Building RAG Systems: A Complete Guide

1. 1Build a knowledge graph using a vector database to store external information
2. 2Configure a retrieval mechanism to fetch relevant data from the graph
3. 3Train a language model to generate queries and retrieve information from the graph
4. 4Test the RAG system using a dataset of user queries
5. 5Fine-tune the model to improve its performance and accuracy

AI engineers and researchers can benefit from this guide to improve the performance of their language models, while product managers can use it to inform their product development strategies

💡 RAG systems enable AI models to retrieve information from external sources, reducing hallucinations and improving accuracy

🤖 Build RAG systems to supercharge your AI models with external knowledge! 🚀