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Medical Q&A Chatbot for Urology using RAG with Pinecone and GPT-4o

Medical Q&A Chatbot for Urology using RAG with Pinecone and GPT-4o

Live
Open / InstallLast updated July 27, 2026

Description

Medical Q&A Chatbot for Urology using RAG with Pinecone and GPT-4o This template provides an AI-powered Q&A assistant for the Urology domain using Retrieval-Augmented Generation (RAG). It uses Pinecone for vector search and GPT-4o for conversational responses. 🧠 Use Case This chatbot is designed for clinics or medical pages that want to automate question answering for Urology-related conditions. It uses a vector store of domain knowledge to return verified responses. šŸ”§ Requirements āœ… OpenAI API key (GPT-4o or GPT-4o-mini) āœ… Pinecone account with an active index āœ… Verified Urology documents embedded into Pinecone āš™ļø Setup Instructions Create a Pinecone vector index and connect it using the Pinecone credentials node. Upload Urology-related documents to embed using the Create Embeddings for Urology Docs node. Customize the chatbot system message to reflect your medical specialty. Deploy this chatbot on your website or link it with Telegram via the chat trigger node. šŸ› ļø Components chatTrigger: Listens for user messages and starts the workflow. Medical AI Agent: GPT-based agent guided by domain-specific instructions. RAG Tool Vector Store: Fetches relevant documents from Pinecone using vector search. Memory Buffer: Maintains conversation context. Create Embeddings for Urology Docs: Encodes documents into vector format. šŸ“ Customization You can replace the knowledge base with any other medical domain by: Updating the documents stored in Pinecone. Modifying the system prompt in the AI Agent node. šŸ“£ CTA This chatbot is ideal for clinics, medical consultants, or educational websites wanting a reliable AI assistant in Urology. An n8n automation workflow template by HoangSP.

Author

HoangSP

Platform

web

Pricing model

free

Categories

Automation
AI

Tags

n8n
workflow
ai-agent
embeddings-openai
openai-chat-model
simple-memory
pinecone-vector-store
vector-store-question-answer-tool

Capabilities

  • 6 nodes
  • 2,637 views