The RAG Process at a Glance
Data Ingestion
Prepare, clean, and index source data
Retrieval
Find and rank relevant information
Generation
Create and improve responses
Key Benefits of RAG
Reduced Hallucinations
Ground responses in factual data rather than training data memorization
Up-to-date Information
Access fresh data not available during model training
Source Attribution
Provide citations and evidence for generated content
Domain Specialization
Enhance performance on specific topics without fine-tuning