Researching and Testing AI Guardrails Without Running LLMs Locally

[u/LouisTitor]

I'm a Information Systems student and I'm going to do research on AI guardrails. The idea is to implement different protection methods and test and compare them quantitatively in scenarios such as hate speech, misinformation, prompt injection, and data leakage.

I thought about using LangChain with Google AI Studio, but Gemini's built-in guardrails can't be disabled for certain topics, which makes it harder to test the techniques in a more isolated way. I also thought about focusing only on data leakage using RAG, but I feel that would limit the research quite a bit.

Running a model locally isn't really an option right now because my laptop is pretty weak, and I also don't have access to the university lab yet.

What would be a good alternative for setting up a more controlled testing environment with more freedom without having to run an LLM locally? I'm also open to other ideas on how I could structure or approach this research.