pchunduri6/rag-demystified
A tutorial project demonstrating how to build RAG pipelines from scratch using LLMs and vector databases.
Not currently ranked — collecting fresh signals.
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This is an educational project that constructs an advanced RAG pipeline from scratch to demystify how these systems work internally. It covers vector retrieval using Faiss, document chunking, and response generation with LLMs like GPT-4, integrating with EvaDB as the application framework. The project explains the mechanics, limitations, and costs behind RAG pipelines, serving as an alternative to opaque frameworks like LlamaIndex and Haystack.
Frequently asked
- What is pchunduri6/rag-demystified?
- A tutorial project demonstrating how to build RAG pipelines from scratch using LLMs and vector databases.
- Is rag-demystified open source?
- Yes — pchunduri6/rag-demystified is open source, released under the Apache-2.0 license.
- What language is rag-demystified written in?
- pchunduri6/rag-demystified is primarily written in Python.
- How popular is rag-demystified?
- pchunduri6/rag-demystified has 858 stars on GitHub.
- Where can I find rag-demystified?
- pchunduri6/rag-demystified is on GitHub at https://github.com/pchunduri6/rag-demystified.