AI-Powered Urology & Andrology Q&A Assistant with RAG
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Empower your urology and andrology practice with an intelligent AI assistant. This workflow leverages Retrieval Augmented Generation (RAG) with GPT-4o and Pinecone to provide accurate, context-aware answers to patient inquiries, enhancing patient engagement and streamlining communication.
About This Workflow
This n8n workflow creates a sophisticated AI assistant specifically trained for Urology and Andrology. When a user sends a chat message, the system activates GPT-4o to process the query. It then intelligently retrieves relevant medical information from a Pinecone vector database, ensuring answers are grounded in factual, expert-vetted data. The AI is designed to provide clear, friendly, and medically relevant responses, avoiding speculation and prioritizing user understanding. It maintains conversational context through session memory, allowing for multi-turn dialogues and personalized interactions. The system also includes built-in directives for handling situations where information is insufficient, ensuring responsible AI deployment.
Key Features
- Expert Medical Knowledge Base: Powered by a curated Urology and Andrology dataset stored in Pinecone.
- Intelligent Q&A: Utilizes GPT-4o for natural language understanding and response generation.
- Retrieval Augmented Generation (RAG): Ensures answers are based solely on verified data, minimizing misinformation.
- Contextual Conversations: Maintains session memory for seamless, multi-turn dialogues.
- Customizable AI Persona: Configurable system messages to tailor tone, style, and response guidelines.
How To Use
- Configure the Chat Trigger: Set up the 'When chat message received' node to establish your public webhook and define initial messages.
- Set up AI Agent Logic: Connect the 'AI Agent' node to define the core AI instructions, including system messages for tone, style, and response guidelines.
- Integrate OpenAI Chat Model: Configure the 'OpenAI Chat Model' nodes (GPT-4o-mini recommended) for processing and generating responses.
- Implement Vector Store Search: Link the 'Answer questions with a vector store' node to your Pinecone index ('namkhoaa2z' in this example) and specify its description.
- Connect Pinecone Vector Store: Configure the 'Pinecone Vector Store' node with your Pinecone API credentials and select the appropriate index.
- Configure Embeddings: Set up the 'Embeddings OpenAI' node to handle the vectorization of data for the Pinecone store.
- Enable Session Memory: Utilize the 'Simple Memory' node, linking it to session IDs to maintain conversational context across user interactions.
Apps Used
Workflow JSON
{
"id": "a31ec3d2-b6b0-40ac-94a9-378c72330950",
"name": "AI-Powered Urology & Andrology Q&A Assistant with RAG",
"nodes": 14,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: a31ec3d2-b6b0...
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