Vector database as a big data analysis tool for AI agents [1/3 anomaly][1/2 KNN]
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 workflow has 13 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Google Cloud Storage. It also calls api.voyageai.com over HTTP.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Qdrant cluster variables (Edit Fields (Set)): sets 4 fields: qdrantCloudURL, collectionName, VoyageEmbeddingsDim…
- Check Qdrant Collection Existence (HTTP Request): calls an HTTP API
- If: checks a condition and branches into true / false
- Google Cloud Storage: work with object
- Create Qdrant Collection (HTTP Request): calls an HTTP API (PUT)
- Get fields for Qdrant (Edit Fields (Set)): sets 1 field: cropName
- Payload index on crop_name (HTTP Request): calls an HTTP API (PUT)
- Filter: keeps only the items that match a condition
- Split in batches, generate uuids for Qdrant points (Code): runs custom Python code
- Batches in the API's format (Edit Fields (Set)): sets 1 field: uuids
…plus 2 more steps. See the full node list below.
Services it uses
HTTP calls to: api.voyageai.com
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)
- Manual Trigger
n8n-nodes-base.manualTrigger - Google Cloud Storage
n8n-nodes-base.googleCloudStorage - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - Code
n8n-nodes-base.code - If
n8n-nodes-base.if - Filter
n8n-nodes-base.filter
From the author
Vector Database as a Big Data Analysis Tool for AI Agents Workflows from the webinar "Build production-ready AI Agents with Qdrant and n8n". This series of workflows shows how to build big data analysis tools for production-ready AI agents with the help of…