NeMo-Guardrails VS rellm

- https://github.com/NVIDIA/NeMo-Guardrails/

Here's "jailbreak detection", in the NeMo-Guardrails project from Nvidia:

https://github.com/NVIDIA/NeMo-Guardrails/blob/327da8a42d5f8...

I.e. they ask the llm if the prompt will break the llm. (I believe that more data /some evaluation on how well this performs is intended to be released. Probably fair to call this stuff "not battle tested".)

I have been playing around with some models locally and creating a discord bot as a fun side project, and I wanted to setup some guardrails on inputs / outputs of the bot to make sure that it isn't violating any ethical boundaries. I was going to use Nvidia's Nemo guardrails, but they only support openai currently. Are there any other good ways to control inputs?

Thanks, I hadn't seen those. I did find https://github.com/NVIDIA/NeMo-Guardrails earlier but haven't looked into it yet.

I'm not sure it solves the problem of restricting the information it uses though. For example, as a proof of concept for a customer, I tried providing information from a vector database as context, but GPT would still answer questions that were not provided in that context. It would base its answers on information that was already crawled from the customer website and in the model. That is concerning because the website might get updated but you can't update the model yourself (among other reasons).

you can use guard rails with langchain - https://github.com/NVIDIA/NeMo-Guardrails

- https://github.com/r2d4/rellm

MS guidance as mentioned and ReLLM

There's probably a better API that wraps generate, but there's a bit more work than the logit mask.

You have to go one token at a time, otherwise the masking becomes combinatoric rather than linear (two tokens at a time -- need to generate all two token pairs, etc.).

But otherwise, that's what the code does! https://github.com/r2d4/rellm/blob/main/rellm/rellm.py#L21