AI Agents

Automate Google Drive

14 nodes 243 116 Automatic trigger
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Workflow Description

A template that integrates an AI agent with Google Drive for automated document processing. Extracts text content, segments it, stores it in a vector database, and answers user queries through an intelligent chat interface powered by advanced language models.

How it works

  1. 1.Monitor Google Drive folders and trigger the workflow when new files are uploaded
  2. 2.Extract document content and split it into manageable text chunks for processing
  3. 3.Generate embedding vectors for text segments and store them in Pinecone vector database
  4. 4.Process user queries through the chat interface using Gemini language model
  5. 5.Search the vector store and retrieve relevant content to provide accurate responses

Use cases

  • Intelligent search engine for Google Drive documents that instantly answers user questions
  • Automated processing of reports and contracts to extract and classify key information
  • Virtual assistant supporting your team in answering document-related queries

Requirements

  • Google account with access permissions to Google Drive
  • Pinecone API key for vector storage
  • Gemini and Open Router credentials for language models
  • Text documents in supported formats (PDF, Word, plain text)

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

AI Agent Google Drive Vector Store Gemini Document Default Data Loader Text Splitter Chat Trigger Lm Chat Open Router

Details

Trigger Automatic trigger
Nodes 14
Apps 8
Views 243
Downloads 116

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (14)

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AI Agent

Agent

#1

Monitor Google Drive for New Files

Google Drive Trigger

#2

Download File from Google Drive

Google Drive

#3

Extract PDF Content

Extract From File

#4

Insert Document into Pinecone Vector Store

Vector Store Pinecone

#5

Generate Document Embeddings (Google Gemini)

Gemini Model

#6

Clean and Normalize PDF Text

Code

#7

Load Document Data for Processing

Document Default Data Loader

#8

Split Document Text into Chunks

Text Splitter Recursive Character Text Splitter

#9

Chat Message Trigger

Chat Trigger

#10

Retrieve Relevant Documents from Pinecone

Vector Store Pinecone

#11

Generate Query Embeddings (Google Gemini)

Gemini Model

#12

Generate Chat Prompt with Context

Code

#13

OpenRouter Chat Model Interface

Lm Chat Open Router

#14