What service can I use to ask questions about my database of blog posts? “Tell me everything you know about Grideon, my fictional character” etc
Retrieval-Augmented Generation (RAG) is probably the tech you’d want. It basically involves a knowledge library being built from the documents you upload, which is then indexed when you ask questions.
NotebookLM by Google is an off the shelf tool that is specialized in this, but you can upload documents to ChatGPT, Copilot, Claude, etc., and get the same benefit.
If you self hosted, Open WebUI with Ollama supports this, but far from the only one.
OP can also use an embedding model and work with vectorial databases for the RAG.
I use Milvus (vector DB engine; open source, can be self hosted) and OpenAI’s text-embedding-small-3 for the embedding (extreeeemely cheap). There’s also some very good open weights embed modelsln HuggingFace.
I understand conceptually how these work, but I have a hard time of how to get started . I have the model, I know embeddings exist and what they are, and rags, and vector dbs, and then I have my SQL DB. I just don’t know what the steps are.
Do you have any guides you recommend?
Milvus documentation has a nice example: link. After this, you just need to use a persistent Milvus DB, instead of the ephimeral one in the documentation.
Let me know if you have further questions.
Thanks, I got NotebookLM working pretty quickly. I think RAG is what I’m after. I’ll continue to look.
If you want to try the openwebui route, This guide might be helpful.
Edit: in fact I don’t think this is for openwebui specifically, but I remember the chapter at the timestamp is what helped me increase the context window. That’s the important bit if you’re wanting to ask it questions about documents.
