I Built a RAG System From Scratch in 4 Weeks — Here’s Everything I Learned

1. 1Build a RAG system using embeddings and ChromaDB
2. 2Configure FastAPI for API development
3. 3Implement retrieval and generation components
4. 4Test and evaluate the system's performance
5. 5Deploy the system to a production environment

This project is ideal for a team of machine learning engineers and data scientists who want to improve their language model capabilities. The team can benefit from the technical breakdown of building a RAG system, which can be applied to various NLP tasks.

💡 Building a production-grade RAG system requires careful consideration of embeddings, retrieval, and generation components

💡 Built a RAG system from scratch in 4 weeks! Learn how to improve your language model capabilities with this technical breakdown #RAG #NLP