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Hi @pkhara31 , the notebook https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-rag-langchain/llm-rag-langchain.ipynb seems to cover the same tasks you described in comment. Could you please check ? Does this match your idea of ​​the notebook you wanted to add ?
Let's discuss this point and leave only something new in this notebook or update the existing notebook

Hi @sbalandi , This NB covers the methodology to evaluate the performance of RAG pipeline by computing the BERT, BLEU, ROGUE, perplexity, racial bias scores.
This notebook also provides ability to scrap web URLs and implement RAG pipeline on the web content as well.
These are the key deltas & additions to the existing notebook on RAG.
Let me know if any more questions!

Thanks for your contribution @pkhara31 Do you think if we can add this NB to RAG notebook, as a separate .ipynb, so users can directly evaluate their RAG system with selected models in your pipeline ?

Another idea is to change this .ipynb to an evaludation_helper.py which can be called inside current NB, and users can evaluate the RAG pipeline without loading the model again. Whats your thought ? @pkhara31

The model loading redundancy can be avoided, but I think the evaluation and the ability to apply RAG pipeline on web docs (scraping) should still remain in the helper.