Gmail RAG Assistant: Full Email History with OpenAI & Qdrant

This advanced n8n workflow creates a Retrieval-Augmented Generation (RAG) assistant for your entire Gmail history. It triggers on new emails every minute via Gmail Trigger, fetches full message data, cleans and normalizes content with a Code node (removing line breaks and extra spaces), generates embeddings using OpenAI, and stores them with metadata in a Qdrant vector database collection named 'emails_history'. Batch processing via SplitInBatches handles large inboxes efficiently in chunks of 50.

For interaction, it sets up a RAG Agent that retrieves relevant email snippets from Qdrant using a chat message trigger. The agent, enhanced with Simple Memory for context retention, answers queries conversationally, making past emails instantly searchable. This ensures real-time updates as new emails arrive.

Ideal for support teams surfacing customer histories in chatbots, sales ops needing quick email summaries, or developers building email-powered AI agents. Benefits include time savings on manual searches, improved accuracy via embeddings, scalability for large inboxes, and seamless integration without custom coding. Setup requires n8n instance, Gmail OAuth2 credentials, OpenAI API key, and Qdrant connection.