[viksit]

i looked at dspy last week, and was trying to wrap my head around how it would be useful for a "fine tune" style use case - where i would want to give the base model more context vs use a vector DB and have the model put together a result.

could you give a high level way to think about how to use dspy for something like this?

[stanbiryukov]

I think of dspy as a programmatic way to guide LLMs with information, whether from context based on retrieval or from input and output pairs, rather than traditional low-rank fine-tuning. Their readme has a high-level introduction to using RAG with a user defined way to pass relevant context. I also found their link to Weaviate's notebooks, where dspy is used with a vector DB, helpful in understanding an end-to-end workflow: [1] https://github.com/weaviate/recipes/tree/main/integrations/d...