RAG with andOpenAI

How it works

1. 1.Trigger the workflow manually or via webhook request
2. 2.Load documents from Google Drive and split them into manageable chunks using Text Splitter
3. 3.Convert text passages into embeddings via OpenAI model and store in Qdrant vector database
4. 4.Execute intelligent agent that retrieves relevant documents and calls language model for response generation
5. 5.Maintain conversation history to ensure continuity and context in dialogue
6. 6.Send response to client through webhook or HTTP endpoint

Use cases

• Build an intelligent assistant that answers employee questions about company policies stored in Google Drive
• Create an automated customer support system extracting information from product databases and procedures
• Develop a knowledge search engine that understands context and retrieves accurate answers from internal documentation

Requirements

• Valid OpenAI API key for accessing embedding and language models
• Authenticated Google Drive connection containing documents to analyze
• Running Qdrant server for vector storage and retrieval operations

Service Value

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