📄 中文摘要
在处理支付失败、API 错误和超时等事件流时，常常缺乏明确且可重复的规则来将这些数据转化为具体的行动指令，如允许、审核或阻止。此时，决策过程往往依赖于人工或临时的判断。此外，缺乏一个集中化的平台来应用这些规则并提供简单易懂的解释，导致决策缺乏叙述性。通过构建一个事件智能引擎，可以实现基于事件计数的确定性决策，并在需要时提供可选的自然语言解释，从而提升决策的透明度和可审计性。
基于规则的决策与可选的 LLM 解释：构建事件智能引擎
📄 English Summary
Rule-Based Decisions + Optional LLM Explanations: Building event-intel-engine
The challenge of managing streams of events such as payment failures, API errors, and timeouts often lies in the absence of clear, repeatable rules that translate these metrics into actionable decisions like allow, review, or block. This leads to reliance on manual or ad-hoc judgments. Additionally, there is frequently no centralized platform that applies these rules while also providing plain language explanations for decisions, resulting in a lack of narrative context. By developing an event-intel-engine, deterministic decisions can be made from event counts, with optional natural language explanations available to enhance transparency and auditability of the decision-making process.