Screening papers for a literature review

The scenario reads PDFs from Google Drive, rates each paper against your criteria, sorts the fits by theme into Postgres PGVector Store and Supabase, and sets the rejects aside.

  • Screening papers by strict criteria
  • Rated without reading each in full
  • Sorted into sub-themes
  • Search by meaning in Postgres PGVector Store
Default Data LoaderEmbeddings Google GeminiQdrant Vector Store
Connect Postgres PGVector Store and goScriptera

How it works

To move data from Google Drive to Supabase automatically, use a ready-made scenario — no manual exports.

  1. Starts when: When clicking ‘Execute workflow’
  2. Then: Search files and folders
  3. Check: Loop Over Items
  4. Then: Download PDF
  5. Then: Extract PDF Text
  6. Then: Cut of bibliography
  7. Then: SLR Agent
  8. Check: If
  9. If yes: Scoring Agent
  10. Check: Route to sub topic
  11. If yes: Vector Store - collection 1
  12. Then: Move file to included folder2
  13. If no: Vector Store - collection 2
  14. Then: Move file to included folder1
  15. If no: Vector Store - collection 3
  16. Then: Move file to included folder
  17. Then: Log Included folder
  18. If no: Log Excluded Paper
  19. Then: Move file to Excluded Folder
  20. Then: Default Data Loader
  21. Then: Default Data Loader1
  22. Then: Default Data Loader2
  23. Then: Embeddings Google Gemini
  24. Then: Embeddings Google Gemini1
  25. Then: Embeddings Google Gemini2
  26. Then: Structured Output Parser
  27. Then: Google Gemini Chat Model1
  28. Then: Structured Output Parser1
  29. Then: Google Gemini Chat Model3
  30. Then: OpenAI Chat Model
  31. Then: OpenAI Chat Model1

You can launch this Google Drive + Supabase integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.

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