Loading JSON via FTP to Qdrant vector database embedding pipeline
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 8 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Qdrant Vector Store and Embeddings OpenAI.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- List all the files (FTP): list
- Loop over one item (Loop Over Items (Split in Batches)): loops over the items in batches
- Downloading item (FTP): uses FTP
- Qdrant Vector Store: stores documents in the Qdrant vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
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 (7)
- Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Manual Trigger
n8n-nodes-base.manualTrigger - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter - FTP
n8n-nodes-base.ftp - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches
From the author
🧠 This workflow is designed for one purpose only, to bulk-upload structured JSON articles from an FTP server into a Qdrant vector database for use in LLM-powered semantic search, RAG systems, or AI assistants. The JSON files are pre-cleaned and contain…