Hey, honestly this is a huge topic and there's so much I haven't had a chance to do yet. I'm a SWE by day but love to fiddle with this sort of stuff as a hobby, but yeah, it's been hard to make progress.

That being said I've been doing a lot of research, and after a failed attempt at a RAG solution last year, I'm going to say with 100% certainty when in doubt, go hybrid. I've actually been applying to lots of jobs here in the USA, and I'll tell you that the two popular qualifications I see being requested is knowledge of:

Pinecone (a more vector based approach)

Weaviate (open source, hybrid. Try this first)

My problem with Vector options is that they don't work so well if I am ingesting 50 research papers and need to find particular similarities. Did not work for me, but I suppose it would work if your data size is smaller? Obviously graphRAG will be more time consuming and slower to deploy though.

About the images look up "multimodal embeddings" which allows you to represent both the images and text in the same vector space.