RAG Workflow for Company Documents Stored in Google Drive

Name: RAG Workflow for Company Documents Stored in Google Drive
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Author: Free N8N

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AI & Machine LearningAI AgentDocument RetrievalGoogle DriveGoogle GeminiKnowledge BasePineconeRAG

Automate RAG for your company's internal documents stored in Google Drive. This workflow ingests new or updated files, processes them into embeddings, and stores them in Pinecone for efficient retrieval by an AI agent.

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About This Workflow

Overview

This n8n workflow enables a Retrieval Augmented Generation (RAG) system for your company's internal documents stored within Google Drive. It's triggered by new or updated files, processes them using Google Gemini embeddings, splits them into manageable chunks, and stores them in a Pinecone vector store. This makes the documents searchable and usable by an AI agent for answering questions.

Key Features

Triggered by Google Drive file creation and updates.
Utilizes Google Gemini for text embedding.
Stores document embeddings in Pinecone for efficient retrieval.
Splits documents into manageable chunks for better AI processing.
Includes an AI Agent node for answering questions based on retrieved documents.

How To Use

Set up Google Cloud Project and Vertex AI API: Create a Google Cloud project and enable the Vertex AI API.
Obtain Google AI API Key: Get an API key from Google AI Studio.
Set up Pinecone Account: Create a Pinecone account, obtain your API key, and create an index named 'company-files'.
Configure Google Drive Folder: Create a dedicated folder in Google Drive for company documents.
Configure n8n Credentials: Set up credentials for Google Drive OAuth2, Google Gemini(PaLM) API, and Pinecone API in your n8n instance.
Import and Configure Workflow: Import this workflow into n8n. Update the Google Drive Trigger nodes to watch your designated Google Drive folder and configure the Pinecone nodes to use your 'company-files' index.

Apps Used

AI Agent

Document Retrieval

Google Drive

Google Gemini

Knowledge Base

Pinecone

RAG

Workflow JSON

{
  "id": "dae5b4f8-b56d-471f-867e-bb1475f3e561",
  "name": "RAG Workflow for Company Documents Stored in Google Drive",
  "nodes": 0,
  "category": "AI & Machine Learning",
  "status": "active",
  "version": "1.0.0"
}

Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.