How to make a RAG application with LangChain4j
SMRTR summary
A new tutorial demonstrates how to create a Q&A chatbot using retrieval-augmented generation (RAG) with MongoDB Atlas and LangChain4J. The application retrieves data from MongoDB, embeds documents as vector embeddings, and uses LangChain4J to query the database and augment LLM prompts, enabling secure and efficient AI-powered applications.
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