Find the most relevant workflow templates using RAG, Qdrant and Gemini
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 18 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Qdrant Vector Store, Embeddings Google Gemini and Google Gemini Chat Model. It also calls api.n8n.io over HTTP.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- AI Agent: runs an AI agent, with model: LLM (Gemini Chat Model); 1 tool (Retriever (Qdrant)); memory: Conversation Memory
- Generate Search Queries (Code): runs custom JavaScript code
- Split Queries (Split Out): splits a list into separate items
- Prepare Search Params (Edit Fields (Set)): sets 3 fields: search, page, maxPages
- Fetch Templates from n8n API (HTTP Request): calls api.n8n.io
- Check If Results Exist (If): checks a condition and branches into true / false
- Split Workflows (Split Out): splits a list into separate items
- Format for Embedding (Content + Metadata) (Code): runs custom JavaScript code
- Remove Duplicate Templates (Code): runs custom JavaScript code
- Store in Vector DB (Qdrant) (Qdrant Vector Store): stores documents in the Qdrant vector store, with embeddings: Generate Embeddings; document loader: Load Documents for Embedding
Services it uses
HTTP calls to: api.n8n.io
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (13)
- Manual Trigger
n8n-nodes-base.manualTrigger - Code
n8n-nodes-base.code - Split Out
n8n-nodes-base.splitOut - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - If
n8n-nodes-base.if - Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Embeddings Google Gemini
@n8n/n8n-nodes-langchain.embeddingsGoogleGemini - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow
From the author
🤖 AI Workflow Recommender (RAG + Qdrant + Gemini) This workflow helps users find the most relevant n8n templates using AI. It combines Retrieval-Augmented Generation (RAG), vector search (Qdrant), and Gemini to understand user intent and recommend workflows…