semantic-layer
Skill0 starsChanged 2 months agoMITView on GitHub
确定性语义层问答——把"哪个基站坏了/哪个 SKU 断货"类分析问题路由到参数化查询，同一问题重复执行答案逐位一致、附 SQL 可审计。当用户要"问数据"但要求生产级稳定性时使用。
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- analyticsengineering/ae-toolkittheir own version, first seen Oct 12, 2026
Other versions1 project uses a version of this.
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- analyticsengineering/ae-toolkit★ 3same name
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Semantic Layer · 确定性语义层问答
对应案例：NO.16（电信网络分析，人工 SQL 按天计 → 分钟级）。
参考实现：cases/16-network-analytics/（路由 100%、稳定性 100%、0.3ms）。
何时使用
- 客户自建"提示词 Agent"同一问题两次答案不同（temperature>0 的随机性 直接暴露给业务），不能进生产
- 分析问题模式相对固定（排名/状态/影响面/根因/趋势），仪表盘又无法支持追问
流程
- 意图清单：从分析师真实追问中归纳意图集（如 rank_faults / site_status / impact / root_cause / trend），每个意图对应确定的查询模板——先有意图 体系，再谈对话。
- 槽位白名单：实体槽位只放行合法格式（如站点号
S\d{2}）， 自由文本不进查询层。 - 参数化查询：全部常量 + 占位符绑定，杜绝拼接；SQL 作为答案的一部分 输出（可审计）。
- 确定性输出：同题重复执行逐位一致；"模型随机性不能成为业务系统 不稳定的借口"（案例 16：汽油不稳定，但汽车工程让汽油安全驱动车辆）。
- 开放问题降级：超出意图集的问题明确回答"不支持并给出最接近的意图"， 不硬猜——生产系统的"我不知道"比编造可信。
- 规模化：语义层与指标口径集中管理（语义层文件），多用户共享同一套 口径，避免"每个分析师一套 SQL"。
验收
- 评测集意图路由正确率 ≥ 95%
- 同题 N 次执行答案指纹一致率 = 100%
- 每个答案附 SQL 与数据行，可独立复查
边界
- 跨意图多跳问题、开放式探索不在此技能内（需 LLM 规划+语义层混合架构， 案例作者口径：复杂任务仍要"工具管计算、模型管理解、人管决策"）
- 数据写操作一律拒绝
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