Enhance Text Generation with RAG, LangChain, and Vertex AI

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use a LangChain "Chain" to orchestrate steps required to query a vector database and submit the results of the query to Gemini to obtain results based on a knowledge base. To do so, you embed a query submitted in a session in order to perform a nearest neighbor search on the vector store. Once results are retrieved, they are added as contextual information when querying a large language model (LLM), in this case, Gemini.

• Enhance Text Generation with RAG, LangChain, and Vertex AI