[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"kb-llm-ops":3},{"id":4,"title":5,"summary":6,"source":7,"category":8,"date":9,"url":10,"content":11},"llm-ops","LLMOps 落地指南：大模型应用的可观测性与评估","如何评估、追踪与治理大模型应用？覆盖提示管理、在线评测、链路追踪与安全护栏。","开源中国","工程实践","2026-08-09","https:\u002F\u002Fwww.oschina.net\u002F",[12,13,14,15],"LLMOps 解决的核心问题：模型不可解释、评测主观、线上问题难定位。","三层观测：调用级（Token\u002F成本\u002F延迟）、行为级（输出质量）、业务级（转化指标）。","在线评测（Online Eval）与回归集（Regression Set）相结合，是控制版本迭代风险的关键手段。","安全护栏（Guardrails）从输入过滤、输出校验到敏感信息脱敏，构建多层防线。"]