Document Q&A RAG System: OpenAI, Pinecone & Google Drive
Builds a Retrieval-Augmented Generation (RAG) system to load PDFs from Google Drive, embed with OpenAI, store in Pinecone, and enable natural language Q&A for documents like contracts and policies.
This n8n workflow creates an AI-powered Document Q&A system using Retrieval-Augmented Generation (RAG). It automates ingesting PDF documents from Google Drive, splitting them into chunks, generating vector embeddings with OpenAI's text-embedding-3-small model, and storing them in Pinecone Vector DB for semantic search. A second flow (via webhook) enables natural language querying, retrieving relevant chunks and generating answers with OpenAI GPT.
Key benefits include effortless document managem
Platform
n8n
Category
Finance
Price
$24.99
Creator
Jordi Faber
RAG
OpenAI
Pinecone
Google Drive
Vector Database
Document QA
AI Chatbot
Semantic Search
PDF Processing
Finance Automation
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.