Chat with Google Drive Documents using GPT, Pinecone, and RAG

📌 Short Overview

Automatically sync files from Google Drive into a searchable AI knowledge base with Pinecone, and answer user queries using GPT-4o with conversational memory.

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🛠️ Workflow Usage Steps

1. Watch Google Drive for file changes

Trigger the workflow when a new file is uploaded or an existing file is updated in a specific Google Drive folder.

2. Download and process the file

Retrieve the file, split it into smaller text chunks with a Recursive Character Text Splitter, and generate vector embeddings using OpenAI.

3. Store embeddings in Pinecone

Save the embeddings in a Pinecone vector database to keep your knowledge base continuously updated and searchable.

4. Search context for chat queries

When a user asks a question, query Pinecone for relevant context, combine results with conversational memory, and process them with GPT-4o.

5. Respond with AI-powered answers

Provide a concise response (100–200 words) that blends knowledge from your documents with the conversation history.

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✅ Use Cases

• Keep a live, AI-ready knowledge base from your Google Drive files.
• Enable team members to query company documents instantly.
• Build a personal assistant that stays up to date with your latest uploads.

⚙️ Setup Steps

1. Google Drive
   • Create a Google Cloud project.
   • Enable the Google Drive API.
   • Generate OAuth credentials and connect them in n8n.
2. OpenAI
   • Sign up at OpenAI.
   • Copy your API key from the dashboard.
   • Add it to n8n under Credentials → OpenAI API.
3. Pinecone
   • Create an account at Pinecone.
   • Create a new index (e.g., docs-embeddings).
   • Copy your API key and environment, then add them to n8n under Credentials → Pinecone API.
4. Workflow Configuration
   • Import this workflow into your n8n instance.
   • Select the Google Drive folder you want to monitor.
   • Set the Pinecone index name in the workflow.
   • Adjust chunk size / overlap in the text splitter if needed.
5. Test the Workflow
   • Upload a new document to your Google Drive folder.
   • Run the workflow to confirm embeddings are created and stored in Pinecone.
   • Ask a sample query and verify the AI returns a context-aware answer.