Create an intelligent RAG agent to answer questions from Google Drive documents using OpenAI

How it works

1. 1.Receive user query through a webhook endpoint
2. 2.Fetch and load documents from Google Drive, then split them into chunks
3. 3.Convert text chunks into embeddings and store them in Qdrant vector store
4. 4.Initialize an AI agent that searches vector store and queries OpenAI language model
5. 5.Maintain conversation history in memory buffer for contextual responses
6. 6.Return the intelligent answer to the user via HTTP response

Use cases

• Self-service customer support answering from company documentation
• Intelligent legal document search system across contracts and regulations
• Research assistant analyzing scientific papers and comprehensive reports
• Internal knowledge base for employee questions on company policies and procedures

Requirements

• Active OpenAI API account with valid authentication key
• Running Qdrant vector database server or cloud-hosted instance
• Read access to Google Drive folder containing documents to be indexed
• HTTP webhook endpoint to receive and process user queries

Service Value

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