Paul Graham Essay Search & Chat with Milvus Vector DB
Creates a RAG system to scrape Paul Graham essays, embed them in Milvus vector DB, and enable semantic search with AI chat.
This n8n workflow implements a Retrieval-Augmented Generation (RAG) pipeline for Paul Graham's essays. It starts by scraping the essay list from paulgraham.com, extracts content, generates vector embeddings, and stores them in a Milvus vector database. Once loaded, users can perform semantic searches and engage in AI-powered conversations about the essays via an integrated chat interface.
Key benefits include efficient knowledge retrieval without manual indexing, scalable vector search for prec
- Platform
- n8n
- Category
- File & Document Management
- Price
- $19.99
- Creator
- Vera Petrenko
- Milvus
- RAG
- Vector Database
- Semantic Search
- AI Agent
- Paul Graham
- Essay Scraping
- Chatbot
- Knowledge Base
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
Related File & Document Management workflows
- Automate Invoice Data Extraction to Airtable with OCR and AI$14.99
- Automate PDF Invoice Creation from Google Sheets Using PDF.co$4.99
- Create Custom PDF Documents from Templates with Gemini & Google Drive$24.99
- Automatically Save and Organize Outlook Email Attachments in OneDrive Folders$9.99
- Automate Invoice Data Extraction from Google Drive to Google Sheets with Mistral OCR$14.99
- Convert Files to Markdown with Datalab.to API in n8n$9.99
More from Vera Petrenko
Need this deployed? We'll set it up for you.
Our automation experts deploy this workflow in your stack, connect your accounts, and verify it works — or build a custom solution from scratch.