Building Enterprise RAG Systems with PostgreSQL - A Comprehensive Implementation Guide

Building Enterprise RAG Systems with PostgreSQL - A Comprehensive Implementation Guide

Trelis Research via YouTube Direct link

- Database setup and configuration

16 of 30

16 of 30

- Database setup and configuration

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Building Enterprise RAG Systems with PostgreSQL - A Comprehensive Implementation Guide

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  1. 1 - Introduction to RAG and Postgres implementation
  2. 2 - Background on using Postgres vs third-party services
  3. 3 - Overview of PG vector and PG best match
  4. 4 - Video structure outline
  5. 5 - Demo of RAG application
  6. 6 - Document upload and chunking process
  7. 7 - Data collation and vector/text search explanation
  8. 8 - Speed optimization using Cerebras/Groq
  9. 9 - Advantages of using Postgres
  10. 10 - Vector vs text search comparison
  11. 11 - Combining search methods
  12. 12 - Performance comparison data
  13. 13 - Vector search explanation
  14. 14 - Text search and BM25 explanation
  15. 15 - Postgres tools overview
  16. 16 - Database setup and configuration
  17. 17 - Basic RAG implementation
  18. 18 - Document embedding process
  19. 19 - Search implementation
  20. 20 - Advanced features:
  21. 21 - BM25 optimization
  22. 22 - Text processing improvements
  23. 23 - Asynchronous database calls
  24. 24 - Performance evaluation
  25. 25 - Command line interface setup
  26. 26 - Document chunking strategies
  27. 27 - Batch processing implementation
  28. 28 - Search functionality demo
  29. 29 - Final implementation review
  30. 30 - Conclusion and resources

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