RAG Document QA System: Milvus, Cohere, OpenAI for Google Drive
Monitors Google Drive for new PDFs, extracts text, embeds with Cohere into Milvus, and enables RAG QA agent with OpenAI for intelligent queries.
This n8n workflow builds a Retrieval Augmented Generation (RAG) system that automatically processes new PDF files from a Google Drive folder. It triggers on new files, downloads them, extracts text content, chunks the data, generates embeddings using Cohere, and stores them in a Milvus vector database. This setup powers a conversational AI agent capable of answering queries by retrieving relevant document chunks and generating responses with OpenAI (ChatGPT 4o).
Key benefits include seamless au
- Platform
- n8n
- Category
- Health & Fitness
- Price
- $24.99
- Creator
- Matt Buds
- RAG
- Milvus
- Cohere
- OpenAI
- Google Drive
- PDF Extraction
- Vector Database
- AI Agent
- Document QA
- Retrieval
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 Health & Fitness workflows
- Nutrition Tracker & Meal Logger with Telegram, Gemini AI, and Google Sheets$24.99
- Automated Telegram Command Filtering and Workflow Management$15.04
- Automate Food Calorie Tracking via Telegram with GPT-4 Vision and Google Sheets$4.99
- Automate Personalized Diet Plan Creation from Health Reports via Email$4.99
- Reinforced Learning Chatbot for Enhanced User Support$24.99
- AI-Powered Triathlon Coaching with Strava Data Analysis$9.99
More from Matt Buds
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.