--- title: A Step-by-Step Guide to Build a Fast Semantic Search and... description: The post provides a tutorial on building a semantic search and retrieval-augmented generation (RAG) system using Together AI embeddings, FAISS retrieval, and... canonical: https://daily.dev/posts/a-step-by-step-guide-to-build-a-fast-semantic-search-and-rag-qa-engine-on-web-scraped-data-using-tog-iijpwh4cx twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: 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 | daily.dev og:description: The post provides a tutorial on building a semantic search and retrieval-augmented generation (RAG) system using Together AI embeddings, FAISS retrieval, and... og:url: https://daily.dev/posts/a-step-by-step-guide-to-build-a-fast-semantic-search-and-rag-qa-engine-on-web-scraped-data-using-tog-iijpwh4cx og:image: https://api.daily.dev/og/posts/iijPwH4cx.png og:image:alt: 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 og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # 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 **[Machine Learning News](https://daily.dev/sources/mlnews)** · 5 min read · 3 upvotes · 0 comments ## Summary The post provides a tutorial on building a semantic search and retrieval-augmented generation (RAG) system using Together AI embeddings, FAISS retrieval, and LangChain. It explains how to transform web-scraped data into a question-answering service by embedding chunks of text and storing them in a millisecond-level vector index. The modular approach allows flexibility in swapping components while maintaining efficiency through the unified Together AI backend. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#langchain](https://daily.dev/tags/langchain), [#vector-search](https://daily.dev/tags/vector-search) [View this post on daily.dev](https://daily.dev/posts/a-step-by-step-guide-to-build-a-fast-semantic-search-and-rag-qa-engine-on-web-scraped-data-using-tog-iijpwh4cx) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"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","url":"https://daily.dev/posts/a-step-by-step-guide-to-build-a-fast-semantic-search-and-rag-qa-engine-on-web-scraped-data-using-tog-iijpwh4cx","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/a-step-by-step-guide-to-build-a-fast-semantic-search-and-rag-qa-engine-on-web-scraped-data-using-tog-iijpwh4cx"},"datePublished":"2025-05-14T07:14:04.121Z","dateModified":"2025-05-14T07:14:38.752Z","description":"The post provides a tutorial on building a semantic search and retrieval-augmented generation (RAG) system using Together AI embeddings, FAISS retrieval, and...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/314b8274d416eb9e91daaad0d6d70004?_a=AQAEuj9","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/314b8274d416eb9e91daaad0d6d70004?_a=AQAEuj9","isAccessibleForFree":true,"articleSection":"Machine Learning News","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Machine Learning News","logo":"https://media.daily.dev/image/upload/s--0PoEtdkd--/f_auto/v1750409401/squads/marktechpost?_a=BAMClqZW0","url":"https://daily.dev/squads/mlnews"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/a-step-by-step-guide-to-build-a-fast-semantic-search-and-rag-qa-engine-on-web-scraped-data-using-tog-iijpwh4cx","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai,machine-learning,langchain,vector-search","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Machine Learning News","item":"https://daily.dev/squads/mlnews"},{"@type":"ListItem","position":3,"name":"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"}]} ```