A complete collection of RAG interview questions, answers (603 questions & 52 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

149 stars 23 forks 149 watchers Jupyter Notebook MIT License
agentic-rag ai deep-learning generative-ai graph-rag interview-preparation interview-questions knowledge-graph langchain large-language-models llamaindex llm machine-learning nlp prompt-engineering rag retrieval-augmented-generation self-rag vector-database vector-search
2 Open Issues Need Help Last updated: Sep 13, 2026

Open Issues Need Help

View All on GitHub

A complete collection of RAG interview questions, answers (603 questions & 52 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

Jupyter Notebook
#agentic-rag#ai#deep-learning#generative-ai#graph-rag#interview-preparation#interview-questions#knowledge-graph#langchain#large-language-models#llamaindex#llm#machine-learning#nlp#prompt-engineering#rag#retrieval-augmented-generation#self-rag#vector-database#vector-search
good first issue

A complete collection of RAG interview questions, answers (603 questions & 52 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

Jupyter Notebook
#agentic-rag#ai#deep-learning#generative-ai#graph-rag#interview-preparation#interview-questions#knowledge-graph#langchain#large-language-models#llamaindex#llm#machine-learning#nlp#prompt-engineering#rag#retrieval-augmented-generation#self-rag#vector-database#vector-search