A comprehensive course on building production-ready RAG (Retrieval Augmented Generation) systems

This repository contains all the code and datasets used in the Search for RAG course. Guest speakers are encouraged to contribute their code, notebooks, and datasets by raising a PR to the respective folders.

• 01 RAG Evals 🔍

  • Understanding RAG metrics and evaluation frameworks
  • Setting up evaluation pipelines
  • Best practices for RAG testing

• 02 Query Understanding 💭

  • Query analysis techniques
  • Query expansion and reformulation
  • Handling different query types and intents

• 03 Jerry Liu 🏗️

  • Hybrid search approaches
  • Multi-stage retrieval
  • Custom retrievers and rankers

• 04 Ofer ⚡

  • Performance optimization strategies
  • Caching and indexing techniques
  • Scaling RAG systems

• 05 Automatic Prompting 🤖

  • Dynamic prompt generation
  • Prompt optimization techniques
  • Automated prompt testing

• 06 Working with Complex Docs 📄

  • Handling structured and unstructured documents
  • Document chunking strategies
  • Multi-modal document processing

• 07 Aditya Gushwork 🏢

  • Enterprise-grade RAG implementations
  • Security and compliance considerations
  • Integration patterns

• 08 John Gilhuly 🚀

  • Deployment strategies
  • Monitoring and observability
  • Production best practices

• 09 Neural IR 🧠

  • Neural search architectures
  • Dense retrievers
  • Cross-encoders and bi-encoders

• 10 Testset Generation 🧪

  • Synthetic data generation
  • Test set validation
  • Quality assurance techniques

• 11 Embedding Models 🔤

  • Understanding embedding spaces
  • Model selection and fine-tuning
  • Multi-modal embeddings

• 12 Vectorsearch Tricks 🎯

  • Advanced indexing techniques
  • Query optimization
  • Performance tuning

• 13 Shreya Shankar 🏗️

  • System architecture patterns
  • Scalability considerations
  • Error handling and recovery

• 14 Atita Arora 🎯

  • Industry-specific implementations
  • Custom knowledge bases
  • Specialized retrieval techniques

• 15 Text Profiling 📊

  • Text classification
  • Content analysis
  • Metadata extraction

• 16 Alberto Romero 🔮

  • Emerging trends
  • Research directions
  • Future applications

• Lab01 Finance Bench 💰
  • Finance-specific RAG implementations
• Office Hours 🎥
  • Recordings and materials from office hours