Medical Records AI Chatbot: Google Drive, Llama 3 & Qdrant RAG

This n8n workflow sets up a powerful document-based AI chatbot tailored for healthcare, specifically medical records stored in Google Drive. It automatically detects new files via a Google Drive trigger, downloads them, splits text into chunks with a Recursive Text Splitter, generates embeddings using Ollama's Nomic-Embed model, and stores them in Qdrant vector database for efficient retrieval. When users query via the Chat Trigger, the AI Agent searches Qdrant for relevant context and generates human-like responses powered by Llama 3, ensuring source-backed accuracy.

The key benefits include overcoming limitations of static AI models by providing real-time access to up-to-date medical documents, reducing manual search time, minimizing errors in information retrieval, and enhancing compliance with context-aware answers. It saves hours of administrative work in healthcare settings by automating knowledge extraction and delivery.

Ideal use cases: Query patient histories or treatment protocols from shared Drive folders; support clinical research by summarizing studies; assist doctors with instant drug interaction checks from internal docs; power patient portals for secure, AI-driven record access; streamline compliance audits with precise document referencing.

Setup is straightforward: Configure Google Drive credentials and folder watch, set Qdrant connection, deploy Ollama/Llama 3 instances, and activate the chat interface for immediate use in medical practices.