Using Ollama for the embeddings with “nomic-embed-text”, with LanceDB for the vector database. Recently updated it to use “agentic” RAG, but probably not fully needed for a small project.
There are so many of us doing the same, just had a similar conversation at $work. It’s pretty exciting. I feel like I’m having to shove another 20 years of development experience into my brain with all these new concepts and abstractions, but the dots have been connecting!
I feel this pain! It feels like in the world of LLMs there is a new acronym to learn every day!
For the curious RAG = Retrieval Augmented Generation. From wikipedia: RAG enables large language models (LLMs) to retrieve and incorporate new information from external data sources
Using Ollama for the embeddings with “nomic-embed-text”, with LanceDB for the vector database. Recently updated it to use “agentic” RAG, but probably not fully needed for a small project.