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Comment on Show HN: An open-source AI Gateway with integrated guardrails

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saw your tweet on X, nice work and congrats on launching!

i'm curious about the caching mechanisms you've implemented to reduce repeated evaluations - are you using a traditional cache store like redis or something more bespoke?

We use a bunch of caching mechanisms on the LLM requests themselves and extend the same to guardrails now.

So there's 2 levels of cache - the LLM request itself might be cached (simple and semantic) and the guardrail response can be cached as well.

We use a mix of a distributed kv store and a vector DB to actually store the data

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