Paul Graham essay search & chat with Milvus vector database
Needs changesWhat this workflow does
This AI workflow has 16 nodes and runs manually, when you click “Execute workflow” (plus 1 other trigger). Along the way it connects Milvus Vector Store, Embeddings OpenAI and OpenAI Chat Model. It also calls paulgraham.com over HTTP.
How it runs
Trigger: Manually, when you click “Execute workflow” (plus 1 other trigger).
- Fetch Essay List (HTTP Request): calls paulgraham.com
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; 1 tool (Milvus Vector Store)
- Extract essay names (HTML): parses or builds HTML
- Split Out: splits a list into separate items
- Limit: keeps the first few items
- Fetch essay texts (HTTP Request): calls an HTTP API
- Extract Text Only (HTML): parses or builds HTML
- Milvus Vector Store: stores documents in the Milvus vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
HTTP calls to: paulgraham.com
Scraping pages by hand? Firecrawl is a simpler option (10% off for new users).
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent (v1.9): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.9) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (12)
- Manual Trigger
n8n-nodes-base.manualTrigger - HTTP Request
n8n-nodes-base.httpRequest - HTML
n8n-nodes-base.html - Split Out
n8n-nodes-base.splitOut - Limit
n8n-nodes-base.limit - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Milvus Vector Store
@n8n/n8n-nodes-langchain.vectorStoreMilvus - AI Agent
@n8n/n8n-nodes-langchain.agent - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
From the author
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: 1. Scrape & Load: Fetches Paul Graham essays, extracts…