This project aims to build a Retrieval-Augmented Generation (RAG) engine to provide context-aware recommendations based on user queries.
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Updated
Apr 23, 2026 - Python
This project aims to build a Retrieval-Augmented Generation (RAG) engine to provide context-aware recommendations based on user queries.
Using keras and tensorflow as Backend
Explore the evolution of Retrieval-Augmented Generation (RAG) through three progressively sophisticated pipelines built with Langflow: Naive RAG (basic retrieval), Advanced RAG (semantic chunking + re-ranking + hallucination control), and Modular RAG (multi-store routing with LLM-powered query classification).
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