Survey Insights with 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 Survey Insights scenario where survey participant responses can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, researchers can save days and even weeks of work breaking down cohorts of participants and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vT6m8XH8JWJTUAfwojc68NAUGC7q0lO7iV738J7aO5fuVjiVzdTRRPkMmT1C4N8TwejaiT0XrmF1Q48/pubhtml How it works All survey questions and response

Help me set up the n8n workflow "Survey Insights with Qdrant, Python and Information Extractor" (https://n8n.io/workflows/2372). It uses: Google Sheets, HTTP Request, 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.