Match medical symptoms to products with OpenAI, Qdrant & Google Sheets RAG
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 13 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Qdrant Vector Store, Embeddings OpenAI, OpenAI Chat Model and Google Sheets.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- RAG Agent (AI Agent): runs an AI agent, with model: OpenAI LLM; 1 tool (Get data from Qdrant database); memory: Store Chats
- Get all products (Google Sheets): uses Google Sheets
- Loop over each product (Loop Over Items (Split in Batches)): loops over the items in batches
- Qdrant Vector Database (Qdrant Vector Store): uses the Qdrant vector store, with embeddings: Create Embedding; document loader: Set Data Properly in vector database
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in RAG Agent (v1.7): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) RAG Agent (v1.7) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (11)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Manual Trigger
n8n-nodes-base.manualTrigger - Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Google Sheets
n8n-nodes-base.googleSheets
From the author
🧠 RAG AI Medical Agent – n8n Workflow 👥 Who’s it for This workflow is perfect for: - Healthcare ecommerce businesses that want to automate product recommendations. - Founders or developers building an AI assistant using retrieval-augmented generation (RAG)…