Vector database as a big data analysis tool for AI agents [3/3 - anomaly]

by Jenny ✓ · 3,310 views · created 2024-12-19 · Engineering, AI Summarization

What this workflow does

This workflow has 9 nodes and runs when another workflow calls it. It uses only n8n's built-in nodes. It also calls api.voyageai.com over HTTP.

How it runs

Trigger: When another workflow calls it.

1. Image URL hardcode (Edit Fields (Set)): sets 1 field: imageURL
2. Variables for medoids (Edit Fields (Set)): sets 4 fields: clusterCenterType, qdrantCloudURL, collectionName…
3. Total Points in Collection (HTTP Request): calls an HTTP API (POST)
4. Each Crop Counts (HTTP Request): calls an HTTP API (POST)
5. Info About Crop Labeled Clusters (Edit Fields (Set)): sets or maps fields
6. Embed image (HTTP Request): calls api.voyageai.com (POST)
7. Get similarity of medoids (HTTP Request): calls an HTTP API (POST)
8. Compare scores (Code): runs custom Python code

HTTP calls to: api.voyageai.com

Before you upgrade to n8n 3.0

Nodes used (4)

• HTTP Requestn8n-nodes-base.httpRequest
• Coden8n-nodes-base.code
• Edit Fields (Set)n8n-nodes-base.set
• Execute Workflow Triggern8n-nodes-base.executeWorkflowTrigger

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…

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