Customer support ai chatbot for website11/22/2023 ![]() We’re also releasing a GitHub repo with examples, including UX, orchestration, prompts, etc., that you can use to learn more or as a starting point for your own application. ![]() Our goal is to give you the tools necessary to build ChatGPT-powered applications starting today, using the "gpt-35-turbo" model that's now in preview. In this blog post we’ll describe the above solution pattern, from the internals of orchestrating conversation and knowledge bases to the considerations in user experience necessary to help end users judge responses and their supporting facts appropriately. It integrates the enterprise-grade characteristics of Azure, the ability of Cognitive Search to index, understand and retrieve the right pieces of your own data across large knowledge bases, and ChatGPT’s impressive capability for interacting in natural language to answer questions or take turns in a conversation. The combination of Azure Cognitive Search and Azure OpenAI Service yields an effective solution for this scenario. In the context of enterprise applications, the question we hear most often is “how do I build something like ChatGPT that uses my own data as the basis for its responses?” Users around the world are seeing potential for applying these large language models to a broad range of scenarios. The interest and excitement around this technology has been remarkable. It took less than a week for OpenAI’s ChatGPT to reach a million users, and it crossed the 100 million user mark in under two months. ![]()
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