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Paul Graham Essay Search & Chat with Milvus Vector Database

by Cheney Zhangadapted from n8n official workflow galleryUpdated Aug 2026
RequiresAAI AgentDDefault Data LoaderEmbeddings OpenAIEmbeddings OpenAIHTMLHTMLHTTP RequestHTTP RequestMilvus Vector StoreMilvus Vector StoreOpenAI Chat ModelOpenAI Chat ModelRecursive Character Text SplitterRecursive Character Text Splitter
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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…TSRecursive Character Text Splitter1Recursive Chara…VSMilvus Vector StoreMilvus Vector S…AgAI AgentChWhen chat message receivedWhen chat messa…DDDefault Data LoaderDefault Data Lo…VSMilvus Vector Store as toolMilvus Vector S…Embeddings OpenAIEmbeddings Open…OpenAI Chat ModelOpenAI Chat Mod…Embeddings OpenAI1Embeddings Open…12345678910
1/5
FLOWS
STEPS · 10
Run manually by an operator

Paul Graham Essay Search & Chat with Milvus Vector Database How It Works This workflow creates a RAG (Retrieval-Augmented Generation) system using Milvus vector database to search Paul Graham essays: Scrape & Load: Fetches Paul Graham essays, extracts text, and stores them as vector embeddings in Milvus Chat Interface: Enables semantic search and AI-powered conversations about the essays Set Up Steps Set up Milvus server following the official installation guide, then create a collection Execute the workflow to scrape essays and load them into your Milvus collection Chat with the AI agent using the Milvus tool to query and discuss essay content

Tags

n8nreference-onlyagentdocument-default-data-loaderembeddings-open-aihtmllm-chat-open-aitext-splitter-recursive-character-text-splittervector-store-milvus
Connects
AAI AgentDDefault Data LoaderembeddingsopenaiEmbeddings OpenAIhtmlHTMLWHTTP RequestmilvusvectorstoreMilvus Vector Store
CategoryAI Automation
Triggermanual
Complexitycomplex
Nodes16
AddedApr 16, 2025

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