type Create[T] = typing.NewProtocol[
both of these approaches use NFAs under the hood, which means O(m * n) matching. our approach is fundamentally different: we encode lookaround information directly in the automaton via derivatives, which gives us O(n) matching with a small constant. the trade-off is that we restrict lookarounds to a normalized form (?<=R1)R2(?=R3) where R1/R2/R3 themselves don’t contain lookarounds. the oracle-based approaches support more general nesting, but pay for it in the matching loop. one open question i have is how they handle memory for the oracle table - if you read a gigabyte of text, do you keep a gigabyte-sized table in memory for each lookaround in the pattern?
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与其说是技术问题，不如说是一个被长期忽视的基础工程问题。，这一点在同城约会中也有详细论述
LLM 的总结支持任意 OpenAI 兼容格式的 API，校对和总结可以使用不同的模型来降低成本。可以自定义 Webhook 地址，方便发送到任意指定的群聊。有 Web 界面方便分享链接，也方便丢到其他 LLM 的 Web 端进行后续提问。