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Create a Paul Graham Essay Q&A System with OpenAI and Milvus Vector Database

by Cheney Zhangadapted from n8n official workflow galleryUpdated Aug 2026
RequiresDDefault Data LoaderEmbeddings OpenAIEmbeddings OpenAIHTMLHTMLHTTP RequestHTTP RequestMilvus Vector StoreMilvus Vector StoreOpenAI Chat ModelOpenAI Chat ModelQuestion and Answer ChainQuestion and Answer ChainRecursive Character Text SplitterRecursive Character Text SplitterVector Store RetrieverVector Store Retriever
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OpenAI Chat ModelOpenAI Chat Mod…MaWhen clicking "Execute Workflow"When clicking "…HRFetch Essay ListHtExtract essay namesExtract essay n…SOSplit out into itemsSplit out into …HRFetch essay textsFetch essay tex…LiLimit to first 3HtExtract Text OnlyExtract Text On…ChWhen chat message receivedWhen chat messa…VSMilvus Vector StoreMilvus Vector S…DDDefault Data LoaderDefault Data Lo…Embeddings OpenAIEmbeddings Open…TSRecursive Character Text SplitterRecursive Chara…Embeddings OpenAI1Embeddings Open…VSMilvus Vector Store1Milvus Vector S…CRQ&A Chain to Retrieve from Milvus and Answer QuestionQ&A Chain to Re…RVMilvus Vector Store RetrieverMilvus Vector S…12345
1/5
FLOWS
STEPS · 5
Starts from a chat message

Create a Paul Graham Essay Q&A System with OpenAI and Milvus Vector Database How It Works This workflow creates a question-answering system based on Paul Graham essays. It has two main steps: Data Collection & Processing: Scrapes Paul Graham essays Extracts text content Loads them into a Milvus vector store Chat Interaction: Provides a question-answering interface using the stored vector embeddings Utilizes OpenAI embeddings for semantic search Set Up Steps Set up a Milvus server following the official guide Create a collection named "my_collection" Run the workflow to scrape and load Paul Graham essays Start chatting with the QA system The workflow handles the entire process from fetching essays, extracting content, generating embeddings via OpenAI, storing vectors in Milvus, and providing retrieval for question answering.

Tags

n8nreference-onlychain-retrieval-qadocument-default-data-loaderembeddings-open-aihtmllm-chat-open-airetriever-vector-storetext-splitter-recursive-character-text-splittervector-store-milvus
Connects
DDefault Data LoaderembeddingsopenaiEmbeddings OpenAIhtmlHTMLWHTTP RequestmilvusvectorstoreMilvus Vector StoreopenaichatmodelOpenAI Chat Model
CategoryAI Automation
Triggermanual
Complexitycomplex
Nodes17
AddedApr 16, 2025

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