Implementation of a Retrieval-Augmented Generation (RAG) system using MongoDB Atlas Vector Search to enhance LLM-powered applications through semantic information retrieval. Developed as part of the MongoDB University - MongoDB Skills course.
Immersive classes offer hands-on experience with MongoDB use cases based on years of field experience
AI-powered semantic search and Q&A system using MongoDB Atlas vector search, OpenAI embeddings, and LangChain agents to retrieve and summarize MongoDB documentation. Developed as part of the MongoDB University - MongoDB Skills course.
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