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