Community Insights using Qdrant, Python and Information Extractor

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights This template demonstrates the Community Insights scenario where HN commments can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, Researchers or HN users can quickly breakdown community consensus on a particular topic and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vQXaQU9XxsxnUIIeqmmf1PuYRuYtwviVXTv6Mz9Vo6a4ty-XaJHSeZsptjWXS3wGGDG8Z4u16rvE7l/pubhtml How it works HN comments are imported via the Hacknews API

Help me set up the n8n workflow "Community Insights using Qdrant, Python and Information Extractor" (https://n8n.io/workflows/2374). It uses: Google Sheets, HTTP Request, Hacker News, Code, Embeddings OpenAI, OpenAI Chat Model, Recursive Character Text Splitter, Default Data Loader, Qdrant Vector Store. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.