Greetings, data enthusiasts and AI aficionados! Looking to polish your skills with AlloyDB or see just how fast you can build working applications using LLMs? Or maybe just excited about what you heard\read at NEXT 24’? Then you are in luck, spend some time with our self paced lab that will have you building a working AI integrated chat app in less than an hour on Google Cloud Skills Boost. This short lab will help you learn the skills to start using your own data to rapidly leverage the capabilities of tool sets like Gen AI, your own high quality datasets and RAG methodology to create productive assets in a hurry.
As the description of our lab details, RAG is a valuable component for keeping Gen AI accurate. Read more below:
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One of the best tools for reducing GenAI hallucinations is to use Retrieval Augmented Generation (RAG). RAG is the concept of retrieving some data or information, then augmenting your prompt used with your Large Language Model (LLM), which allows it to generate more accurate responses based on the data included in the prompt.
You'll also leverage the capabilities of AlloyDB AI, Google Cloud's database for AI-powered applications, and LangChain, a framework for developing applications, to connect the LLM to external data sources. By the end of this lab, you'll have a functional chat application that can intelligently answer questions by retrieving relevant information from your database.
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So go try Build an LLM and RAG-based Chat Application using AlloyDB and LangChain today. Whether you're a lone wolf or part of a mighty enterprise, this quest will bestow upon you the skills to craft intelligent applications using AlloyDB, LangChain, and LLMs.
Good luck out there fellow cloud users.
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