Vector Search

I am building a Go-based Hotel Reviews RAG system with Vertex AI Vector Search, BigQuery and Gemini. This post will describe some MLops, AI Text models, and overall working with Google Cloud platform’s latest Generative AI and Machine Learning tools. I will walk you through the process of setting up an end-to-end Retrieval Augmented Generation system with Vertex AI Vector Search. The project is called Alpaca which is my Hotel Review Search turbocharged with AI. End goal: finding quality hotels that meet your criteria based on natural language analysis and a fine-tuned curation of LLMs, Vector Similarity Search, and the related APIs. My preliminary research shows that it is possible to do better than a raw ChatGPT/Grok/Gemini/Llama question and answer prompt. ...

The goal is to gather as many real Hotel reviews as possible to process them into vector embeddings and run similarity searches with RAG (Retrieval Augmented Generation). The resulting matched reviews will be combined as input prompts for the Generative AI (GenAI) LLM model such as Gemini, Grok, Claude, or ChatGPT. This will allows us to find the best hotels in any given city. The Hotel Assistant will return results based on custom criteria or a user question. ...