{"id":123300,"date":"2026-11-07T01:17:02","date_gmt":"2026-11-06T17:17:02","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/123300.html"},"modified":"2026-11-07T01:17:02","modified_gmt":"2026-11-06T17:17:02","slug":"sa-k-05-%e7%9f%a5%e8%af%86%e4%b8%8e%e6%a3%80%e7%b4%a2%e5%b7%a5%e7%a8%8b-%e6%b7%b7%e5%90%88%e6%a3%80%e7%b4%a2%e4%b8%8e%e9%87%8d%e6%8e%92","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/123300.html","title":{"rendered":"SA-K-05 \u77e5\u8bc6\u4e0e\u68c0\u7d22\u5de5\u7a0b \u6df7\u5408\u68c0\u7d22\u4e0e\u91cd\u6392"},"content":{"rendered":"

\u6df7\u5408\u68c0\u7d22\u4e0e\u91cd\u6392\u503c\u4e0d\u503c\u90a3 200ms：\u4e09\u8def\u5408\u6d41\u7684\u6f0f\u53ec\u8bca\u65ad\u4e0e\u878d\u5408\u5b9e\u73b0<\/h2>\n

\u7cfb\u5217\u5bfc\u822a：00 \u7cfb\u5217\u5bfc\u822a \u00b7 01 \u56db\u7c7b\u77e5\u8bc6 \u00b7 02A \u89e3\u6790\u4e94\u73af \u00b7 02B \u65ad\u88c2\u4fee\u590d \u00b7 03 \u5207\u5206\u6807\u5b9a \u00b7 04 \u67e5\u8be2\u7406\u89e3 \u00b7 \u672c\u7bc7（05） \u00b7 06 \u5f15\u7528\u9a8c\u8bc1 \u00b7 07 \u77e5\u8bc6\u65b0\u9c9c\u5ea6 \u00b7 08 \u591a\u6e90\u4e00\u81f4\u6027 \u00b7 09 \u7ba1\u9053\u95e8\u7981 \u00b7 10 \u5168\u7c07\u603b\u7ed3 \u00b7 11 \u5c55\u671b<\/p>\n

\u5c0f\u63d0\u4e00\u53e5： \u7531\u4e8e\u5e73\u53f0\u6bcf\u65e5\u53d1\u5e03\u7b14\u8bb0\u6570\u91cf\u9650\u5236，\u76ee\u524d\u7cfb\u5217\u7b14\u8bb0\u8fd8\u6ca1\u5168\u90e8\u4e0a\u4f20\u3002\u540e\u7eed\u5185\u5bb9\u4f1a\u6301\u7eed\u66f4\u65b0，\u5927\u5bb6\u53ef\u4ee5\u5148\u70b9\u4e2a\u5173\u6ce8\u3001\u6536\u85cf，\u4ee5\u514d\u9519\u8fc7\u3002 \u8c22\u8c22！<\/p>\n

\n

\u5f15\u5b50：\u4e24\u5904\u6539\u52a8，\u4e00\u79cd\u8bf4\u6cd5，\u4e70\u56de\u6765\u7684\u4e0d\u662f\u540c\u4e00\u79cd\u4e1c\u897f<\/h3>\n

\u4e00\u6b21\u5178\u578b\u8c03\u53c2：\u503c\u73ed\u4eba\u5458\u62b1\u6028\u300c\u7b54\u6848\u8001\u62c9\u4e0d\u5230\u5bf9\u7684 runbook\u300d，\u7b2c\u4e00\u53cd\u5e94\u662f\u63a5\u4e00\u4e2a cross-encoder \u91cd\u6392\u3002\u4e0a\u7ebf\u540e P95 \u4ece 1.2s \u62ac\u5230 1.4s，\u4e0b\u6e38\u51c6\u786e\u7387\u6da8\u4e86 1.3pp [\u7b97]\u3002\u4e24\u5468\u540e\u53e6\u4e00\u62e8\u4eba\u52a0\u4e86\u4e00\u884c\u4e0d\u8d77\u773c\u7684\u903b\u8f91：\u628a\u67e5\u8be2\u91cc\u7684 runbook \u7f16\u53f7\u62bd\u51fa\u6765\u505a\u7cbe\u786e\u5339\u914d\u3002P95 \u51e0\u4e4e\u6ca1\u52a8，\u540c\u6279\u8bc4\u6d4b\u91cc\u300c\u5e94\u547d\u4e2d\u7684\u7247\u6bb5\u538b\u6839\u6ca1\u8fdb\u5019\u9009\u96c6\u300d\u7684\u6bd4\u4f8b\u4ece 11% \u6389\u5230 4%\u3002<\/p>\n

\u4e24\u6b21\u6539\u52a8\u90fd\u6302\u5728\u300c\u4f18\u5316\u68c0\u7d22\u300d\u540d\u4e0b，\u4e70\u7684\u5374\u4e0d\u662f\u540c\u4e00\u79cd\u4e1c\u897f：\u4e00\u6b21\u4e70\u7684\u662f\u6392\u5f97\u66f4\u51c6，\u4e00\u6b21\u4e70\u7684\u662f\u4e0d\u518d\u4e22\u3002\u4e22\u6389\u7684（top-50 \u91cc\u6839\u672c\u6ca1\u6709 gold）\u548c\u6392\u9519\u7684（top-50 \u91cc\u6709 gold \u4f46\u6392\u5728\u7b2c 12）\u4f4d\u7f6e\u4e0d\u540c，\u80fd\u4fee\u7684\u624b\u6bb5\u4e5f\u4e0d\u540c，\u4ee3\u4ef7\u5dee\u4e00\u4e2a\u91cf\u7ea7\u3002\u6df7\u4e3a\u4e00\u8c08，\u5f88\u5bb9\u6613\u628a\u91cd\u6392\u5f53\u6210\u4e07\u80fd\u8865\u4e01，\u4e3a\u4e00\u4e2a\u81ea\u5df1\u90fd\u6ca1\u6709\u7684\u95ee\u9898\u4ed8\u4e09\u500d\u5ef6\u8fdf\u3002<\/p>\n

\u672c\u6587\u53ea\u56de\u7b54\u4e00\u4e2a\u95ee\u9898：\u540c\u6837\u53eb\u300c\u4f18\u5316\u68c0\u7d22\u300d，\u4e3a\u4ec0\u4e48\u52a0\u4e00\u884c\u7cbe\u786e\u5339\u914d\u51e0\u4e4e\u4e0d\u82b1\u5ef6\u8fdf\u3001\u4e0a\u91cd\u6392\u5374\u8d35\u4e09\u500d，\u5230\u5e95\u8be5\u5148\u505a\u54ea\u4e2a？ \u7b54\u6848\u662f\u5148\u7ed9\u7eaf\u5411\u91cf\u6f0f\u53ec\u7684\u5f52\u56e0\u65b9\u6cd5\u3001\u4e09\u8def\u5408\u6d41\u7684\u53ef\u8fd0\u884c\u5185\u6838，\u518d\u7ed9\u300c\u8981\u4e0d\u8981\u4e0a\u91cd\u6392\u300d\u7684\u5224\u636e\u3002\u4e0d\u8bb2 ANN \u7d22\u5f15\u539f\u7406（HNSW \/ IVF \u53ea\u7ed9\u540d\u8bcd\u7ea7\u89e3\u91ca\u5e76\u6307\u5411\u8d44\u6599），\u4e0d\u505a embedding \u9009\u578b，\u4e0d\u5199\u6846\u67b6 API \u7528\u6cd5\u3002<\/p>\n

#mermaid-svg-IgWB7pZdSPthfSrO{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-IgWB7pZdSPthfSrO .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-IgWB7pZdSPthfSrO .error-icon{fill:#552222;}#mermaid-svg-IgWB7pZdSPthfSrO .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-IgWB7pZdSPthfSrO .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-IgWB7pZdSPthfSrO .marker{fill:#333333;stroke:#333333;}#mermaid-svg-IgWB7pZdSPthfSrO .marker.cross{stroke:#333333;}#mermaid-svg-IgWB7pZdSPthfSrO svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-IgWB7pZdSPthfSrO p{margin:0;}#mermaid-svg-IgWB7pZdSPthfSrO .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-IgWB7pZdSPthfSrO .cluster-label text{fill:#333;}#mermaid-svg-IgWB7pZdSPthfSrO .cluster-label span{color:#333;}#mermaid-svg-IgWB7pZdSPthfSrO .cluster-label span p{background-color:transparent;}#mermaid-svg-IgWB7pZdSPthfSrO .label text,#mermaid-svg-IgWB7pZdSPthfSrO span{fill:#333;color:#333;}#mermaid-svg-IgWB7pZdSPthfSrO .node rect,#mermaid-svg-IgWB7pZdSPthfSrO .node circle,#mermaid-svg-IgWB7pZdSPthfSrO .node ellipse,#mermaid-svg-IgWB7pZdSPthfSrO .node polygon,#mermaid-svg-IgWB7pZdSPthfSrO .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-IgWB7pZdSPthfSrO .rough-node .label text,#mermaid-svg-IgWB7pZdSPthfSrO .node .label text,#mermaid-svg-IgWB7pZdSPthfSrO .image-shape .label,#mermaid-svg-IgWB7pZdSPthfSrO .icon-shape .label{text-anchor:middle;}#mermaid-svg-IgWB7pZdSPthfSrO .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-IgWB7pZdSPthfSrO .rough-node .label,#mermaid-svg-IgWB7pZdSPthfSrO .node .label,#mermaid-svg-IgWB7pZdSPthfSrO .image-shape .label,#mermaid-svg-IgWB7pZdSPthfSrO .icon-shape .label{text-align:center;}#mermaid-svg-IgWB7pZdSPthfSrO .node.clickable{cursor:pointer;}#mermaid-svg-IgWB7pZdSPthfSrO .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-IgWB7pZdSPthfSrO .arrowheadPath{fill:#333333;}#mermaid-svg-IgWB7pZdSPthfSrO .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-IgWB7pZdSPthfSrO .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-IgWB7pZdSPthfSrO .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-IgWB7pZdSPthfSrO .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-IgWB7pZdSPthfSrO .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-IgWB7pZdSPthfSrO .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-IgWB7pZdSPthfSrO .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-IgWB7pZdSPthfSrO .cluster text{fill:#333;}#mermaid-svg-IgWB7pZdSPthfSrO .cluster span{color:#333;}#mermaid-svg-IgWB7pZdSPthfSrO div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-IgWB7pZdSPthfSrO .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-IgWB7pZdSPthfSrO rect.text{fill:none;stroke-width:0;}#mermaid-svg-IgWB7pZdSPthfSrO .icon-shape,#mermaid-svg-IgWB7pZdSPthfSrO .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-IgWB7pZdSPthfSrO .icon-shape p,#mermaid-svg-IgWB7pZdSPthfSrO .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-IgWB7pZdSPthfSrO .icon-shape .label rect,#mermaid-svg-IgWB7pZdSPthfSrO .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-IgWB7pZdSPthfSrO .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-IgWB7pZdSPthfSrO .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-IgWB7pZdSPthfSrO :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

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\u5426<\/p>\n

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\u662f<\/p>\n

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\u503c\u73ed\u53e3\u8bed\u67e5\u8be2<\/p>\n

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\u67e5\u8be2\u7ed3\u6784\u5316\u610f\u56fe+\u7ea6\u675f+\u5b9e\u4f53<\/p>\n

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\u5411\u91cf\u8def\u76f8\u4f3c\u5ea6<\/p>\n

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\u7a00\u758f\u8defBM25 \u5012\u6392<\/p>\n

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\u7b26\u53f7\u8defID \u4e0e\u5143\u6570\u636e<\/p>\n

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\u878d\u5408\u5c42RRF \u6216\u52a0\u6743<\/p>\n

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\u7b26\u53f7\u4fdd\u5e95\u5fc5\u987b\u8fdb\u5019\u9009\u96c6<\/p>\n

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\u91cd\u6392\u95f8\u95e8\u770b\u5019\u9009\u8d28\u91cf<\/p>\n

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\u76f4\u63a5\u53d6 top-k<\/p>\n

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cross-encoder\u6216 LLM \u91cd\u6392<\/p>\n

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\u6700\u7ec8\u4e0a\u4e0b\u6587<\/p>\n

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\n

\u4e00\u3001\u7eaf\u5411\u91cf\u6f0f\u6389\u7684\u662f\u54ea\u4e09\u7c7b，\u5404\u81ea\u9760\u4ec0\u4e48\u515c\u4f4f？<\/h3>\n

\u5148\u628a\u540d\u8bcd\u6446\u6e05\u695a，\u540e\u9762\u4e0d\u518d\u56de\u5934\u89e3\u91ca：<\/p>\n\n\u540d\u8bcd\u4e00\u53e5\u8bdd\u539f\u7406\u77e5\u8bc6\u7ed3\u6784\u5b9a\u4f4d\u672c\u6587\u8026\u5408\u70b9<\/tr>\n\n\n\n\n
BM25<\/td>\n\u8bcd\u9891 \u00d7 \u9006\u6587\u6863\u9891\u7387 \u00d7 \u957f\u5ea6\u60e9\u7f5a\u7684\u7a00\u758f\u6392\u5e8f\u51fd\u6570，\u53ea\u8ba4\u5b57\u9762\u547d\u4e2d<\/td>\n\u4e0a\u4f4d：\u7a00\u758f\u68c0\u7d22；\u4e0b\u4f4d：Okapi BM25<\/td>\n\u515c\u4f4f\u7f55\u89c1\u672f\u8bed\u4e0e\u7cbe\u786e\u4e32；k1=1.2\u3001b=0.75 [\u516c\u5f00]<\/td>\n<\/tr>\n
cross-encoder<\/td>\n\u67e5\u8be2\u4e0e\u6587\u6863\u62fc\u6210\u4e00\u4e2a\u5e8f\u5217\u8fc7 Transformer，\u76f4\u63a5\u8f93\u51fa\u76f8\u5173\u5206<\/td>\n\u4e0a\u4f4d：\u91cd\u6392；\u4e0b\u4f4d：ColBERT \u591a\u5411\u91cf<\/td>\n\u6bcf\u5bf9\u5019\u9009\u4e00\u6b21\u524d\u5411，\u5ef6\u8fdf\u968f\u6df1\u5ea6\u7ebf\u6027\u589e\u957f<\/td>\n<\/tr>\n
RRF<\/td>\n\u53ea\u53d6\u5404\u8def\u540d\u6b21\u7684\u5012\u6570\u548c\u4f5c\u4e3a\u878d\u5408\u5206，\u4e0d\u770b\u539f\u59cb\u5206\u6570<\/td>\n\u4e0a\u4f4d：\u7ed3\u679c\u878d\u5408；\u540c\u65cf：CombMNZ<\/td>\nk=60；\u5bf9\u91cf\u7eb2\u514d\u75ab，\u4f46\u5bf9\u300c\u591a\u8def\u5171\u8bc6\u300d\u76f2\u4fe1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e0d\u5728\u8868\u91cc\u7684\u540d\u8bcd\u987a\u5e26\u4ea4\u4ee3：\u76f8\u4f3c\u5ea6\u88ab L2 \u5f52\u4e00\u5316\u538b\u5728 \u22121~1，\u4e0e BM25 \u7684 0~30 \u4e0d\u540c\u91cf\u7eb2；\u5143\u6570\u636e\u8fc7\u6ee4\u7528\u7ed3\u6784\u5316\u5b57\u6bb5\u7f29\u5c0f\u5019\u9009\u96c6，\u6761\u4ef6\u53ea\u80fd\u6765\u81ea\u67e5\u8be2\u7ed3\u6784；bi-encoder \u4e0e\u53ec\u56de\u540c\u6e90\u540c\u7c92\u5ea6\u65f6\u51e0\u4e4e\u6ca1\u6709\u589e\u76ca（\u7b2c\u4e94\u8282\u53cd\u4f8b）；ANN \u672c\u7bc7\u53ea\u5047\u8bbe\u300c\u5411\u91cf\u8def\u80fd\u7ed9\u51fa top-N\u300d\u3002<\/p>\n

\u67e5\u8be2\u7ed3\u6784\u5316\u4ea7\u7269\u5c31\u662f 04 \u7bc7\u90a3\u4e00\u7bc7\u7684\u8f93\u51fa，\u672c\u7bc7\u628a\u5b83\u5f53\u6210\u5df2\u6807\u5b9a\u7684\u8f93\u5165：<\/p>\n

{<\/span>
\n "qid"<\/span>:<\/span> "ops-20261017-0031"<\/span>,<\/span>
\n "intent"<\/span>:<\/span> "\u5904\u7f6e\u52a8\u4f5c\u67e5\u8be2"<\/span>,<\/span>
\n "constraints"<\/span>:<\/span> {<\/span>"service"<\/span>:<\/span> "svc-order"<\/span>,<\/span> "severity"<\/span>:<\/span> "P1"<\/span>}<\/span>,<\/span>
\n "entities"<\/span>:<\/span> [<\/span>{<\/span>"type"<\/span>:<\/span> "runbook_id"<\/span>,<\/span> "value"<\/span>:<\/span> "RB-214"<\/span>,<\/span> "hard"<\/span>:<\/span> true<\/span>}<\/span>,<\/span>
\n {<\/span>"type"<\/span>:<\/span> "symptom"<\/span>,<\/span> "value"<\/span>:<\/span> "\u78c1\u76d8\u544a\u8b66"<\/span>,<\/span> "hard"<\/span>:<\/span> false<\/span>}<\/span>]<\/span>,<\/span>
\n "alias"<\/span>:<\/span> {<\/span>"\u78c1\u76d8\u544a\u8b66"<\/span>:<\/span> "DISK_FULL"<\/span>}<\/span>
\n}<\/span><\/p>\n

hard \u8fd9\u4e2a\u5b57\u6bb5\u51b3\u5b9a\u5b83\u662f\u786c\u8fc7\u6ee4\u8fd8\u662f\u8f6f\u52a0\u5206，\u7b2c\u56db\u8282\u4f1a\u5c55\u5f00\u5b83\u4e3a\u4f55\u80fd\u51b3\u5b9a\u6574\u5957\u8fc7\u6ee4\u8bbe\u8ba1\u7684\u6210\u8d25\u3002<\/p>\n

\u7eaf\u5411\u91cf\u7684\u6f0f\u53ec，\u843d\u5230\u8fd9\u4e09\u7c7b：<\/p>\n\n\u6f0f\u53ec\u7c7b\u578b\u89e6\u53d1\u6761\u4ef6\u73b0\u573a\u8868\u73b0\u515c\u5e95\u624b\u6bb5<\/tr>\n\n\n\n\n
\u540c\u4e49\u6539\u5199<\/td>\n\u53e3\u8bed\u4e0e\u6587\u6863\u7528\u8bcd\u4e0d\u5171\u4eab\u8bcd\u9762，\u8bed\u4e49\u8ddd\u79bb\u88ab\u540c\u4e3b\u9898\u90bb\u8fd1\u6587\u6863\u62c9\u5e73<\/td>\ntop-k \u91cc\u5168\u662f\u540c\u9898\u6750\u7247\u6bb5，gold \u843d\u5728 k+1<\/td>\n\u522b\u540d\u8868（04 \u7684\u4ea7\u51fa）\u843d\u5230\u7b26\u53f7\u8def<\/td>\n<\/tr>\n
\u7cbe\u786e\u6807\u8bc6\u7b26<\/td>\n\u67e5\u8be2\u91cc\u51fa\u73b0 RB-214\u3001\u670d\u52a1\u540d\u8fd9\u7c7b\u5f3a\u7279\u5f81\u4e32<\/td>\n\u8bb2\u539f\u7406\u7684\u957f\u6bb5\u843d\u6392\u524d\u9762，\u5e26\u7f16\u53f7\u90a3\u6761\u88ab\u6324\u5230\u540e\u9762<\/td>\n\u6b63\u5219\u62bd\u51fa\u6807\u8bc6\u7b26，\u7b26\u53f7\u8def\u7cbe\u786e\u5339\u914d\u5e76\u63d0\u5230\u961f\u9996<\/td>\n<\/tr>\n
\u7f55\u89c1\u672f\u8bed<\/td>\n\u672f\u8bed\u53ea\u51fa\u73b0\u4e00\u4e24\u6b21，embedding \u5b66\u4e0d\u51fa\u7a33\u5b9a\u8868\u5f81<\/td>\n\u6392\u4e0a\u6765\u7684\u90fd\u662f\u5b57\u9762\u63a5\u8fd1\u4f46\u8bed\u4e49\u4e0d\u540c\u7684\u624b\u518c<\/td>\n\u6587\u6863\u9891\u7387 \u22642 \u5224\u4e3a\u7f55\u89c1\u8bcd，\u76f4\u63a5\u8fdb\u7b26\u53f7\u8def<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u8fd9\u4e09\u7c7b\u6709\u4e00\u4e2a\u5171\u540c\u70b9：\u90fd\u4e0d\u9760\u8bed\u4e49\u76f8\u4f3c\u5ea6\u80fd\u89e3\u51b3\u3002\u6240\u4ee5\u300c\u52a0\u91cd\u6392\u300d\u4e4b\u524d\u5148\u770b\u6f0f\u53ec\u5f52\u5c5e\u2014\u2014\u91cd\u6392\u53ea\u80fd\u5728\u5df2\u6709\u5019\u9009\u6c60\u91cc\u91cd\u6392，\u5bf9\u6ca1\u8fdb\u6c60\u5b50\u7684 gold \u6beb\u65e0\u4f5c\u7528\u300206 \u7bc7\u4f1a\u4ece\u300c\u5f15\u7528\u8be5\u600e\u4e48\u9a8c\u300d\u7684\u89d2\u5ea6\u518d\u7528\u8fd9\u5f20\u5206\u5de5\u8868\u3002<\/p>\n

\u4e00\u53e5\u8bdd\u5224\u65ad：\u6df7\u5408\u68c0\u7d22\u7684\u6536\u76ca，\u4e3b\u8981\u6765\u81ea\u7b26\u53f7\u4e0e\u7a00\u758f\u4e24\u8def\u628a\u6f0f\u53ec\u8865\u56de\u6765；\u878d\u5408\u6743\u91cd\u600e\u4e48\u8c03，\u5f71\u54cd\u8fdc\u5c0f\u4e8e\u300c\u8fc7\u6ee4\u6761\u4ef6\u9009\u5bf9\u6ca1\u6709\u300d\u3002<\/p>\n

\n

\u4e8c\u3001\u4e09\u8def\u5206\u6570\u600e\u4e48\u5408，\u4e3a\u4ec0\u4e48\u76f4\u63a5\u52a0\u6743\u7b49\u4e8e\u8ba9 BM25 \u72ec\u88c1？<\/h3>\n

\u5148\u770b\u4e00\u4e2a\u4e09\u884c\u7684\u7b97\u672f\u3002vec \u8def\u7ed9 gold \u7684\u76f8\u4f3c\u5ea6\u662f 0.82，bm25 \u8def\u7ed9\u540c\u4e00\u6761\u7684\u5206\u6570\u662f 12.4，\u6743\u91cd\u4e94\u4e94\u5f00：<\/p>\n

0.5 * 12.4 + 0.5 * 0.82 = 6.2 + 0.41 = 6.61
\nBM25 \u8d21\u732e\u5360\u6bd4 = 6.2 \/ 6.61 = 93.8% [\u7b97]<\/p>\n

\u540d\u4e49\u4e0a\u7684\u4e94\u4e94\u5f00，\u5b9e\u9645\u662f BM25 \u72ec\u88c1\u3002\u539f\u56e0\u4e0d\u662f\u6743\u91cd\u5199\u9519，\u800c\u662f\u4e24\u8def\u5206\u6570\u91cf\u7eb2\u4e0d\u53ef\u6bd4：\u76f8\u4f3c\u5ea6\u88ab L2 \u5f52\u4e00\u5316\u538b\u5728 \u22121~1，BM25 \u662f\u65e0\u4e0a\u754c\u7d2f\u52a0\u503c，\u957f\u6587\u6863\u4e0a\u8f7b\u6613\u8d85\u8fc7 30\u3002<\/p>\n

2.1 \u4e24\u79cd\u878d\u5408\u5f0f\u7684\u9002\u7528\u4e0e\u9677\u9631<\/h4>\n\n\u7ef4\u5ea6RRF\u5f52\u4e00\u5316\u540e\u52a0\u6743<\/tr>\n\n\n\n\n\n\n
\u662f\u5426\u9700\u8981\u6807\u5b9a<\/td>\n\u4e0d\u9700\u8981，\u53ea\u5403\u540d\u6b21<\/td>\n\u9700\u8981，\u4e14\u6807\u5b9a\u70b9\u4f1a\u6f02\u79fb<\/td>\n<\/tr>\n
\u5bf9\u91cf\u7eb2\u654f\u611f<\/td>\n\u4e0d\u654f\u611f<\/td>\n\u5f52\u4e00\u5316\u524d\u654f\u611f，\u4e4b\u540e\u53d6\u51b3\u4e8e\u6807\u5c3a\u600e\u4e48\u53d6<\/td>\n<\/tr>\n
\u5bf9\u5019\u9009\u96c6\u89c4\u6a21\u654f\u611f<\/td>\n\u5f31（\u540d\u6b21\u622a\u65ad\u5728 top-N \u5185）<\/td>\n\u5f3a，\u6700\u5927\u5206\u503c\u968f N \u53d8\u5316<\/td>\n<\/tr>\n
\u80fd\u5426\u8868\u8fbe\u300c\u54ea\u4e00\u8def\u66f4\u53ef\u4fe1\u300d<\/td>\n\u53ea\u80fd\u9760 \u03b1 \u52a0\u6743，\u7c92\u5ea6\u7c97<\/td>\n\u53ef\u4ee5\u76f4\u63a5\u7ed9\u4e0d\u540c\u6743\u91cd<\/td>\n<\/tr>\n
\u4ec0\u4e48\u65f6\u5019\u5931\u6548<\/td>\n\u591a\u8def\u90fd\u4e0d\u76f8\u5173\u65f6\u4ecd\u7ed9\u300c\u591a\u8def\u5171\u8bc6\u300d\u6700\u9ad8\u5206<\/td>\n\u6807\u5c3a\u53d6\u672c\u6b21\u67e5\u8be2\u6700\u5927\u503c，\u628a\u7b2c\u4e00\u540d\u538b\u6210 1.0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u6211\u4eec\u7684\u5224\u65ad\u662f：\u9ed8\u8ba4\u7528 RRF，\u53ea\u6709\u5f53\u4f60\u660e\u786e\u77e5\u9053\u300c\u67d0\u4e00\u8def\u66f4\u53ef\u4fe1\u300d\u4e14\u6709\u80fd\u529b\u79bb\u7ebf\u6807\u5b9a（\u7b2c\u4e03\u8282\u7ed9\u6d41\u7a0b）\u65f6\u624d\u6362\u6210\u52a0\u6743\u3002 \u6807\u5b9a\u7684\u6027\u4ef7\u6bd4\u901a\u5e38\u88ab\u9ad8\u4f30\u2014\u2014\u6743\u91cd\u4ece 0.5\/0.5 \u632a\u5230 0.6\/0.4，\u5728 opsqa-200 \u4e0a\u7684\u5dee\u5f02\u843d\u5728 1pp \u5185 ，\u800c\u6761\u4ef6\u9009\u9519\u4e00\u4e2a，\u53ec\u56de\u7387\u80fd\u6389 5pp \u4ee5\u4e0a\u3002<\/p>\n

\u4e24\u5904\u6700\u5e38\u89c1\u7684\u5199\u6cd5\u5bf9\u7167：\u274c 0.5*bm25 + 0.5*cos \u76f4\u63a5\u76f8\u52a0 \u2192 \u2705 \u6539 RRF \u6216\u5148\u505a\u5206\u4f4d\u6570\u5f52\u4e00\u5316\u518d\u52a0\u6743；\u274c \u7528\u300c\u672c\u6b21\u67e5\u8be2\u8def\u5185\u6700\u9ad8\u5206\u300d\u5f53\u5206\u6bcd \u2192 \u2705 \u7528\u62bd\u6837\u5206\u4f4d\u6570\u505a\u6807\u5c3a\u3002\u53e6\u4e24\u6761\u5bb9\u6613\u6f0f：\u7b26\u53f7\u8def\u4e0d\u8d5b\u9a6c（\u5e03\u5c14\u7ea6\u675f\u4e0d\u662f\u76f8\u4f3c\u5ea6），\u591a\u8def\u90fd\u62ff\u4e0d\u5230\u8bc1\u636e\u65f6\u8981\u89e6\u53d1\u300c\u65e0\u8bc1\u636e\u300d\u5206\u652f\u4ea4\u7ed9 06 \u7bc7\u2014\u2014RRF \u4fdd\u8bc1\u7684\u662f\u5171\u8bc6，\u4e0d\u662f\u76f8\u5173\u3002<\/p>\n

Anthropic \u5728 Contextual Retrieval \u91cc\u7ed9\u4e86\u53ef\u5bf9\u7167\u6570\u636e：\u57fa\u7ebf top-20 \u68c0\u7d22\u5931\u8d25\u7387 5.7%，\u52a0 Contextual Embeddings \u964d\u5230 3.7%，\u518d\u53e0 Contextual BM25 \u964d\u5230 2.9%，\u52a0\u91cd\u6392\u964d\u5230 1.9%，\u8bc4\u6d4b\u57df\u662f\u4ee3\u7801\u5e93\u3001\u5c0f\u8bf4\u3001arXiv \u4e0e\u79d1\u5b66\u8bba\u6587\u56db\u7c7b，\u53d1\u5e03\u65e5 2024-09-19 [\u516c\u5f00]\u3002\u52a0\u4e00\u8def BM25 \u8d21\u732e 0.8pp，\u52a0\u91cd\u6392\u8d21\u732e 1.0pp\u2014\u2014\u7edd\u5bf9\u503c\u63a5\u8fd1，\u4f46\u52a0\u5012\u6392\u7684\u5ef6\u8fdf\u6210\u672c\u8fd1\u4e4e\u4e3a\u96f6，\u91cd\u6392\u5374\u8981\u5148\u628a\u5019\u9009\u6c60\u62c9\u5230 150 \u6761\u518d\u9010\u5bf9\u6253\u5206\u3002\u7edd\u5bf9\u503c\u63a5\u8fd1\u4e0d\u7b49\u4e8e\u6027\u4ef7\u6bd4\u63a5\u8fd1，\u7b2c\u4e94\u8282\u90a3\u5f20\u8868\u5c31\u662f\u8fd9\u4e48\u6765\u7684\u3002<\/p>\n

\n

\u4e09\u3001\u4e09\u8def\u53ec\u56de + \u878d\u5408\u7684\u5185\u6838\u600e\u4e48\u8dd1\u901a<\/h3>\n

3.1 \u8f93\u5165\u662f\u4ec0\u4e48，\u8f93\u51fa\u662f\u4ec0\u4e48，\u8dd1\u6b6a\u4e86\u5148\u770b\u54ea<\/h4>\n

\u8f93\u5165：\u6761\u76ee\u5217\u8868 (id, text, meta)（meta \u81f3\u5c11\u542b tag）\u3001\u4e00\u4e2a\u67e5\u8be2\u4e32\u3001\u4e00\u6761\u5df2\u77e5\u5e94\u547d\u4e2d\u7684 gold id\u3002\u5904\u7406：BM25 \u5efa\u5012\u6392\u3001Vec \u5efa\u5411\u91cf\u3001symbolic \u62bd\u7b26\u53f7\u8bc1\u636e，\u4e09\u8def\u53ec\u56de\u540e\u7ecf symbol_gate \u4fdd\u5e95\u3001\u878d\u5408\u3001rerank \u6392\u5e8f\u3002\u8f93\u51fa：\u6bcf\u8def\u662f\u5426\u547d\u4e2d gold \u53ca\u5176\u540d\u6b21（\u6f0f\u53ec\u8bca\u65ad）+ \u878d\u5408\u540e gold \u540d\u6b21 + \u6700\u7ec8 top-k\u3002\u9a8c\u8bc1：symbol \u547d\u4e2d\u800c vec \u672a\u547d\u4e2d，\u8bf4\u660e\u6f0f\u53ec\u5c5e\u4e8e\u7b2c\u4e00\u8282\u4e09\u7c7b\u4e4b\u4e00，\u8be5\u8865\u8bc1\u636e；\u4e09\u884c\u5168 False \u5219\u95ee\u9898\u5728 03 \u7bc7\u7684\u5207\u5206\u6216 02A \u7bc7\u7684\u89e3\u6790\u3002<\/p>\n

# hybrid_search.py \u2014\u2014 \u4e09\u8def\u53ec\u56de\u878d\u5408\u4e0e\u91cd\u6392\u95f8\u95e8\u5185\u6838（\u96f6\u4f9d\u8d56，\u4ec5\u6807\u51c6\u5e93）<\/span>
\nimport<\/span> math,<\/span> re,<\/span> zlib
\nfrom<\/span> collections import<\/span> Counter<\/p>\n

TOKEN =<\/span> re.<\/span>compile<\/span>(<\/span>r"[a-z0-9]+|[\\\\u4e00-\\\\u9fff]"<\/span>)<\/span>
\nIDPAT =<\/span> re.<\/span>compile<\/span>(<\/span>r"\\\\b[A-Z]{2,}[-_]?\\\\d{2,}\\\\b"<\/span>)<\/span>
\nK1,<\/span> B,<\/span> RRF_K =<\/span> 1.2<\/span>,<\/span> 0.75<\/span>,<\/span> 60<\/span><\/p>\n

def<\/span> tokenize<\/span>(<\/span>s)<\/span>:<\/span>
\n return<\/span> TOKEN.<\/span>findall(<\/span>s.<\/span>lower(<\/span>)<\/span>)<\/span><\/p>\n

# \u2500\u2500 \u9002\u914d\u53e3 1：\u7a20\u5bc6\u5411\u91cf\u3002\u63a5\u771f\u5b9e embedding \u65f6\u66ff\u6362\u8fd9\u4e00\u4e2a\u51fd\u6570 \u2500\u2500<\/span>
\ndef<\/span> embed<\/span>(<\/span>text)<\/span>:<\/span>
\n """\u5360\u4f4d\u5b9e\u73b0：\u90bb\u8fd1\u4e8c\u5b57\u6563\u5217\u5230 64 \u7ef4\u540e L2 \u5f52\u4e00\u5316，\u53ea\u6c42\u811a\u672c\u80fd\u72ec\u7acb\u8dd1\u901a\u3002"""<\/span>
\n v =<\/span> [<\/span>0.0<\/span>]<\/span> *<\/span> 64<\/span>
\n for<\/span> i in<\/span> range<\/span>(<\/span>len<\/span>(<\/span>text)<\/span> –<\/span> 1<\/span>)<\/span>:<\/span>
\n v[<\/span>zlib.<\/span>crc32(<\/span>text[<\/span>i:<\/span>i +<\/span> 2<\/span>]<\/span>.<\/span>encode(<\/span>"utf-8"<\/span>)<\/span>)<\/span> %<\/span> 64<\/span>]<\/span> +=<\/span> 1.0<\/span>
\n n =<\/span> math.<\/span>sqrt(<\/span>sum<\/span>(<\/span>x *<\/span> x for<\/span> x in<\/span> v)<\/span>)<\/span> or<\/span> 1.0<\/span>
\n return<\/span> [<\/span>x \/<\/span> n for<\/span> x in<\/span> v]<\/span><\/p>\n

def<\/span> cos<\/span>(<\/span>a,<\/span> b)<\/span>:<\/span>
\n return<\/span> sum<\/span>(<\/span>x *<\/span> y for<\/span> x,<\/span> y in<\/span> zip<\/span>(<\/span>a,<\/span> b)<\/span>)<\/span><\/p>\n

# \u522b\u540d\u8868：\u53e3\u8bed \u2192 \u6587\u6863\u5199\u6cd5\u3002\u8fd9\u662f 04 \u7bc7\u7684\u4ea7\u51fa，\u672c\u7bc7\u5f53\u5df2\u6807\u5b9a\u8f93\u5165<\/span>
\nALIAS =<\/span> {<\/span>"\u78c1\u76d8\u544a\u8b66"<\/span>:<\/span> "DISK_FULL"<\/span>,<\/span> "\u6269\u5bb9"<\/span>:<\/span> "SCALE_OUT"<\/span>,<\/span> "\u56de\u6eda"<\/span>:<\/span> "ROLLBACK"<\/span>}<\/span><\/p>\n

def<\/span> _top<\/span>(<\/span>sc,<\/span> k)<\/span>:<\/span>
\n return<\/span> sorted<\/span>(<\/span>sc.<\/span>items(<\/span>)<\/span>,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>x[<\/span>1<\/span>]<\/span>)<\/span>[<\/span>:<\/span>k]<\/span><\/p>\n

# \u2500\u2500 \u8def\u4e00：\u7a00\u758f\u5012\u6392（Okapi BM25） \u2500\u2500<\/span>
\nclass<\/span> BM25<\/span>:<\/span>
\n def<\/span> __init__<\/span>(<\/span>self,<\/span> docs)<\/span>:<\/span>
\n self.<\/span>docs,<\/span> self.<\/span>N =<\/span> docs,<\/span> len<\/span>(<\/span>docs)<\/span>
\n self.<\/span>tf,<\/span> self.<\/span>ln,<\/span> self.<\/span>df =<\/span> [<\/span>]<\/span>,<\/span> [<\/span>]<\/span>,<\/span> Counter(<\/span>)<\/span>
\n for<\/span> _,<\/span> text,<\/span> _ in<\/span> docs:<\/span>
\n c =<\/span> Counter(<\/span>tokenize(<\/span>text)<\/span>)<\/span>
\n self.<\/span>tf.<\/span>append(<\/span>c)<\/span>;<\/span> self.<\/span>ln.<\/span>append(<\/span>sum<\/span>(<\/span>c.<\/span>values(<\/span>)<\/span>)<\/span>)<\/span>
\n self.<\/span>df.<\/span>update(<\/span>c.<\/span>keys(<\/span>)<\/span>)<\/span>
\n self.<\/span>avg =<\/span> (<\/span>sum<\/span>(<\/span>self.<\/span>ln)<\/span> \/<\/span> self.<\/span>N)<\/span> or<\/span> 1.0<\/span>
\n self.<\/span>rare =<\/span> {<\/span>w for<\/span> w,<\/span> n in<\/span> self.<\/span>df.<\/span>items(<\/span>)<\/span> if<\/span> n <=<\/span> 2<\/span> and<\/span> len<\/span>(<\/span>w)<\/span> ><\/span> 1<\/span>}<\/span><\/p>\n

def<\/span> search<\/span>(<\/span>self,<\/span> q,<\/span> topk=<\/span>50<\/span>)<\/span>:<\/span>
\n out =<\/span> {<\/span>}<\/span>
\n for<\/span> i,<\/span> tf in<\/span> enumerate<\/span>(<\/span>self.<\/span>tf)<\/span>:<\/span>
\n s =<\/span> 0.0<\/span>
\n for<\/span> w in<\/span> tokenize(<\/span>q)<\/span>:<\/span>
\n f =<\/span> tf.<\/span>get(<\/span>w,<\/span> 0<\/span>)<\/span>
\n if<\/span> not<\/span> f:<\/span> continue<\/span>
\n idf =<\/span> math.<\/span>log(<\/span>1<\/span> +<\/span> (<\/span>self.<\/span>N –<\/span> self.<\/span>df[<\/span>w]<\/span> +<\/span> 0.5<\/span>)<\/span> \/<\/span> (<\/span>self.<\/span>df[<\/span>w]<\/span> +<\/span> 0.5<\/span>)<\/span>)<\/span>
\n s +=<\/span> idf *<\/span> f *<\/span> (<\/span>K1 +<\/span> 1<\/span>)<\/span> \/<\/span> (<\/span>f +<\/span> K1 *<\/span> (<\/span>1<\/span> –<\/span> B +<\/span> B *<\/span> self.<\/span>ln[<\/span>i]<\/span> \/<\/span> self.<\/span>avg)<\/span>)<\/span>
\n if<\/span> s ><\/span> 0<\/span>:<\/span> out[<\/span>self.<\/span>docs[<\/span>i]<\/span>[<\/span>0<\/span>]<\/span>]<\/span> =<\/span> s
\n return<\/span> _top(<\/span>out,<\/span> topk)<\/span><\/p>\n

# \u2500\u2500 \u8def\u4e8c：\u7a20\u5bc6\u5411\u91cf（\u76f8\u4f3c\u5ea6） \u2500\u2500<\/span>
\nclass<\/span> Vec<\/span>:<\/span>
\n def<\/span> __init__<\/span>(<\/span>self,<\/span> docs)<\/span>:<\/span>
\n self.<\/span>v =<\/span> {<\/span>d[<\/span>0<\/span>]<\/span>:<\/span> embed(<\/span>d[<\/span>1<\/span>]<\/span>)<\/span> for<\/span> d in<\/span> docs}<\/span>
\n def<\/span> search<\/span>(<\/span>self,<\/span> q,<\/span> topk=<\/span>50<\/span>)<\/span>:<\/span>
\n qv =<\/span> embed(<\/span>q)<\/span>
\n return<\/span> _top(<\/span>{<\/span>i:<\/span> cos(<\/span>qv,<\/span> v)<\/span> for<\/span> i,<\/span> v in<\/span> self.<\/span>v.<\/span>items(<\/span>)<\/span>}<\/span>,<\/span> topk)<\/span><\/p>\n

# \u2500\u2500 \u8def\u4e09：\u7b26\u53f7\u53ec\u56de（\u7cbe\u786e\u6807\u8bc6\u7b26 \/ \u6539\u5199\u522b\u540d \/ \u7f55\u89c1\u672f\u8bed） \u2500\u2500<\/span>
\ndef<\/span> symbolic<\/span>(<\/span>q,<\/span> docs,<\/span> bm)<\/span>:<\/span>
\n keys =<\/span> set<\/span>(<\/span>IDPAT.<\/span>findall(<\/span>q.<\/span>upper(<\/span>)<\/span>)<\/span>)<\/span>
\n keys |<\/span>=<\/span> {<\/span>ALIAS[<\/span>k]<\/span> for<\/span> k in<\/span> ALIAS if<\/span> k in<\/span> q}<\/span>
\n keys |<\/span>=<\/span> {<\/span>w for<\/span> w in<\/span> tokenize(<\/span>q)<\/span> if<\/span> w in<\/span> bm.<\/span>rare}<\/span>
\n out =<\/span> {<\/span>}<\/span>
\n for<\/span> did,<\/span> text,<\/span> meta in<\/span> docs:<\/span>
\n hay =<\/span> (<\/span>text +<\/span> " "<\/span> +<\/span> " "<\/span>.<\/span>join(<\/span>meta.<\/span>values(<\/span>)<\/span>)<\/span>)<\/span>.<\/span>upper(<\/span>)<\/span>
\n hit =<\/span> sum<\/span>(<\/span>hay.<\/span>count(<\/span>k)<\/span> for<\/span> k in<\/span> keys)<\/span>
\n if<\/span> hit:<\/span> out[<\/span>did]<\/span> =<\/span> float<\/span>(<\/span>hit)<\/span>
\n return<\/span> out<\/p>\n

# \u2500\u2500 \u878d\u5408\u4e24\u5f0f \u2500\u2500<\/span>
\ndef<\/span> rrf<\/span>(<\/span>runs,<\/span> topk=<\/span>50<\/span>,<\/span> k=<\/span>RRF_K)<\/span>:<\/span>
\n """Reciprocal Rank Fusion：\u53ea\u7528\u540d\u6b21\u4e0d\u770b\u5206\u6570，\u5929\u7136\u514d\u75ab\u91cf\u7eb2\u5dee\u5f02\u3002"""<\/span>
\n out =<\/span> Counter(<\/span>)<\/span>
\n for<\/span> _,<\/span> res in<\/span> runs:<\/span>
\n for<\/span> rank,<\/span> (<\/span>did,<\/span> _)<\/span> in<\/span> enumerate<\/span>(<\/span>res,<\/span> 1<\/span>)<\/span>:<\/span>
\n out[<\/span>did]<\/span> +=<\/span> 1.0<\/span> \/<\/span> (<\/span>k +<\/span> rank)<\/span>
\n return<\/span> sorted<\/span>(<\/span>out.<\/span>items(<\/span>)<\/span>,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>x[<\/span>1<\/span>]<\/span>)<\/span>[<\/span>:<\/span>topk]<\/span><\/p>\n

def<\/span> weighted<\/span>(<\/span>runs,<\/span> w,<\/span> topk=<\/span>50<\/span>)<\/span>:<\/span>
\n """\u5148\u6309\u8def\u5185\u6700\u9ad8\u5206\u5f52\u4e00\u5316\u5230 0~1 \u518d\u52a0\u6743；\u4e0d\u5f52\u4e00\u5316\u7684\u8bdd BM25 \u4f1a\u72ec\u88c1\u3002"""<\/span>
\n out =<\/span> Counter(<\/span>)<\/span>
\n for<\/span> src,<\/span> res in<\/span> runs:<\/span>
\n mx =<\/span> max<\/span>(<\/span>(<\/span>s for<\/span> _,<\/span> s in<\/span> res)<\/span>,<\/span> default=<\/span>1.0<\/span>)<\/span> or<\/span> 1.0<\/span>
\n for<\/span> did,<\/span> s in<\/span> res:<\/span>
\n out[<\/span>did]<\/span> +=<\/span> w.<\/span>get(<\/span>src,<\/span> 0.0<\/span>)<\/span> *<\/span> (<\/span>s \/<\/span> mx)<\/span>
\n return<\/span> sorted<\/span>(<\/span>out.<\/span>items(<\/span>)<\/span>,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>x[<\/span>1<\/span>]<\/span>)<\/span>[<\/span>:<\/span>topk]<\/span><\/p>\n

def<\/span> symbol_gate<\/span>(<\/span>fused,<\/span> sym)<\/span>:<\/span>
\n """\u7b26\u53f7\u547d\u4e2d\u9879\u63d0\u5230\u961f\u9996：\u5b83\u4eec\u662f\u5fc5\u987b\u8fdb\u573a\u7684\u5019\u9009，\u4e0d\u53c2\u4e0e\u5206\u6570\u8d5b\u9a6c\u3002"""<\/span>
\n if<\/span> not<\/span> sym:<\/span> return<\/span> fused
\n sc =<\/span> dict<\/span>(<\/span>fused)<\/span>
\n head =<\/span> sorted<\/span>(<\/span>(<\/span>d for<\/span> d in<\/span> sym if<\/span> d in<\/span> sc)<\/span>,<\/span> key=<\/span>lambda<\/span> d:<\/span> –<\/span>sc[<\/span>d]<\/span>)<\/span>
\n return<\/span> [<\/span>(<\/span>d,<\/span> sc[<\/span>d]<\/span>)<\/span> for<\/span> d in<\/span> head]<\/span> +<\/span> [<\/span>(<\/span>d,<\/span> s)<\/span> for<\/span> d,<\/span> s in<\/span> fused if<\/span> d not<\/span> in<\/span> sym]<\/span><\/p>\n

# \u2500\u2500 \u91cd\u6392\u95f8\u95e8：\u4e09\u6863，\u540e\u4e24\u6863\u8981\u5148\u8fdb\u9002\u914d\u53e3 \u2500\u2500<\/span>
\nCROSS =<\/span> None<\/span> # \u9002\u914d\u53e3 2：cross_score(q, doc) -> float，\u5982 BGE-reranker<\/span>
\nLLM_RANK =<\/span> None<\/span> # \u9002\u914d\u53e3 3：llm_rank(q, ids) -> list[id]，\u6ed1\u52a8\u7a97\u53e3\u5f0f<\/span><\/p>\n

def<\/span> rerank<\/span>(<\/span>q,<\/span> fused,<\/span> texts,<\/span> mode=<\/span>"none"<\/span>,<\/span> depth=<\/span>50<\/span>,<\/span> topk=<\/span>8<\/span>)<\/span>:<\/span>
\n """depth = \u53c2\u4e0e\u91cd\u6392\u7684\u5019\u9009\u6df1\u5ea6，topk = \u6700\u7ec8\u8fdb\u4e0a\u4e0b\u6587\u7684\u6761\u6570\u3002"""<\/span>
\n cand =<\/span> fused[<\/span>:<\/span>depth]<\/span>
\n if<\/span> mode ==<\/span> "none"<\/span>:<\/span> return<\/span> cand[<\/span>:<\/span>topk]<\/span>
\n if<\/span> mode ==<\/span> "bi"<\/span>:<\/span> return<\/span> sorted<\/span>(<\/span>cand,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>cos(<\/span>embed(<\/span>q)<\/span>,<\/span> embed(<\/span>texts[<\/span>x[<\/span>0<\/span>]<\/span>]<\/span>)<\/span>)<\/span>)<\/span>[<\/span>:<\/span>topk]<\/span>
\n if<\/span> mode ==<\/span> "cross"<\/span>:<\/span>
\n if<\/span> CROSS is<\/span> None<\/span>:<\/span> raise<\/span> RuntimeError(<\/span>"\u5148\u63a5\u901a CROSS \u9002\u914d\u53e3"<\/span>)<\/span>
\n return<\/span> sorted<\/span>(<\/span>cand,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>CROSS(<\/span>q,<\/span> texts[<\/span>x[<\/span>0<\/span>]<\/span>]<\/span>)<\/span>)<\/span>[<\/span>:<\/span>topk]<\/span>
\n if<\/span> mode ==<\/span> "llm"<\/span>:<\/span>
\n if<\/span> LLM_RANK is<\/span> None<\/span>:<\/span> raise<\/span> RuntimeError(<\/span>"\u5148\u63a5\u901a LLM_RANK \u9002\u914d\u53e3"<\/span>)<\/span>
\n pos =<\/span> {<\/span>d:<\/span> i for<\/span> i,<\/span> d in<\/span> enumerate<\/span>(<\/span>LLM_RANK(<\/span>q,<\/span> [<\/span>d for<\/span> d,<\/span> _ in<\/span> cand]<\/span>)<\/span>)<\/span>}<\/span>
\n return<\/span> sorted<\/span>(<\/span>cand,<\/span> key=<\/span>lambda<\/span> x:<\/span> pos.<\/span>get(<\/span>x[<\/span>0<\/span>]<\/span>,<\/span> len<\/span>(<\/span>pos)<\/span>)<\/span>)<\/span>[<\/span>:<\/span>topk]<\/span>
\n raise<\/span> ValueError(<\/span>"\u672a\u77e5\u91cd\u6392\u6863\u4f4d: "<\/span> +<\/span> mode)<\/span><\/p>\n

# \u2500\u2500 \u6f0f\u53ec\u8bca\u65ad：gold \u5230\u5e95\u662f\u54ea\u4e00\u8def\u635e\u56de\u6765\u7684 \u2500\u2500<\/span>
\ndef<\/span> diagnose<\/span>(<\/span>gold,<\/span> runs,<\/span> fused)<\/span>:<\/span>
\n rows =<\/span> [<\/span>]<\/span>
\n for<\/span> src,<\/span> res in<\/span> runs:<\/span>
\n ids =<\/span> [<\/span>d for<\/span> d,<\/span> _ in<\/span> res]<\/span>
\n rows.<\/span>append(<\/span>(<\/span>src,<\/span> bool<\/span>(<\/span>gold in<\/span> ids)<\/span>,<\/span> ids.<\/span>index(<\/span>gold)<\/span> +<\/span> 1<\/span> if<\/span> gold in<\/span> ids else<\/span> "-"<\/span>)<\/span>)<\/span>
\n fids =<\/span> [<\/span>d for<\/span> d,<\/span> _ in<\/span> fused]<\/span>
\n return<\/span> rows,<\/span> (<\/span>fids.<\/span>index(<\/span>gold)<\/span> +<\/span> 1<\/span> if<\/span> gold in<\/span> fids else<\/span> "-"<\/span>)<\/span><\/p>\n

\u4e0a\u9762\u662f\u5185\u6838\u3002\u4e0b\u9762\u628a\u516d\u6761 runbook \u704c\u8fdb\u53bb，\u8dd1\u4e00\u6b21\u6f0f\u53ec\u8bca\u65ad：<\/p>\n

# demo.py \u2014\u2014 6 \u6761 runbook，\u8dd1\u4e00\u6b21\u6f0f\u53ec\u8bca\u65ad<\/span>
\nfrom<\/span> hybrid_search import<\/span> BM25,<\/span> Vec,<\/span> symbolic,<\/span> rrf,<\/span> weighted,<\/span> symbol_gate,<\/span> rerank,<\/span> diagnose<\/p>\n

DOCS =<\/span> [<\/span>
\n (<\/span>"rb-214"<\/span>,<\/span> "\u5355\u636e\u5e8f\u53f7 RB-214：\u5207\u6362\u5199\u8def\u5f84，\u6e05\u7406\u5f52\u6863\u65e5\u5fd7\u3002"<\/span>,<\/span> {<\/span>"tag"<\/span>:<\/span> "DISK_FULL"<\/span>}<\/span>)<\/span>,<\/span>
\n (<\/span>"rb-301"<\/span>,<\/span> "\u6269\u5bb9\u9884\u6848：\u5148\u6458\u6d41\u91cf\u518d\u6269\u526f\u672c，\u907f\u514d\u7f13\u5b58\u51fb\u7a7f\u3002"<\/span>,<\/span> {<\/span>"tag"<\/span>:<\/span> "SCALE_OUT"<\/span>}<\/span>)<\/span>,<\/span>
\n (<\/span>"rb-118"<\/span>,<\/span> "\u78c1\u76d8 IO \u6253\u6ee1\u65f6\u5148\u6293\u706b\u7130\u56fe，\u518d\u51b3\u5b9a\u662f\u5426\u9650\u6d41\u3002"<\/span>,<\/span> {<\/span>"tag"<\/span>:<\/span> "IO"<\/span>}<\/span>)<\/span>,<\/span>
\n (<\/span>"rb-455"<\/span>,<\/span> "\u56de\u6eda：\u4fdd\u7559\u4e0a\u4e00\u4e2a\u955c\u50cf\u53f7，\u56de\u6eda\u540e\u8865\u4e00\u6b21\u5192\u70df\u3002"<\/span>,<\/span> {<\/span>"tag"<\/span>:<\/span> "ROLLBACK"<\/span>}<\/span>)<\/span>,<\/span>
\n (<\/span>"topo-7"<\/span>,<\/span> "svc-order \u4f9d\u8d56 Redis \u4e0e DB，\u62d3\u6251\u89c1\u9644\u4ef6\u4e00\u3002"<\/span>,<\/span> {<\/span>"tag"<\/span>:<\/span> "TOPO"<\/span>}<\/span>)<\/span>,<\/span>
\n (<\/span>"rb-902"<\/span>,<\/span> "\u8bc1\u4e66\u8f6e\u6362\u540e\u91cd\u542f\u7f51\u5173，\u6ce8\u610f\u7070\u5ea6\u987a\u5e8f\u3002"<\/span>,<\/span> {<\/span>"tag"<\/span>:<\/span> "CERT"<\/span>}<\/span>)<\/span>,<\/span>
\n]<\/span>
\nTEXTS =<\/span> {<\/span>d[<\/span>0<\/span>]<\/span>:<\/span> d[<\/span>1<\/span>]<\/span> for<\/span> d in<\/span> DOCS}<\/span>
\nBM,<\/span> VEC =<\/span> BM25(<\/span>DOCS)<\/span>,<\/span> Vec(<\/span>DOCS)<\/span><\/p>\n

def<\/span> ask<\/span>(<\/span>q,<\/span> gold,<\/span> mode=<\/span>"none"<\/span>,<\/span> fuse=<\/span>"rrf"<\/span>)<\/span>:<\/span>
\n sym =<\/span> symbolic(<\/span>q,<\/span> DOCS,<\/span> BM)<\/span>
\n runs =<\/span> [<\/span>(<\/span>"vec"<\/span>,<\/span> VEC.<\/span>search(<\/span>q)<\/span>)<\/span>,<\/span> (<\/span>"bm25"<\/span>,<\/span> BM.<\/span>search(<\/span>q)<\/span>)<\/span>,<\/span>
\n (<\/span>"symbol"<\/span>,<\/span> sorted<\/span>(<\/span>sym.<\/span>items(<\/span>)<\/span>,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>x[<\/span>1<\/span>]<\/span>)<\/span>)<\/span>]<\/span>
\n raw =<\/span> rrf(<\/span>runs)<\/span> if<\/span> fuse ==<\/span> "rrf"<\/span> else<\/span> weighted(<\/span>runs,<\/span> {<\/span>"vec"<\/span>:<\/span> .5<\/span>,<\/span> "bm25"<\/span>:<\/span> .3<\/span>,<\/span> "symbol"<\/span>:<\/span> .2<\/span>}<\/span>)<\/span>
\n fused =<\/span> symbol_gate(<\/span>raw,<\/span> sym)<\/span>
\n rows,<\/span> fin =<\/span> diagnose(<\/span>gold,<\/span> runs,<\/span> fused)<\/span>
\n top3 =<\/span> [<\/span>d for<\/span> d,<\/span> _ in<\/span> rerank(<\/span>q,<\/span> fused,<\/span> TEXTS,<\/span> mode=<\/span>mode,<\/span> topk=<\/span>3<\/span>)<\/span>]<\/span>
\n print<\/span>(<\/span>"Q: %-22s gold=%s"<\/span> %<\/span> (<\/span>q,<\/span> gold)<\/span>)<\/span>
\n for<\/span> src,<\/span> hit,<\/span> rank in<\/span> rows:<\/span>
\n print<\/span>(<\/span>" %-6s \u547d\u4e2d=%-5s \u540d\u6b21=%s"<\/span> %<\/span> (<\/span>src,<\/span> hit,<\/span> rank)<\/span>)<\/span>
\n print<\/span>(<\/span>" \u878d\u5408(%s)\u540e\u540d\u6b21=%-3s top3=%s\\\\n"<\/span> %<\/span> (<\/span>fuse,<\/span> fin,<\/span> top3)<\/span>)<\/span><\/p>\n

ask(<\/span>"\u78c1\u76d8\u544a\u8b66\u548b\u6574，\u8981\u4e0d\u8981\u6269\u5bb9"<\/span>,<\/span> "rb-214"<\/span>)<\/span>
\nask(<\/span>"\u78c1\u76d8\u544a\u8b66\u548b\u6574，\u8981\u4e0d\u8981\u6269\u5bb9"<\/span>,<\/span> "rb-214"<\/span>,<\/span> fuse=<\/span>"weighted"<\/span>)<\/span>
\nask(<\/span>"RB-214 \u8fd9\u4e2a\u6587\u4ef6\u8bb2\u5565"<\/span>,<\/span> "rb-214"<\/span>)<\/span>
\nask(<\/span>"\u78c1\u76d8\u544a\u8b66\u548b\u6574，\u8981\u4e0d\u8981\u6269\u5bb9"<\/span>,<\/span> "rb-214"<\/span>,<\/span> mode=<\/span>"bi"<\/span>)<\/span><\/p>\n

3.2 \u9010\u6bb5\u8bfb\u8fd9\u4efd\u811a\u672c<\/h4>\n
    \n
  • embed \/ cos：\u552f\u4e00\u9002\u914d\u53e3\u3002\u5360\u4f4d\u5b9e\u73b0\u7528\u76f8\u90bb\u4e8c\u5b57\u6563\u5217，\u6ca1\u6709\u8bed\u4e49，\u8f93\u51fa\u91cc\u7684\u5411\u91cf\u540d\u6b21\u53ea\u4ee3\u8868\u5b57\u9762\u91cd\u53e0\u7a0b\u5ea6\u3002<\/li>\n
  • symbolic：\u4e09\u7c7b\u8bc1\u636e\u5408\u6210\u4e00\u5f20 key \u96c6\u5408\u2014\u2014\u6b63\u5219\u6807\u8bc6\u7b26\u3001ALIAS \u522b\u540d\u3001rare \u7f55\u89c1\u8bcd\u3002hay \u628a text \u4e0e meta \u62fc\u8d77\u6765\u6bd4\u5bf9，\u5143\u6570\u636e\u91cc\u6709\u6ca1\u6709 DISK_FULL \u51b3\u5b9a\u8fd9\u6761\u8def\u80fd\u5426\u547d\u4e2d\u3002<\/li>\n
  • rrf \/ weighted \/ rerank：weighted \u5148\u9664\u4ee5\u8def\u5185\u6700\u9ad8\u5206，\u8fd9\u662f\u90a3\u4e2a 93.8% \u7684\u552f\u4e00\u89e3\u836f；rrf \u7684 k=60 \u8ba9\u7b2c 1\u30012 \u540d\u5dee\u7ea6 1.6% [\u7b97]；rerank \u7684 depth \/ topk \u5206\u79bb\u662f\u523b\u610f\u7684，cross \/ llm \u7559\u6210 None \u907f\u514d\u9759\u9ed8\u9000\u5316\u6210\u300c\u6ca1\u91cd\u6392\u300d\u3002<\/li>\n<\/ul>\n

    \u5df2\u77e5\u504f\u5dee\u4e24\u6761：\u2460 \u5360\u4f4d embedding \u65e0\u8bed\u4e49\u80fd\u529b，\u771f\u5b9e\u573a\u666f\u91cc vec \u8def\u66f4\u5f3a，\u300c\u540c\u4e49\u6539\u5199\u300d\u7c7b\u6f0f\u53ec\u4f1a\u5c11\u89c1\u4e00\u4e9b\u4f46\u4e0d\u6d88\u5931；\u2461 bi \u6863\u4e0e\u53ec\u56de\u5171\u7528 embed，\u4f1a\u628a\u5019\u9009\u96c6\u91cd\u6392\u56de\u53ec\u56de\u987a\u5e8f\u2014\u2014\u6700\u540e\u4e00\u884c\u8fd0\u884c\u7ed3\u679c\u6f14\u793a\u4e86\u8fd9\u4e2a\u9000\u5316\u3002<\/p>\n

    \u8fd0\u884c\u7ed3\u679c：<\/p>\n

    Q: \u78c1\u76d8\u544a\u8b66\u548b\u6574，\u8981\u4e0d\u8981\u6269\u5bb9 gold=rb-214
    \n vec \u547d\u4e2d=True \u540d\u6b21=5
    \n bm25 \u547d\u4e2d=False \u540d\u6b21=-
    \n symbol \u547d\u4e2d=True \u540d\u6b21=1
    \n \u878d\u5408(rrf)\u540e\u540d\u6b21=2 top3=['rb-301', 'rb-214', 'rb-118']<\/p>\n

    Q: \u78c1\u76d8\u544a\u8b66\u548b\u6574，\u8981\u4e0d\u8981\u6269\u5bb9 gold=rb-214
    \n vec \u547d\u4e2d=True \u540d\u6b21=5
    \n bm25 \u547d\u4e2d=False \u540d\u6b21=-
    \n symbol \u547d\u4e2d=True \u540d\u6b21=1
    \n \u878d\u5408(weighted)\u540e\u540d\u6b21=2 top3=['rb-301', 'rb-214', 'rb-118']<\/p>\n

    Q: RB-214 \u8fd9\u4e2a\u6587\u4ef6\u8bb2\u5565 gold=rb-214
    \n vec \u547d\u4e2d=True \u540d\u6b21=1
    \n bm25 \u547d\u4e2d=True \u540d\u6b21=1
    \n symbol \u547d\u4e2d=True \u540d\u6b21=1
    \n \u878d\u5408(rrf)\u540e\u540d\u6b21=1 top3=['rb-214', 'rb-455', 'rb-118']<\/p>\n

    Q: \u78c1\u76d8\u544a\u8b66\u548b\u6574，\u8981\u4e0d\u8981\u6269\u5bb9 gold=rb-214
    \n vec \u547d\u4e2d=True \u540d\u6b21=5
    \n bm25 \u547d\u4e2d=False \u540d\u6b21=-
    \n symbol \u547d\u4e2d=True \u540d\u6b21=1
    \n \u878d\u5408(rrf)\u540e\u540d\u6b21=2 top3=['rb-118', 'rb-301', 'topo-7']<\/p>\n

    \u7b2c\u4e00\u6761\u6700\u503c\u5f97\u770b：vec \u628a gold \u6392\u5230\u7b2c 5\u3001bm25 \u5b8c\u5168\u6ca1\u635e\u5230，\u53ea\u6709 symbol \u9760\u522b\u540d\u515c\u4f4f，\u878d\u5408\u540e\u56de\u5230\u7b2c 2\u3002\u7b2c\u4e8c\u6761\u8bf4\u660e：RRF \u4e0e\u5f52\u4e00\u5316\u52a0\u6743\u7ed9\u51fa\u5b8c\u5168\u76f8\u540c\u7684 top-3，\u6743\u91cd\u4e4b\u4e89\u8fdc\u4e0d\u5982\u300c\u5143\u6570\u636e\u91cc\u6709\u6ca1\u6709\u8fd9\u4e2a\u522b\u540d\u300d\u91cd\u8981\u3002\u6700\u540e\u4e00\u6761\u662f\u53cd\u4f8b：\u6253\u5f00 bi \u91cd\u6392，gold \u6389\u51fa top-3\u2014\u2014\u5b83\u4e0e\u53ec\u56de\u540c\u6e90，\u7b49\u4e8e\u628a symbol_gate \u6276\u4e0a\u53bb\u7684\u6761\u76ee\u53c8\u6309\u56de\u53bb\u3002<\/p>\n

    #mermaid-svg-rM3SpIi3rKYJ9dnI{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-rM3SpIi3rKYJ9dnI .error-icon{fill:#552222;}#mermaid-svg-rM3SpIi3rKYJ9dnI .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-rM3SpIi3rKYJ9dnI .marker{fill:#333333;stroke:#333333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .marker.cross{stroke:#333333;}#mermaid-svg-rM3SpIi3rKYJ9dnI svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-rM3SpIi3rKYJ9dnI p{margin:0;}#mermaid-svg-rM3SpIi3rKYJ9dnI .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .cluster-label text{fill:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .cluster-label span{color:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .cluster-label span p{background-color:transparent;}#mermaid-svg-rM3SpIi3rKYJ9dnI .label text,#mermaid-svg-rM3SpIi3rKYJ9dnI span{fill:#333;color:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .node rect,#mermaid-svg-rM3SpIi3rKYJ9dnI .node circle,#mermaid-svg-rM3SpIi3rKYJ9dnI .node ellipse,#mermaid-svg-rM3SpIi3rKYJ9dnI .node polygon,#mermaid-svg-rM3SpIi3rKYJ9dnI .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .rough-node .label text,#mermaid-svg-rM3SpIi3rKYJ9dnI .node .label text,#mermaid-svg-rM3SpIi3rKYJ9dnI .image-shape .label,#mermaid-svg-rM3SpIi3rKYJ9dnI .icon-shape .label{text-anchor:middle;}#mermaid-svg-rM3SpIi3rKYJ9dnI .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .rough-node .label,#mermaid-svg-rM3SpIi3rKYJ9dnI .node .label,#mermaid-svg-rM3SpIi3rKYJ9dnI .image-shape .label,#mermaid-svg-rM3SpIi3rKYJ9dnI .icon-shape .label{text-align:center;}#mermaid-svg-rM3SpIi3rKYJ9dnI .node.clickable{cursor:pointer;}#mermaid-svg-rM3SpIi3rKYJ9dnI .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .arrowheadPath{fill:#333333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-rM3SpIi3rKYJ9dnI .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-rM3SpIi3rKYJ9dnI .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-rM3SpIi3rKYJ9dnI .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-rM3SpIi3rKYJ9dnI .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .cluster text{fill:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI .cluster span{color:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-rM3SpIi3rKYJ9dnI .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-rM3SpIi3rKYJ9dnI rect.text{fill:none;stroke-width:0;}#mermaid-svg-rM3SpIi3rKYJ9dnI .icon-shape,#mermaid-svg-rM3SpIi3rKYJ9dnI .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-rM3SpIi3rKYJ9dnI .icon-shape p,#mermaid-svg-rM3SpIi3rKYJ9dnI .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-rM3SpIi3rKYJ9dnI .icon-shape .label rect,#mermaid-svg-rM3SpIi3rKYJ9dnI .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-rM3SpIi3rKYJ9dnI .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-rM3SpIi3rKYJ9dnI .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-rM3SpIi3rKYJ9dnI :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

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

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

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

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

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

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

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

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

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

    <\/p>\n

    \u67e5\u8be2\u78c1\u76d8\u544a\u8b66\u548b\u6574<\/p>\n

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

    <\/p>\n

    \u5411\u91cf\u5019\u9009\u96c6top50 \u76f8\u4f3c\u5ea6 0.14<\/p>\n

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

    <\/p>\n

    BM25 \u5019\u9009\u96c6top50 \u65e0 gold<\/p>\n

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

    <\/p>\n

    \u7b26\u53f7\u5019\u9009\u96c6\u522b\u540d\u547d\u4e2d rb-214<\/p>\n

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

    <\/p>\n

    \u878d\u5408\u5206RRF \u540d\u6b21\u5012\u6570\u548c<\/p>\n

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

    <\/p>\n

    \u7b26\u53f7\u4fdd\u5e95rb-214 \u8fdb\u524d 8<\/p>\n

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

    <\/p>\n

    \u91cd\u6392\u5206\u53ef\u8df3\u8fc7<\/p>\n

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

    <\/p>\n

    \u6700\u7ec8\u4e0a\u4e0b\u6587top8 \u5e26\u6765\u6e90<\/p>\n

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

    \n

    \u56db\u3001\u5143\u6570\u636e\u8fc7\u6ee4\u7684\u6761\u4ef6\u4ece\u54ea\u6765，\u4e3a\u4ec0\u4e48\u4e0d\u8bb8\u4ece embedding \u6765<\/h3>\n

    \u4e00\u53e5\u8bdd\u89c4\u5219：\u8fc7\u6ee4\u6761\u4ef6\u4ece\u67e5\u8be2\u7ed3\u6784\u91cc\u62bd，\u4e0d\u4ece embedding \u8ddd\u79bb\u91cc\u780d\u3002 \u524d\u8005\u7684\u8f93\u51fa\u662f\u5e03\u5c14\u7ea6\u675f（\u670d\u52a1\u7b49\u4e8e svc-order），\u540e\u8005\u53ea\u662f\u8ddd\u79bb\u9608\u503c\u2014\u2014\u8ddd\u79bb\u8fd1\u7edd\u4e0d\u610f\u5473\u7740\u6761\u4ef6\u6210\u7acb\u3002<\/p>\n

    #mermaid-svg-hYVO8ief8ACl3kJc{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;fill:#333;}@keyframes edge-animation-frame{from{stroke-dashoffset:0;}}@keyframes dash{to{stroke-dashoffset:0;}}#mermaid-svg-hYVO8ief8ACl3kJc .edge-animation-slow{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 50s linear infinite;stroke-linecap:round;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-animation-fast{stroke-dasharray:9,5!important;stroke-dashoffset:900;animation:dash 20s linear infinite;stroke-linecap:round;}#mermaid-svg-hYVO8ief8ACl3kJc .error-icon{fill:#552222;}#mermaid-svg-hYVO8ief8ACl3kJc .error-text{fill:#552222;stroke:#552222;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-thickness-normal{stroke-width:1px;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-thickness-thick{stroke-width:3.5px;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-pattern-solid{stroke-dasharray:0;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-thickness-invisible{stroke-width:0;fill:none;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-svg-hYVO8ief8ACl3kJc .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-svg-hYVO8ief8ACl3kJc .marker{fill:#333333;stroke:#333333;}#mermaid-svg-hYVO8ief8ACl3kJc .marker.cross{stroke:#333333;}#mermaid-svg-hYVO8ief8ACl3kJc svg{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:16px;}#mermaid-svg-hYVO8ief8ACl3kJc p{margin:0;}#mermaid-svg-hYVO8ief8ACl3kJc .label{font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;color:#333;}#mermaid-svg-hYVO8ief8ACl3kJc .cluster-label text{fill:#333;}#mermaid-svg-hYVO8ief8ACl3kJc .cluster-label span{color:#333;}#mermaid-svg-hYVO8ief8ACl3kJc .cluster-label span p{background-color:transparent;}#mermaid-svg-hYVO8ief8ACl3kJc .label text,#mermaid-svg-hYVO8ief8ACl3kJc span{fill:#333;color:#333;}#mermaid-svg-hYVO8ief8ACl3kJc .node rect,#mermaid-svg-hYVO8ief8ACl3kJc .node circle,#mermaid-svg-hYVO8ief8ACl3kJc .node ellipse,#mermaid-svg-hYVO8ief8ACl3kJc .node polygon,#mermaid-svg-hYVO8ief8ACl3kJc .node path{fill:#ECECFF;stroke:#9370DB;stroke-width:1px;}#mermaid-svg-hYVO8ief8ACl3kJc .rough-node .label text,#mermaid-svg-hYVO8ief8ACl3kJc .node .label text,#mermaid-svg-hYVO8ief8ACl3kJc .image-shape .label,#mermaid-svg-hYVO8ief8ACl3kJc .icon-shape .label{text-anchor:middle;}#mermaid-svg-hYVO8ief8ACl3kJc .node .katex path{fill:#000;stroke:#000;stroke-width:1px;}#mermaid-svg-hYVO8ief8ACl3kJc .rough-node .label,#mermaid-svg-hYVO8ief8ACl3kJc .node .label,#mermaid-svg-hYVO8ief8ACl3kJc .image-shape .label,#mermaid-svg-hYVO8ief8ACl3kJc .icon-shape .label{text-align:center;}#mermaid-svg-hYVO8ief8ACl3kJc .node.clickable{cursor:pointer;}#mermaid-svg-hYVO8ief8ACl3kJc .root .anchor path{fill:#333333!important;stroke-width:0;stroke:#333333;}#mermaid-svg-hYVO8ief8ACl3kJc .arrowheadPath{fill:#333333;}#mermaid-svg-hYVO8ief8ACl3kJc .edgePath .path{stroke:#333333;stroke-width:2.0px;}#mermaid-svg-hYVO8ief8ACl3kJc .flowchart-link{stroke:#333333;fill:none;}#mermaid-svg-hYVO8ief8ACl3kJc .edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-hYVO8ief8ACl3kJc .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-hYVO8ief8ACl3kJc .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-hYVO8ief8ACl3kJc .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-hYVO8ief8ACl3kJc .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-hYVO8ief8ACl3kJc .cluster text{fill:#333;}#mermaid-svg-hYVO8ief8ACl3kJc .cluster span{color:#333;}#mermaid-svg-hYVO8ief8ACl3kJc div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-hYVO8ief8ACl3kJc .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-hYVO8ief8ACl3kJc rect.text{fill:none;stroke-width:0;}#mermaid-svg-hYVO8ief8ACl3kJc .icon-shape,#mermaid-svg-hYVO8ief8ACl3kJc .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-hYVO8ief8ACl3kJc .icon-shape p,#mermaid-svg-hYVO8ief8ACl3kJc .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-hYVO8ief8ACl3kJc .icon-shape .label rect,#mermaid-svg-hYVO8ief8ACl3kJc .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-hYVO8ief8ACl3kJc .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-hYVO8ief8ACl3kJc .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-hYVO8ief8ACl3kJc :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}<\/p>\n

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

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

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

    <\/p>\n

    \u91cd\u6392\u5c42 \u9884\u7b97 200ms<\/p>\n

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

    <\/p>\n

    cross-encoder\u9010\u5bf9\u6253\u5206<\/p>\n

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

    <\/p>\n

    LLM \u6ed1\u52a8\u7a97<\/p>\n

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

    <\/p>\n

    \u878d\u5408\u5c42 \u9884\u7b97 5ms<\/p>\n

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

    <\/p>\n

    RRF \u6216\u5f52\u4e00\u5316\u52a0\u6743<\/p>\n

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

    <\/p>\n

    \u7b26\u53f7\u4fdd\u5e95\u4e0e\u786c\u8fc7\u6ee4<\/p>\n

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

    <\/p>\n

    \u53ec\u56de\u5c42 \u9884\u7b97 60ms<\/p>\n

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

    <\/p>\n

    \u5411\u91cf\u8defHNSW \u7d22\u5f15<\/p>\n

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

    <\/p>\n

    BM25 \u8def\u5012\u6392\u7d22\u5f15<\/p>\n

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

    <\/p>\n

    \u7b26\u53f7\u8def\u5143\u6570\u636e\u7d22\u5f15<\/p>\n

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

    <\/p>\n

    top-k \u8fdb\u4e0a\u4e0b\u6587<\/p>\n

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

    \u9884\u7b97\u8fd9\u6837\u5207\u7684\u7406\u7531\u5f88\u7b80\u5355：\u53ec\u56de\u5c42\u4e09\u8def\u53ef\u5e76\u884c，\u878d\u5408\u5c42\u662f\u7eaf\u7b97\u672f，\u53ea\u6709\u91cd\u6392\u5c42\u662f\u4e32\u884c\u9010\u5bf9\u524d\u5411\u3002\u628a\u9884\u7b97\u538b\u5728\u91cd\u6392\u5c42\u6700\u5bb9\u6613\u5931\u63a7\u2014\u2014\u5019\u9009\u6df1\u5ea6\u6bcf\u52a0\u4e00\u500d，\u8017\u65f6\u5c31\u52a0\u4e00\u500d\u3002\u8fd9\u5957\u6570\u5b57\u662f OpsAgent \u53e3\u5f84，\u6362\u786c\u4ef6\u8981\u91cd\u7b97\u3002<\/p>\n

    \u4e94\u6761\u89c4\u5219：\u786c\u8bc1\u636e（ID\u3001\u670d\u52a1\u540d\u3001\u65f6\u95f4\u7a97）\u8d70\u524d\u7f6e\u8fc7\u6ee4，\u8f6f\u8bc1\u636e\u53ea\u52a0\u5206\u4e0d\u5254\u9664；\u5143\u6570\u636e\u7f3a\u5931\u6309\u300c\u901a\u8fc7\u5e76\u964d\u6743\u300d\u5904\u7406；\u522b\u540d\u8868\u8981\u6709\u7ef4\u62a4\u8005，\u6309\u9891\u6b21\u6392\u5e8f\u3001\u6309\u5468\u8865；\u91cd\u6392\u4e4b\u540e\u518d\u9a8c\u4e00\u6b21\u786c\u8fc7\u6ee4；\u5148\u8fc7\u6ee4\u540e\u622a\u65ad\u3002<\/p>\n

    \u8fd9\u4e94\u6761\u5bf9\u5e94\u7684\u5931\u8d25\u6a21\u5f0f\u5982\u4e0b：<\/p>\n\n\u9677\u9631\u89e6\u53d1\u6761\u4ef6\u73b0\u8c61\u6839\u56e0\u68c0\u6d4b\u89c4\u907f<\/tr>\n\n\n\n\n\n\n
    \u786c\u8fc7\u6ee4\u5199\u6210\u8f6f\u52a0\u5206<\/td>\nID \u7c7b\u5b9e\u4f53\u4e5f\u4e22\u8fdb\u52a0\u6743<\/td>\n\u5e26\u9519\u7f16\u53f7\u7684\u7247\u6bb5\u7a33\u5b9a\u6392\u8fdb top-5<\/td>\n\u5e03\u5c14\u7ea6\u675f\u88ab\u5f53\u6210\u76f8\u4f3c\u5ea6\u8d5b\u9a6c<\/td>\n\u62bd\u6837\u770b ID \u9519\u8bef\u5360\u6bd4<\/td>\nhard=true \u53ea\u505a\u8fc7\u6ee4<\/td>\n<\/tr>\n
    \u7f3a\u5931\u5b57\u6bb5\u88ab\u5f53\u6210\u4e0d\u6ee1\u8db3<\/td>\n\u8fc7\u6ee4\u5199\u6210\u4e25\u683c\u7b49\u4e8e<\/td>\n\u8001\u7248\u672c runbook \u6574\u4f53\u6d88\u5931<\/td>\n\u7f3a\u5931\u503c\u8bed\u4e49\u88ab\u9ed8\u8ba4\u4e3a False<\/td>\n\u7edf\u8ba1\u547d\u4e2d\u96c6\u5143\u6570\u636e\u5b8c\u6574\u7387<\/td>\n\u7f3a\u5931\u4e00\u5f8b\u901a\u8fc7\u5e76\u964d\u6743<\/td>\n<\/tr>\n
    \u7528\u76f8\u4f3c\u5ea6\u9608\u503c\u5f53\u8fc7\u6ee4\u5668<\/td>\n\u5199\u6210 sim > 0.7 \u624d\u7559\u4e0b<\/td>\n\u9608\u503c\u4e00\u8c03，\u53ec\u56de\u7387\u8df3\u51e0\u4e2a\u767e\u5206\u70b9<\/td>\n\u8ddd\u79bb\u4e0d\u7b49\u4e8e\u6761\u4ef6<\/td>\n\u753b\u9608\u503c-\u53ec\u56de\u66f2\u7ebf\u770b\u9661\u5ced\u7a0b\u5ea6<\/td>\n\u9608\u503c\u53ea\u505a\u7c97\u6392\u88c1\u526a<\/td>\n<\/tr>\n
    \u522b\u540d\u8868\u65e0\u4eba\u7ef4\u62a4<\/td>\n\u4e0a\u7ebf\u540e\u672a\u518d\u66f4\u65b0<\/td>\n\u65b0\u672f\u8bed\u7684\u6f0f\u53ec\u9010\u5b63\u4e0a\u5347<\/td>\n\u522b\u540d\u662f\u5bf9\u9f50\u4ea7\u7269，\u9700\u8981\u6301\u7eed\u5bf9\u9f50<\/td>\n\u6309\u6708\u7edf\u8ba1\u7b26\u53f7\u8def\u96f6\u547d\u4e2d\u5360\u6bd4<\/td>\n\u6309\u67e5\u8be2\u9891\u6b21\u6392\u5e8f，\u5468\u66f4<\/td>\n<\/tr>\n
    \u5148\u622a\u65ad\u518d\u8fc7\u6ee4<\/td>\n\u8fc7\u6ee4\u5199\u5728 top-k \u4e4b\u540e<\/td>\n\u5019\u9009\u6c60\u91cc\u6ca1\u6709\u7b26\u5408\u670d\u52a1\u7684\u6761\u76ee<\/td>\n\u622a\u65ad\u53d1\u751f\u5728\u6761\u4ef6\u4e4b\u524d<\/td>\n\u6bd4\u300c\u622a\u65ad\u524d \/ \u540e\u300d\u547d\u4e2d\u7387<\/td>\n\u8fc7\u6ee4\u5c42\u5fc5\u987b\u5728 ANN \u4e4b\u524d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u7b2c\u4e8c\u8282\u90a3\u53e5\u300c\u878d\u5408\u6743\u91cd\u7684\u5f71\u54cd\u5c0f\u4e8e\u8fc7\u6ee4\u6761\u4ef6\u300d\u5c31\u662f\u5bf9\u7740\u8fd9\u5f20\u8868\u8bf4\u7684：\u524d\u4e09\u6761\u4efb\u4f55\u4e00\u6761\u8e29\u4e2d，\u6389\u7684\u90fd\u662f 5pp \u8d77\u6b65，\u8c03\u6743\u91cd\u53ea\u5728\u4e00\u4e24\u4e2a\u767e\u5206\u70b9\u91cc\u6765\u56de\u3002<\/p>\n

    \n

    \u4e94\u3001\u91cd\u6392\u4ec0\u4e48\u65f6\u5019\u662f\u51c0\u6536\u76ca，top-k \u8be5\u622a\u5728\u54ea？<\/h3>\n

    5.1 top-k \u622a\u65ad\u5728\u91cd\u6392\u524d\u8fd8\u662f\u91cd\u6392\u540e，\u5dee\u522b\u6709\u591a\u5927<\/h4>\n

    \u5dee\u522b\u662f\u51b3\u5b9a\u6027\u7684\u3002\u5148\u622a\u65ad\u518d\u91cd\u6392，\u7b49\u4e8e\u8ba9\u91cd\u6392\u5728\u4e00\u4e2a\u5df2\u7ecf\u88ab\u7b5b\u574f\u7684\u6c60\u5b50\u91cc\u9009\u3002 \u811a\u672c\u91cc bi \u90a3\u6b21\u5c31\u662f\u8fd9\u6837：gold \u6392\u5728\u878d\u5408\u540e\u7b2c 2，\u622a\u65ad\u5230 3 \u518d\u7cbe\u6392\u5c31\u88ab\u540c\u6e90\u504f\u597d\u6324\u4e86\u51fa\u53bb\u3002\u6b63\u786e\u987a\u5e8f\u662f\u300c\u6df1\u5019\u9009 \u2192 \u91cd\u6392 \u2192 \u6d45\u622a\u65ad\u300d：<\/p>\n\n\u6863\u4f4d\u6bcf\u6b21\u989d\u5916 P95 \u5ef6\u8fdf\u8d28\u91cf\u6210\u672c\u9002\u7528<\/tr>\n\n\n\n\n\n
    \u4e0d\u505a\u91cd\u6392<\/td>\n0<\/td>\n\u57fa\u7ebf<\/td>\n0<\/td>\n\u5019\u9009\u8d28\u91cf\u5206\u4f4d \u22650.90<\/td>\n<\/tr>\n
    bi-encoder \u7cbe\u6392<\/td>\n5\u201320ms<\/td>\n\u4e0e\u53ec\u56de\u540c\u6e90\u5219\u51e0\u4e4e\u65e0\u589e\u76ca，\u6362\u66f4\u5927\u6a21\u578b\u624d\u6709<\/td>\n\u4f4e<\/td>\n\u9884\u7b97\u6781\u7d27\u3001\u4e14\u80fd\u628a\u7cbe\u6392\u6362\u6210\u4e0d\u540c\u6a21\u578b<\/td>\n<\/tr>\n
    cross-encoder<\/td>\n\u6bcf 10 \u6761\u5019\u9009 20\u201340ms<\/td>\n\u9ad8，\u5bf9\u300c\u8bed\u4e49\u76f8\u8fd1\u4f46\u7b54\u975e\u6240\u95ee\u300d\u6700\u6709\u6548<\/td>\n\u4e2d，\u6bcf\u6b21\u8c03\u7528\u90fd\u8981\u7b97<\/td>\n\u4e3b\u529b\u9009\u9879，depth=50 \u8d77<\/td>\n<\/tr>\n
    LLM \u91cd\u6392<\/td>\n300ms\u20133s<\/td>\n\u6700\u9ad8，\u80fd\u5904\u7406\u591a\u8df3\u4e0e\u9690\u542b\u610f\u56fe<\/td>\n\u9ad8，token \u4e0e wall clock \u53cc\u4efd<\/td>\n\u4f4e\u9891\u9ad8\u4ef7\u503c\u67e5\u8be2，depth \u226420<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u4e0a\u8868\u7684\u5ef6\u8fdf\u4f9d\u8d56\u6a21\u578b\u5c3a\u5bf8\u4e0e\u6279\u5904\u7406，\u662f\u672c\u673a\u5355\u5361\u53e3\u5f84\u3002\u91cd\u6392\u4e09\u6863\u7684\u4e0b\u6e38\u6536\u76ca，\u7b2c\u516b\u8282\u90a3\u5f20\u5bf9\u7167\u8868\u7ed9\u51fa\u5b9e\u6d4b\u4f4d\u3002<\/p>\n

    5.2 \u53d6\u503c\u8868<\/h4>\n\n\u573a\u666f\u5019\u9009\u6df1\u5ea6 depth\u6700\u7ec8 top-k\u8bf4\u660e<\/tr>\n\n\n\n\n\n\n
    \u5355\u8df3\u4e8b\u5b9e\u95ee\u7b54<\/td>\n50<\/td>\n8<\/td>\n\u591a\u4f59\u4f1a\u88ab 06 \u7bc7\u7684\u5f15\u7528\u9a8c\u8bc1\u5f53\u566a\u58f0<\/td>\n<\/tr>\n
    \u591a\u8df3\u3001\u8de8\u5757（\u89c1 03）<\/td>\n100<\/td>\n12\u201316<\/td>\n\u7b54\u6848\u5206\u6563\u65f6\u5b81\u53ef\u591a\u9009，\u522b\u8ba9 evidence \u65ad\u94fe<\/td>\n<\/tr>\n
    cross-encoder \u91cd\u6392<\/td>\n50<\/td>\n8<\/td>\n\u6df1\u5ea6\u518d\u9ad8，\u5ef6\u8fdf\u7ebf\u6027\u6da8\u800c\u6536\u76ca\u6536\u655b<\/td>\n<\/tr>\n
    LLM \u6ed1\u52a8\u7a97\u91cd\u6392<\/td>\n20<\/td>\n8<\/td>\n\u7a97\u957f\u53d7\u9650，\u6df1\u4e8e\u6b64\u503c\u9700\u591a\u8f6e\u7a97\u53e3<\/td>\n<\/tr>\n
    \u4f4e\u5ef6\u8fdf\u63a5\u53e3\u578b\u670d\u52a1<\/td>\n30<\/td>\n5<\/td>\n\u4f18\u5148\u4fdd P95，\u727a\u7272\u5c3e\u90e8\u53ec\u56de<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    5.3 \u4ec0\u4e48\u65f6\u5019\u4e0d\u8be5\u4e0a\u91cd\u6392<\/h4>\n

    \u4e0d\u8be5\u4e0a\u91cd\u6392\u7684\u56db\u79cd\u60c5\u51b5：\u5019\u9009\u8d28\u91cf\u5206\u4f4d \u22650.90（\u62bd\u6837\u91cc gold \u843d\u5728 top-50 \u8fbe\u4e5d\u6210），\u6b64\u65f6\u91cd\u6392\u5728 top-8 \u7684\u63d0\u5347\u9884\u671f 1pp \u4e0a\u4e0b，\u800c\u91cd\u6392\u5c42\u9884\u7b97\u662f\u53ec\u56de\u5c42\u7684\u4e09\u500d；\u5ef6\u8fdf\u9884\u7b97\u4f59\u91cf <100ms；\u91cd\u6392\u6a21\u578b\u4e0e\u53ec\u56de\u540c\u6e90\u540c\u7c92\u5ea6；top-50 \u91cc\u6839\u672c\u6ca1\u6709 gold\u2014\u2014\u8fd9\u65f6\u8981\u505a\u7684\u662f\u7b2c\u4e00\u8282\u7684\u4e09\u7c7b\u8bc1\u636e\u3002<\/p>\n

    \u5224\u5b9a\u987a\u5e8f\u5982\u56fe：<\/p>\n

    \u5148\u6d4b\u5019\u9009\u96c6\u8d28\u91cf\u5206\u4f4d = \u62bd\u6837\u96c6\u91cc gold \u843d\u5728 top-50 \u7684\u6bd4\u4f8b
    \n \u2265 0.90 \u2192 \u4e0d\u4e0a\u91cd\u6392；\u628a\u9884\u7b97\u82b1\u5728\u5143\u6570\u636e\u4e0e\u522b\u540d\u4e0a
    \n 0.75 ~ 0.90 \u2192 cross-encoder，depth=50，top-k=8
    \n < 0.75 \u2192 \u5148\u4fee\u53ec\u56de（03 \u7684\u5757\u8fb9\u754c \/ 04 \u7684\u6539\u5199），\u91cd\u6392\u6551\u4e0d\u4e86\u6f0f\u53ec<\/p>\n

    \u518d\u770b\u5ef6\u8fdf\u9884\u7b97\u4f59\u91cf（P95）
    \n \u2265 300ms \u4e14 QPS \u4f4e \u2192 \u53ef\u4ee5\u8bd5 LLM \u91cd\u6392（depth \u226420）
    \n 100 ~ 300ms \u2192 cross-encoder
    \n < 100ms \u2192 \u53ea\u7559\u878d\u5408\u5c42，\u4e0d\u52a8\u91cd\u6392<\/p>\n

    \n

    \u516d\u30011405ms \u7684 P95 \u82b1\u5728\u54ea\u4e00\u7ea7，\u8d85\u9884\u7b97\u5148\u964d\u54ea\u4e00\u7ea7？<\/h3>\n

    P95 \u662f\u7aef\u5230\u7aef\u7684，\u4f46\u51b3\u7b56\u8981\u843d\u5728\u67d0\u4e00\u7ea7\u4e0a\u3002\u628a C \u6863\u7684 1405ms \u62c6\u5f00（depth=50\u3001\u5355\u5361 T4\u3001\u6279 8），\u62c6\u5b8c\u5c31\u77e5\u9053\u94b1\u82b1\u5728\u54ea：<\/p>\n\n\u9636\u6bb5P50 msP95 ms\u957f\u5c3e\u4e3b\u56e0<\/tr>\n\n\n\n\n\n
    \u67e5\u8be2\u7ed3\u6784\u5316（04 \u4ea7\u51fa，\u7f13\u5b58\u547d\u4e2d 62%）<\/td>\n8<\/td>\n35<\/td>\n\u672a\u547d\u4e2d\u8981\u8d70\u4e00\u6b21\u6539\u5199<\/td>\n<\/tr>\n
    \u4e09\u8def\u5e76\u884c\u53ec\u56de + \u878d\u5408\u4fdd\u5e95<\/td>\n42<\/td>\n107<\/td>\nHNSW \u957f\u67e5\u8be2\u9000\u5316\u6210\u8fd1\u5168\u626b\u63cf<\/td>\n<\/tr>\n
    cross-encoder depth=50<\/td>\n162<\/td>\n200<\/td>\n\u5019\u9009\u8d85 512 token \u65f6\u622a\u65ad\u91cd\u7b97<\/td>\n<\/tr>\n
    \u4e0b\u6e38\u751f\u6210<\/td>\n785<\/td>\n1005<\/td>\n\u8f93\u51fa\u957f\u5ea6\u65b9\u5dee<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u5408\u8ba1 997 \/ 1347ms，\u7aef\u5230\u7aef\u518d\u52a0 58ms \u6392\u961f\u4e0e\u7f51\u7edc\u3002\u5f80\u4e0b\u63a8\u4e24\u4e2a\u6863\u4f4d\u4e5f\u5bf9\u5f97\u4e0a：\u5173\u6389 cross \u90a3\u6863\u5c31\u662f A \u6863\u7684 1205ms；\u7eaf\u5411\u91cf\u4e00\u8def\u53ec\u56de\u662f 37 \/ 82ms，\u6bd4\u4e09\u8def\u5e76\u884c\u5c11 25ms，\u4e8e\u662f\u57fa\u7ebf 1180ms\u2014\u2014\u7b2c\u516b\u8282\u90a3\u4e09\u4e2a P95 \u5c31\u662f\u8fd9\u4e48\u6765\u7684\u3002<\/p>\n

    \u771f\u6b63\u80fd\u7701\u7684\u662f\u7b2c\u4e8c\u3001\u4e09\u884c，\u964d\u4ef7\u94fe\u6309\u300c\u5148\u964d\u8d35\u7684\u3001\u518d\u52a8\u7ed3\u6784\u300d\u6392（\u6210\u672c\u89c1\u4e0b）：<\/p>\n

      \n
    • L0 \u5e38\u6001：RRF + cross depth=50，top-k=8 \u2192 P95 1405ms，precision@10 0.650\u3002<\/li>\n
    • L1（P95 \u8fde\u7eed 5 min >1400ms）：depth 50\u219230，cross \u6863 200\u2192118ms \u2192 1323ms，precision@10 0.630\u3002<\/li>\n
    • L2（>1600ms）：\u5173 cross-encoder，\u9000\u56de A \u6863\u878d\u5408 top-8 \u2192 1205ms，precision@10 0.560\u3002<\/li>\n
    • L3（>2000ms）：\u5f00 5 \u5206\u949f\u67e5\u8be2\u7f13\u5b58（\u547d\u4e2d\u7387\u6309 45% \u6298\u7b97）+ \u9000\u56de\u7eaf\u5411\u91cf top-5 \u2192 620ms，precision@10 0.510\u3002<\/li>\n<\/ul>\n

      L3 \u7684 precision \u6389 5pp \u4e0d\u662f\u622a\u65ad\u9020\u6210\u7684，\u662f\u7b26\u53f7\u8def\u88ab\u5173\u6389\u540e recall@50 \u56de\u5230 0.890\u3002\u6210\u672c\u6309\u89c4\u8303\u5355\u4ef7\u63a8：50 \u5bf9\u5019\u9009 \u00d7180 token \u00d7 0.02 USD\/M = 0.18 USD\/\u5343\u6b21 [\u7b97]，\u5173\u6389\u540e\u53ea\u5269\u67e5\u8be2\u4fa7 embedding \u7684 0.0002 USD\/\u5343\u6b21；LLM \u91cd\u6392\u662f 2,400 \u8f93\u5165 token \u00d7 0.02\/M + 60 \u8f93\u51fa\u5e8f\u53f7 token \u00d7 15\/M = 0.95 USD\/\u5343\u6b21 [\u7b97]，\u6bd4 cross \u8d35 5.3 \u500d\u3002<\/p>\n

      \n

      \u4e03\u3001\u878d\u5408\u6743\u91cd\u4e0e\u5f52\u4e00\u5316\u6807\u5c3a，\u600e\u4e48\u79bb\u7ebf\u6807\u5b9a？<\/h3>\n

      \u7b2c\u4e8c\u8282\u8bf4\u300c\u6807\u5c3a\u53d6\u81ea\u79bb\u7ebf\u5206\u4f4d\u6570\u300d\u5374\u6ca1\u7ed9\u6d41\u7a0b，\u8fd9\u8282\u8865\u4e0a\u3002\u6807\u5b9a\u4ea7\u51fa\u4e24\u6837\u4e1c\u897f：\u6bcf\u8def\u4e00\u4e2a\u5206\u6bcd（\u6807\u5c3a）\u548c\u4e00\u7ec4\u6743\u91cd\u3002\u6807\u5c3a\u9519\u4e86，\u52a0\u6743\u5c31\u662f\u90a3\u4e2a 93.8%\u3002<\/p>\n

      7.1 \u6807\u5b9a\u6d41\u7a0b\u4e0e\u91cd\u6807\u7ebf<\/h4>\n\n\u6b65\u9aa4\u505a\u4ec0\u4e48\u53d6\u4ec0\u4e48\u6570\u91c7\u7eb3\u5224\u636e<\/tr>\n\n\n\n\n\n
      1 \u62bd\u6837<\/td>\n\u62bd 300 \u6761\u771f\u5b9e\u67e5\u8be2，\u6309\u9891\u6b21\u52a0\u6743<\/td>\n\u8986\u76d6 80% \u67e5\u8be2\u9891\u6b21<\/td>\n\u62bd\u6837\u96c6 recall@50 \u4e0e\u5168\u91cf\u5dee <1pp<\/td>\n<\/tr>\n
      2 \u6253\u5206<\/td>\n\u4e09\u8def\u5404\u8dd1 top-50，\u843d\u76d8\u8def\u5185\u5206\u6570<\/td>\n\u6bcf\u8def 15000 \u4e2a\u5206\u6570<\/td>\n\u5206\u5e03\u4e0d\u9000\u5316\u6210\u5355\u70b9<\/td>\n<\/tr>\n
      3 \u5b9a\u6807\u5c3a<\/td>\n\u53d6\u6bcf\u8def P95 \u4f5c\u5206\u6bcd，\u8d85\u51fa\u622a\u65ad\u5230 1.0<\/td>\nscale_vec=0.86\u3001scale_bm25=18.4<\/td>\n\u88ab\u622a\u65ad\u7684\u6bd4\u4f8b \u22645%<\/td>\n<\/tr>\n
      4 \u5b9a\u6743\u91cd<\/td>\nvec \/ bm25 \u6743\u91cd\u505a grid，\u6b65\u957f 0.1<\/td>\n11 \u7ec4\u5019\u9009\u53d6\u6700\u4f18<\/td>\n\u6bd4 0.5\/0.5 \u9ad8 \u22651pp \u624d\u91c7\u7eb3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u91cd\u6807\u89e6\u53d1\u7ebf\u56db\u6761：\u8bed\u6599\u5757\u6570 +20% \u53ea\u91cd\u7b97\u6807\u5c3a，\u7ea6 12 min；\u6362 embedding \u6a21\u578b\u5fc5\u987b\u6807\u5c3a\u4e0e\u6743\u91cd\u5168\u91cd\u6807，\u76f8\u4f3c\u5ea6\u5206\u5e03\u6574\u4f53\u5e73\u79fb\u4f1a\u8ba9\u65e7\u6807\u5c3a\u5931\u6548，\u4ee3\u4ef7\u662f\u5168\u91cf\u91cd\u7b97\u5411\u91cf\u7ea6 40 min；\u6539 03 \u7bc7\u7684\u5207\u5206\u53c2\u6570\u53ea\u91cd\u7b97 bm25 \u6807\u5c3a，\u7ea6 12 min；\u53ea\u52a0\u522b\u540d\u8868\u6761\u76ee\u4e0d\u91cd\u6807（\u7b26\u53f7\u8def\u4e0d\u8fdb\u52a0\u6743）\u3002<\/p>\n

      7.2 \u6807\u5b9a\u811a\u672c<\/h4>\n

      \u8f93\u5165：runs.json（{\u8def\u540d: {qid: [[did, score], …]}}，\u6765\u81ea\u7b2c\u516b\u8282\u90a3\u6279\u62bd\u6837\u6253\u5206）\u4e0e gold.json（{qid: gold_id}）\u3002\u600e\u4e48\u6267\u884c：python calibrate.py runs.json gold.json\u3002\u8f93\u51fa\u4ec0\u4e48：\u6bcf\u8def\u6807\u5c3a\u3001grid \u6700\u4f18\u6743\u91cd\u4e0e\u5b83\u7684 recall@50\u30010.5\/0.5 \u57fa\u7ebf\u7684 recall@50，\u5916\u52a0 adopt \u5efa\u8bae\u3002\u7ed3\u679c\u4e0d\u5bf9\u67e5\u54ea：\u6807\u5c3a\u51fa\u73b0 0.0 \u8bf4\u660e\u8be5\u8def\u5168\u96f6\u547d\u4e2d，\u5148\u67e5\u53ec\u56de；11 \u7ec4 recall@50 \u82e5\u76f8\u540c，\u8bf4\u660e\u4e24\u8def\u53ec\u56de\u540d\u5355\u51e0\u4e4e\u91cd\u5408\u3002<\/p>\n

      # calibrate.py \u2014\u2014 \u5f52\u4e00\u5316\u6807\u5c3a\u4e0e\u878d\u5408\u6743\u91cd\u7684\u79bb\u7ebf\u6807\u5b9a（\u96f6\u4f9d\u8d56，\u4ec5\u6807\u51c6\u5e93）<\/span>
      \nimport<\/span> json,<\/span> sys<\/p>\n

      def<\/span> pct<\/span>(<\/span>xs,<\/span> p)<\/span>:<\/span>
      \n """\u53d6\u6700\u8fd1\u79e9\u5206\u4f4d\u6570；xs \u9700\u5df2\u6392\u5e8f，\u7a7a\u5217\u8868\u8fd4\u56de 0.0\u3002"""<\/span>
      \n if<\/span> not<\/span> xs:<\/span>
      \n return<\/span> 0.0<\/span>
      \n return<\/span> xs[<\/span>min<\/span>(<\/span>len<\/span>(<\/span>xs)<\/span> –<\/span> 1<\/span>,<\/span> int<\/span>(<\/span>round<\/span>(<\/span>(<\/span>len<\/span>(<\/span>xs)<\/span> –<\/span> 1<\/span>)<\/span> *<\/span> p \/<\/span> 100.0<\/span>)<\/span>)<\/span>)<\/span>]<\/span><\/p>\n

      def<\/span> fit_scale<\/span>(<\/span>runs,<\/span> p=<\/span>95<\/span>)<\/span>:<\/span>
      \n """\u8f93\u5165 {\u8def\u540d: {qid: [[did, score], …]}}；\u8f93\u51fa\u6bcf\u8def\u4e00\u4e2a\u5206\u6bcd\u3002"""<\/span>
      \n out =<\/span> {<\/span>}<\/span>
      \n for<\/span> src,<\/span> qmap in<\/span> runs.<\/span>items(<\/span>)<\/span>:<\/span>
      \n pool =<\/span> sorted<\/span>(<\/span>s for<\/span> res in<\/span> qmap.<\/span>values(<\/span>)<\/span> for<\/span> _,<\/span> s in<\/span> res)<\/span>
      \n out[<\/span>src]<\/span> =<\/span> pct(<\/span>pool,<\/span> p)<\/span> or<\/span> 1.0<\/span> # \u5206\u4f4d\u6570\u4e3a 0 \u65f6\u9000\u5316\u4e3a 1，\u907f\u514d\u9664\u96f6<\/span>
      \n return<\/span> out<\/p>\n

      def<\/span> fuse<\/span>(<\/span>qres,<\/span> scale,<\/span> w,<\/span> clip=<\/span>1.0<\/span>,<\/span> topk=<\/span>50<\/span>)<\/span>:<\/span>
      \n """\u6309\u6807\u5c3a\u5f52\u4e00\u5316\u540e\u52a0\u6743\u6c42\u548c；\u8d85\u8fc7 1.0 \u7684\u90e8\u5206\u622a\u65ad\u3002"""<\/span>
      \n acc =<\/span> {<\/span>}<\/span>
      \n for<\/span> src,<\/span> res in<\/span> qres.<\/span>items(<\/span>)<\/span>:<\/span>
      \n for<\/span> did,<\/span> s in<\/span> res:<\/span>
      \n acc[<\/span>did]<\/span> =<\/span> acc.<\/span>get(<\/span>did,<\/span> 0.0<\/span>)<\/span> +<\/span> w.<\/span>get(<\/span>src,<\/span> 0.0<\/span>)<\/span> *<\/span> min<\/span>(<\/span>s \/<\/span> scale[<\/span>src]<\/span>,<\/span> clip)<\/span>
      \n return<\/span> sorted<\/span>(<\/span>acc.<\/span>items(<\/span>)<\/span>,<\/span> key=<\/span>lambda<\/span> x:<\/span> –<\/span>x[<\/span>1<\/span>]<\/span>)<\/span>[<\/span>:<\/span>topk]<\/span><\/p>\n

      def<\/span> recall_at<\/span>(<\/span>runs,<\/span> scale,<\/span> gold,<\/span> wv,<\/span> topk=<\/span>50<\/span>)<\/span>:<\/span>
      \n """\u7ed9\u5b9a vec \u8def\u6743\u91cd（bm25 \u53d6 1-wv），\u7b97\u62bd\u6837\u96c6\u4e0a\u7684 recall@topk\u3002"""<\/span>
      \n w =<\/span> {<\/span>"vec"<\/span>:<\/span> wv,<\/span> "bm25"<\/span>:<\/span> round<\/span>(<\/span>1.0<\/span> –<\/span> wv,<\/span> 2<\/span>)<\/span>}<\/span>
      \n hit =<\/span> 0<\/span>
      \n for<\/span> q,<\/span> g in<\/span> gold.<\/span>items(<\/span>)<\/span>:<\/span>
      \n qres =<\/span> {<\/span>s:<\/span> m[<\/span>q]<\/span> for<\/span> s,<\/span> m in<\/span> runs.<\/span>items(<\/span>)<\/span> if<\/span> q in<\/span> m}<\/span>
      \n hit +=<\/span> int<\/span>(<\/span>g in<\/span> [<\/span>d for<\/span> d,<\/span> _ in<\/span> fuse(<\/span>qres,<\/span> scale,<\/span> w,<\/span> topk=<\/span>topk)<\/span>]<\/span>)<\/span>
      \n return<\/span> hit \/<\/span> len<\/span>(<\/span>gold)<\/span><\/p>\n

      if<\/span> __name__ ==<\/span> "__main__"<\/span>:<\/span>
      \n runs =<\/span> json.<\/span>load(<\/span>open<\/span>(<\/span>sys.<\/span>argv[<\/span>1<\/span>]<\/span>,<\/span> encoding=<\/span>"utf-8"<\/span>)<\/span>)<\/span> # \u62bd\u6837\u6253\u5206<\/span>
      \n gold =<\/span> json.<\/span>load(<\/span>open<\/span>(<\/span>sys.<\/span>argv[<\/span>2<\/span>]<\/span>,<\/span> encoding=<\/span>"utf-8"<\/span>)<\/span>)<\/span> # {qid: gold_id}<\/span>
      \n scale =<\/span> fit_scale(<\/span>runs)<\/span>
      \n grid =<\/span> [<\/span>(<\/span>round<\/span>(<\/span>i *<\/span> 0.1<\/span>,<\/span> 2<\/span>)<\/span>,<\/span> recall_at(<\/span>runs,<\/span> scale,<\/span> gold,<\/span> round<\/span>(<\/span>i *<\/span> 0.1<\/span>,<\/span> 2<\/span>)<\/span>)<\/span>)<\/span> for<\/span> i in<\/span> range<\/span>(<\/span>11<\/span>)<\/span>]<\/span>
      \n best =<\/span> max<\/span>(<\/span>grid,<\/span> key=<\/span>lambda<\/span> x:<\/span> x[<\/span>1<\/span>]<\/span>)<\/span>
      \n base =<\/span> min<\/span>(<\/span>grid,<\/span> key=<\/span>lambda<\/span> x:<\/span> abs<\/span>(<\/span>x[<\/span>0<\/span>]<\/span> –<\/span> 0.5<\/span>)<\/span>)<\/span>[<\/span>1<\/span>]<\/span>
      \n print<\/span>(<\/span>"scale :"<\/span>,<\/span> {<\/span>k:<\/span> round<\/span>(<\/span>v,<\/span> 3<\/span>)<\/span> for<\/span> k,<\/span> v in<\/span> scale.<\/span>items(<\/span>)<\/span>}<\/span>)<\/span>
      \n print<\/span>(<\/span>"best : w_vec=%.1f recall@50=%.3f"<\/span> %<\/span> best)<\/span>
      \n print<\/span>(<\/span>"base : w_vec=0.5 recall@50=%.3f"<\/span> %<\/span> base)<\/span>
      \n print<\/span>(<\/span>"adopt :"<\/span>,<\/span> "yes"<\/span> if<\/span> best[<\/span>1<\/span>]<\/span> –<\/span> base >=<\/span> 0.01<\/span> else<\/span> "no, keep 0.5\/0.5"<\/span>)<\/span><\/p>\n

      7.3 \u9010\u6bb5\u8bfb\u8fd9\u4efd\u811a\u672c<\/h4>\n
        \n
      • pct \/ fit_scale：\u5206\u4f4d\u6570\u53d6\u6700\u8fd1\u79e9\u800c\u975e\u63d2\u503c，\u6837\u672c\u5c11\u65f6\u4f1a\u8df3\u6863\u3002p=95 \u662f\u523b\u610f\u7684\u2014\u2014\u53d6 max \u628a\u6807\u5c3a\u62ac\u5230\u6781\u7aef\u503c，\u53d6 P50 \u53c8\u8ba9\u592a\u591a\u5206\u6570\u88ab\u622a\u65ad\u5230 1.0\u3002<\/li>\n
      • fuse：clip=1.0 \u628a\u8d85\u51fa\u6807\u5c3a\u7684\u90e8\u5206\u62b9\u5e73，\u6b63\u662f\u8fd9\u4e00\u6b65\u8ba9 BM25 \u7684\u957f\u5c3e\u4e0d\u518d\u72ec\u88c1\u3002w \u91cc\u6ca1\u6709 symbol \u952e，\u7b26\u53f7\u8def\u6c38\u8fdc\u8d70 symbol_gate\u3002<\/li>\n
      • recall_at \/ __main__：\u53ea\u5728 recall@50 \u4e0a\u6bd4，\u56e0\u4e3a\u6807\u5c3a\u7684\u76ee\u6807\u662f\u628a gold \u62ac\u8fdb\u5019\u9009\u6c60，\u6392\u5e8f\u4ea4\u7ed9\u91cd\u6392\u5c42；grid \u53ea\u641c vec \u4e00\u8def\u5171 11 \u7ec4，\u4e0d\u8db3 1pp \u5c31\u5efa\u8bae\u522b\u52a8\u6743\u91cd\u3002<\/li>\n<\/ul>\n

        \u5df2\u77e5\u504f\u5dee\u4e24\u6761：\u2460 \u5206\u4f4d\u6570\u7528\u6700\u8fd1\u79e9，\u62bd\u6837\u5c11\u4e8e 1000 \u6761\u65f6 P95 \u4f1a\u8df3\u6863\u3001\u6807\u5c3a\u968f\u4e4b\u6296\u52a8，\u6240\u4ee5\u7b2c 2 \u6b65\u8981 15000 \u4e2a\u5206\u6570；\u2461 grid \u53ea\u4f18\u5316\u53ec\u56de\u4e0d\u770b\u7cbe\u786e\u7387，\u6700\u4f18\u6743\u91cd\u53ef\u80fd\u5bf9\u300c\u591a\u585e\u8fdb\u524d 50\u300d\u6709\u5229\u800c\u5bf9 top-8 \u65e0\u76ca，\u91c7\u7eb3\u524d\u8981\u56de\u7b2c\u516b\u8282\u590d\u6838\u3002<\/p>\n

        \n

        \u516b\u3001\u600e\u4e48\u6d4b，\u8fb9\u9645\u5ef6\u8fdf\u624d\u4e0d\u4f1a\u9a97\u4f60<\/h3>\n

        \u5b9e\u9a8c\u7eaa\u5f8b\u6cbf\u7528 00 \u7bc7\u7684\u4e09\u5c42\u53e3\u5f84：\u68c0\u7d22\u5c42\u770b\u53ec\u56de\u7387\u4e0e\u7cbe\u786e\u7387，\u4e0b\u6e38\u5c42\u770b opsqa-200 \u7684\u51c6\u786e\u7387，\u6210\u672c\u5c42\u770b P95 \u5ef6\u8fdf\u4e0e token\u3002\u4e09\u8005\u5fc5\u987b\u540c\u65f6\u51fa，\u53ea\u6709\u4e2d\u95f4\u6307\u6807\u53d8\u597d\u4e0d\u7b97\u6570\u2014\u2014\u53ec\u56de\u7387\u6da8\u4e86\u800c\u7b54\u6848\u53d8\u5dee，\u662f\u878d\u5408\u628a\u66f4\u5168\u4f46\u66f4\u6742\u7684\u5019\u9009\u704c\u7ed9\u6a21\u578b\u65f6\u7684\u5e38\u89c1\u7ed3\u679c\u3002<\/p>\n

        \u5bf9\u7167\u8bbe\u8ba1：\u57fa\u7ebf＝\u7eaf\u5411\u91cf top-8；\u5bf9\u7167\u7ec4＝\u6df7\u5408 \u00d7 {RRF, \u52a0\u6743} \u00d7 \u91cd\u6392 {\u65e0, cross, LLM}\u3002<\/p>\n\n\u914d\u7f6erecall@50precision@10P95 \u5ef6\u8fdf ms\u6bcf +1pp \u4e0b\u6e38\u51c6\u786e\u7387 ms\u4e0b\u6e38 accuracy<\/tr>\n\n\n\n\n\n\n
        \u57fa\u7ebf：\u7eaf\u5411\u91cf top-8<\/td>\n0.890<\/td>\n0.520<\/td>\n1180<\/td>\n\u2014<\/td>\n0.740<\/td>\n<\/tr>\n
        A：\u6df7\u5408 RRF \u00d7 \u65e0\u91cd\u6392<\/td>\n0.960<\/td>\n0.560<\/td>\n1205<\/td>\n31<\/td>\n0.748<\/td>\n<\/tr>\n
        B：\u6df7\u5408 \u52a0\u6743 \u00d7 \u65e0\u91cd\u6392<\/td>\n0.955<\/td>\n0.555<\/td>\n1208<\/td>\n47<\/td>\n0.746<\/td>\n<\/tr>\n
        C：A + cross-encoder（depth=50）<\/td>\n0.960<\/td>\n0.650<\/td>\n1405<\/td>\n154<\/td>\n0.761<\/td>\n<\/tr>\n
        D：A + LLM \u91cd\u6392（depth=20）<\/td>\n0.960<\/td>\n0.680<\/td>\n2600<\/td>\n775<\/td>\n0.766<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        \u6570\u636e\u8dd1\u51fa\u6765\u586b results\/k05.csv，\u8868\u5934\u5982\u4e0b：<\/p>\n

        arm,recall@50,precision@10,fusion_mode,rerank,p95_latency_ms,marginal_ms_per_pp,accuracy<\/p>\n

        \u6700\u540e\u4e00\u5217\u6700\u5bb9\u6613\u88ab\u7701\u6389\u3002\u6700\u6709\u7528\u7684\u8bfb\u6570：\u62ff\u672c\u884c\u4e0e\u300c\u66f4\u4fbf\u5b9c\u90a3\u4e00\u6863\u300d\u7684 P95 \u4e4b\u5dee，\u9664\u4ee5\u4e0b\u6e38\u51c6\u786e\u7387\u4e4b\u5dee（\u767e\u5206\u70b9），\u5c31\u662f\u300c\u6bcf\u4e70 1pp \u8981\u4ed8\u591a\u5c11\u6beb\u79d2\u300d\u3002\u5f15\u5b50\u90a3\u6b21\u8c03\u53c2\u6b63\u662f\u8fd9\u4e2a\u7b97\u6cd5：200ms \u00f7 1.3pp \u2248 154ms\/pp [\u7b97]\u3002\u4e09\u884c recall \u90fd\u662f 0.960 \u4e5f\u662f\u673a\u5236\u4f7f\u7136：\u91cd\u6392\u4e0d\u53ec\u56de，\u53ea\u91cd\u6392\u3002<\/p>\n

        \u56db\u7c7b\u8bef\u6d4b：<\/p>\n\n\u8bef\u6d4b\u600e\u4e48\u88ab\u6d4b\u9519\u6b63\u786e\u6d4b\u6cd5<\/tr>\n\n\n\n\n\n
        \u53ea\u770b top-8 \u7cbe\u786e\u7387<\/td>\n\u6f0f\u53ec\u8fd9\u7c7b\u9519\u8bef\u5728 top-8 \u91cc\u5b8c\u5168\u770b\u4e0d\u89c1<\/td>\n\u540c\u65f6\u62a5 top-50 \u53ec\u56de\u7387，\u4e24\u8005\u4e00\u8d77\u770b\u8d8b\u52bf<\/td>\n<\/tr>\n
        \u5ef6\u8fdf\u7528\u5747\u503c<\/td>\n\u957f\u5c3e\u88ab\u5747\u503c\u62b9\u5e73，\u51b3\u7b56\u65f6\u770b\u5230\u7684\u662f\u300c\u624d\u52a0\u4e86 40ms\u300d<\/td>\n\u4e00\u5f8b\u53d6 P95 \/ P99，\u5e76\u6309 QPS \u6298\u7b97\u6279\u5904\u7406\u6548\u5e94<\/td>\n<\/tr>\n
        \u5355\u673a\u8dd1\u4e00\u6b21\u5c31\u4e0b\u7ed3\u8bba<\/td>\n\u5019\u9009\u96c6\u89c4\u6a21\u4e0d\u540c，ANN \u7684\u8fd1\u4f3c\u8bef\u5dee\u4e5f\u4e0d\u540c<\/td>\n\u56fa\u5b9a\u7d22\u5f15\u7248\u672c\u4e0e\u673a\u5668，\u8dd1 bootstrap \u770b\u7f6e\u4fe1\u533a\u95f4<\/td>\n<\/tr>\n
        \u53ea\u7528\u4e00\u4e2a embedding \u8bc4\u81ea\u5df1\u7684\u7ba1\u9053<\/td>\n\u7ed3\u8bba\u4e0d\u53ef\u8fc1\u79fb<\/td>\n\u81f3\u5c11\u4e24\u4e2a\u4e0d\u540c\u6e90\u7684 embedding \u5404\u8dd1\u4e00\u904d（\u89c1 MTEB \/ BEIR）<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        \u7b2c\u4e09\u6761\u5c94\u51fa\u53bb\u4e00\u53e5：\u7d22\u5f15\u91cd\u5efa\u4f1a\u6539\u53d8\u5019\u9009\u96c6\u5206\u5e03，\u8fd9\u5957\u6570\u8981\u5728 09 \u7bc7\u7684\u95e8\u7981\u91cc\u91cd\u8dd1，\u4e0d\u80fd\u53ea\u6d4b\u4e00\u6b21\u3002<\/p>\n

        \n

        \u4e5d\u3001\u5c0f\u7ed3<\/h3>\n

        \u8fd9\u91cc\u7684\u5206\u6c34\u5cad\u662f：\u5148\u8865\u9f50\u6f0f\u53ec，\u518d\u8c08\u6392\u5e8f\u3002 \u6df7\u5408\u68c0\u7d22\u7684\u6536\u76ca\u96c6\u4e2d\u5728\u7b26\u53f7\u4e0e\u7a00\u758f\u4e24\u8def\u628a\u4e09\u7c7b\u6f0f\u53ec\u63a5\u4f4f，\u878d\u5408\u6743\u91cd\u662f\u4e8c\u9636\u53d8\u91cf；\u91cd\u6392\u7684\u6536\u76ca\u968f\u5019\u9009\u96c6\u8d28\u91cf\u4e0a\u5347\u800c\u4e0b\u964d，\u524d\u7f6e\u6761\u4ef6\u662f\u300c\u5019\u9009\u8d28\u91cf\u4e2d\u7b49\u53ca\u4ee5\u4e0b\u300d\u800c\u4e0d\u662f\u300c\u60f3\u8981\u66f4\u9ad8\u51c6\u786e\u7387\u300d\u3002<\/p>\n

        \u56db\u6761\u6392\u5e8f\u89c4\u5219：<\/p>\n

      • \u6f0f\u53ec\u5fc5\u5148\u5f52\u56e0：\u6807\u8bc6\u7b26\u4e0e\u7f55\u89c1\u672f\u8bed\u8d70\u7b26\u53f7\u8def\u3001\u540c\u4e49\u6539\u5199\u8d70\u522b\u540d\u2014\u2014\u5f52\u56e0\u9519\u4e86，\u540e\u9762\u8c03\u53c2\u5168\u5728\u539f\u5730\u6253\u8f6c\u3002<\/li>\n
      • \u878d\u5408\u9ed8\u8ba4 RRF；\u8981\u52a0\u6743\u5c31\u5148\u5f52\u4e00\u5316，\u6807\u5c3a\u53d6\u81ea\u79bb\u7ebf\u5206\u4f4d\u6570\u800c\u4e0d\u662f\u672c\u6b21\u67e5\u8be2\u6700\u5927\u503c\u3002<\/li>\n
      • \u5143\u6570\u636e\u8fc7\u6ee4\u662f\u524d\u7f6e\u786c\u7ea6\u675f，\u4e0d\u662f\u540e\u7f6e\u4fee\u526a；\u7f3a\u5931\u5b57\u6bb5\u901a\u8fc7\u5e76\u964d\u6743\u3002<\/li>\n
      • \u4e0a\u91cd\u6392\u7684\u5224\u636e\u662f\u5019\u9009\u8d28\u91cf\u5206\u4f4d + \u5ef6\u8fdf\u9884\u7b97\u4f59\u91cf，\u90fd\u4e0d\u6ee1\u8db3\u65f6，200ms \u4e70\u4e0d\u56de 1pp\u3002<\/li>\n

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        \n

        \u53c2\u8003<\/h4>\n
          \n
        • Okapi BM25（BM25 \u539f\u7406\u4e0e k1=1.2 \/ b=0.75 \u9ed8\u8ba4\u53c2\u6570）<\/li>\n
        • Reciprocal Rank Fusion (Cormack et al., 2009)（\u652f\u6491 rrf \u4e0e\u300c\u53ea\u5403\u540d\u6b21\u300d\u8fd9\u4e00\u6027\u8d28）<\/li>\n
        • ColBERT \u00b7 SPLADE（\u7a00\u758f\/\u591a\u5411\u91cf\u4e24\u6761\u4e2d\u95f4\u8def\u7ebf，\u4e0d\u9009\u5b83\u4eec\u7684\u7406\u7531\u5728\u7b2c\u4e09\u8282）<\/li>\n
        • Sentence-BERT（bi-encoder \u53cc\u5854\u7ed3\u6784\u7684\u51fa\u5904，\u652f\u6491\u300c\u540c\u6e90\u8be5\u6362\u7c92\u5ea6\u300d）<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"

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