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...