Retrieval Augmented Generation (RAG) resources
This is a collection of RAG resources, either informative blogposts or tutorials, along with tweets, youtube videos, short courses, etc, that I found useful at some point during my career.
Blogposts
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Building a Multi-Hop QA on Global Warming Using DSPy and Qdrant By Rito, May, 2024
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Evaluating Retrieval Augmented Generation using RAGAS By Superlinked Team, May, 2024
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An evaluation of RAG Retrieval Chunking Methods By Superlinked Team, April, 2024
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Your AI Product Needs Evals By Hamel Husain, March, 2024
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12 RAG Pain Points and Proposed Solutions By Wenqi Glantz, January, 2024
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A Practical Guide to RAG Pipeline Evaluation (Part 1: Retrieval) By Yi Zhang and Pasquale Antonante, December, 2023
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Patterns for Building LLM-based Systems & Products By Eugene Yan, July, 2023
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Building RAG-based LLM Applications for Production By Goku Mohandas and Philipp Moritz, October, 2023
Practical guide to building successful LLM products
By Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu and Shreya Shankar
- Tactical: What We Learned from a Year of Building with LLMs (Part I) May, 2024
- Operational: What We Learned from a Year of Building with LLMs (Part II) June, 2024
- Strategis: What We Learned from a Year of Building with LLMs (Part III) June, 2024
Blogs from Jason Liu
- RAG is more than just embedding search September, 2023
- How to build a terrible RAG system January, 2024
- Stop using LGTM@Few as a metric (Better RAG) February, 2024
- Levels of Complexity: RAG Applications February, 2024
- Systematically Improving Your RAG May, 2024