simpleAI VS NeMo-Guardrails

Not related to my own project SimpleAI despite the name, but looks like we can easily make the two work together, to keep it « simple ». Nice work!

Using this as an opportunity to mention my own related project, perhaps it can end up on your nice list one day. :)

https://github.com/lhenault/SimpleAI

You could have a look at a project I’ve been working on, SimpleAI, doing exactly this by replicating the OpenAI endpoints (you can then use their JS client for integration). Adding StableLM should be straightforward, I plan to add it to the examples in the upcoming days once I have a bit of time.

I’ve built SimpleAI with exactly these kinds of use cases in mind. That should allow supporting any model with minimal / no change to your project. Good job and good luck with LoopGPT, that looks nice!

You could give this a shot: https://github.com/lhenault/simpleAI

I don't know if this applies to your use case but this would probably work if you are looking for an llm to help with programming. Haven't really played around with it but this may work for general llm tasks, it doesn't have a web UI though.

As per llama.cpp specifically, you can indeed add any model, it's just a matter of doing a bit of glue code and declaring it in your models.toml config. It's quite straightforward thanks to some provided tools for Python (see here for instance). For any other language it's a matter of integrating it through the gRPC interface (which shouldn't be too hard for Llama.cpp if you're comfortable in C++). I'm planning to also add support for REST for model in the backend at some point too.

Shameless plug but I’ve been recently working on SimpleAI, a project replicating the main endpoints from OpenAI API, allowing you to seamlessly switch from their API to your own one, as it’s compatible with OpenAI client.

I wanted to share with you SimpleAI, a self-hosted alternative to OpenAI API.

- 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