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RAG & Knowledge Bases

Store Reviews in Qdrant for Clustering and Sheets

When you run it or another workflow calls it, it extracts reviews from a zip, embeds them with OpenAI into Qdrant and logs results to Google Sheets.

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What it does

## Step 3. Store Reviews in Qdrant [Learn more about the Qdrant Vector Store]({{ $env.WEBHOOK_URL }} Vector databases are a great way to store data if you're interested in perform similiarity searches which applies here as we want to group similar reviews to find patterns. Qdrant is a powerful vector database and tool of choice because of its robust API implementation and advanced filtering capabilities.

The steps

  1. When clicking ‘Test workflow’
  2. Zip Entries
  3. Extract Reviews
  4. Reviews to List
  5. Default Data Loader
  6. Recursive Character Text Splitter
  7. Embeddings OpenAI
  8. Set Variables
  9. Get Payload of Points
  10. Clusters To List
  11. OpenAI Chat Model
  12. Only Clusters With 3+ points
  13. Set Variables1
  14. Find Reviews

64 steps in total.

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