RAG (Retrieval-Augmented Generation)

RAG is a technique that combines the power of LLMs with external knowledge retrieval. This method allows the model to access and incorporate relevant information from a curated knowledge base, improving the accuracy and factual correctness of its outputs. RAG typically involves:

• Creating and maintaining a knowledge base
• Implementing a retrieval system to find relevant information
• Integrating the retrieved information into the prompt
• Fine-tuning the model to effectively use the retrieved information