Create a RAG system with Paul Essays, Milvus, and OpenAI for cited answers
Create a RAG System with Paul Essays, Milvus, and OpenAI for Cited Answers This workflow automates the process of creating a document-based AI retrieval system using Milvus, an open-source vector database. It consists of two main steps: 1. Data collection/processing 2. Retrieval/response generation The system scrapes Paul Graham essays, processes them, and loads them into a Milvus vector store. When users ask questions, it retrieves relevant information and generates responses with citations. St
At a glance
Create a RAG system with Paul Essays, Milvus, and OpenAI for cited answers is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects OpenAI. It's free to download. Follow the 5-step import below to go live in minutes.
- Platform
- n8n
- Connects
- OpenAI
- Modules
- 20
- Price
- Free
- Version
- v1.0

About this workflow
Create a RAG System with Paul Essays, Milvus, and OpenAI for Cited Answers This workflow automates the process of creating a document-based AI retrieval system using Milvus, an open-source vector database. It consists of two main steps: 1. Data collection/processing 2. Retrieval/response generation The system scrapes Paul Graham essays, processes them, and loads them into a Milvus vector store. When users ask questions, it retrieves relevant information and generates responses with citations. Step 1: Data Collection and Processing 1. Set up a Milvus server using the official guide 2. Create a collection named "mycollection" 3. Execute the workflow to scrape Paul Graham essays: - Fetch essay lists - Extract names - Split content into manageable items - Limit results (if needed) - Fetch texts - Extract content - Load everything into Milvus Vector Store This step uses OpenAI embeddings for vectorization. Step 2: Retrieval and Response Generation When a chat message is received, the system: Sets chunks to send to the model Retrieves relevant information from the Milvus Vector Store Prepares chunks Answers the query based on those chunks Composes citations Generates a comprehensive response This process uses OpenAI embeddings and models to ensure accurate and relevant answers with proper citations. For more information on vector databases and similarity search, visit Milvus documentation.
How to import this n8n workflow
- 1
Download the workflow JSON file after purchase.
- 2
Open n8n → click the menu → Import from File.
- 3
Select the downloaded JSON and import.
- 4
Set up credentials for each node that requires them.
- 5
Click Execute Workflow to test, then activate.
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