Retrieval-Augmented Generation (RAG) with SUTRA
This directory contains examples and best practices for implementing Retrieval-Augmented Generation (RAG) systems using SUTRA.
Contents
- RAG architecture patterns
- Vector database integrations
- Document processing pipelines
- Query optimization techniques
- Evaluation frameworks
Key Concepts
- Document chunking and embedding
- Semantic search implementation
- Context augmentation strategies
- Hybrid retrieval approaches
Use Cases
- Question answering over private data
- Knowledge base assistants
- Document summarization
- Factual grounding for LLM outputs