Vectorless RAG vs every flavour of vector RAG: a head-to-head on real 10-Ks.

1. 1Build a vectorless RAG pipeline using a suitable library
2. 2Configure 10 different vector RAG pipelines with varying parameters
3. 3Run each pipeline on a set of 54 finance questions
4. 4Test and compare the performance of each pipeline on real 10-Ks data
5. 5Evaluate the results to identify where each pipeline breaks or excels

Data scientists and ML engineers can benefit from this comparison to choose the best RAG pipeline for their finance-related question-answering tasks

💡 Vectorless RAG and different vector RAG pipelines have varying strengths and weaknesses when applied to finance-related question-answering tasks

📊 Compare vectorless RAG with vector RAG pipelines on real 10-Ks finance questions! 💡