Build a RAG Evaluation Tool and Python Library

Welcome to my tutorial on how to build a Retrieval-Augmented Generation (RAG) Evaluation Tool and Python Library! In this video, I will guide you through the process of creating a comprehensive evaluation tool for RAG systems, complete with various metrics to assess the quality of generated text.
What You'll Learn:
✅ Setting up the project structure
✅ Implementing evaluation metrics such as BLEU, ROUGE, BERT Score, Perplexity, Diversity, and Racial Bias
✅ Creating a Python library that can be easily installed and used
✅ Writing test cases to ensure the robustness of the tool
✅ Packaging and publishing the library to PyPI
By the end of this tutorial, you'll have a powerful evaluation tool to enhance the performance and reliability of your RAG systems.
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GitHub: github.com/AIAnytime/rag-eval...
Library: pypi.org/project/rag-evaluator/
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#rag #ai #chatbot

[@yusufersayyem7242]

AI anytime channel "is all you need" 🙂
Thank you so much ❤

[@AIAnytime]

Thank you sir 🙏

[@sumankalyanghosh4838]

ERROR: Could not find a version that satisfies the requirement rag-evaluator (from versions: none)
ERROR: No matching distribution found for rag-evaluator

[@AIAnytime]

Let me check.

[@sumankalyanghosh4838]

@@AIAnytime is it fixed?

[@Vedhar2104]

can you create videos in azure with llm

[@AIAnytime]

I already have 2-3 videos for Azure OpenAI. Check RAG playlist.

[@rustik_tak]

where is code with streamlit?

[@AIAnytime]

Updated in the same GitHub repo

[@sauravmohanty3946]

streamlit code ?

[@AIAnytime]

Updated in the same GitHub repo.

[@NathanChambers]

The 1st 10 minutes of the video could have been 10-15 seconds. I guess you really like to pad your user watch time. :/ But for me, I comment and leave after all the fake video padding.