RAG Workflow For Company Documents Stored in Google Drive
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A RAG workflow to query company documents stored in Google Drive.
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About This Workflow
Overview
This workflow implements a Retrieval-Augmented Generation (RAG) system to allow users to query company documents stored in Google Drive. It indexes documents into a Pinecone vector store, enabling efficient retrieval of relevant information to answer user questions using an AI agent.
Key Features
- Indexes documents from Google Drive into Pinecone.
- Utilizes Google Gemini for embeddings and chat model.
- Supports file creation and updates in Google Drive as triggers.
- Provides a chat interface for querying documents.
How To Use
- Ensure your Google Drive and Pinecone credentials are set up in n8n.
- Configure the
Google Drive File CreatedandGoogle Drive File Updatedtriggers to watch the desired folder. - Set up the
Pinecone Vector Storenode to ingest documents. - Connect the
AI Agentnode with theVector Store Toolfor querying. - Use the
When chat message receivedwebhook to interact with the AI agent.
Apps Used
Workflow JSON
{
"id": "10a2b615-0eec-4e3e-b9dd-b1f380a20a12",
"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.
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ID: 10a2b615-0eec...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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