Find the most relevant workflow templates using RAG, Qdrant and Gemini

🤖 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 based on meaning, not just keywords.

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⚙️ How it works

1. Collect workflow templates from the n8n API using multiple search queries 2. Process and clean the data (split, format, deduplicate) 3. Convert workflows into embeddings using Gemini 4. Store embeddings in a vector database (Qdrant) 5. Accept user queries via chat interface 6. Convert queries into embeddings 7. Retrieve relevant workflows using semantic search 8. Generate AI-powered recommendations with explanations and template links

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🚀 What this workflow does