Build an Application to Chat with Documents Using RAG
Learn how to use PostgreSQL pgvector and langchaingo to implement RAG.
Let’s begin by applying the RAG technique to enhance the chat application further.
First, the contents of the chapter from ‘War and Peace’ are converted into vector embeddings and loaded into a PostgreSQL database.
When a user interacts with the chat application and asks questions about the chapter, RAG is used behind the scenes to get a response and send it back to the user.
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