Chat with Google Drive documents using OpenAI and Pinecone RAG search

Description

Try it out

This n8n workflow template lets you chat with your Google Drive documents (.docx, .json, .md, .txt, .pdf) using OpenAI and Pinecone vector database. It retrieves relevant context from your files in real time so you can get accurate, context-aware answers about your proprietary data—without the need to train your own LLM.
Not interested in chunking and embedding your own data or figuring out which search method to use?

Try our n8n quickstart for Pinecone Assistant here or check out the full workflow to chat with your Google Drive documents here.

Prerequisites

A Pinecone account
A GCP project with Google Drive API enabled and configured
An Open AI account and API key
A Cohere account and API key

Setup

Create a Pinecone index in the Pinecone Console here
Name your index n8n-dense-index
Select OpenAI's text-embedding-3-small
Set the Dimension to 1536
Leave everything else as default
If you use a different index name, update the related nodes to reflect this change
Use the Connect to Pinecone button to authenticate to Pinecone or if you self-host n8n, create a Pinecone credential and add your Pinecone API key directly
Setup your Google Drive OAuth2 API, Open AI, and Cohere credentials in n8n
Download these files and add them to a Drive folder named n8n-pinecone-demo in the root of your My Drive
https://docs.pinecone.io/release-notes/2022.md
https://docs.pinecone.io/release-notes/2023.md
https://docs.pinecone.io/release-notes/2024.md
https://docs.pinecone.io/release-notes/2025.md
https://docs.pinecone.io/release-notes/2026.md
Activate the workflow or test it with a manual execution to ingest the documents
Enter the chat prompts to chat with the Pinecone release notes
What support does Pinecone have for MCP?
When was fetch by metadata released?

Ideas for customizing this workflow

Use your own data and adjust the chunking strategy
Update the AI Agent System Message to reflect how the Pinecone Vector Store Tool will be used. Be sure to include info on what data can be retrieved using that tool.
Update the Pinecone Vector Store Tool Description to reflect what data you are storing in the Pinecone index
Need help?

You can find help by asking in the Pinecone Discord community or filing an issue on this repo.