Context and prompt engineering is the most important of AI, hands down.
There are plenty of lightweight retrieval options that don't require a separate vector database (I'm the author of txtai [https://github.com/neuml/txtai], which is one of them).
It can be as simple this in Python: you pass an index operation a data generator and save the index to a local folder. Then use that for RAG.
Context and prompt engineering are super automatable. DSPy can automate prompt generation that massively outperforms human prompts, and instead of hand packing context, you can use IR/ML algorithms to intelligently select the optimal context bundle to produce the desired output.
Context and prompt engineering are going to be replaced by algorithms, 100%.
Yep, context, however you build it.
Strongly agree, I also found txtai is super interesting! Thank you for your open-source effort!
You got it!