A Step-by-Step Guide to Build a Fast Semantic Search and RAG QA Engine on Web-Scraped Data Using Together AI Embeddings, FAISS Retrieval, and LangChain

A Step-by-Step Guide to Build a Fast Semantic Search and RAG QA Engine on Web-Scraped Data Using Together AI Embeddings, FAISS Retrieval, and LangChain

In this tutorial, we lean hard on Together AI’s growing ecosystem to show how quickly we can turn unstructured text into a question-answering service that cites its sources. We’ll scrape a handful of live web pages, slice them into coherent chunks, and feed those chunks to the togethercomputer/m2-bert-80M-8k-retrieval embedding model. Those vectors land in a FAISS index for millisecond similarity search, after which a lightweight ChatTogether mo…