推理服务 / NAVIN RESEARCH
Prompt Caching: Structure Requests for Reuse
Place stable prefixes first, separate volatile data, monitor cache hits, and protect tenant boundaries.
Place stable prefixes first, separate volatile data, monitor cache hits, and protect tenant boundaries.
简要回答: Caching works best when many requests share an identical or sufficiently similar prefix. Put stable instructions and reusable reference material before volatile user data, avoid meaningless prompt changes, and verify provider-specific caching, retention, and billing behavior.
实施步骤
- Measure repeated input volume by prompt segment.
- Order content from stable to dynamic where the API recommends it.
- Version shared prompts intentionally instead of injecting timestamps.
- Monitor cached-token usage, latency, cost, and correctness.
验证清单
- Test cache isolation across tenants.
- Confirm policy updates invalidate old prefixes.
- Compare total cost at production request rates.
常见错误
- Caching user-specific secrets in shared layers.
- Assuming every request receives a cache hit.
- Changing stable prompts on every deployment without need.
实际决策
先交付能够通过上述检查的最小设计。记录测试中使用的模型、提示词、工具、数据集与运行时版本，让后续变化可以被比较而不是被猜测。依赖供应商的限制、模型名称、价格或预览功能之前，请重新检查链接文档；这些细节变化往往快于本文的工程原则。
