Our Journey: Building With Generative AI, Part II

Revelry built RevBot, a RAG (Retrieval Augmented Generation) prototype using LangChain that answers questions about the company by querying a vector database with semantic search and injecting relevant results into prompts sent to an LLM. The system converts user queries into vector embeddings, retrieves semantically similar documents from a vector database using cosine similarity, and passes those results to GPT-3.5-turbo to generate contextually grounded answers—advancing beyond their initial StoryBot experiment that relied solely on hard-coded prompts.

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