:.55rem .5rem;border-bottom:1px solid var(--rule);text-align:center;vertical-align:middle}\ntbody tr:nth-child(even){background:var(--bg)}\ntbody td:first-child{text-align:left;font-weight:600}\n.terminal{background:#1a1a2e;color:#a8e6cf;border-radius:var(--radius);padding:.9rem 1rem;font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;font-size:.82rem;line-height:1.6;margin:.6rem 0;overflow-x:auto;border:1px solid #333}\n.terminal .prompt{color:#60a5fa}.terminal .comment{color:#6c7086;font-style:italic}.terminal .output{color:#e2e4f0}\n[data-theme=\"dark\"] .terminal{background:#08081a}\n.steps{counter-reset:step;list-style:none;padding:0}\n.steps li{counter-increment:step;position:relative;padding:.85rem 1rem .85rem 2.8rem;margin-bottom:.5rem;border-left:2px solid var(--rule);border-radius:0 var(--radius) 0;background:var(--card-bg);box-shadow:var(--shadow)}\n.steps li::before{content:counter(step);position:absolute;left:-13px;top:.85rem;width:26px;height:26px;border-radius:50%;background:var(--accent);color:#fff;display:flex;align-items:center;justify-content:center;font-size:.78rem;font-weight:700}\n.steps li .cmd{display:block;background:var(--code-bg);padding:.4rem .7rem;border-radius:5px;font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;font-size:.82rem;margin:.3rem 0;overflow-x:auto;border:1px solid var(--rule)}\n.steps li .note{display:block;color:var(--muted);font-size:.82rem;margin-top:.2rem}\n.flow-diagram{background:var(--card-bg);border:1px solid var(--rule);border-radius:var(--radius);padding:1.25rem;margin:1.25rem 0;text-align:center}\n.flow-row{display:flex;align-items:center;justify-content:center;flex-wrap:wrap;gap:.35rem;margin:.4rem 0}\n.flow-item{display:inline-block;padding:.4rem .8rem;border-radius:6px;font-weight:600;font-size:.82rem;text-align:center;background:var(--accent);color:#fff;min-width:60px}\n.flow-item.green{background:var(--accent2)}.flow-item.red{background:var(--accent3)}.flow-item.yellow{background:var(--accent4);color:#1a1a2e}.flow-item.purple{background:var(--accent5)}\n.flow-arrow{color:var(--muted);font-size:1rem}\n.cmd-grid{display:grid;grid-template-columns:repeat(auto-fill,minmax(280px,1fr));gap:.75rem;margin:1rem 0}\n.cmd-card{background:var(--card-bg);border:1px solid var(--rule);border-radius:var(--radius);padding:.9rem;box-shadow:var(--shadow)}\n.cmd-card h4{margin:0 0 .35rem;font-size:.88rem;color:var(--accent)}\n.cmd-card .cmd{font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;font-size:.8rem;background:var(--code-bg);padding:.3rem .5rem;border-radius:4px;display:block;margin-bottom:.3rem;border:1px solid var(--rule)}\n.cmd-card .desc{font-size:.8rem;color:var(--muted)}\n.two-col{display:grid;grid-template-columns:1fr 1fr;gap:1.25rem;margin:1.25rem 0}\n.col{background:var(--card-bg);border:1px solid var(--rule);border-radius:var(--radius);padding:1.25rem;box-shadow:var(--shadow)}\n.col h4{margin-top:0}\n.compare-box{display:grid;grid-template-columns:1fr 1fr;gap:1rem;margin:1rem 0}\n.compare-col{background:var(--card-bg);border:1px solid var(--rule);border-radius:var(--radius);padding:1rem;box-shadow:var(--shadow)}\n.compare-col h4{margin:0 0 .4rem;font-size:.88rem}\n.compare-col.bad h4{color:var(--accent3)}\n.compare-col.good h4{color:var(--accent2)}\npre.example{background:var(--code-bg);padding:.6rem .8rem;border-radius:6px;font-family:\"SF Mono\",Consolas,\"Courier New\",monospace;font-size:.78rem;line-height:1.5;margin:.4rem 0;border:1px solid var(--rule);color:var(--ink)}\nfooter{max-width:var(--max-w);margin:3rem auto 0;padding:2rem 1.5rem 3rem;border-top:1px solid var(--rule);text-align:center;font-size:.82rem;color:var(--muted)}\nfooter .links{display:flex;justify-content:center;gap:1.5rem;flex-wrap:wrap;margin-bottom:.8rem}\nfooter .links a{color:var(--muted)}footer .links a:hover{color:var(--accent)}\n@media(max-width:640px){\n h1{font-size:1.4rem}.toc ol{columns:1}.header-inner{padding:0 1rem}main{padding:72px 1rem 2rem}\n .steps li{padding-left:2.4rem}.steps li::before{left:-11px;width:22px;height:22px;font-size:.7rem}\n .two-col{grid-template-columns:1fr}.cmd-grid{grid-template-columns:1fr}.compare-box{grid-template-columns:1fr}\n}\n<\/style>\n<\/head>\n<body>\n<header>\n <div class=\"header-inner\">\n <div class=\"logo\"><span>\ud83d\ude80<\/span> \u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357<\/div>\n <div class=\"controls\">\n <div class=\"lang-switch\">\n <button class=\"active\" onclick=\"setLang('zh')\" id=\"btn-zh\">\u4e2d\u6587<\/button>\n <button onclick=\"setLang('en')\" id=\"btn-en\">English<\/button>\n <\/div>\n <button class=\"theme-toggle\" onclick=\"toggleTheme()\" title=\"\u5207\u6362\u660e\u6697\u4e3b\u9898\">☼<\/button>\n <\/div>\n <\/div>\n<\/header>\n<main>\n\n<div class=\"lang-section active\" id=\"lang-zh\">\n<div class=\"hero\">\n <h1>\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357\uff08\u6982\u5ff5\u2192\u5b9e\u8df5\u2192\u963f\u91cc\u4e91\u767e\u70bc\u5b9e\u6218\uff09<span class=\"sub\">\u7406\u89e3\u6279\u91cf\u63a8\u7406\u7684\u6838\u5fc3\u4ef7\u503c\uff0c\u638c\u63e1\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u7684\u5b8c\u6574\u4f7f\u7528\u6d41\u7a0b<\/span><\/h1>\n <p>\u6279\u91cf\u63a8\u7406 vs \u5b9e\u65f6\u63a8\u7406\u3001\u9002\u7528\u573a\u666f\u3001JSONL \u6570\u636e\u51c6\u5907\u3001\u4efb\u52a1\u63d0\u4ea4\u4e0e\u76d1\u63a7\u3001\u7ed3\u679c\u83b7\u53d6\u3001\u6210\u672c\u4f18\u5316\u3001\u5e38\u89c1\u95ee\u9898\u5168\u8986\u76d6<\/p>\n<\/div>\n\n<div class=\"toc\">\n <h3>\u76ee\u5f55<\/h3>\n <ol>\n <li><a href=\"#zh-1\">\u4e00\u3001\u4ec0\u4e48\u662f\u6279\u91cf\u63a8\u7406\uff08Batch Inference\uff09<\/a><\/li>\n <li><a href=\"#zh-2\">\u4e8c\u3001\u6279\u91cf\u63a8\u7406 vs \u5b9e\u65f6\u63a8\u7406\u5bf9\u6bd4<\/a><\/li>\n <li><a href=\"#zh-3\">\u4e09\u3001\u9002\u7528\u573a\u666f\u4e0e\u6838\u5fc3\u4ef7\u503c<\/a><\/li>\n <li><a href=\"#zh-4\">\u56db\u3001\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6982\u89c8<\/a><\/li>\n <li><a href=\"#zh-5\">\u4e94\u3001\u6570\u636e\u51c6\u5907\uff1aJSONL \u683c\u5f0f\u89c4\u8303<\/a><\/li>\n <li><a href=\"#zh-6\">\u516d\u3001\u63d0\u4ea4\u6279\u91cf\u63a8\u7406\u4efb\u52a1\uff08\u5b8c\u6574\u4ee3\u7801\uff09<\/a><\/li>\n <li><a href=\"#zh-7\">\u4e03\u3001\u4efb\u52a1\u76d1\u63a7\u4e0e\u72b6\u6001\u7ba1\u7406<\/a><\/li>\n <li><a href=\"#zh-8\">\u516b\u3001\u7ed3\u679c\u83b7\u53d6\u4e0e\u540e\u5904\u7406<\/a><\/li>\n <li><a href=\"#zh-9\">\u4e5d\u3001\u6210\u672c\u4f18\u5316\u4e0e\u6700\u4f73\u5b9e\u8df5<\/a><\/li>\n <li><a href=\"#zh-10\">\u5341\u3001\u5e38\u89c1\u95ee\u9898\u4e0e\u6392\u67e5<\/a><\/li>\n <\/ol>\n<\/div>\n\n\n<h2 id=\"zh-1\">\u4e00\u3001\u4ec0\u4e48\u662f\u6279\u91cf\u63a8\u7406\uff08Batch Inference\uff09<\/h2>\n\n<p>\u6279\u91cf\u63a8\u7406\uff08Batch Inference\uff09\u662f\u6307\u5c06\u5927\u91cf\u72ec\u7acb\u7684\u63a8\u7406\u8bf7\u6c42\u6c47\u603b\u6210\u4e00\u4e2a\u6279\u6b21\uff0c\u7edf\u4e00\u63d0\u4ea4\u7ed9\u6a21\u578b\u8fdb\u884c\u5904\u7406\uff0c\u5728\u540e\u53f0\u79bb\u7ebf\u6267\u884c\u5e76\u5f02\u6b65\u8fd4\u56de\u7ed3\u679c\u7684\u8ba1\u7b97\u6a21\u5f0f\u3002<\/p>\n\n<div class=\"flow-diagram\">\n <div class=\"flow-row\">\n <span class=\"flow-item green\">\u51c6\u5907\u6570\u636e<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item\">\u4e0a\u4f20\u6587\u4ef6<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item yellow\">\u63d0\u4ea4\u4efb\u52a1<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item purple\">\u540e\u53f0\u5904\u7406<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item green\">\u83b7\u53d6\u7ed3\u679c<\/span>\n <\/div>\n<\/div>\n\n<div class=\"card\">\n <h4>\u6279\u91cf\u63a8\u7406\u7684\u56db\u5927\u7279\u5f81<\/h4>\n <p><span class=\"tag tag-b\">\u5f02\u6b65\u5904\u7406<\/span> \u63d0\u4ea4\u4efb\u52a1\u540e\u7acb\u5373\u8fd4\u56de\uff0c\u65e0\u9700\u7b49\u5f85\uff0c\u540e\u53f0\u6392\u961f\u5904\u7406<\/p>\n <p><span class=\"tag tag-g\">\u9ad8\u541e\u5410<\/span> \u5145\u5206\u5229\u7528 GPU \u5e76\u884c\u8ba1\u7b97\u80fd\u529b\uff0c\u5355\u4f4d\u65f6\u95f4\u5904\u7406\u66f4\u591a\u8bf7\u6c42<\/p>\n <p><span class=\"tag tag-y\">\u4f4e\u6210\u672c<\/span> \u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6210\u672c\u4ec5\u4e3a\u5b9e\u65f6\u8c03\u7528\u7684 50%<\/p>\n <p><span class=\"tag tag-p\">\u79bb\u7ebf\u6267\u884c<\/span> \u4e0d\u5360\u7528\u5b9e\u65f6\u670d\u52a1\u8d44\u6e90\uff0c\u9002\u5408\u975e\u65f6\u6548\u6027\u4efb\u52a1<\/p>\n<\/div>\n\n\n<h2 id=\"zh-2\">\u4e8c\u3001\u6279\u91cf\u63a8\u7406 vs \u5b9e\u65f6\u63a8\u7406\u5bf9\u6bd4<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead>\n <tr><th>\u7ef4\u5ea6<\/th><th>\u6279\u91cf\u63a8\u7406\uff08Batch\uff09<\/th><th>\u5b9e\u65f6\u63a8\u7406\uff08Online\uff09<\/th><\/tr>\n <\/thead>\n <tbody>\n <tr><td>\u54cd\u5e94\u65b9\u5f0f<\/td><td>\u5f02\u6b65\uff0c\u63d0\u4ea4\u540e\u540e\u53f0\u5904\u7406<\/td><td>\u540c\u6b65\uff0c\u5373\u65f6\u8fd4\u56de\u7ed3\u679c<\/td><\/tr>\n <tr><td>\u5ef6\u8fdf\u8981\u6c42<\/td><td>\u5206\u949f\u7ea7~\u5c0f\u65f6\u7ea7\uff0c\u53ef\u63a5\u53d7<\/td><td>\u6beb\u79d2\u7ea7~\u79d2\u7ea7\uff0c\u8981\u6c42\u4f4e\u5ef6\u8fdf<\/td><\/tr>\n <tr><td>\u6210\u672c<\/td><td>\u4f4e\uff08\u7ea6\u4e3a\u5b9e\u65f6\u7684 50%\uff09<\/td><td>\u9ad8\uff08\u6309\u5b9e\u65f6\u8c03\u7528\u8ba1\u8d39\uff09<\/td><\/tr>\n <tr><td>\u541e\u5410\u91cf<\/td><td>\u9ad8\uff08GPU \u6279\u91cf\u5e76\u884c\uff09<\/td><td>\u53d7\u5e76\u53d1\u9650\u5236<\/td><\/tr>\n <tr><td>\u6570\u636e\u89c4\u6a21<\/td><td>\u5927\u89c4\u6a21\uff08\u5343~\u767e\u4e07\u6761\uff09<\/td><td>\u5c0f\u89c4\u6a21\uff08\u5355\u6761\u6216\u5c11\u91cf\uff09<\/td><\/tr>\n <tr><td>\u9002\u7528\u573a\u666f<\/td><td>\u6570\u636e\u5206\u6790\u3001\u5185\u5bb9\u751f\u6210\u3001\u6a21\u578b\u8bc4\u4f30<\/td><td>\u5bf9\u8bdd\u5e94\u7528\u3001\u5b9e\u65f6\u63a8\u8350\u3001\u5728\u7ebf\u5ba2\u670d<\/td><\/tr>\n <tr><td>\u8d44\u6e90\u5229\u7528<\/td><td>\u95f2\u65f6\u8c03\u5ea6\uff0c\u8d44\u6e90\u590d\u7528\u7387\u9ad8<\/td><td>\u5e38\u9a7b\u670d\u52a1\uff0c\u9884\u7559\u8d44\u6e90<\/td><\/tr>\n <tr><td>\u5bb9\u9519\u6027<\/td><td>\u652f\u6301\u65ad\u70b9\u7eed\u4f20\uff0c\u5931\u8d25\u53ef\u91cd\u8bd5<\/td><td>\u5355\u6b21\u5931\u8d25\u5373\u8fd4\u56de\u9519\u8bef<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"compare-box\">\n <div class=\"compare-col good\">\n <h4>\u2705 \u9009\u62e9\u6279\u91cf\u63a8\u7406<\/h4>\n <p>\u9700\u8981\u5904\u7406\u6570\u4e07\u6761\u6587\u672c\u5206\u7c7b<\/p>\n <p>\u6279\u91cf\u751f\u6210\u8425\u9500\u6587\u6848<\/p>\n <p>\u5bf9\u5386\u53f2\u6570\u636e\u505a\u60c5\u611f\u5206\u6790<\/p>\n <p>\u6a21\u578b\u6548\u679c\u6279\u91cf\u8bc4\u4f30\u6d4b\u8bd5<\/p>\n <p>\u975e\u5de5\u4f5c\u65f6\u95f4\u7684\u6570\u636e\u5904\u7406<\/p>\n <\/div>\n <div class=\"compare-col bad\">\n <h4>\u274c \u9009\u62e9\u5b9e\u65f6\u63a8\u7406<\/h4>\n <p>\u7528\u6237\u5b9e\u65f6\u5bf9\u8bdd\u4ea4\u4e92<\/p>\n <p>\u5728\u7ebf\u63a8\u8350\u7cfb\u7edf<\/p>\n <p>\u5b9e\u65f6\u98ce\u63a7\u5224\u65ad<\/p>\n <p>\u9700\u8981\u5373\u65f6\u54cd\u5e94\u7684 API<\/p>\n <p>\u5355\u6b21\u3001\u5c11\u91cf\u3001\u9ad8\u9891\u8bf7\u6c42<\/p>\n <\/div>\n<\/div>\n\n\n<h2 id=\"zh-3\">\u4e09\u3001\u9002\u7528\u573a\u666f\u4e0e\u6838\u5fc3\u4ef7\u503c<\/h2>\n\n<h3>3.1 \u5178\u578b\u5e94\u7528\u573a\u666f<\/h3>\n<div class=\"cmd-grid\">\n <div class=\"cmd-card\">\n <h4>\u6570\u636e\u5206\u6790<\/h4>\n <div class=\"desc\">\u5bf9\u6d77\u91cf\u7528\u6237\u8bc4\u8bba\u3001\u53cd\u9988\u3001\u65e5\u5fd7\u8fdb\u884c\u60c5\u611f\u5206\u6790\u3001\u4e3b\u9898\u5206\u7c7b\u3001\u5b9e\u4f53\u63d0\u53d6\uff0c\u6d1e\u5bdf\u4e1a\u52a1\u8d8b\u52bf\u3002<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>\u5185\u5bb9\u751f\u6210<\/h4>\n <div class=\"desc\">\u6279\u91cf\u751f\u6210\u5546\u54c1\u63cf\u8ff0\u3001\u8425\u9500\u6587\u6848\u3001\u7ffb\u8bd1\u5185\u5bb9\u3001\u4ee3\u7801\u6ce8\u91ca\uff0c\u63d0\u5347\u5185\u5bb9\u751f\u4ea7\u6548\u7387\u3002<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>\u6a21\u578b\u8bc4\u4f30<\/h4>\n <div class=\"desc\">\u4f7f\u7528\u6807\u51c6\u6d4b\u8bd5\u96c6\u5bf9\u6a21\u578b\u8fdb\u884c\u6279\u91cf\u8bc4\u4f30\uff0c\u83b7\u53d6\u51c6\u786e\u7387\u3001F1 \u5206\u6570\u7b49\u6307\u6807\u3002<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>\u6570\u636e\u6807\u6ce8<\/h4>\n <div class=\"desc\">\u5229\u7528\u6a21\u578b\u9884\u6807\u6ce8\u6570\u636e\uff0c\u4eba\u5de5\u590d\u6838\u4fee\u6b63\uff0c\u964d\u4f4e\u6807\u6ce8\u6210\u672c 70% \u4ee5\u4e0a\u3002<\/div>\n <\/div>\n<\/div>\n\n<h3>3.2 \u6838\u5fc3\u4ef7\u503c\u603b\u7ed3<\/h3>\n<div class=\"info-box\">\n <strong>\u6279\u91cf\u63a8\u7406\u7684\u6838\u5fc3\u4ef7\u503c\u516c\u5f0f\uff1a\u66f4\u4f4e\u7684\u5355\u4f4d\u6210\u672c \u00d7 \u66f4\u9ad8\u7684\u541e\u5410\u91cf \u00d7 \u7075\u6d3b\u7684\u65f6\u95f4\u7a97\u53e3 = \u5927\u89c4\u6a21 AI \u5904\u7406\u7684\u7ecf\u6d4e\u6700\u4f18\u89e3\u3002<\/strong>\n<\/div>\n\n\n<h2 id=\"zh-4\">\u56db\u3001\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6982\u89c8<\/h2>\n\n<p>\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u662f\u4e13\u4e3a\u5927\u89c4\u6a21\u3001\u975e\u5b9e\u65f6\u63a8\u7406\u4efb\u52a1\u8bbe\u8ba1\u7684\u5f02\u6b65\u5904\u7406\u670d\u52a1\uff0c\u652f\u6301\u901a\u8fc7\u6587\u4ef6\u4e00\u6b21\u6027\u63d0\u4ea4\u6d77\u91cf\u8bf7\u6c42\uff0c\u5728\u540e\u53f0\u79bb\u7ebf\u5904\u7406\u3002<\/p>\n\n<div class=\"card\">\n <h4>\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6838\u5fc3\u80fd\u529b<\/h4>\n <p><span class=\"tag tag-b\">\u6587\u4ef6\u63d0\u4ea4<\/span> \u652f\u6301 JSONL \u683c\u5f0f\u6587\u4ef6\uff0c\u6bcf\u884c\u4e00\u4e2a\u72ec\u7acb\u8bf7\u6c42<\/p>\n <p><span class=\"tag tag-g\">\u6a21\u578b\u4e30\u5bcc<\/span> \u652f\u6301\u901a\u4e49\u5343\u95ee\u3001Llama\u3001DeepSeek \u7b49\u4e3b\u6d41\u5927\u6a21\u578b<\/p>\n <p><span class=\"tag tag-y\">\u6210\u672c\u4f18\u5316<\/span> \u6279\u91cf\u63a8\u7406\u4ef7\u683c\u7ea6\u4e3a\u5b9e\u65f6\u8c03\u7528\u7684 50%<\/p>\n <p><span class=\"tag tag-p\">\u72b6\u6001\u8ffd\u8e2a<\/span> \u63d0\u4f9b\u4efb\u52a1\u521b\u5efa\u3001\u6392\u961f\u3001\u8fd0\u884c\u3001\u5b8c\u6210\u5168\u6d41\u7a0b\u72b6\u6001\u67e5\u8be2<\/p>\n <p><span class=\"tag tag-r\">\u7ed3\u679c\u6301\u4e45<\/span> \u5904\u7406\u5b8c\u6210\u540e\u7ed3\u679c\u6587\u4ef6\u4fdd\u5b58\uff0c\u652f\u6301\u4e0b\u8f7d\u548c\u89e3\u6790<\/p>\n<\/div>\n\n<h3>4.1 \u4f7f\u7528\u524d\u51c6\u5907<\/h3>\n<ol class=\"steps\">\n <li>\u6ce8\u518c\u963f\u91cc\u4e91\u8d26\u53f7\u5e76\u5b8c\u6210\u5b9e\u540d\u8ba4\u8bc1\n <span class=\"note\"><a href=\"https:\/\/www.aliyun.com\/\" target=\"_blank\" rel=\"noopener\">\u963f\u91cc\u4e91\u5b98\u7f51<\/a><\/span>\n <\/li>\n <li>\u5f00\u901a\u767e\u70bc\uff08Model Studio\uff09\u670d\u52a1\n <span class=\"note\">\u5728\u963f\u91cc\u4e91\u63a7\u5236\u53f0\u641c\u7d22”\u767e\u70bc”\u6216”Model Studio”\uff0c\u6309\u6307\u5f15\u5f00\u901a<\/span>\n <\/li>\n <li>\u83b7\u53d6 API-Key\n <span class=\"cmd\">\u767e\u70bc\u63a7\u5236\u53f0 \u2192 API-Key \u7ba1\u7406 \u2192 \u521b\u5efa API-Key<\/span>\n <span class=\"note\">\u59a5\u5584\u4fdd\u5b58 Key\uff0c\u4e0d\u8981\u786c\u7f16\u7801\u5728\u4ee3\u7801\u4e2d\u63d0\u4ea4\u5230\u4ed3\u5e93<\/span>\n <\/li>\n <li>\u5b89\u88c5 Python SDK\n <span class=\"cmd\">pip install alibabacloud-bailian20231229<\/span>\n <span class=\"note\">\u6216\u901a\u8fc7 OpenAI \u517c\u5bb9\u63a5\u53e3\u4f7f\u7528 openai \u5e93<\/span>\n <\/li>\n<\/ol>\n\n\n<h2 id=\"zh-5\">\u4e94\u3001\u6570\u636e\u51c6\u5907\uff1aJSONL \u683c\u5f0f\u89c4\u8303<\/h2>\n\n<div class=\"info-box\">\n <strong>JSONL\uff08JSON Lines\uff09\u662f\u6279\u91cf\u63a8\u7406\u7684\u6807\u51c6\u8f93\u5165\u683c\u5f0f\uff0c\u6bcf\u884c\u4e00\u4e2a\u72ec\u7acb\u7684 JSON \u5bf9\u8c61\uff0c\u8868\u793a\u4e00\u4e2a\u63a8\u7406\u8bf7\u6c42\u3002\u6587\u4ef6\u65e0\u9700\u9996\u5c3e\u62ec\u53f7\uff0c\u7eaf\u6587\u672c\u5373\u53ef\u3002<\/strong>\n<\/div>\n\n<h3>5.1 JSONL \u683c\u5f0f\u793a\u4f8b<\/h3>\n<pre class=\"code-block\">{\"custom_id\": \"req-001\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"\u8bf7\u7528\u4e00\u53e5\u8bdd\u603b\u7ed3\uff1a\u4eba\u5de5\u667a\u80fd\u6b63\u5728\u6539\u53d8\u5404\u4e2a\u884c\u4e1a\u3002\"}]}}\n{\"custom_id\": \"req-002\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"\u8bf7\u7ffb\u8bd1\u4e3a\u82f1\u6587\uff1a\u4f60\u597d\uff0c\u4e16\u754c\u3002\"}]}}\n{\"custom_id\": \"req-003\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"\u5224\u65ad\u60c5\u611f\u503e\u5411\uff1a\u8fd9\u6b3e\u4ea7\u54c1\u592a\u68d2\u4e86\uff0c\u975e\u5e38\u6ee1\u610f\uff01\"}]}}\n<\/pre>\n\n<h3>5.2 JSONL \u5b57\u6bb5\u8bf4\u660e<\/h3>\n<div class=\"table-wrap\">\n<table>\n <thead>\n <tr><th>\u5b57\u6bb5<\/th><th>\u7c7b\u578b<\/th><th>\u5fc5\u586b<\/th><th>\u8bf4\u660e<\/th><\/tr>\n <\/thead>\n <tbody>\n <tr><td>custom_id<\/td><td>string<\/td><td>\u662f<\/td><td>\u81ea\u5b9a\u4e49\u8bf7\u6c42\u6807\u8bc6\uff0c\u7528\u4e8e\u7ed3\u679c\u5339\u914d<\/td><\/tr>\n <tr><td>method<\/td><td>string<\/td><td>\u662f<\/td><td>HTTP \u65b9\u6cd5\uff0c\u56fa\u5b9a\u4e3a “POST”<\/td><\/tr>\n <tr><td>url<\/td><td>string<\/td><td>\u662f<\/td><td>\u63a5\u53e3\u8def\u5f84\uff0c”\/v1\/chat\/completions”<\/td><\/tr>\n <tr><td>body<\/td><td>object<\/td><td>\u662f<\/td><td>\u8bf7\u6c42\u4f53\uff0c\u4e0e\u5b9e\u65f6 API \u53c2\u6570\u4e00\u81f4<\/td><\/tr>\n <tr><td>body.model<\/td><td>string<\/td><td>\u662f<\/td><td>\u6a21\u578b\u540d\u79f0\uff0c\u5982 qwen-turbo<\/td><\/tr>\n <tr><td>body.messages<\/td><td>array<\/td><td>\u662f<\/td><td>\u5bf9\u8bdd\u6d88\u606f\u5217\u8868<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h3>5.3 \u6570\u636e\u51c6\u5907\u4ee3\u7801<\/h3>\n<pre class=\"code-block\">import json\nfrom pathlib import Path\n\n\ndef prepare_batch_input(\n items: list[dict],\n output_path: str = \"batch_input.jsonl\",\n model: str = \"qwen-turbo\"\n) -> str:\n \"\"\"\u5c06\u6570\u636e\u5217\u8868\u8f6c\u6362\u4e3a JSONL \u6279\u91cf\u63a8\u7406\u8f93\u5165\u6587\u4ef6\u3002\n\n Args:\n items: \u6bcf\u6761\u5305\u542b\u81ea\u5b9a\u4e49\u5b57\u6bb5\u7684\u6570\u636e\u5b57\u5178\n output_path: \u8f93\u51fa JSONL \u6587\u4ef6\u8def\u5f84\n model: \u4f7f\u7528\u7684\u6a21\u578b\u540d\u79f0\n\n Returns:\n \u8f93\u51fa\u6587\u4ef6\u7684\u7edd\u5bf9\u8def\u5f84\n \"\"\"\n output = Path(output_path)\n with output.open(\"w\", encoding=\"utf-8\") as f:\n for idx, item in enumerate(items, 1):\n record = {\n \"custom_id\": item.get(\"id\", f\"req-{idx:04d}\"),\n \"method\": \"POST\",\n \"url\": \"\/v1\/chat\/completions\",\n \"body\": {\n \"model\": model,\n \"messages\": [\n {\"role\": \"system\", \"content\": item.get(\"system\", \"\")},\n {\"role\": \"user\", \"content\": item[\"prompt\"]}\n ] if item.get(\"system\") else [\n {\"role\": \"user\", \"content\": item[\"prompt\"]}\n ],\n \"max_tokens\": item.get(\"max_tokens\", 512),\n \"temperature\": item.get(\"temperature\", 0.7)\n }\n }\n f.write(json.dumps(record, ensure_ascii=False) + \"\\n\")\n\n return str(output.resolve())\n\n\n# \u4f7f\u7528\u793a\u4f8b\ndata = [\n {\"id\": \"sentiment-001\", \"prompt\": \"\u5224\u65ad\u60c5\u611f\uff1a\u4ea7\u54c1\u8d28\u91cf\u5f88\u5dee\uff0c\u9000\u8d27\u4e86\u3002\"},\n {\"id\": \"sentiment-002\", \"prompt\": \"\u5224\u65ad\u60c5\u611f\uff1a\u7269\u6d41\u5f88\u5feb\uff0c\u5305\u88c5\u5b8c\u597d\u3002\"},\n {\"id\": \"summary-001\", \"prompt\": \"\u603b\u7ed3\uff1a\u672c\u6587\u4ecb\u7ecd\u4e86\u6279\u91cf\u63a8\u7406\u7684\u4f18\u52bf\u548c\u5e94\u7528\u573a\u666f\u3002\"},\n]\n\nfile_path = prepare_batch_input(data, model=\"qwen-turbo\")\nprint(f\"\u5df2\u751f\u6210\u6279\u91cf\u63a8\u7406\u8f93\u5165\u6587\u4ef6: {file_path}\")\n<\/pre>\n\n<h3>5.4 \u6570\u636e\u6821\u9a8c<\/h3>\n<pre class=\"code-block\">def validate_jsonl(file_path: str) -> tuple[int, list[str]]:\n \"\"\"\u6821\u9a8c JSONL \u6587\u4ef6\u683c\u5f0f\u662f\u5426\u6b63\u786e\u3002\n\n Returns:\n (\u6709\u6548\u884c\u6570, \u9519\u8bef\u5217\u8868)\n \"\"\"\n errors = []\n valid_count = 0\n\n with open(file_path, \"r\", encoding=\"utf-8\") as f:\n for line_num, line in enumerate(f, 1):\n line = line.strip()\n if not line:\n continue\n try:\n obj = json.loads(line)\n required = [\"custom_id\", \"method\", \"url\", \"body\"]\n for field in required:\n if field not in obj:\n errors.append(f\"\u7b2c {line_num} \u884c\u7f3a\u5c11\u5b57\u6bb5: {field}\")\n break\n else:\n valid_count += 1\n except json.JSONDecodeError as e:\n errors.append(f\"\u7b2c {line_num} \u884c JSON \u89e3\u6790\u9519\u8bef: {e}\")\n\n return valid_count, errors\n\n\ncount, errs = validate_jsonl(\"batch_input.jsonl\")\nprint(f\"\u6709\u6548\u8bf7\u6c42: {count} \u6761\")\nif errs:\n for e in errs:\n print(f\"\u9519\u8bef: {e}\")\n<\/pre>\n\n\n<h2 id=\"zh-6\">\u516d\u3001\u63d0\u4ea4\u6279\u91cf\u63a8\u7406\u4efb\u52a1\uff08\u5b8c\u6574\u4ee3\u7801\uff09<\/h2>\n\n<h3>6.1 \u4f7f\u7528 OpenAI \u517c\u5bb9\u63a5\u53e3\uff08\u63a8\u8350\uff09<\/h3>\n<pre class=\"code-block\">import os\nfrom pathlib import Path\nfrom openai import OpenAI\n\n\ndef create_batch_job(\n input_file: str,\n api_key: str | None = None,\n base_url: str = \"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n) -> dict:\n \"\"\"\u521b\u5efa\u963f\u91cc\u4e91\u767e\u70bc\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u3002\n\n Args:\n input_file: JSONL \u8f93\u5165\u6587\u4ef6\u8def\u5f84\n api_key: \u767e\u70bc API-Key\uff0c\u9ed8\u8ba4\u4ece\u73af\u5883\u53d8\u91cf DASHSCOPE_API_KEY \u8bfb\u53d6\n base_url: \u767e\u70bc\u517c\u5bb9\u63a5\u53e3\u5730\u5740\n\n Returns:\n \u4efb\u52a1\u4fe1\u606f\u5b57\u5178\uff0c\u5305\u542b batch_id\n \"\"\"\n api_key = api_key or os.getenv(\"DASHSCOPE_API_KEY\")\n if not api_key:\n raise ValueError(\"\u8bf7\u8bbe\u7f6e API-Key\uff1a\u73af\u5883\u53d8\u91cf DASHSCOPE_API_KEY \u6216\u53c2\u6570\u4f20\u5165\")\n\n client = OpenAI(api_key=api_key, base_url=base_url)\n\n # 1. \u4e0a\u4f20\u8f93\u5165\u6587\u4ef6\n with open(input_file, \"rb\") as f:\n file_obj = client.files.create(file=f, purpose=\"batch\")\n print(f\"\u6587\u4ef6\u4e0a\u4f20\u6210\u529f: {file_obj.id}\")\n\n # 2. \u521b\u5efa\u6279\u91cf\u4efb\u52a1\n batch = client.batches.create(\n input_file_id=file_obj.id,\n endpoint=\"\/v1\/chat\/completions\",\n completion_window=\"24h\" # \u4efb\u52a1\u8d85\u65f6\u65f6\u95f4\n )\n print(f\"\u6279\u91cf\u4efb\u52a1\u521b\u5efa\u6210\u529f: {batch.id}\")\n print(f\"\u72b6\u6001: {batch.status}\")\n\n return {\n \"batch_id\": batch.id,\n \"input_file_id\": file_obj.id,\n \"status\": batch.status\n }\n\n\n# \u4f7f\u7528\njob = create_batch_job(\"batch_input.jsonl\")\n<\/pre>\n\n<h3>6.2 \u4f7f\u7528\u963f\u91cc\u4e91\u5b98\u65b9 SDK<\/h3>\n<pre class=\"code-block\">import os\nfrom alibabacloud_bailian20231229.client import Client as BailianClient\nfrom alibabacloud_tea_openapi import models as open_api_models\n\n\ndef create_batch_job_sdk(\n input_file_url: str,\n access_key_id: str | None = None,\n access_key_secret: str | None = None,\n model: str = \"qwen-turbo\"\n) -> str:\n \"\"\"\u4f7f\u7528\u963f\u91cc\u4e91 SDK \u521b\u5efa\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u3002\n\n Args:\n input_file_url: \u5df2\u4e0a\u4f20\u5230 OSS \u7684\u8f93\u5165\u6587\u4ef6 URL\n access_key_id: \u963f\u91cc\u4e91 AccessKey ID\n access_key_secret: \u963f\u91cc\u4e91 AccessKey Secret\n model: \u6a21\u578b\u540d\u79f0\n\n Returns:\n \u4efb\u52a1 ID\n \"\"\"\n access_key_id = access_key_id or os.getenv(\"ALIBABA_CLOUD_ACCESS_KEY_ID\")\n access_key_secret = access_key_secret or os.getenv(\"ALIBABA_CLOUD_ACCESS_KEY_SECRET\")\n\n config = open_api_models.Config(\n access_key_id=access_key_id,\n access_key_secret=access_key_secret\n )\n config.endpoint = \"bailian.cn-beijing.aliyuncs.com\"\n client = BailianClient(config)\n\n # \u521b\u5efa\u6279\u91cf\u4efb\u52a1\n response = client.create_batch_inference_job(\n model=model,\n input_file_url=input_file_url,\n output_file_prefix=\"batch-output\/\"\n )\n\n job_id = response.body.job_id\n print(f\"\u4efb\u52a1\u521b\u5efa\u6210\u529f: {job_id}\")\n return job_id\n<\/pre>\n\n\n<h2 id=\"zh-7\">\u4e03\u3001\u4efb\u52a1\u76d1\u63a7\u4e0e\u72b6\u6001\u7ba1\u7406<\/h2>\n\n<h3>7.1 \u4efb\u52a1\u72b6\u6001\u6d41\u8f6c<\/h3>\n<div class=\"flow-diagram\">\n <div class=\"flow-row\">\n <span class=\"flow-item\">validating<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item yellow\">in_progress<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item green\">completed<\/span>\n <\/div>\n <div class=\"flow-row\" style=\"font-size:.78rem;color:var(--muted);margin-top:.3rem\">\n <span>\u6587\u4ef6\u6821\u9a8c\u4e2d<\/span>\n <span> <\/span>\n <span>\u6b63\u5728\u5904\u7406<\/span>\n <span> <\/span>\n <span>\u5df2\u5b8c\u6210<\/span>\n <\/div>\n <div class=\"flow-row\" style=\"margin-top:.5rem\">\n <span class=\"flow-item red\">failed<\/span>\n <span style=\"font-size:.78rem;color:var(--muted)\">\uff08\u5f02\u5e38\u7ec8\u6b62\uff09<\/span>\n <span class=\"flow-item red\">expired<\/span>\n <span style=\"font-size:.78rem;color:var(--muted)\">\uff08\u8d85\u65f6\uff09<\/span>\n <span class=\"flow-item red\">cancelled<\/span>\n <span style=\"font-size:.78rem;color:var(--muted)\">\uff08\u5df2\u53d6\u6d88\uff09<\/span>\n <\/div>\n<\/div>\n\n<h3>7.2 \u72b6\u6001\u67e5\u8be2\u4ee3\u7801<\/h3>\n<pre class=\"code-block\">import time\nfrom openai import OpenAI\n\n\ndef wait_for_batch_completion(\n batch_id: str,\n api_key: str | None = None,\n poll_interval: int = 30,\n max_wait: int = 86400\n) -> dict:\n \"\"\"\u8f6e\u8be2\u7b49\u5f85\u6279\u91cf\u4efb\u52a1\u5b8c\u6210\u3002\n\n Args:\n batch_id: \u6279\u91cf\u4efb\u52a1 ID\n api_key: API-Key\n poll_interval: \u8f6e\u8be2\u95f4\u9694\uff08\u79d2\uff09\n max_wait: \u6700\u5927\u7b49\u5f85\u65f6\u95f4\uff08\u79d2\uff09\n\n Returns:\n \u6700\u7ec8\u4efb\u52a1\u72b6\u6001\u4fe1\u606f\n \"\"\"\n client = OpenAI(\n api_key=api_key or os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n )\n\n start_time = time.time()\n while True:\n batch = client.batches.retrieve(batch_id)\n elapsed = int(time.time() - start_time)\n\n print(f\"[{elapsed}s] \u72b6\u6001: {batch.status} | \"\n f\"\u5b8c\u6210: {batch.request_counts.completed}\/\"\n f\"{batch.request_counts.total} | \"\n f\"\u5931\u8d25: {batch.request_counts.failed}\")\n\n if batch.status in (\"completed\", \"failed\", \"expired\", \"cancelled\"):\n return {\n \"status\": batch.status,\n \"batch\": batch,\n \"elapsed_seconds\": elapsed\n }\n\n if elapsed > max_wait:\n raise TimeoutError(f\"\u4efb\u52a1\u7b49\u5f85\u8d85\u65f6\uff08>{max_wait}\u79d2\uff09\")\n\n time.sleep(poll_interval)\n\n\n# \u4f7f\u7528\nresult = wait_for_batch_completion(job[\"batch_id\"], poll_interval=30)\nprint(f\"\u6700\u7ec8\u72b6\u6001: {result['status']}\")\n<\/pre>\n\n<h3>7.3 \u4efb\u52a1\u5217\u8868\u9762\u677f<\/h3>\n<pre class=\"code-block\">def list_batch_jobs(api_key: str | None = None, limit: int = 10) -> list[dict]:\n \"\"\"\u5217\u51fa\u6700\u8fd1\u7684\u6279\u91cf\u4efb\u52a1\u3002\"\"\"\n client = OpenAI(\n api_key=api_key or os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n )\n\n batches = client.batches.list(limit=limit)\n jobs = []\n for batch in batches.data:\n jobs.append({\n \"id\": batch.id,\n \"status\": batch.status,\n \"created_at\": batch.created_at,\n \"completed\": batch.request_counts.completed,\n \"failed\": batch.request_counts.failed,\n \"total\": batch.request_counts.total\n })\n return jobs\n\n\n# \u6253\u5370\u4efb\u52a1\u5217\u8868\nfor job in list_batch_jobs():\n print(f\"{job['id'][:20]:20s} | {job['status']:12s} | \"\n f\"{job['completed']:>4d}\/{job['total']:<4d} | \"\n f\"\u5931\u8d25: {job['failed']}\")\n<\/pre>\n\n\n<h2 id=\"zh-8\">\u516b\u3001\u7ed3\u679c\u83b7\u53d6\u4e0e\u540e\u5904\u7406<\/h2>\n\n<h3>8.1 \u4e0b\u8f7d\u7ed3\u679c\u6587\u4ef6<\/h3>\n<pre class=\"code-block\">def download_batch_results(batch_id: str, api_key: str | None = None) -> list[dict]:\n \"\"\"\u4e0b\u8f7d\u5e76\u89e3\u6790\u6279\u91cf\u63a8\u7406\u7ed3\u679c\u3002\n\n Returns:\n \u7ed3\u679c\u8bb0\u5f55\u5217\u8868\uff0c\u6bcf\u6761\u5305\u542b custom_id \u548c\u6a21\u578b\u8f93\u51fa\n \"\"\"\n client = OpenAI(\n api_key=api_key or os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n )\n\n # \u83b7\u53d6\u4efb\u52a1\u4fe1\u606f\n batch = client.batches.retrieve(batch_id)\n if batch.status != \"completed\":\n raise ValueError(f\"\u4efb\u52a1\u672a\u5b8c\u6210\uff0c\u5f53\u524d\u72b6\u6001: {batch.status}\")\n\n # \u4e0b\u8f7d\u8f93\u51fa\u6587\u4ef6\n output_file = client.files.content(batch.output_file_id)\n content = output_file.read().decode(\"utf-8\")\n\n # \u89e3\u6790 JSONL\n results = []\n for line in content.strip().split(\"\\n\"):\n if not line.strip():\n continue\n obj = json.loads(line)\n results.append({\n \"custom_id\": obj.get(\"custom_id\"),\n \"status_code\": obj.get(\"status_code\"),\n \"response\": obj.get(\"response\", {}),\n \"error\": obj.get(\"error\")\n })\n\n return results\n\n\n# \u4f7f\u7528\nresults = download_batch_results(job[\"batch_id\"])\n\n# \u67e5\u770b\u7ed3\u679c\nfor r in results[:3]:\n cid = r[\"custom_id\"]\n if r[\"error\"]:\n print(f\"[{cid}] \u9519\u8bef: {r['error']}\")\n else:\n content = r[\"response\"][\"body\"][\"choices\"][0][\"message\"][\"content\"]\n print(f\"[{cid}] \u7ed3\u679c: {content[:100]}...\")\n<\/pre>\n\n<h3>8.2 \u7ed3\u679c\u4e0e\u8f93\u5165\u5339\u914d<\/h3>\n<pre class=\"code-block\">def merge_results_with_input(\n input_items: list[dict],\n results: list[dict]\n) -> list[dict]:\n \"\"\"\u5c06\u6279\u91cf\u63a8\u7406\u7ed3\u679c\u4e0e\u539f\u59cb\u8f93\u5165\u6570\u636e\u5408\u5e76\u3002\n\n Returns:\n \u5408\u5e76\u540e\u7684\u8bb0\u5f55\u5217\u8868\n \"\"\"\n result_map = {r[\"custom_id\"]: r for r in results}\n merged = []\n\n for item in input_items:\n cid = item.get(\"id\", \"\")\n result = result_map.get(cid, {})\n\n merged.append({\n **item,\n \"status_code\": result.get(\"status_code\"),\n \"output\": result.get(\"response\", {})\n .get(\"body\", {})\n .get(\"choices\", [{}])[0]\n .get(\"message\", {})\n .get(\"content\", \"\"),\n \"error\": result.get(\"error\")\n })\n\n return merged\n\n\n# \u4fdd\u5b58\u4e3a CSV\nimport csv\n\nmerged = merge_results_with_input(data, results)\nwith open(\"batch_results.csv\", \"w\", newline=\"\", encoding=\"utf-8-sig\") as f:\n writer = csv.DictWriter(f, fieldnames=[\"id\", \"prompt\", \"output\", \"error\"])\n writer.writeheader()\n for row in merged:\n writer.writerow({\n \"id\": row[\"id\"],\n \"prompt\": row[\"prompt\"],\n \"output\": row[\"output\"],\n \"error\": row[\"error\"] or \"\"\n })\n\nprint(\"\u7ed3\u679c\u5df2\u4fdd\u5b58\u5230 batch_results.csv\")\n<\/pre>\n\n\n<h2 id=\"zh-9\">\u4e5d\u3001\u6210\u672c\u4f18\u5316\u4e0e\u6700\u4f73\u5b9e\u8df5<\/h2>\n\n<h3>9.1 \u6210\u672c\u63a7\u5236\u7b56\u7565<\/h3>\n<div class=\"card\">\n <h4>\u6279\u91cf\u63a8\u7406\u964d\u672c\u4e94\u6cd5<\/h4>\n <p>1. <span class=\"tag tag-g\">\u6279\u91cf\u4ee3\u66ff\u5b9e\u65f6<\/span> \u975e\u7d27\u6025\u4efb\u52a1\u7edf\u4e00\u8d70 BatchAPI\uff0c\u6210\u672c\u964d\u4f4e\u7ea6 50%<\/p>\n <p>2. <span class=\"tag tag-b\">\u9009\u62e9\u5408\u9002\u6a21\u578b<\/span> \u7b80\u5355\u4efb\u52a1\u7528 qwen-turbo\uff08\u5feb\u4e14\u4fbf\u5b9c\uff09\uff0c\u590d\u6742\u4efb\u52a1\u518d\u7528 qwen-max<\/p>\n <p>3. <span class=\"tag tag-y\">\u9650\u5236\u8f93\u51fa\u957f\u5ea6<\/span> \u8bbe\u7f6e\u5408\u7406\u7684 max_tokens\uff0c\u907f\u514d\u6a21\u578b\u8fc7\u5ea6\u751f\u6210\u6d6a\u8d39 Token<\/p>\n <p>4. <span class=\"tag tag-p\">\u5408\u5e76\u76f8\u4f3c\u8bf7\u6c42<\/span> \u5c06\u76f8\u540c system prompt \u7684\u8bf7\u6c42\u5408\u5e76\uff0c\u51cf\u5c11\u91cd\u590d\u8ba1\u7b97<\/p>\n <p>5. <span class=\"tag tag-r\">\u5931\u8d25\u91cd\u8bd5\u673a\u5236<\/span> \u53ea\u91cd\u8bd5\u5931\u8d25\u7684\u8bf7\u6c42\uff0c\u907f\u514d\u5168\u91cf\u91cd\u65b0\u63d0\u4ea4<\/p>\n<\/div>\n\n<h3>9.2 \u6700\u4f73\u5b9e\u8df5\u6e05\u5355<\/h3>\n<pre class=\"code-block\">\u25a1 \u6570\u636e\u51c6\u5907\n - \u63d0\u524d\u6821\u9a8c JSONL \u683c\u5f0f\uff0c\u907f\u514d\u4e0a\u4f20\u540e\u6821\u9a8c\u5931\u8d25\n - \u5355\u6587\u4ef6\u8bf7\u6c42\u6570\u63a7\u5236\u5728\u5408\u7406\u8303\u56f4\uff08\u5efa\u8bae 1\u4e07~10\u4e07\u6761\uff09\n - \u5355\u6761\u8bf7\u6c42\u4e0d\u8981\u592a\u957f\uff0c\u907f\u514d\u8d85\u65f6\n\n\u25a1 \u4efb\u52a1\u63d0\u4ea4\n - \u907f\u5f00\u4e1a\u52a1\u9ad8\u5cf0\u671f\u63d0\u4ea4\uff0c\u51cf\u5c11\u6392\u961f\u65f6\u95f4\n - \u5927\u4efb\u52a1\u62c6\u5206\u4e3a\u591a\u4e2a\u5c0f\u6279\u91cf\uff0c\u964d\u4f4e\u5355\u70b9\u5931\u8d25\u98ce\u9669\n - \u8bb0\u5f55 batch_id\uff0c\u4fbf\u4e8e\u540e\u7eed\u67e5\u8be2\u548c\u8ddf\u8e2a\n\n\u25a1 \u76d1\u63a7\u7ba1\u7406\n - \u8bbe\u7f6e\u5408\u7406\u7684\u8f6e\u8be2\u95f4\u9694\uff0830~60 \u79d2\uff09\uff0c\u907f\u514d\u9891\u7e41\u8c03\u7528\n - \u4efb\u52a1\u5b8c\u6210\u540e\u53ca\u65f6\u4e0b\u8f7d\u7ed3\u679c\uff0c\u91ca\u653e\u5b58\u50a8\n - \u5b9a\u671f\u68c0\u67e5\u5931\u8d25\u8bf7\u6c42\uff0c\u5206\u6790\u5931\u8d25\u539f\u56e0\n\n\u25a1 \u7ed3\u679c\u5904\u7406\n - \u89e3\u6790\u7ed3\u679c\u65f6\u505a\u597d\u5f02\u5e38\u5904\u7406\uff0c\u517c\u5bb9\u683c\u5f0f\u53d8\u5316\n - \u5c06\u7ed3\u679c\u4e0e\u8f93\u5165\u901a\u8fc7 custom_id \u7cbe\u786e\u5339\u914d\n - \u5bf9\u5931\u8d25\u8bf7\u6c42\u5355\u72ec\u8bb0\u5f55\uff0c\u4fbf\u4e8e\u540e\u7eed\u91cd\u8bd5\n<\/pre>\n\n<h3>9.3 \u5931\u8d25\u91cd\u8bd5\u6d41\u7a0b<\/h3>\n<pre class=\"code-block\">def retry_failed_requests(\n input_file: str,\n results: list[dict],\n api_key: str | None = None\n) -> dict | None:\n \"\"\"\u63d0\u53d6\u5931\u8d25\u7684\u8bf7\u6c42\uff0c\u751f\u6210\u65b0\u7684\u91cd\u8bd5\u6279\u6b21\u3002\n\n Returns:\n \u65b0\u4efb\u52a1\u4fe1\u606f\uff0c\u5982\u679c\u6ca1\u6709\u5931\u8d25\u5219\u8fd4\u56de None\n \"\"\"\n failed_ids = {r[\"custom_id\"] for r in results if r[\"error\"]}\n if not failed_ids:\n print(\"\u6ca1\u6709\u5931\u8d25\u8bf7\u6c42\uff0c\u65e0\u9700\u91cd\u8bd5\")\n return None\n\n # \u8bfb\u53d6\u539f\u59cb\u8f93\u5165\n retry_items = []\n with open(input_file, \"r\", encoding=\"utf-8\") as f:\n for line in f:\n obj = json.loads(line.strip())\n if obj[\"custom_id\"] in failed_ids:\n retry_items.append(obj)\n\n # \u5199\u5165\u91cd\u8bd5\u6587\u4ef6\n retry_file = input_file.replace(\".jsonl\", \"_retry.jsonl\")\n with open(retry_file, \"w\", encoding=\"utf-8\") as f:\n for item in retry_items:\n f.write(json.dumps(item, ensure_ascii=False) + \"\\n\")\n\n print(f\"\u63d0\u53d6 {len(retry_items)} \u6761\u5931\u8d25\u8bf7\u6c42\uff0c\u5199\u5165 {retry_file}\")\n return create_batch_job(retry_file, api_key)\n\n\n# \u4f7f\u7528\nretry_job = retry_failed_requests(\"batch_input.jsonl\", results)\n<\/pre>\n\n\n<h2 id=\"zh-10\">\u5341\u3001\u5e38\u89c1\u95ee\u9898\u4e0e\u6392\u67e5<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead>\n <tr><th>\u95ee\u9898\u73b0\u8c61<\/th><th>\u539f\u56e0<\/th><th>\u89e3\u51b3\u65b9\u6848<\/th><\/tr>\n <\/thead>\n <tbody>\n <tr>\n <td>\u6587\u4ef6\u4e0a\u4f20\u5931\u8d25<\/td>\n <td>JSONL \u683c\u5f0f\u9519\u8bef\u3001\u6587\u4ef6\u8fc7\u5927\uff08\u8d85\u8fc7 100MB\uff09\u3001\u7f16\u7801\u975e UTF-8<\/td>\n <td>\u4f7f\u7528 validate_jsonl() \u9884\u6821\u9a8c\uff0c\u5927\u6587\u4ef6\u62c6\u5206\u4e3a\u591a\u4e2a\uff0c\u786e\u8ba4 UTF-8 \u7f16\u7801<\/td>\n <\/tr>\n <tr>\n <td>\u4efb\u52a1\u72b6\u6001 validating \u5f88\u4e45<\/td>\n <td>\u6587\u4ef6\u6b63\u5728\u683c\u5f0f\u6821\u9a8c\uff0c\u6216\u8bf7\u6c42\u6570\u91cf\u8fc7\u5927<\/td>\n <td>\u7b49\u5f85\u5373\u53ef\uff0c\u901a\u5e38\u51e0\u5206\u949f\u5185\u5b8c\u6210\uff1b\u5982\u8d85 30 \u5206\u949f\u8054\u7cfb\u5ba2\u670d<\/td>\n <\/tr>\n <tr>\n <td>\u90e8\u5206\u8bf7\u6c42\u5931\u8d25<\/td>\n <td>\u4e2a\u522b\u8bf7\u6c42\u53c2\u6570\u975e\u6cd5\u3001\u8d85\u957f\u3001\u6216\u6a21\u578b\u4e0d\u652f\u6301<\/td>\n <td>\u4e0b\u8f7d\u7ed3\u679c\u67e5\u770b error \u5b57\u6bb5\uff0c\u4fee\u590d\u540e\u5355\u72ec\u91cd\u8bd5\u5931\u8d25\u9879<\/td>\n <\/tr>\n <tr>\n <td>\u4efb\u52a1\u72b6\u6001 failed<\/td>\n <td>\u6587\u4ef6\u683c\u5f0f\u4e25\u91cd\u9519\u8bef\u3001\u6743\u9650\u4e0d\u8db3\u3001\u6a21\u578b\u4e0d\u53ef\u7528<\/td>\n <td>\u68c0\u67e5 API-Key \u6743\u9650\u3001\u6a21\u578b\u662f\u5426\u5df2\u5f00\u901a\u3001JSONL \u683c\u5f0f<\/td>\n <\/tr>\n <tr>\n <td>\u7ed3\u679c\u4e0e\u8f93\u5165\u4e0d\u5339\u914d<\/td>\n <td>custom_id \u91cd\u590d\u6216\u683c\u5f0f\u4e0d\u4e00\u81f4<\/td>\n <td>\u786e\u4fdd custom_id \u5168\u5c40\u552f\u4e00\uff0c\u5efa\u8bae\u4f7f\u7528 UUID \u6216\u4e1a\u52a1 ID<\/td>\n <\/tr>\n <tr>\n <td>\u4efb\u52a1\u6392\u961f\u65f6\u95f4\u957f<\/td>\n <td>\u9ad8\u5cf0\u671f\u63d0\u4ea4\uff0c\u8d44\u6e90\u7d27\u5f20<\/td>\n <td>\u907f\u5f00\u9ad8\u5cf0\uff08\u5de5\u4f5c\u65e5\u4e0a\u5348 10~12 \u70b9\uff09\uff0c\u6216\u591c\u95f4\u63d0\u4ea4<\/td>\n <\/tr>\n <tr>\n <td>\u7ed3\u679c\u6587\u4ef6\u65e0\u6cd5\u4e0b\u8f7d<\/td>\n <td>\u7ed3\u679c\u6587\u4ef6\u5df2\u8fc7\u671f\uff08\u901a\u5e38\u4fdd\u7559 7 \u5929\uff09<\/td>\n <td>\u4efb\u52a1\u5b8c\u6210\u540e\u5c3d\u5feb\u4e0b\u8f7d\uff0c\u8bbe\u7f6e\u81ea\u52a8\u4e0b\u8f7d\u811a\u672c<\/td>\n <\/tr>\n <tr>\n <td>Token \u6d88\u8017\u8d85\u9884\u671f<\/td>\n <td>max_tokens \u8bbe\u7f6e\u8fc7\u5927\uff0c\u6216\u8f93\u5165\u5185\u5bb9\u8fc7\u957f<\/td>\n <td>\u4f18\u5316 prompt \u957f\u5ea6\uff0c\u8bbe\u7f6e\u5408\u7406\u7684 max_tokens \u4e0a\u9650<\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h3>\u5b8c\u6574\u5de5\u4f5c\u6d41\u4ee3\u7801\u6a21\u677f<\/h3>\n<pre class=\"code-block\">\"\"\"\n\u963f\u91cc\u4e91\u767e\u70bc\u6279\u91cf\u63a8\u7406\u5b8c\u6574\u5de5\u4f5c\u6d41\u6a21\u677f\n\u4e00\u6b65\u5b8c\u6210\uff1a\u6570\u636e\u51c6\u5907 \u2192 \u63d0\u4ea4\u4efb\u52a1 \u2192 \u76d1\u63a7 \u2192 \u83b7\u53d6\u7ed3\u679c \u2192 \u4fdd\u5b58 CSV\n\"\"\"\n\nimport os\nimport json\nimport time\nimport csv\nfrom pathlib import Path\nfrom openai import OpenAI\n\nAPI_KEY = os.getenv(\"DASHSCOPE_API_KEY\")\nBASE_URL = \"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\nMODEL = \"qwen-turbo\"\n\n\ndef run_batch_pipeline(input_items: list[dict], output_csv: str = \"results.csv\") -> None:\n \"\"\"\u6279\u91cf\u63a8\u7406\u5b8c\u6574\u6d41\u6c34\u7ebf\u3002\"\"\"\n\n # Step 1: \u51c6\u5907 JSONL\n jsonl_path = \"batch_input.jsonl\"\n with open(jsonl_path, \"w\", encoding=\"utf-8\") as f:\n for idx, item in enumerate(input_items, 1):\n record = {\n \"custom_id\": item.get(\"id\", f\"req-{idx:04d}\"),\n \"method\": \"POST\",\n \"url\": \"\/v1\/chat\/completions\",\n \"body\": {\n \"model\": MODEL,\n \"messages\": [{\"role\": \"user\", \"content\": item[\"prompt\"]}],\n \"max_tokens\": item.get(\"max_tokens\", 512)\n }\n }\n f.write(json.dumps(record, ensure_ascii=False) + \"\\n\")\n print(f\"\u2705 \u5df2\u751f\u6210\u8f93\u5165\u6587\u4ef6: {jsonl_path} ({len(input_items)} \u6761)\")\n\n # Step 2: \u521b\u5efa\u4efb\u52a1\n client = OpenAI(api_key=API_KEY, base_url=BASE_URL)\n with open(jsonl_path, \"rb\") as f:\n file_obj = client.files.create(file=f, purpose=\"batch\")\n batch = client.batches.create(\n input_file_id=file_obj.id,\n endpoint=\"\/v1\/chat\/completions\",\n completion_window=\"24h\"\n )\n print(f\"\u2705 \u4efb\u52a1\u5df2\u521b\u5efa: {batch.id}\")\n\n # Step 3: \u7b49\u5f85\u5b8c\u6210\n while True:\n batch = client.batches.retrieve(batch.id)\n print(f\"\u23f3 \u72b6\u6001: {batch.status} | \"\n f\"\u5b8c\u6210: {batch.request_counts.completed}\/{batch.request_counts.total}\")\n if batch.status in (\"completed\", \"failed\", \"expired\"):\n break\n time.sleep(30)\n\n if batch.status != \"completed\":\n raise RuntimeError(f\"\u4efb\u52a1\u672a\u6210\u529f\u5b8c\u6210: {batch.status}\")\n\n # Step 4: \u4e0b\u8f7d\u7ed3\u679c\n output_file = client.files.content(batch.output_file_id)\n content = output_file.read().decode(\"utf-8\")\n\n # Step 5: \u89e3\u6790\u5e76\u4fdd\u5b58 CSV\n results = [json.loads(line) for line in content.strip().split(\"\\n\") if line.strip()]\n\n with open(output_csv, \"w\", newline=\"\", encoding=\"utf-8-sig\") as f:\n writer = csv.writer(f)\n writer.writerow([\"id\", \"prompt\", \"output\", \"error\"])\n for r in results:\n cid = r.get(\"custom_id\", \"\")\n error = r.get(\"error\", \"\")\n output = \"\"\n if not error:\n try:\n output = r[\"response\"][\"body\"][\"choices\"][0][\"message\"][\"content\"]\n except (KeyError, IndexError):\n output = \"[\u89e3\u6790\u5931\u8d25]\"\n writer.writerow([cid, \"\", output, error or \"\"])\n\n print(f\"\u2705 \u7ed3\u679c\u5df2\u4fdd\u5b58: {output_csv}\")\n print(f\"\ud83d\udcca \u603b\u8ba1: {len(results)} \u6761 | \"\n f\"\u6210\u529f: {sum(1 for r in results if not r.get('error'))} | \"\n f\"\u5931\u8d25: {sum(1 for r in results if r.get('error'))}\")\n\n\n# \u8fd0\u884c\nif __name__ == \"__main__\":\n test_data = [\n {\"id\": \"test-001\", \"prompt\": \"\u7528\u4e00\u53e5\u8bdd\u603b\u7ed3\u4eba\u5de5\u667a\u80fd\u7684\u53d1\u5c55\u8d8b\u52bf\"},\n {\"id\": \"test-002\", \"prompt\": \"\u5c06'Hello World'\u7ffb\u8bd1\u4e3a\u4e2d\u6587\"},\n ]\n run_batch_pipeline(test_data, \"batch_results.csv\")\n<\/pre>\n\n<div class=\"info-box\">\n <strong>\u5168\u6d41\u7a0b\u603b\u7ed3\uff1a\u7406\u89e3\u6279\u91cf\u63a8\u7406\u7684\u5f02\u6b65\u79bb\u7ebf\u7279\u5f81 \u2192 \u533a\u5206\u6279\u91cf\u4e0e\u5b9e\u65f6\u7684\u9002\u7528\u573a\u666f \u2192 \u6309 JSONL \u89c4\u8303\u51c6\u5907\u6570\u636e \u2192 \u901a\u8fc7 OpenAI \u517c\u5bb9\u63a5\u53e3\u63d0\u4ea4\u4efb\u52a1 \u2192 \u8f6e\u8be2\u76d1\u63a7\u4efb\u52a1\u72b6\u6001 \u2192 \u4e0b\u8f7d\u5e76\u89e3\u6790\u7ed3\u679c\u6587\u4ef6 \u2192 \u5931\u8d25\u8bf7\u6c42\u5355\u72ec\u91cd\u8bd5 \u2192 \u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u548c\u53c2\u6570\u63a7\u5236\u6210\u672c\u3002\u6279\u91cf\u63a8\u7406\u662f\u5927\u89c4\u6a21 AI \u5904\u7406\u7684\u964d\u672c\u5229\u5668\u3002<\/strong>\n<\/div>\n\n<\/div>\n\n\n<div class=\"lang-section\" id=\"lang-en\">\n<div class=\"hero\">\n <h1>Batch Inference Complete Guide<span class=\"sub\">Concept \u2192 Practice \u2192 Alibaba Cloud Bailian BatchAPI<\/span><\/h1>\n <p>Batch vs online inference, use cases, JSONL data prep, job submission & monitoring, result retrieval, cost optimization, troubleshooting<\/p>\n<\/div>\n\n<div class=\"toc\">\n <h3>Table of Contents<\/h3>\n <ol>\n <li><a href=\"#en-1\">1 What is Batch Inference<\/a><\/li>\n <li><a href=\"#en-2\">2 Batch vs Online Inference<\/a><\/li>\n <li><a href=\"#en-3\">3 Use Cases & Value<\/a><\/li>\n <li><a href=\"#en-4\">4 Alibaba Cloud Bailian BatchAPI<\/a><\/li>\n <li><a href=\"#en-5\">5 JSONL Data Preparation<\/a><\/li>\n <li><a href=\"#en-6\">6 Submitting Batch Jobs<\/a><\/li>\n <li><a href=\"#en-7\">7 Job Monitoring<\/a><\/li>\n <li><a href=\"#en-8\">8 Result Retrieval<\/a><\/li>\n <li><a href=\"#en-9\">9 Cost Optimization<\/a><\/li>\n <li><a href=\"#en-10\">10 FAQ & Troubleshooting<\/a><\/li>\n <\/ol>\n<\/div>\n\n<h2 id=\"en-1\">1 What is Batch Inference<\/h2>\n\n<p>Batch Inference aggregates large numbers of independent inference requests into a single batch, submitted to the model for background offline processing with asynchronous result delivery.<\/p>\n\n<div class=\"card\">\n <h4>Four Key Characteristics<\/h4>\n <p><span class=\"tag tag-b\">Asynchronous<\/span> Submit and return immediately, process in background queue<\/p>\n <p><span class=\"tag tag-g\">High Throughput<\/span> Fully utilize GPU parallel computing<\/p>\n <p><span class=\"tag tag-y\">Low Cost<\/span> Alibaba Cloud BatchAPI costs ~50% of real-time calls<\/p>\n <p><span class=\"tag tag-p\">Offline<\/span> Doesn't consume real-time service resources<\/p>\n<\/div>\n\n<h2 id=\"en-2\">2 Batch vs Online Inference<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead><tr><th>Dimension<\/th><th>Batch<\/th><th>Online<\/th><\/tr><\/thead>\n <tbody>\n <tr><td>Response<\/td><td>Async, background<\/td><td>Sync, immediate<\/td><\/tr>\n <tr><td>Latency<\/td><td>Minutes to hours OK<\/td><td>Milliseconds to seconds<\/td><\/tr>\n <tr><td>Cost<\/td><td>~50% of real-time<\/td><td>Full real-time pricing<\/td><\/tr>\n <tr><td>Scale<\/td><td>Thousands to millions<\/td><td>Single or small batches<\/td><\/tr>\n <tr><td>Use Case<\/td><td>Data analysis, generation<\/td><td>Chat, recommendation<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h2 id=\"en-3\">3 Use Cases & Value<\/h2>\n\n<div class=\"cmd-grid\">\n <div class=\"cmd-card\">\n <h4>Data Analysis<\/h4>\n <div class=\"desc\">Sentiment analysis, topic classification, entity extraction on massive review\/feedback datasets.<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>Content Generation<\/h4>\n <div class=\"desc\">Batch generate product descriptions, marketing copy, translations at scale.<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>Model Evaluation<\/h4>\n <div class=\"desc\">Run benchmark tests to get accuracy, F1 scores across standard test sets.<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>Data Labeling<\/h4>\n <div class=\"desc\">Use model for pre-labeling, human review correction, reduce costs 70%+.<\/div>\n <\/div>\n<\/div>\n\n<h2 id=\"en-4\">4 Alibaba Cloud Bailian BatchAPI<\/h2>\n\n<div class=\"card\">\n <h4>Bailian BatchAPI Capabilities<\/h4>\n <p><span class=\"tag tag-b\">File Upload<\/span> JSONL format, one request per line<\/p>\n <p><span class=\"tag tag-g\">Model Support<\/span> Qwen, Llama, DeepSeek and more<\/p>\n <p><span class=\"tag tag-y\">Cost Savings<\/span> ~50% of real-time API pricing<\/p>\n <p><span class=\"tag tag-p\">Status Tracking<\/span> Full lifecycle: created \u2192 queued \u2192 running \u2192 completed<\/p>\n <p><span class=\"tag tag-r\">Persistent Results<\/span> Output files saved after completion<\/p>\n<\/div>\n\n<h3>Prerequisites<\/h3>\n<ol class=\"steps\">\n <li>Alibaba Cloud account with real-name verification<\/li>\n <li>Activate Bailian (Model Studio) service<\/li>\n <li>Get API-Key from Bailian Console<\/li>\n <li>Install SDK: <span class=\"cmd\">pip install openai<\/span><\/li>\n<\/ol>\n\n<h2 id=\"en-5\">5 JSONL Data Preparation<\/h2>\n\n<pre class=\"code-block\">{\"custom_id\": \"req-001\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"Summarize AI trends\"}]}}\n{\"custom_id\": \"req-002\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"Translate to Chinese\"}]}}\n<\/pre>\n\n<div class=\"table-wrap\">\n<table>\n <thead><tr><th>Field<\/th><th>Type<\/th><th>Required<\/th><th>Description<\/th><\/tr><\/thead>\n <tbody>\n <tr><td>custom_id<\/td><td>string<\/td><td>Yes<\/td><td>Custom request identifier<\/td><\/tr>\n <tr><td>method<\/td><td>string<\/td><td>Yes<\/td><td>HTTP method, always \"POST\"<\/td><\/tr>\n <tr><td>url<\/td><td>string<\/td><td>Yes<\/td><td>API path<\/td><\/tr>\n <tr><td>body<\/td><td>object<\/td><td>Yes<\/td><td>Request body, same as real-time API<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h2 id=\"en-6\">6 Submitting Batch Jobs<\/h2>\n\n<pre class=\"code-block\">import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n api_key=os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n)\n\n# Upload file\nwith open(\"batch_input.jsonl\", \"rb\") as f:\n file_obj = client.files.create(file=f, purpose=\"batch\")\n\n# Create batch job\nbatch = client.batches.create(\n input_file_id=file_obj.id,\n endpoint=\"\/v1\/chat\/completions\",\n completion_window=\"24h\"\n)\nprint(f\"Job created: {batch.id}\")\n<\/pre>\n\n<h2 id=\"en-7\">7 Job Monitoring<\/h2>\n\n<h3>Status Flow<\/h3>\n<div class=\"flow-diagram\">\n <div class=\"flow-row\">\n <span class=\"flow-item\">validating<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item yellow\">in_progress<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item green\">completed<\/span>\n <\/div>\n <div class=\"flow-row\" style=\"margin-top:.5rem\">\n <span class=\"flow-item red\">failed<\/span>\n <span class=\"flow-item red\">expired<\/span>\n <span class=\"flow-item red\">cancelled<\/span>\n <\/div>\n<\/div>\n\n<pre class=\"code-block\">def wait_for_completion(batch_id: str, poll_interval: int = 30):\n while True:\n batch = client.batches.retrieve(batch_id)\n print(f\"Status: {batch.status} | \"\n f\"Done: {batch.request_counts.completed}\/{batch.request_counts.total}\")\n if batch.status in (\"completed\", \"failed\", \"expired\"):\n return batch\n time.sleep(poll_interval)\n<\/pre>\n\n<h2 id=\"en-8\">8 Result Retrieval<\/h2>\n\n<pre class=\"code-block\">batch = client.batches.retrieve(batch_id)\noutput_file = client.files.content(batch.output_file_id)\ncontent = output_file.read().decode(\"utf-8\")\n\nresults = []\nfor line in content.strip().split(\"\\n\"):\n obj = json.loads(line)\n results.append({\n \"custom_id\": obj[\"custom_id\"],\n \"response\": obj.get(\"response\", {}),\n \"error\": obj.get(\"error\")\n })\n<\/pre>\n\n<h2 id=\"en-9\">9 Cost Optimization<\/h2>\n\n<div class=\"card\">\n <h4>Five Cost Reduction Strategies<\/h4>\n <p>1. <span class=\"tag tag-g\">Batch over online<\/span> Use BatchAPI for non-urgent tasks (~50% savings)<\/p>\n <p>2. <span class=\"tag tag-b\">Right-size model<\/span> Use qwen-turbo for simple tasks<\/p>\n <p>3. <span class=\"tag tag-y\">Limit max_tokens<\/span> Set reasonable output length caps<\/p>\n <p>4. <span class=\"tag tag-p\">Merge requests<\/span> Group similar prompts to reduce overhead<\/p>\n <p>5. <span class=\"tag tag-r\">Retry failures only<\/span> Don't resubmit entire batch<\/p>\n<\/div>\n\n<h2 id=\"en-10\">10 FAQ & Troubleshooting<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead><tr><th>Issue<\/th><th>Solution<\/th><\/tr><\/thead>\n <tbody>\n <tr><td>Upload fails<\/td><td>Validate JSONL format, check file size < 100MB, ensure UTF-8<\/td><\/tr>\n <tr><td>Stuck validating<\/td><td>Wait normally; contact support if > 30 min<\/td><\/tr>\n <tr><td>Partial failures<\/td><td>Check error field in results, retry failed items only<\/td><\/tr>\n <tr><td>Job failed<\/td><td>Verify API-Key permissions, model availability, JSONL format<\/td><\/tr>\n <tr><td>Long queue time<\/td><td>Avoid peak hours (10am-12pm), submit during off-hours<\/td><\/tr>\n <tr><td>Result expired<\/td><td>Download within 7 days; set up auto-download script<\/td><\/tr>\n <tr><td>Unexpected token usage<\/td><td>Optimize prompt length, set max_tokens limit<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"info-box\">\n <strong>Summary: Understand async offline nature of batch inference \u2192 Distinguish batch vs online use cases \u2192 Prepare data in JSONL format \u2192 Submit via OpenAI-compatible API \u2192 Poll for completion \u2192 Download and parse results \u2192 Retry failed requests separately \u2192 Choose right model and parameters to control costs. Batch inference is a powerful cost-saving tool for large-scale AI processing.<\/strong>\n<\/div>\n\n<\/div>\n<\/main>\n\n<footer>\n <div class=\"links\">\n <a href=\"https:\/\/help.aliyun.com\/zh\/model-studio\/getting-started\/what-is-model-studio\" target=\"_blank\" rel=\"noopener\">Alibaba Cloud Bailian<\/a>\n <a href=\"https:\/\/www.alibabacloud.com\/help\/en\/model-studio\/developer-reference\/use-bailian-api\" target=\"_blank\" rel=\"noopener\">Bailian API Docs<\/a>\n <a href=\"https:\/\/platform.openai.com\/docs\/guides\/batch\" target=\"_blank\" rel=\"noopener\">OpenAI Batch API<\/a>\n <\/div>\n <p>Batch Inference Complete Guide<\/p>\n<\/footer>\n\n<script>\nfunction setLang(lang){\n document.querySelectorAll('.lang-section').forEach(el=>el.classList.remove('active'));\n document.getElementById('lang-'+lang).classList.add('active');\n document.querySelectorAll('.lang-switch button').forEach(btn=>btn.classList.remove('active'));\n document.getElementById('btn-'+lang).classList.add('active');\n document.documentElement.lang = lang==='zh'?'zh-CN':'en';\n const prefix = lang==='zh'?'zh':'en';\n const newHash = window.location.hash.replace(\/^#(zh|en)-\/, prefix+\"-\");\n if(newHash) window.location.hash = newHash;\n}\nfunction toggleTheme(){\n const html = document.documentElement;\n if(html.hasAttribute('data-theme')){\n html.removeAttribute('data-theme');\n localStorage.removeItem('theme');\n }else{\n html.setAttribute('data-theme','dark');\n localStorage.setItem('theme','dark');\n }\n}\n(function(){\n if(localStorage.getItem('theme')==='dark') document.documentElement.setAttribute('data-theme','dark');\n const hash = window.location.hash;\n if(hash){\n const target = document.querySelector(hash);\n if(target) setTimeout(()=>target.scrollIntoView({behavior:'smooth'}),100);\n }\n})();\n<\/script>\n<\/body>\n<\/html>\n","protected":false},"excerpt":{"rendered":"<p>\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357 \u00b7 Batch Inference Complete Guide \ud83d\ude80 \u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,9],"tags":[],"class_list":["post-363","post","type-post","status-publish","format-standard","hentry","category-cad","category-ai"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts\/363","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=363"}],"version-history":[{"count":1,"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts\/363\/revisions"}],"predecessor-version":[{"id":364,"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts\/363\/revisions\/364"}],"wp:attachment":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=363"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=363"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=363"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

{"id":363,"date":"2026-07-16T17:56:00","date_gmt":"2026-07-16T09:56:00","guid":{"rendered":"https:\/\/numsimlab.com\/?p=363"},"modified":"2026-07-16T17:56:00","modified_gmt":"2026-07-16T09:56:00","slug":"%e6%89%b9%e9%87%8f%e6%8e%a8%e7%90%86%e4%bb%bb%e5%8a%a1%e5%ae%8c%e6%95%b4%e6%8c%87%e5%8d%97","status":"publish","type":"post","link":"https:\/\/numsimlab.com\/?p=363","title":{"rendered":"\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357"},"content":{"rendered":"\n\n\n\n\n\n\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357 \u00b7 Batch Inference Complete Guide<\/title>\n<style>\n*,*::before,*::after{box-sizing:border-box;margin:0;padding:0}\nhtml{scroll-behavior:smooth}\n:root{\n --bg:#f8f9fa;--bg2:#fff;--ink:#1a1a2e;--muted:#6c7086;--rule:#e2e4eb;\n --accent:#2563eb;--accent2:#16a34a;--accent3:#dc2626;--accent4:#d97706;--accent5:#7c3aed;\n --card-bg:#fff;--code-bg:#f1f3f5;\n --tag-g:#dcfce7;--tag-g-t:#166534;--tag-b:#dbeafe;--tag-b-t:#1e40af;\n 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.links{display:flex;justify-content:center;gap:1.5rem;flex-wrap:wrap;margin-bottom:.8rem}\nfooter .links a{color:var(--muted)}footer .links a:hover{color:var(--accent)}\n@media(max-width:640px){\n h1{font-size:1.4rem}.toc ol{columns:1}.header-inner{padding:0 1rem}main{padding:72px 1rem 2rem}\n .steps li{padding-left:2.4rem}.steps li::before{left:-11px;width:22px;height:22px;font-size:.7rem}\n .two-col{grid-template-columns:1fr}.cmd-grid{grid-template-columns:1fr}.compare-box{grid-template-columns:1fr}\n}\n<\/style>\n<\/head>\n<body>\n<header>\n <div class=\"header-inner\">\n <div class=\"logo\"><span>\ud83d\ude80<\/span> \u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357<\/div>\n <div class=\"controls\">\n <div class=\"lang-switch\">\n <button class=\"active\" onclick=\"setLang('zh')\" id=\"btn-zh\">\u4e2d\u6587<\/button>\n <button onclick=\"setLang('en')\" id=\"btn-en\">English<\/button>\n <\/div>\n <button class=\"theme-toggle\" onclick=\"toggleTheme()\" title=\"\u5207\u6362\u660e\u6697\u4e3b\u9898\">☼<\/button>\n <\/div>\n <\/div>\n<\/header>\n<main>\n\n<div class=\"lang-section active\" id=\"lang-zh\">\n<div class=\"hero\">\n <h1>\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357\uff08\u6982\u5ff5\u2192\u5b9e\u8df5\u2192\u963f\u91cc\u4e91\u767e\u70bc\u5b9e\u6218\uff09<span class=\"sub\">\u7406\u89e3\u6279\u91cf\u63a8\u7406\u7684\u6838\u5fc3\u4ef7\u503c\uff0c\u638c\u63e1\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u7684\u5b8c\u6574\u4f7f\u7528\u6d41\u7a0b<\/span><\/h1>\n <p>\u6279\u91cf\u63a8\u7406 vs \u5b9e\u65f6\u63a8\u7406\u3001\u9002\u7528\u573a\u666f\u3001JSONL \u6570\u636e\u51c6\u5907\u3001\u4efb\u52a1\u63d0\u4ea4\u4e0e\u76d1\u63a7\u3001\u7ed3\u679c\u83b7\u53d6\u3001\u6210\u672c\u4f18\u5316\u3001\u5e38\u89c1\u95ee\u9898\u5168\u8986\u76d6<\/p>\n<\/div>\n\n<div class=\"toc\">\n <h3>\u76ee\u5f55<\/h3>\n <ol>\n <li><a href=\"#zh-1\">\u4e00\u3001\u4ec0\u4e48\u662f\u6279\u91cf\u63a8\u7406\uff08Batch Inference\uff09<\/a><\/li>\n <li><a href=\"#zh-2\">\u4e8c\u3001\u6279\u91cf\u63a8\u7406 vs \u5b9e\u65f6\u63a8\u7406\u5bf9\u6bd4<\/a><\/li>\n <li><a href=\"#zh-3\">\u4e09\u3001\u9002\u7528\u573a\u666f\u4e0e\u6838\u5fc3\u4ef7\u503c<\/a><\/li>\n <li><a href=\"#zh-4\">\u56db\u3001\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6982\u89c8<\/a><\/li>\n <li><a href=\"#zh-5\">\u4e94\u3001\u6570\u636e\u51c6\u5907\uff1aJSONL \u683c\u5f0f\u89c4\u8303<\/a><\/li>\n <li><a href=\"#zh-6\">\u516d\u3001\u63d0\u4ea4\u6279\u91cf\u63a8\u7406\u4efb\u52a1\uff08\u5b8c\u6574\u4ee3\u7801\uff09<\/a><\/li>\n <li><a href=\"#zh-7\">\u4e03\u3001\u4efb\u52a1\u76d1\u63a7\u4e0e\u72b6\u6001\u7ba1\u7406<\/a><\/li>\n <li><a href=\"#zh-8\">\u516b\u3001\u7ed3\u679c\u83b7\u53d6\u4e0e\u540e\u5904\u7406<\/a><\/li>\n <li><a href=\"#zh-9\">\u4e5d\u3001\u6210\u672c\u4f18\u5316\u4e0e\u6700\u4f73\u5b9e\u8df5<\/a><\/li>\n <li><a href=\"#zh-10\">\u5341\u3001\u5e38\u89c1\u95ee\u9898\u4e0e\u6392\u67e5<\/a><\/li>\n <\/ol>\n<\/div>\n\n\n<h2 id=\"zh-1\">\u4e00\u3001\u4ec0\u4e48\u662f\u6279\u91cf\u63a8\u7406\uff08Batch Inference\uff09<\/h2>\n\n<p>\u6279\u91cf\u63a8\u7406\uff08Batch Inference\uff09\u662f\u6307\u5c06\u5927\u91cf\u72ec\u7acb\u7684\u63a8\u7406\u8bf7\u6c42\u6c47\u603b\u6210\u4e00\u4e2a\u6279\u6b21\uff0c\u7edf\u4e00\u63d0\u4ea4\u7ed9\u6a21\u578b\u8fdb\u884c\u5904\u7406\uff0c\u5728\u540e\u53f0\u79bb\u7ebf\u6267\u884c\u5e76\u5f02\u6b65\u8fd4\u56de\u7ed3\u679c\u7684\u8ba1\u7b97\u6a21\u5f0f\u3002<\/p>\n\n<div class=\"flow-diagram\">\n <div class=\"flow-row\">\n <span class=\"flow-item green\">\u51c6\u5907\u6570\u636e<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item\">\u4e0a\u4f20\u6587\u4ef6<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item yellow\">\u63d0\u4ea4\u4efb\u52a1<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item purple\">\u540e\u53f0\u5904\u7406<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item green\">\u83b7\u53d6\u7ed3\u679c<\/span>\n <\/div>\n<\/div>\n\n<div class=\"card\">\n <h4>\u6279\u91cf\u63a8\u7406\u7684\u56db\u5927\u7279\u5f81<\/h4>\n <p><span class=\"tag tag-b\">\u5f02\u6b65\u5904\u7406<\/span> \u63d0\u4ea4\u4efb\u52a1\u540e\u7acb\u5373\u8fd4\u56de\uff0c\u65e0\u9700\u7b49\u5f85\uff0c\u540e\u53f0\u6392\u961f\u5904\u7406<\/p>\n <p><span class=\"tag tag-g\">\u9ad8\u541e\u5410<\/span> \u5145\u5206\u5229\u7528 GPU \u5e76\u884c\u8ba1\u7b97\u80fd\u529b\uff0c\u5355\u4f4d\u65f6\u95f4\u5904\u7406\u66f4\u591a\u8bf7\u6c42<\/p>\n <p><span class=\"tag tag-y\">\u4f4e\u6210\u672c<\/span> \u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6210\u672c\u4ec5\u4e3a\u5b9e\u65f6\u8c03\u7528\u7684 50%<\/p>\n <p><span class=\"tag tag-p\">\u79bb\u7ebf\u6267\u884c<\/span> \u4e0d\u5360\u7528\u5b9e\u65f6\u670d\u52a1\u8d44\u6e90\uff0c\u9002\u5408\u975e\u65f6\u6548\u6027\u4efb\u52a1<\/p>\n<\/div>\n\n\n<h2 id=\"zh-2\">\u4e8c\u3001\u6279\u91cf\u63a8\u7406 vs \u5b9e\u65f6\u63a8\u7406\u5bf9\u6bd4<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead>\n <tr><th>\u7ef4\u5ea6<\/th><th>\u6279\u91cf\u63a8\u7406\uff08Batch\uff09<\/th><th>\u5b9e\u65f6\u63a8\u7406\uff08Online\uff09<\/th><\/tr>\n <\/thead>\n <tbody>\n <tr><td>\u54cd\u5e94\u65b9\u5f0f<\/td><td>\u5f02\u6b65\uff0c\u63d0\u4ea4\u540e\u540e\u53f0\u5904\u7406<\/td><td>\u540c\u6b65\uff0c\u5373\u65f6\u8fd4\u56de\u7ed3\u679c<\/td><\/tr>\n <tr><td>\u5ef6\u8fdf\u8981\u6c42<\/td><td>\u5206\u949f\u7ea7~\u5c0f\u65f6\u7ea7\uff0c\u53ef\u63a5\u53d7<\/td><td>\u6beb\u79d2\u7ea7~\u79d2\u7ea7\uff0c\u8981\u6c42\u4f4e\u5ef6\u8fdf<\/td><\/tr>\n <tr><td>\u6210\u672c<\/td><td>\u4f4e\uff08\u7ea6\u4e3a\u5b9e\u65f6\u7684 50%\uff09<\/td><td>\u9ad8\uff08\u6309\u5b9e\u65f6\u8c03\u7528\u8ba1\u8d39\uff09<\/td><\/tr>\n <tr><td>\u541e\u5410\u91cf<\/td><td>\u9ad8\uff08GPU \u6279\u91cf\u5e76\u884c\uff09<\/td><td>\u53d7\u5e76\u53d1\u9650\u5236<\/td><\/tr>\n <tr><td>\u6570\u636e\u89c4\u6a21<\/td><td>\u5927\u89c4\u6a21\uff08\u5343~\u767e\u4e07\u6761\uff09<\/td><td>\u5c0f\u89c4\u6a21\uff08\u5355\u6761\u6216\u5c11\u91cf\uff09<\/td><\/tr>\n <tr><td>\u9002\u7528\u573a\u666f<\/td><td>\u6570\u636e\u5206\u6790\u3001\u5185\u5bb9\u751f\u6210\u3001\u6a21\u578b\u8bc4\u4f30<\/td><td>\u5bf9\u8bdd\u5e94\u7528\u3001\u5b9e\u65f6\u63a8\u8350\u3001\u5728\u7ebf\u5ba2\u670d<\/td><\/tr>\n <tr><td>\u8d44\u6e90\u5229\u7528<\/td><td>\u95f2\u65f6\u8c03\u5ea6\uff0c\u8d44\u6e90\u590d\u7528\u7387\u9ad8<\/td><td>\u5e38\u9a7b\u670d\u52a1\uff0c\u9884\u7559\u8d44\u6e90<\/td><\/tr>\n <tr><td>\u5bb9\u9519\u6027<\/td><td>\u652f\u6301\u65ad\u70b9\u7eed\u4f20\uff0c\u5931\u8d25\u53ef\u91cd\u8bd5<\/td><td>\u5355\u6b21\u5931\u8d25\u5373\u8fd4\u56de\u9519\u8bef<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"compare-box\">\n <div class=\"compare-col good\">\n <h4>\u2705 \u9009\u62e9\u6279\u91cf\u63a8\u7406<\/h4>\n <p>\u9700\u8981\u5904\u7406\u6570\u4e07\u6761\u6587\u672c\u5206\u7c7b<\/p>\n <p>\u6279\u91cf\u751f\u6210\u8425\u9500\u6587\u6848<\/p>\n <p>\u5bf9\u5386\u53f2\u6570\u636e\u505a\u60c5\u611f\u5206\u6790<\/p>\n <p>\u6a21\u578b\u6548\u679c\u6279\u91cf\u8bc4\u4f30\u6d4b\u8bd5<\/p>\n <p>\u975e\u5de5\u4f5c\u65f6\u95f4\u7684\u6570\u636e\u5904\u7406<\/p>\n <\/div>\n <div class=\"compare-col bad\">\n <h4>\u274c \u9009\u62e9\u5b9e\u65f6\u63a8\u7406<\/h4>\n <p>\u7528\u6237\u5b9e\u65f6\u5bf9\u8bdd\u4ea4\u4e92<\/p>\n <p>\u5728\u7ebf\u63a8\u8350\u7cfb\u7edf<\/p>\n <p>\u5b9e\u65f6\u98ce\u63a7\u5224\u65ad<\/p>\n <p>\u9700\u8981\u5373\u65f6\u54cd\u5e94\u7684 API<\/p>\n <p>\u5355\u6b21\u3001\u5c11\u91cf\u3001\u9ad8\u9891\u8bf7\u6c42<\/p>\n <\/div>\n<\/div>\n\n\n<h2 id=\"zh-3\">\u4e09\u3001\u9002\u7528\u573a\u666f\u4e0e\u6838\u5fc3\u4ef7\u503c<\/h2>\n\n<h3>3.1 \u5178\u578b\u5e94\u7528\u573a\u666f<\/h3>\n<div class=\"cmd-grid\">\n <div class=\"cmd-card\">\n <h4>\u6570\u636e\u5206\u6790<\/h4>\n <div class=\"desc\">\u5bf9\u6d77\u91cf\u7528\u6237\u8bc4\u8bba\u3001\u53cd\u9988\u3001\u65e5\u5fd7\u8fdb\u884c\u60c5\u611f\u5206\u6790\u3001\u4e3b\u9898\u5206\u7c7b\u3001\u5b9e\u4f53\u63d0\u53d6\uff0c\u6d1e\u5bdf\u4e1a\u52a1\u8d8b\u52bf\u3002<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>\u5185\u5bb9\u751f\u6210<\/h4>\n <div class=\"desc\">\u6279\u91cf\u751f\u6210\u5546\u54c1\u63cf\u8ff0\u3001\u8425\u9500\u6587\u6848\u3001\u7ffb\u8bd1\u5185\u5bb9\u3001\u4ee3\u7801\u6ce8\u91ca\uff0c\u63d0\u5347\u5185\u5bb9\u751f\u4ea7\u6548\u7387\u3002<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>\u6a21\u578b\u8bc4\u4f30<\/h4>\n <div class=\"desc\">\u4f7f\u7528\u6807\u51c6\u6d4b\u8bd5\u96c6\u5bf9\u6a21\u578b\u8fdb\u884c\u6279\u91cf\u8bc4\u4f30\uff0c\u83b7\u53d6\u51c6\u786e\u7387\u3001F1 \u5206\u6570\u7b49\u6307\u6807\u3002<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>\u6570\u636e\u6807\u6ce8<\/h4>\n <div class=\"desc\">\u5229\u7528\u6a21\u578b\u9884\u6807\u6ce8\u6570\u636e\uff0c\u4eba\u5de5\u590d\u6838\u4fee\u6b63\uff0c\u964d\u4f4e\u6807\u6ce8\u6210\u672c 70% \u4ee5\u4e0a\u3002<\/div>\n <\/div>\n<\/div>\n\n<h3>3.2 \u6838\u5fc3\u4ef7\u503c\u603b\u7ed3<\/h3>\n<div class=\"info-box\">\n <strong>\u6279\u91cf\u63a8\u7406\u7684\u6838\u5fc3\u4ef7\u503c\u516c\u5f0f\uff1a\u66f4\u4f4e\u7684\u5355\u4f4d\u6210\u672c \u00d7 \u66f4\u9ad8\u7684\u541e\u5410\u91cf \u00d7 \u7075\u6d3b\u7684\u65f6\u95f4\u7a97\u53e3 = \u5927\u89c4\u6a21 AI \u5904\u7406\u7684\u7ecf\u6d4e\u6700\u4f18\u89e3\u3002<\/strong>\n<\/div>\n\n\n<h2 id=\"zh-4\">\u56db\u3001\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6982\u89c8<\/h2>\n\n<p>\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u662f\u4e13\u4e3a\u5927\u89c4\u6a21\u3001\u975e\u5b9e\u65f6\u63a8\u7406\u4efb\u52a1\u8bbe\u8ba1\u7684\u5f02\u6b65\u5904\u7406\u670d\u52a1\uff0c\u652f\u6301\u901a\u8fc7\u6587\u4ef6\u4e00\u6b21\u6027\u63d0\u4ea4\u6d77\u91cf\u8bf7\u6c42\uff0c\u5728\u540e\u53f0\u79bb\u7ebf\u5904\u7406\u3002<\/p>\n\n<div class=\"card\">\n <h4>\u963f\u91cc\u4e91\u767e\u70bc BatchAPI \u6838\u5fc3\u80fd\u529b<\/h4>\n <p><span class=\"tag tag-b\">\u6587\u4ef6\u63d0\u4ea4<\/span> \u652f\u6301 JSONL \u683c\u5f0f\u6587\u4ef6\uff0c\u6bcf\u884c\u4e00\u4e2a\u72ec\u7acb\u8bf7\u6c42<\/p>\n <p><span class=\"tag tag-g\">\u6a21\u578b\u4e30\u5bcc<\/span> \u652f\u6301\u901a\u4e49\u5343\u95ee\u3001Llama\u3001DeepSeek \u7b49\u4e3b\u6d41\u5927\u6a21\u578b<\/p>\n <p><span class=\"tag tag-y\">\u6210\u672c\u4f18\u5316<\/span> \u6279\u91cf\u63a8\u7406\u4ef7\u683c\u7ea6\u4e3a\u5b9e\u65f6\u8c03\u7528\u7684 50%<\/p>\n <p><span class=\"tag tag-p\">\u72b6\u6001\u8ffd\u8e2a<\/span> \u63d0\u4f9b\u4efb\u52a1\u521b\u5efa\u3001\u6392\u961f\u3001\u8fd0\u884c\u3001\u5b8c\u6210\u5168\u6d41\u7a0b\u72b6\u6001\u67e5\u8be2<\/p>\n <p><span class=\"tag tag-r\">\u7ed3\u679c\u6301\u4e45<\/span> \u5904\u7406\u5b8c\u6210\u540e\u7ed3\u679c\u6587\u4ef6\u4fdd\u5b58\uff0c\u652f\u6301\u4e0b\u8f7d\u548c\u89e3\u6790<\/p>\n<\/div>\n\n<h3>4.1 \u4f7f\u7528\u524d\u51c6\u5907<\/h3>\n<ol class=\"steps\">\n <li>\u6ce8\u518c\u963f\u91cc\u4e91\u8d26\u53f7\u5e76\u5b8c\u6210\u5b9e\u540d\u8ba4\u8bc1\n <span class=\"note\"><a href=\"https:\/\/www.aliyun.com\/\" target=\"_blank\" rel=\"noopener\">\u963f\u91cc\u4e91\u5b98\u7f51<\/a><\/span>\n <\/li>\n <li>\u5f00\u901a\u767e\u70bc\uff08Model Studio\uff09\u670d\u52a1\n <span class=\"note\">\u5728\u963f\u91cc\u4e91\u63a7\u5236\u53f0\u641c\u7d22”\u767e\u70bc”\u6216”Model Studio”\uff0c\u6309\u6307\u5f15\u5f00\u901a<\/span>\n <\/li>\n <li>\u83b7\u53d6 API-Key\n <span class=\"cmd\">\u767e\u70bc\u63a7\u5236\u53f0 \u2192 API-Key \u7ba1\u7406 \u2192 \u521b\u5efa API-Key<\/span>\n <span class=\"note\">\u59a5\u5584\u4fdd\u5b58 Key\uff0c\u4e0d\u8981\u786c\u7f16\u7801\u5728\u4ee3\u7801\u4e2d\u63d0\u4ea4\u5230\u4ed3\u5e93<\/span>\n <\/li>\n <li>\u5b89\u88c5 Python SDK\n <span class=\"cmd\">pip install alibabacloud-bailian20231229<\/span>\n <span class=\"note\">\u6216\u901a\u8fc7 OpenAI \u517c\u5bb9\u63a5\u53e3\u4f7f\u7528 openai \u5e93<\/span>\n <\/li>\n<\/ol>\n\n\n<h2 id=\"zh-5\">\u4e94\u3001\u6570\u636e\u51c6\u5907\uff1aJSONL \u683c\u5f0f\u89c4\u8303<\/h2>\n\n<div class=\"info-box\">\n <strong>JSONL\uff08JSON Lines\uff09\u662f\u6279\u91cf\u63a8\u7406\u7684\u6807\u51c6\u8f93\u5165\u683c\u5f0f\uff0c\u6bcf\u884c\u4e00\u4e2a\u72ec\u7acb\u7684 JSON \u5bf9\u8c61\uff0c\u8868\u793a\u4e00\u4e2a\u63a8\u7406\u8bf7\u6c42\u3002\u6587\u4ef6\u65e0\u9700\u9996\u5c3e\u62ec\u53f7\uff0c\u7eaf\u6587\u672c\u5373\u53ef\u3002<\/strong>\n<\/div>\n\n<h3>5.1 JSONL \u683c\u5f0f\u793a\u4f8b<\/h3>\n<pre class=\"code-block\">{\"custom_id\": \"req-001\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"\u8bf7\u7528\u4e00\u53e5\u8bdd\u603b\u7ed3\uff1a\u4eba\u5de5\u667a\u80fd\u6b63\u5728\u6539\u53d8\u5404\u4e2a\u884c\u4e1a\u3002\"}]}}\n{\"custom_id\": \"req-002\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"\u8bf7\u7ffb\u8bd1\u4e3a\u82f1\u6587\uff1a\u4f60\u597d\uff0c\u4e16\u754c\u3002\"}]}}\n{\"custom_id\": \"req-003\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"\u5224\u65ad\u60c5\u611f\u503e\u5411\uff1a\u8fd9\u6b3e\u4ea7\u54c1\u592a\u68d2\u4e86\uff0c\u975e\u5e38\u6ee1\u610f\uff01\"}]}}\n<\/pre>\n\n<h3>5.2 JSONL \u5b57\u6bb5\u8bf4\u660e<\/h3>\n<div class=\"table-wrap\">\n<table>\n <thead>\n <tr><th>\u5b57\u6bb5<\/th><th>\u7c7b\u578b<\/th><th>\u5fc5\u586b<\/th><th>\u8bf4\u660e<\/th><\/tr>\n <\/thead>\n <tbody>\n <tr><td>custom_id<\/td><td>string<\/td><td>\u662f<\/td><td>\u81ea\u5b9a\u4e49\u8bf7\u6c42\u6807\u8bc6\uff0c\u7528\u4e8e\u7ed3\u679c\u5339\u914d<\/td><\/tr>\n <tr><td>method<\/td><td>string<\/td><td>\u662f<\/td><td>HTTP \u65b9\u6cd5\uff0c\u56fa\u5b9a\u4e3a “POST”<\/td><\/tr>\n <tr><td>url<\/td><td>string<\/td><td>\u662f<\/td><td>\u63a5\u53e3\u8def\u5f84\uff0c”\/v1\/chat\/completions”<\/td><\/tr>\n <tr><td>body<\/td><td>object<\/td><td>\u662f<\/td><td>\u8bf7\u6c42\u4f53\uff0c\u4e0e\u5b9e\u65f6 API \u53c2\u6570\u4e00\u81f4<\/td><\/tr>\n <tr><td>body.model<\/td><td>string<\/td><td>\u662f<\/td><td>\u6a21\u578b\u540d\u79f0\uff0c\u5982 qwen-turbo<\/td><\/tr>\n <tr><td>body.messages<\/td><td>array<\/td><td>\u662f<\/td><td>\u5bf9\u8bdd\u6d88\u606f\u5217\u8868<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h3>5.3 \u6570\u636e\u51c6\u5907\u4ee3\u7801<\/h3>\n<pre class=\"code-block\">import json\nfrom pathlib import Path\n\n\ndef prepare_batch_input(\n items: list[dict],\n output_path: str = \"batch_input.jsonl\",\n model: str = \"qwen-turbo\"\n) -> str:\n \"\"\"\u5c06\u6570\u636e\u5217\u8868\u8f6c\u6362\u4e3a JSONL \u6279\u91cf\u63a8\u7406\u8f93\u5165\u6587\u4ef6\u3002\n\n Args:\n items: \u6bcf\u6761\u5305\u542b\u81ea\u5b9a\u4e49\u5b57\u6bb5\u7684\u6570\u636e\u5b57\u5178\n output_path: \u8f93\u51fa JSONL \u6587\u4ef6\u8def\u5f84\n model: \u4f7f\u7528\u7684\u6a21\u578b\u540d\u79f0\n\n Returns:\n \u8f93\u51fa\u6587\u4ef6\u7684\u7edd\u5bf9\u8def\u5f84\n \"\"\"\n output = Path(output_path)\n with output.open(\"w\", encoding=\"utf-8\") as f:\n for idx, item in enumerate(items, 1):\n record = {\n \"custom_id\": item.get(\"id\", f\"req-{idx:04d}\"),\n \"method\": \"POST\",\n \"url\": \"\/v1\/chat\/completions\",\n \"body\": {\n \"model\": model,\n \"messages\": [\n {\"role\": \"system\", \"content\": item.get(\"system\", \"\")},\n {\"role\": \"user\", \"content\": item[\"prompt\"]}\n ] if item.get(\"system\") else [\n {\"role\": \"user\", \"content\": item[\"prompt\"]}\n ],\n \"max_tokens\": item.get(\"max_tokens\", 512),\n \"temperature\": item.get(\"temperature\", 0.7)\n }\n }\n f.write(json.dumps(record, ensure_ascii=False) + \"\\n\")\n\n return str(output.resolve())\n\n\n# \u4f7f\u7528\u793a\u4f8b\ndata = [\n {\"id\": \"sentiment-001\", \"prompt\": \"\u5224\u65ad\u60c5\u611f\uff1a\u4ea7\u54c1\u8d28\u91cf\u5f88\u5dee\uff0c\u9000\u8d27\u4e86\u3002\"},\n {\"id\": \"sentiment-002\", \"prompt\": \"\u5224\u65ad\u60c5\u611f\uff1a\u7269\u6d41\u5f88\u5feb\uff0c\u5305\u88c5\u5b8c\u597d\u3002\"},\n {\"id\": \"summary-001\", \"prompt\": \"\u603b\u7ed3\uff1a\u672c\u6587\u4ecb\u7ecd\u4e86\u6279\u91cf\u63a8\u7406\u7684\u4f18\u52bf\u548c\u5e94\u7528\u573a\u666f\u3002\"},\n]\n\nfile_path = prepare_batch_input(data, model=\"qwen-turbo\")\nprint(f\"\u5df2\u751f\u6210\u6279\u91cf\u63a8\u7406\u8f93\u5165\u6587\u4ef6: {file_path}\")\n<\/pre>\n\n<h3>5.4 \u6570\u636e\u6821\u9a8c<\/h3>\n<pre class=\"code-block\">def validate_jsonl(file_path: str) -> tuple[int, list[str]]:\n \"\"\"\u6821\u9a8c JSONL \u6587\u4ef6\u683c\u5f0f\u662f\u5426\u6b63\u786e\u3002\n\n Returns:\n (\u6709\u6548\u884c\u6570, \u9519\u8bef\u5217\u8868)\n \"\"\"\n errors = []\n valid_count = 0\n\n with open(file_path, \"r\", encoding=\"utf-8\") as f:\n for line_num, line in enumerate(f, 1):\n line = line.strip()\n if not line:\n continue\n try:\n obj = json.loads(line)\n required = [\"custom_id\", \"method\", \"url\", \"body\"]\n for field in required:\n if field not in obj:\n errors.append(f\"\u7b2c {line_num} \u884c\u7f3a\u5c11\u5b57\u6bb5: {field}\")\n break\n else:\n valid_count += 1\n except json.JSONDecodeError as e:\n errors.append(f\"\u7b2c {line_num} \u884c JSON \u89e3\u6790\u9519\u8bef: {e}\")\n\n return valid_count, errors\n\n\ncount, errs = validate_jsonl(\"batch_input.jsonl\")\nprint(f\"\u6709\u6548\u8bf7\u6c42: {count} \u6761\")\nif errs:\n for e in errs:\n print(f\"\u9519\u8bef: {e}\")\n<\/pre>\n\n\n<h2 id=\"zh-6\">\u516d\u3001\u63d0\u4ea4\u6279\u91cf\u63a8\u7406\u4efb\u52a1\uff08\u5b8c\u6574\u4ee3\u7801\uff09<\/h2>\n\n<h3>6.1 \u4f7f\u7528 OpenAI \u517c\u5bb9\u63a5\u53e3\uff08\u63a8\u8350\uff09<\/h3>\n<pre class=\"code-block\">import os\nfrom pathlib import Path\nfrom openai import OpenAI\n\n\ndef create_batch_job(\n input_file: str,\n api_key: str | None = None,\n base_url: str = \"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n) -> dict:\n \"\"\"\u521b\u5efa\u963f\u91cc\u4e91\u767e\u70bc\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u3002\n\n Args:\n input_file: JSONL \u8f93\u5165\u6587\u4ef6\u8def\u5f84\n api_key: \u767e\u70bc API-Key\uff0c\u9ed8\u8ba4\u4ece\u73af\u5883\u53d8\u91cf DASHSCOPE_API_KEY \u8bfb\u53d6\n base_url: \u767e\u70bc\u517c\u5bb9\u63a5\u53e3\u5730\u5740\n\n Returns:\n \u4efb\u52a1\u4fe1\u606f\u5b57\u5178\uff0c\u5305\u542b batch_id\n \"\"\"\n api_key = api_key or os.getenv(\"DASHSCOPE_API_KEY\")\n if not api_key:\n raise ValueError(\"\u8bf7\u8bbe\u7f6e API-Key\uff1a\u73af\u5883\u53d8\u91cf DASHSCOPE_API_KEY \u6216\u53c2\u6570\u4f20\u5165\")\n\n client = OpenAI(api_key=api_key, base_url=base_url)\n\n # 1. \u4e0a\u4f20\u8f93\u5165\u6587\u4ef6\n with open(input_file, \"rb\") as f:\n file_obj = client.files.create(file=f, purpose=\"batch\")\n print(f\"\u6587\u4ef6\u4e0a\u4f20\u6210\u529f: {file_obj.id}\")\n\n # 2. \u521b\u5efa\u6279\u91cf\u4efb\u52a1\n batch = client.batches.create(\n input_file_id=file_obj.id,\n endpoint=\"\/v1\/chat\/completions\",\n completion_window=\"24h\" # \u4efb\u52a1\u8d85\u65f6\u65f6\u95f4\n )\n print(f\"\u6279\u91cf\u4efb\u52a1\u521b\u5efa\u6210\u529f: {batch.id}\")\n print(f\"\u72b6\u6001: {batch.status}\")\n\n return {\n \"batch_id\": batch.id,\n \"input_file_id\": file_obj.id,\n \"status\": batch.status\n }\n\n\n# \u4f7f\u7528\njob = create_batch_job(\"batch_input.jsonl\")\n<\/pre>\n\n<h3>6.2 \u4f7f\u7528\u963f\u91cc\u4e91\u5b98\u65b9 SDK<\/h3>\n<pre class=\"code-block\">import os\nfrom alibabacloud_bailian20231229.client import Client as BailianClient\nfrom alibabacloud_tea_openapi import models as open_api_models\n\n\ndef create_batch_job_sdk(\n input_file_url: str,\n access_key_id: str | None = None,\n access_key_secret: str | None = None,\n model: str = \"qwen-turbo\"\n) -> str:\n \"\"\"\u4f7f\u7528\u963f\u91cc\u4e91 SDK \u521b\u5efa\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u3002\n\n Args:\n input_file_url: \u5df2\u4e0a\u4f20\u5230 OSS \u7684\u8f93\u5165\u6587\u4ef6 URL\n access_key_id: \u963f\u91cc\u4e91 AccessKey ID\n access_key_secret: \u963f\u91cc\u4e91 AccessKey Secret\n model: \u6a21\u578b\u540d\u79f0\n\n Returns:\n \u4efb\u52a1 ID\n \"\"\"\n access_key_id = access_key_id or os.getenv(\"ALIBABA_CLOUD_ACCESS_KEY_ID\")\n access_key_secret = access_key_secret or os.getenv(\"ALIBABA_CLOUD_ACCESS_KEY_SECRET\")\n\n config = open_api_models.Config(\n access_key_id=access_key_id,\n access_key_secret=access_key_secret\n )\n config.endpoint = \"bailian.cn-beijing.aliyuncs.com\"\n client = BailianClient(config)\n\n # \u521b\u5efa\u6279\u91cf\u4efb\u52a1\n response = client.create_batch_inference_job(\n model=model,\n input_file_url=input_file_url,\n output_file_prefix=\"batch-output\/\"\n )\n\n job_id = response.body.job_id\n print(f\"\u4efb\u52a1\u521b\u5efa\u6210\u529f: {job_id}\")\n return job_id\n<\/pre>\n\n\n<h2 id=\"zh-7\">\u4e03\u3001\u4efb\u52a1\u76d1\u63a7\u4e0e\u72b6\u6001\u7ba1\u7406<\/h2>\n\n<h3>7.1 \u4efb\u52a1\u72b6\u6001\u6d41\u8f6c<\/h3>\n<div class=\"flow-diagram\">\n <div class=\"flow-row\">\n <span class=\"flow-item\">validating<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item yellow\">in_progress<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item green\">completed<\/span>\n <\/div>\n <div class=\"flow-row\" style=\"font-size:.78rem;color:var(--muted);margin-top:.3rem\">\n <span>\u6587\u4ef6\u6821\u9a8c\u4e2d<\/span>\n <span> <\/span>\n <span>\u6b63\u5728\u5904\u7406<\/span>\n <span> <\/span>\n <span>\u5df2\u5b8c\u6210<\/span>\n <\/div>\n <div class=\"flow-row\" style=\"margin-top:.5rem\">\n <span class=\"flow-item red\">failed<\/span>\n <span style=\"font-size:.78rem;color:var(--muted)\">\uff08\u5f02\u5e38\u7ec8\u6b62\uff09<\/span>\n <span class=\"flow-item red\">expired<\/span>\n <span style=\"font-size:.78rem;color:var(--muted)\">\uff08\u8d85\u65f6\uff09<\/span>\n <span class=\"flow-item red\">cancelled<\/span>\n <span style=\"font-size:.78rem;color:var(--muted)\">\uff08\u5df2\u53d6\u6d88\uff09<\/span>\n <\/div>\n<\/div>\n\n<h3>7.2 \u72b6\u6001\u67e5\u8be2\u4ee3\u7801<\/h3>\n<pre class=\"code-block\">import time\nfrom openai import OpenAI\n\n\ndef wait_for_batch_completion(\n batch_id: str,\n api_key: str | None = None,\n poll_interval: int = 30,\n max_wait: int = 86400\n) -> dict:\n \"\"\"\u8f6e\u8be2\u7b49\u5f85\u6279\u91cf\u4efb\u52a1\u5b8c\u6210\u3002\n\n Args:\n batch_id: \u6279\u91cf\u4efb\u52a1 ID\n api_key: API-Key\n poll_interval: \u8f6e\u8be2\u95f4\u9694\uff08\u79d2\uff09\n max_wait: \u6700\u5927\u7b49\u5f85\u65f6\u95f4\uff08\u79d2\uff09\n\n Returns:\n \u6700\u7ec8\u4efb\u52a1\u72b6\u6001\u4fe1\u606f\n \"\"\"\n client = OpenAI(\n api_key=api_key or os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n )\n\n start_time = time.time()\n while True:\n batch = client.batches.retrieve(batch_id)\n elapsed = int(time.time() - start_time)\n\n print(f\"[{elapsed}s] \u72b6\u6001: {batch.status} | \"\n f\"\u5b8c\u6210: {batch.request_counts.completed}\/\"\n f\"{batch.request_counts.total} | \"\n f\"\u5931\u8d25: {batch.request_counts.failed}\")\n\n if batch.status in (\"completed\", \"failed\", \"expired\", \"cancelled\"):\n return {\n \"status\": batch.status,\n \"batch\": batch,\n \"elapsed_seconds\": elapsed\n }\n\n if elapsed > max_wait:\n raise TimeoutError(f\"\u4efb\u52a1\u7b49\u5f85\u8d85\u65f6\uff08>{max_wait}\u79d2\uff09\")\n\n time.sleep(poll_interval)\n\n\n# \u4f7f\u7528\nresult = wait_for_batch_completion(job[\"batch_id\"], poll_interval=30)\nprint(f\"\u6700\u7ec8\u72b6\u6001: {result['status']}\")\n<\/pre>\n\n<h3>7.3 \u4efb\u52a1\u5217\u8868\u9762\u677f<\/h3>\n<pre class=\"code-block\">def list_batch_jobs(api_key: str | None = None, limit: int = 10) -> list[dict]:\n \"\"\"\u5217\u51fa\u6700\u8fd1\u7684\u6279\u91cf\u4efb\u52a1\u3002\"\"\"\n client = OpenAI(\n api_key=api_key or os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n )\n\n batches = client.batches.list(limit=limit)\n jobs = []\n for batch in batches.data:\n jobs.append({\n \"id\": batch.id,\n \"status\": batch.status,\n \"created_at\": batch.created_at,\n \"completed\": batch.request_counts.completed,\n \"failed\": batch.request_counts.failed,\n \"total\": batch.request_counts.total\n })\n return jobs\n\n\n# \u6253\u5370\u4efb\u52a1\u5217\u8868\nfor job in list_batch_jobs():\n print(f\"{job['id'][:20]:20s} | {job['status']:12s} | \"\n f\"{job['completed']:>4d}\/{job['total']:<4d} | \"\n f\"\u5931\u8d25: {job['failed']}\")\n<\/pre>\n\n\n<h2 id=\"zh-8\">\u516b\u3001\u7ed3\u679c\u83b7\u53d6\u4e0e\u540e\u5904\u7406<\/h2>\n\n<h3>8.1 \u4e0b\u8f7d\u7ed3\u679c\u6587\u4ef6<\/h3>\n<pre class=\"code-block\">def download_batch_results(batch_id: str, api_key: str | None = None) -> list[dict]:\n \"\"\"\u4e0b\u8f7d\u5e76\u89e3\u6790\u6279\u91cf\u63a8\u7406\u7ed3\u679c\u3002\n\n Returns:\n \u7ed3\u679c\u8bb0\u5f55\u5217\u8868\uff0c\u6bcf\u6761\u5305\u542b custom_id \u548c\u6a21\u578b\u8f93\u51fa\n \"\"\"\n client = OpenAI(\n api_key=api_key or os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n )\n\n # \u83b7\u53d6\u4efb\u52a1\u4fe1\u606f\n batch = client.batches.retrieve(batch_id)\n if batch.status != \"completed\":\n raise ValueError(f\"\u4efb\u52a1\u672a\u5b8c\u6210\uff0c\u5f53\u524d\u72b6\u6001: {batch.status}\")\n\n # \u4e0b\u8f7d\u8f93\u51fa\u6587\u4ef6\n output_file = client.files.content(batch.output_file_id)\n content = output_file.read().decode(\"utf-8\")\n\n # \u89e3\u6790 JSONL\n results = []\n for line in content.strip().split(\"\\n\"):\n if not line.strip():\n continue\n obj = json.loads(line)\n results.append({\n \"custom_id\": obj.get(\"custom_id\"),\n \"status_code\": obj.get(\"status_code\"),\n \"response\": obj.get(\"response\", {}),\n \"error\": obj.get(\"error\")\n })\n\n return results\n\n\n# \u4f7f\u7528\nresults = download_batch_results(job[\"batch_id\"])\n\n# \u67e5\u770b\u7ed3\u679c\nfor r in results[:3]:\n cid = r[\"custom_id\"]\n if r[\"error\"]:\n print(f\"[{cid}] \u9519\u8bef: {r['error']}\")\n else:\n content = r[\"response\"][\"body\"][\"choices\"][0][\"message\"][\"content\"]\n print(f\"[{cid}] \u7ed3\u679c: {content[:100]}...\")\n<\/pre>\n\n<h3>8.2 \u7ed3\u679c\u4e0e\u8f93\u5165\u5339\u914d<\/h3>\n<pre class=\"code-block\">def merge_results_with_input(\n input_items: list[dict],\n results: list[dict]\n) -> list[dict]:\n \"\"\"\u5c06\u6279\u91cf\u63a8\u7406\u7ed3\u679c\u4e0e\u539f\u59cb\u8f93\u5165\u6570\u636e\u5408\u5e76\u3002\n\n Returns:\n \u5408\u5e76\u540e\u7684\u8bb0\u5f55\u5217\u8868\n \"\"\"\n result_map = {r[\"custom_id\"]: r for r in results}\n merged = []\n\n for item in input_items:\n cid = item.get(\"id\", \"\")\n result = result_map.get(cid, {})\n\n merged.append({\n **item,\n \"status_code\": result.get(\"status_code\"),\n \"output\": result.get(\"response\", {})\n .get(\"body\", {})\n .get(\"choices\", [{}])[0]\n .get(\"message\", {})\n .get(\"content\", \"\"),\n \"error\": result.get(\"error\")\n })\n\n return merged\n\n\n# \u4fdd\u5b58\u4e3a CSV\nimport csv\n\nmerged = merge_results_with_input(data, results)\nwith open(\"batch_results.csv\", \"w\", newline=\"\", encoding=\"utf-8-sig\") as f:\n writer = csv.DictWriter(f, fieldnames=[\"id\", \"prompt\", \"output\", \"error\"])\n writer.writeheader()\n for row in merged:\n writer.writerow({\n \"id\": row[\"id\"],\n \"prompt\": row[\"prompt\"],\n \"output\": row[\"output\"],\n \"error\": row[\"error\"] or \"\"\n })\n\nprint(\"\u7ed3\u679c\u5df2\u4fdd\u5b58\u5230 batch_results.csv\")\n<\/pre>\n\n\n<h2 id=\"zh-9\">\u4e5d\u3001\u6210\u672c\u4f18\u5316\u4e0e\u6700\u4f73\u5b9e\u8df5<\/h2>\n\n<h3>9.1 \u6210\u672c\u63a7\u5236\u7b56\u7565<\/h3>\n<div class=\"card\">\n <h4>\u6279\u91cf\u63a8\u7406\u964d\u672c\u4e94\u6cd5<\/h4>\n <p>1. <span class=\"tag tag-g\">\u6279\u91cf\u4ee3\u66ff\u5b9e\u65f6<\/span> \u975e\u7d27\u6025\u4efb\u52a1\u7edf\u4e00\u8d70 BatchAPI\uff0c\u6210\u672c\u964d\u4f4e\u7ea6 50%<\/p>\n <p>2. <span class=\"tag tag-b\">\u9009\u62e9\u5408\u9002\u6a21\u578b<\/span> \u7b80\u5355\u4efb\u52a1\u7528 qwen-turbo\uff08\u5feb\u4e14\u4fbf\u5b9c\uff09\uff0c\u590d\u6742\u4efb\u52a1\u518d\u7528 qwen-max<\/p>\n <p>3. <span class=\"tag tag-y\">\u9650\u5236\u8f93\u51fa\u957f\u5ea6<\/span> \u8bbe\u7f6e\u5408\u7406\u7684 max_tokens\uff0c\u907f\u514d\u6a21\u578b\u8fc7\u5ea6\u751f\u6210\u6d6a\u8d39 Token<\/p>\n <p>4. <span class=\"tag tag-p\">\u5408\u5e76\u76f8\u4f3c\u8bf7\u6c42<\/span> \u5c06\u76f8\u540c system prompt \u7684\u8bf7\u6c42\u5408\u5e76\uff0c\u51cf\u5c11\u91cd\u590d\u8ba1\u7b97<\/p>\n <p>5. <span class=\"tag tag-r\">\u5931\u8d25\u91cd\u8bd5\u673a\u5236<\/span> \u53ea\u91cd\u8bd5\u5931\u8d25\u7684\u8bf7\u6c42\uff0c\u907f\u514d\u5168\u91cf\u91cd\u65b0\u63d0\u4ea4<\/p>\n<\/div>\n\n<h3>9.2 \u6700\u4f73\u5b9e\u8df5\u6e05\u5355<\/h3>\n<pre class=\"code-block\">\u25a1 \u6570\u636e\u51c6\u5907\n - \u63d0\u524d\u6821\u9a8c JSONL \u683c\u5f0f\uff0c\u907f\u514d\u4e0a\u4f20\u540e\u6821\u9a8c\u5931\u8d25\n - \u5355\u6587\u4ef6\u8bf7\u6c42\u6570\u63a7\u5236\u5728\u5408\u7406\u8303\u56f4\uff08\u5efa\u8bae 1\u4e07~10\u4e07\u6761\uff09\n - \u5355\u6761\u8bf7\u6c42\u4e0d\u8981\u592a\u957f\uff0c\u907f\u514d\u8d85\u65f6\n\n\u25a1 \u4efb\u52a1\u63d0\u4ea4\n - \u907f\u5f00\u4e1a\u52a1\u9ad8\u5cf0\u671f\u63d0\u4ea4\uff0c\u51cf\u5c11\u6392\u961f\u65f6\u95f4\n - \u5927\u4efb\u52a1\u62c6\u5206\u4e3a\u591a\u4e2a\u5c0f\u6279\u91cf\uff0c\u964d\u4f4e\u5355\u70b9\u5931\u8d25\u98ce\u9669\n - \u8bb0\u5f55 batch_id\uff0c\u4fbf\u4e8e\u540e\u7eed\u67e5\u8be2\u548c\u8ddf\u8e2a\n\n\u25a1 \u76d1\u63a7\u7ba1\u7406\n - \u8bbe\u7f6e\u5408\u7406\u7684\u8f6e\u8be2\u95f4\u9694\uff0830~60 \u79d2\uff09\uff0c\u907f\u514d\u9891\u7e41\u8c03\u7528\n - \u4efb\u52a1\u5b8c\u6210\u540e\u53ca\u65f6\u4e0b\u8f7d\u7ed3\u679c\uff0c\u91ca\u653e\u5b58\u50a8\n - \u5b9a\u671f\u68c0\u67e5\u5931\u8d25\u8bf7\u6c42\uff0c\u5206\u6790\u5931\u8d25\u539f\u56e0\n\n\u25a1 \u7ed3\u679c\u5904\u7406\n - \u89e3\u6790\u7ed3\u679c\u65f6\u505a\u597d\u5f02\u5e38\u5904\u7406\uff0c\u517c\u5bb9\u683c\u5f0f\u53d8\u5316\n - \u5c06\u7ed3\u679c\u4e0e\u8f93\u5165\u901a\u8fc7 custom_id \u7cbe\u786e\u5339\u914d\n - \u5bf9\u5931\u8d25\u8bf7\u6c42\u5355\u72ec\u8bb0\u5f55\uff0c\u4fbf\u4e8e\u540e\u7eed\u91cd\u8bd5\n<\/pre>\n\n<h3>9.3 \u5931\u8d25\u91cd\u8bd5\u6d41\u7a0b<\/h3>\n<pre class=\"code-block\">def retry_failed_requests(\n input_file: str,\n results: list[dict],\n api_key: str | None = None\n) -> dict | None:\n \"\"\"\u63d0\u53d6\u5931\u8d25\u7684\u8bf7\u6c42\uff0c\u751f\u6210\u65b0\u7684\u91cd\u8bd5\u6279\u6b21\u3002\n\n Returns:\n \u65b0\u4efb\u52a1\u4fe1\u606f\uff0c\u5982\u679c\u6ca1\u6709\u5931\u8d25\u5219\u8fd4\u56de None\n \"\"\"\n failed_ids = {r[\"custom_id\"] for r in results if r[\"error\"]}\n if not failed_ids:\n print(\"\u6ca1\u6709\u5931\u8d25\u8bf7\u6c42\uff0c\u65e0\u9700\u91cd\u8bd5\")\n return None\n\n # \u8bfb\u53d6\u539f\u59cb\u8f93\u5165\n retry_items = []\n with open(input_file, \"r\", encoding=\"utf-8\") as f:\n for line in f:\n obj = json.loads(line.strip())\n if obj[\"custom_id\"] in failed_ids:\n retry_items.append(obj)\n\n # \u5199\u5165\u91cd\u8bd5\u6587\u4ef6\n retry_file = input_file.replace(\".jsonl\", \"_retry.jsonl\")\n with open(retry_file, \"w\", encoding=\"utf-8\") as f:\n for item in retry_items:\n f.write(json.dumps(item, ensure_ascii=False) + \"\\n\")\n\n print(f\"\u63d0\u53d6 {len(retry_items)} \u6761\u5931\u8d25\u8bf7\u6c42\uff0c\u5199\u5165 {retry_file}\")\n return create_batch_job(retry_file, api_key)\n\n\n# \u4f7f\u7528\nretry_job = retry_failed_requests(\"batch_input.jsonl\", results)\n<\/pre>\n\n\n<h2 id=\"zh-10\">\u5341\u3001\u5e38\u89c1\u95ee\u9898\u4e0e\u6392\u67e5<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead>\n <tr><th>\u95ee\u9898\u73b0\u8c61<\/th><th>\u539f\u56e0<\/th><th>\u89e3\u51b3\u65b9\u6848<\/th><\/tr>\n <\/thead>\n <tbody>\n <tr>\n <td>\u6587\u4ef6\u4e0a\u4f20\u5931\u8d25<\/td>\n <td>JSONL \u683c\u5f0f\u9519\u8bef\u3001\u6587\u4ef6\u8fc7\u5927\uff08\u8d85\u8fc7 100MB\uff09\u3001\u7f16\u7801\u975e UTF-8<\/td>\n <td>\u4f7f\u7528 validate_jsonl() \u9884\u6821\u9a8c\uff0c\u5927\u6587\u4ef6\u62c6\u5206\u4e3a\u591a\u4e2a\uff0c\u786e\u8ba4 UTF-8 \u7f16\u7801<\/td>\n <\/tr>\n <tr>\n <td>\u4efb\u52a1\u72b6\u6001 validating \u5f88\u4e45<\/td>\n <td>\u6587\u4ef6\u6b63\u5728\u683c\u5f0f\u6821\u9a8c\uff0c\u6216\u8bf7\u6c42\u6570\u91cf\u8fc7\u5927<\/td>\n <td>\u7b49\u5f85\u5373\u53ef\uff0c\u901a\u5e38\u51e0\u5206\u949f\u5185\u5b8c\u6210\uff1b\u5982\u8d85 30 \u5206\u949f\u8054\u7cfb\u5ba2\u670d<\/td>\n <\/tr>\n <tr>\n <td>\u90e8\u5206\u8bf7\u6c42\u5931\u8d25<\/td>\n <td>\u4e2a\u522b\u8bf7\u6c42\u53c2\u6570\u975e\u6cd5\u3001\u8d85\u957f\u3001\u6216\u6a21\u578b\u4e0d\u652f\u6301<\/td>\n <td>\u4e0b\u8f7d\u7ed3\u679c\u67e5\u770b error \u5b57\u6bb5\uff0c\u4fee\u590d\u540e\u5355\u72ec\u91cd\u8bd5\u5931\u8d25\u9879<\/td>\n <\/tr>\n <tr>\n <td>\u4efb\u52a1\u72b6\u6001 failed<\/td>\n <td>\u6587\u4ef6\u683c\u5f0f\u4e25\u91cd\u9519\u8bef\u3001\u6743\u9650\u4e0d\u8db3\u3001\u6a21\u578b\u4e0d\u53ef\u7528<\/td>\n <td>\u68c0\u67e5 API-Key \u6743\u9650\u3001\u6a21\u578b\u662f\u5426\u5df2\u5f00\u901a\u3001JSONL \u683c\u5f0f<\/td>\n <\/tr>\n <tr>\n <td>\u7ed3\u679c\u4e0e\u8f93\u5165\u4e0d\u5339\u914d<\/td>\n <td>custom_id \u91cd\u590d\u6216\u683c\u5f0f\u4e0d\u4e00\u81f4<\/td>\n <td>\u786e\u4fdd custom_id \u5168\u5c40\u552f\u4e00\uff0c\u5efa\u8bae\u4f7f\u7528 UUID \u6216\u4e1a\u52a1 ID<\/td>\n <\/tr>\n <tr>\n <td>\u4efb\u52a1\u6392\u961f\u65f6\u95f4\u957f<\/td>\n <td>\u9ad8\u5cf0\u671f\u63d0\u4ea4\uff0c\u8d44\u6e90\u7d27\u5f20<\/td>\n <td>\u907f\u5f00\u9ad8\u5cf0\uff08\u5de5\u4f5c\u65e5\u4e0a\u5348 10~12 \u70b9\uff09\uff0c\u6216\u591c\u95f4\u63d0\u4ea4<\/td>\n <\/tr>\n <tr>\n <td>\u7ed3\u679c\u6587\u4ef6\u65e0\u6cd5\u4e0b\u8f7d<\/td>\n <td>\u7ed3\u679c\u6587\u4ef6\u5df2\u8fc7\u671f\uff08\u901a\u5e38\u4fdd\u7559 7 \u5929\uff09<\/td>\n <td>\u4efb\u52a1\u5b8c\u6210\u540e\u5c3d\u5feb\u4e0b\u8f7d\uff0c\u8bbe\u7f6e\u81ea\u52a8\u4e0b\u8f7d\u811a\u672c<\/td>\n <\/tr>\n <tr>\n <td>Token \u6d88\u8017\u8d85\u9884\u671f<\/td>\n <td>max_tokens \u8bbe\u7f6e\u8fc7\u5927\uff0c\u6216\u8f93\u5165\u5185\u5bb9\u8fc7\u957f<\/td>\n <td>\u4f18\u5316 prompt \u957f\u5ea6\uff0c\u8bbe\u7f6e\u5408\u7406\u7684 max_tokens \u4e0a\u9650<\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h3>\u5b8c\u6574\u5de5\u4f5c\u6d41\u4ee3\u7801\u6a21\u677f<\/h3>\n<pre class=\"code-block\">\"\"\"\n\u963f\u91cc\u4e91\u767e\u70bc\u6279\u91cf\u63a8\u7406\u5b8c\u6574\u5de5\u4f5c\u6d41\u6a21\u677f\n\u4e00\u6b65\u5b8c\u6210\uff1a\u6570\u636e\u51c6\u5907 \u2192 \u63d0\u4ea4\u4efb\u52a1 \u2192 \u76d1\u63a7 \u2192 \u83b7\u53d6\u7ed3\u679c \u2192 \u4fdd\u5b58 CSV\n\"\"\"\n\nimport os\nimport json\nimport time\nimport csv\nfrom pathlib import Path\nfrom openai import OpenAI\n\nAPI_KEY = os.getenv(\"DASHSCOPE_API_KEY\")\nBASE_URL = \"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\nMODEL = \"qwen-turbo\"\n\n\ndef run_batch_pipeline(input_items: list[dict], output_csv: str = \"results.csv\") -> None:\n \"\"\"\u6279\u91cf\u63a8\u7406\u5b8c\u6574\u6d41\u6c34\u7ebf\u3002\"\"\"\n\n # Step 1: \u51c6\u5907 JSONL\n jsonl_path = \"batch_input.jsonl\"\n with open(jsonl_path, \"w\", encoding=\"utf-8\") as f:\n for idx, item in enumerate(input_items, 1):\n record = {\n \"custom_id\": item.get(\"id\", f\"req-{idx:04d}\"),\n \"method\": \"POST\",\n \"url\": \"\/v1\/chat\/completions\",\n \"body\": {\n \"model\": MODEL,\n \"messages\": [{\"role\": \"user\", \"content\": item[\"prompt\"]}],\n \"max_tokens\": item.get(\"max_tokens\", 512)\n }\n }\n f.write(json.dumps(record, ensure_ascii=False) + \"\\n\")\n print(f\"\u2705 \u5df2\u751f\u6210\u8f93\u5165\u6587\u4ef6: {jsonl_path} ({len(input_items)} \u6761)\")\n\n # Step 2: \u521b\u5efa\u4efb\u52a1\n client = OpenAI(api_key=API_KEY, base_url=BASE_URL)\n with open(jsonl_path, \"rb\") as f:\n file_obj = client.files.create(file=f, purpose=\"batch\")\n batch = client.batches.create(\n input_file_id=file_obj.id,\n endpoint=\"\/v1\/chat\/completions\",\n completion_window=\"24h\"\n )\n print(f\"\u2705 \u4efb\u52a1\u5df2\u521b\u5efa: {batch.id}\")\n\n # Step 3: \u7b49\u5f85\u5b8c\u6210\n while True:\n batch = client.batches.retrieve(batch.id)\n print(f\"\u23f3 \u72b6\u6001: {batch.status} | \"\n f\"\u5b8c\u6210: {batch.request_counts.completed}\/{batch.request_counts.total}\")\n if batch.status in (\"completed\", \"failed\", \"expired\"):\n break\n time.sleep(30)\n\n if batch.status != \"completed\":\n raise RuntimeError(f\"\u4efb\u52a1\u672a\u6210\u529f\u5b8c\u6210: {batch.status}\")\n\n # Step 4: \u4e0b\u8f7d\u7ed3\u679c\n output_file = client.files.content(batch.output_file_id)\n content = output_file.read().decode(\"utf-8\")\n\n # Step 5: \u89e3\u6790\u5e76\u4fdd\u5b58 CSV\n results = [json.loads(line) for line in content.strip().split(\"\\n\") if line.strip()]\n\n with open(output_csv, \"w\", newline=\"\", encoding=\"utf-8-sig\") as f:\n writer = csv.writer(f)\n writer.writerow([\"id\", \"prompt\", \"output\", \"error\"])\n for r in results:\n cid = r.get(\"custom_id\", \"\")\n error = r.get(\"error\", \"\")\n output = \"\"\n if not error:\n try:\n output = r[\"response\"][\"body\"][\"choices\"][0][\"message\"][\"content\"]\n except (KeyError, IndexError):\n output = \"[\u89e3\u6790\u5931\u8d25]\"\n writer.writerow([cid, \"\", output, error or \"\"])\n\n print(f\"\u2705 \u7ed3\u679c\u5df2\u4fdd\u5b58: {output_csv}\")\n print(f\"\ud83d\udcca \u603b\u8ba1: {len(results)} \u6761 | \"\n f\"\u6210\u529f: {sum(1 for r in results if not r.get('error'))} | \"\n f\"\u5931\u8d25: {sum(1 for r in results if r.get('error'))}\")\n\n\n# \u8fd0\u884c\nif __name__ == \"__main__\":\n test_data = [\n {\"id\": \"test-001\", \"prompt\": \"\u7528\u4e00\u53e5\u8bdd\u603b\u7ed3\u4eba\u5de5\u667a\u80fd\u7684\u53d1\u5c55\u8d8b\u52bf\"},\n {\"id\": \"test-002\", \"prompt\": \"\u5c06'Hello World'\u7ffb\u8bd1\u4e3a\u4e2d\u6587\"},\n ]\n run_batch_pipeline(test_data, \"batch_results.csv\")\n<\/pre>\n\n<div class=\"info-box\">\n <strong>\u5168\u6d41\u7a0b\u603b\u7ed3\uff1a\u7406\u89e3\u6279\u91cf\u63a8\u7406\u7684\u5f02\u6b65\u79bb\u7ebf\u7279\u5f81 \u2192 \u533a\u5206\u6279\u91cf\u4e0e\u5b9e\u65f6\u7684\u9002\u7528\u573a\u666f \u2192 \u6309 JSONL \u89c4\u8303\u51c6\u5907\u6570\u636e \u2192 \u901a\u8fc7 OpenAI \u517c\u5bb9\u63a5\u53e3\u63d0\u4ea4\u4efb\u52a1 \u2192 \u8f6e\u8be2\u76d1\u63a7\u4efb\u52a1\u72b6\u6001 \u2192 \u4e0b\u8f7d\u5e76\u89e3\u6790\u7ed3\u679c\u6587\u4ef6 \u2192 \u5931\u8d25\u8bf7\u6c42\u5355\u72ec\u91cd\u8bd5 \u2192 \u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u548c\u53c2\u6570\u63a7\u5236\u6210\u672c\u3002\u6279\u91cf\u63a8\u7406\u662f\u5927\u89c4\u6a21 AI \u5904\u7406\u7684\u964d\u672c\u5229\u5668\u3002<\/strong>\n<\/div>\n\n<\/div>\n\n\n<div class=\"lang-section\" id=\"lang-en\">\n<div class=\"hero\">\n <h1>Batch Inference Complete Guide<span class=\"sub\">Concept \u2192 Practice \u2192 Alibaba Cloud Bailian BatchAPI<\/span><\/h1>\n <p>Batch vs online inference, use cases, JSONL data prep, job submission & monitoring, result retrieval, cost optimization, troubleshooting<\/p>\n<\/div>\n\n<div class=\"toc\">\n <h3>Table of Contents<\/h3>\n <ol>\n <li><a href=\"#en-1\">1 What is Batch Inference<\/a><\/li>\n <li><a href=\"#en-2\">2 Batch vs Online Inference<\/a><\/li>\n <li><a href=\"#en-3\">3 Use Cases & Value<\/a><\/li>\n <li><a href=\"#en-4\">4 Alibaba Cloud Bailian BatchAPI<\/a><\/li>\n <li><a href=\"#en-5\">5 JSONL Data Preparation<\/a><\/li>\n <li><a href=\"#en-6\">6 Submitting Batch Jobs<\/a><\/li>\n <li><a href=\"#en-7\">7 Job Monitoring<\/a><\/li>\n <li><a href=\"#en-8\">8 Result Retrieval<\/a><\/li>\n <li><a href=\"#en-9\">9 Cost Optimization<\/a><\/li>\n <li><a href=\"#en-10\">10 FAQ & Troubleshooting<\/a><\/li>\n <\/ol>\n<\/div>\n\n<h2 id=\"en-1\">1 What is Batch Inference<\/h2>\n\n<p>Batch Inference aggregates large numbers of independent inference requests into a single batch, submitted to the model for background offline processing with asynchronous result delivery.<\/p>\n\n<div class=\"card\">\n <h4>Four Key Characteristics<\/h4>\n <p><span class=\"tag tag-b\">Asynchronous<\/span> Submit and return immediately, process in background queue<\/p>\n <p><span class=\"tag tag-g\">High Throughput<\/span> Fully utilize GPU parallel computing<\/p>\n <p><span class=\"tag tag-y\">Low Cost<\/span> Alibaba Cloud BatchAPI costs ~50% of real-time calls<\/p>\n <p><span class=\"tag tag-p\">Offline<\/span> Doesn't consume real-time service resources<\/p>\n<\/div>\n\n<h2 id=\"en-2\">2 Batch vs Online Inference<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead><tr><th>Dimension<\/th><th>Batch<\/th><th>Online<\/th><\/tr><\/thead>\n <tbody>\n <tr><td>Response<\/td><td>Async, background<\/td><td>Sync, immediate<\/td><\/tr>\n <tr><td>Latency<\/td><td>Minutes to hours OK<\/td><td>Milliseconds to seconds<\/td><\/tr>\n <tr><td>Cost<\/td><td>~50% of real-time<\/td><td>Full real-time pricing<\/td><\/tr>\n <tr><td>Scale<\/td><td>Thousands to millions<\/td><td>Single or small batches<\/td><\/tr>\n <tr><td>Use Case<\/td><td>Data analysis, generation<\/td><td>Chat, recommendation<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h2 id=\"en-3\">3 Use Cases & Value<\/h2>\n\n<div class=\"cmd-grid\">\n <div class=\"cmd-card\">\n <h4>Data Analysis<\/h4>\n <div class=\"desc\">Sentiment analysis, topic classification, entity extraction on massive review\/feedback datasets.<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>Content Generation<\/h4>\n <div class=\"desc\">Batch generate product descriptions, marketing copy, translations at scale.<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>Model Evaluation<\/h4>\n <div class=\"desc\">Run benchmark tests to get accuracy, F1 scores across standard test sets.<\/div>\n <\/div>\n <div class=\"cmd-card\">\n <h4>Data Labeling<\/h4>\n <div class=\"desc\">Use model for pre-labeling, human review correction, reduce costs 70%+.<\/div>\n <\/div>\n<\/div>\n\n<h2 id=\"en-4\">4 Alibaba Cloud Bailian BatchAPI<\/h2>\n\n<div class=\"card\">\n <h4>Bailian BatchAPI Capabilities<\/h4>\n <p><span class=\"tag tag-b\">File Upload<\/span> JSONL format, one request per line<\/p>\n <p><span class=\"tag tag-g\">Model Support<\/span> Qwen, Llama, DeepSeek and more<\/p>\n <p><span class=\"tag tag-y\">Cost Savings<\/span> ~50% of real-time API pricing<\/p>\n <p><span class=\"tag tag-p\">Status Tracking<\/span> Full lifecycle: created \u2192 queued \u2192 running \u2192 completed<\/p>\n <p><span class=\"tag tag-r\">Persistent Results<\/span> Output files saved after completion<\/p>\n<\/div>\n\n<h3>Prerequisites<\/h3>\n<ol class=\"steps\">\n <li>Alibaba Cloud account with real-name verification<\/li>\n <li>Activate Bailian (Model Studio) service<\/li>\n <li>Get API-Key from Bailian Console<\/li>\n <li>Install SDK: <span class=\"cmd\">pip install openai<\/span><\/li>\n<\/ol>\n\n<h2 id=\"en-5\">5 JSONL Data Preparation<\/h2>\n\n<pre class=\"code-block\">{\"custom_id\": \"req-001\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"Summarize AI trends\"}]}}\n{\"custom_id\": \"req-002\", \"method\": \"POST\", \"url\": \"\/v1\/chat\/completions\", \"body\": {\"model\": \"qwen-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"Translate to Chinese\"}]}}\n<\/pre>\n\n<div class=\"table-wrap\">\n<table>\n <thead><tr><th>Field<\/th><th>Type<\/th><th>Required<\/th><th>Description<\/th><\/tr><\/thead>\n <tbody>\n <tr><td>custom_id<\/td><td>string<\/td><td>Yes<\/td><td>Custom request identifier<\/td><\/tr>\n <tr><td>method<\/td><td>string<\/td><td>Yes<\/td><td>HTTP method, always \"POST\"<\/td><\/tr>\n <tr><td>url<\/td><td>string<\/td><td>Yes<\/td><td>API path<\/td><\/tr>\n <tr><td>body<\/td><td>object<\/td><td>Yes<\/td><td>Request body, same as real-time API<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<h2 id=\"en-6\">6 Submitting Batch Jobs<\/h2>\n\n<pre class=\"code-block\">import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n api_key=os.getenv(\"DASHSCOPE_API_KEY\"),\n base_url=\"https:\/\/dashscope.aliyuncs.com\/compatible-mode\/v1\"\n)\n\n# Upload file\nwith open(\"batch_input.jsonl\", \"rb\") as f:\n file_obj = client.files.create(file=f, purpose=\"batch\")\n\n# Create batch job\nbatch = client.batches.create(\n input_file_id=file_obj.id,\n endpoint=\"\/v1\/chat\/completions\",\n completion_window=\"24h\"\n)\nprint(f\"Job created: {batch.id}\")\n<\/pre>\n\n<h2 id=\"en-7\">7 Job Monitoring<\/h2>\n\n<h3>Status Flow<\/h3>\n<div class=\"flow-diagram\">\n <div class=\"flow-row\">\n <span class=\"flow-item\">validating<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item yellow\">in_progress<\/span>\n <span class=\"flow-arrow\">→<\/span>\n <span class=\"flow-item green\">completed<\/span>\n <\/div>\n <div class=\"flow-row\" style=\"margin-top:.5rem\">\n <span class=\"flow-item red\">failed<\/span>\n <span class=\"flow-item red\">expired<\/span>\n <span class=\"flow-item red\">cancelled<\/span>\n <\/div>\n<\/div>\n\n<pre class=\"code-block\">def wait_for_completion(batch_id: str, poll_interval: int = 30):\n while True:\n batch = client.batches.retrieve(batch_id)\n print(f\"Status: {batch.status} | \"\n f\"Done: {batch.request_counts.completed}\/{batch.request_counts.total}\")\n if batch.status in (\"completed\", \"failed\", \"expired\"):\n return batch\n time.sleep(poll_interval)\n<\/pre>\n\n<h2 id=\"en-8\">8 Result Retrieval<\/h2>\n\n<pre class=\"code-block\">batch = client.batches.retrieve(batch_id)\noutput_file = client.files.content(batch.output_file_id)\ncontent = output_file.read().decode(\"utf-8\")\n\nresults = []\nfor line in content.strip().split(\"\\n\"):\n obj = json.loads(line)\n results.append({\n \"custom_id\": obj[\"custom_id\"],\n \"response\": obj.get(\"response\", {}),\n \"error\": obj.get(\"error\")\n })\n<\/pre>\n\n<h2 id=\"en-9\">9 Cost Optimization<\/h2>\n\n<div class=\"card\">\n <h4>Five Cost Reduction Strategies<\/h4>\n <p>1. <span class=\"tag tag-g\">Batch over online<\/span> Use BatchAPI for non-urgent tasks (~50% savings)<\/p>\n <p>2. <span class=\"tag tag-b\">Right-size model<\/span> Use qwen-turbo for simple tasks<\/p>\n <p>3. <span class=\"tag tag-y\">Limit max_tokens<\/span> Set reasonable output length caps<\/p>\n <p>4. <span class=\"tag tag-p\">Merge requests<\/span> Group similar prompts to reduce overhead<\/p>\n <p>5. <span class=\"tag tag-r\">Retry failures only<\/span> Don't resubmit entire batch<\/p>\n<\/div>\n\n<h2 id=\"en-10\">10 FAQ & Troubleshooting<\/h2>\n\n<div class=\"table-wrap\">\n<table>\n <thead><tr><th>Issue<\/th><th>Solution<\/th><\/tr><\/thead>\n <tbody>\n <tr><td>Upload fails<\/td><td>Validate JSONL format, check file size < 100MB, ensure UTF-8<\/td><\/tr>\n <tr><td>Stuck validating<\/td><td>Wait normally; contact support if > 30 min<\/td><\/tr>\n <tr><td>Partial failures<\/td><td>Check error field in results, retry failed items only<\/td><\/tr>\n <tr><td>Job failed<\/td><td>Verify API-Key permissions, model availability, JSONL format<\/td><\/tr>\n <tr><td>Long queue time<\/td><td>Avoid peak hours (10am-12pm), submit during off-hours<\/td><\/tr>\n <tr><td>Result expired<\/td><td>Download within 7 days; set up auto-download script<\/td><\/tr>\n <tr><td>Unexpected token usage<\/td><td>Optimize prompt length, set max_tokens limit<\/td><\/tr>\n <\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"info-box\">\n <strong>Summary: Understand async offline nature of batch inference \u2192 Distinguish batch vs online use cases \u2192 Prepare data in JSONL format \u2192 Submit via OpenAI-compatible API \u2192 Poll for completion \u2192 Download and parse results \u2192 Retry failed requests separately \u2192 Choose right model and parameters to control costs. Batch inference is a powerful cost-saving tool for large-scale AI processing.<\/strong>\n<\/div>\n\n<\/div>\n<\/main>\n\n<footer>\n <div class=\"links\">\n <a href=\"https:\/\/help.aliyun.com\/zh\/model-studio\/getting-started\/what-is-model-studio\" target=\"_blank\" rel=\"noopener\">Alibaba Cloud Bailian<\/a>\n <a href=\"https:\/\/www.alibabacloud.com\/help\/en\/model-studio\/developer-reference\/use-bailian-api\" target=\"_blank\" rel=\"noopener\">Bailian API Docs<\/a>\n <a href=\"https:\/\/platform.openai.com\/docs\/guides\/batch\" target=\"_blank\" rel=\"noopener\">OpenAI Batch API<\/a>\n <\/div>\n <p>Batch Inference Complete Guide<\/p>\n<\/footer>\n\n<script>\nfunction setLang(lang){\n document.querySelectorAll('.lang-section').forEach(el=>el.classList.remove('active'));\n document.getElementById('lang-'+lang).classList.add('active');\n document.querySelectorAll('.lang-switch button').forEach(btn=>btn.classList.remove('active'));\n document.getElementById('btn-'+lang).classList.add('active');\n document.documentElement.lang = lang==='zh'?'zh-CN':'en';\n const prefix = lang==='zh'?'zh':'en';\n const newHash = window.location.hash.replace(\/^#(zh|en)-\/, prefix+\"-\");\n if(newHash) window.location.hash = newHash;\n}\nfunction toggleTheme(){\n const html = document.documentElement;\n if(html.hasAttribute('data-theme')){\n html.removeAttribute('data-theme');\n localStorage.removeItem('theme');\n }else{\n html.setAttribute('data-theme','dark');\n localStorage.setItem('theme','dark');\n }\n}\n(function(){\n if(localStorage.getItem('theme')==='dark') document.documentElement.setAttribute('data-theme','dark');\n const hash = window.location.hash;\n if(hash){\n const target = document.querySelector(hash);\n if(target) setTimeout(()=>target.scrollIntoView({behavior:'smooth'}),100);\n }\n})();\n<\/script>\n<\/body>\n<\/html>\n","protected":false},"excerpt":{"rendered":"<p>\u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307\u5357 \u00b7 Batch Inference Complete Guide \ud83d\ude80 \u6279\u91cf\u63a8\u7406\u4efb\u52a1\u5b8c\u6574\u6307 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,9],"tags":[],"class_list":["post-363","post","type-post","status-publish","format-standard","hentry","category-cad","category-ai"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts\/363","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=363"}],"version-history":[{"count":1,"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts\/363\/revisions"}],"predecessor-version":[{"id":364,"href":"https:\/\/numsimlab.com\/index.php?rest_route=\/wp\/v2\/posts\/363\/revisions\/364"}],"wp:attachment":[{"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=363"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=363"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/numsimlab.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=363"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}