Overview
Simple RAG Document QA is a lightweight Retrieval-Augmented Generation (RAG) project that answers user questions using information retrieved from a local document. The project demonstrates the complete RAG pipeline, including text preprocessing, lemmatization, document chunking, Hugging Face embeddings, FAISS vector search, and local Llama 3.1 gene
Pricing
Free
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Features
Answer questions from local documents
Preprocess document text
Lemmatize text before retrieval
Split documents into chunks
Generate Hugging Face embeddings
Search vectors with FAISS
Generate answers with local Llama 3.1
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