andrew0

You’re right! Sorry for the typo. The older nomic-embed-text model is often used in examples, but granite-embedding is a more recent one and smaller for English-only text (30M parameters). If your use case is multi-language, they also offer a bigger one (278M parameters) that can handle English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, Chinese (Simplified). I would test them out a bit to see what works best for you.

Furthermore, if you’re not dependent on MariaDB for something else in your system, there are also some other vector databases I would recommend. Qdrant also works quite well, and you can integrate it pretty easily in something like LangChain. It really depends on how much you want to push your RAG workflow, but let me know if you have any other questions.

Have a look at Ollama embeddings. Easy to set up and the models are much smaller than a typical LLM.

Fooyin is also a solid choice.

Proton offers a Drive, and they’re based in Switzerland. I don’t see them being strong-armed like this by the UK government any time soon.