Build a Zero-Cost RAG Pipeline for PDFs (FAISS + Hugging Face)

Build a retrieval-augmented generation pipeline without paying for tools. Turn PDFs into grounded answers using a simple RAG workflow. This video breaks down how to build a zero-cost RAG engine that can read PDF documents, retrieve the most relevant chunks for a query, and generate a response that uses that retrieved context. The focus is on practical steps: chunking, embeddings, vector search, and generation. This is for US learners building AI prototypes, data/ML students, and developers who want document Q&A without relying on paid vector databases. It helps solve the common problem of LL…