Then, in lines 17-22, we are preparing our text. First, on line 14, we are initiating our AI model, which is OpenAI. This code may look intimidating, but it’s actually pretty simple. Now, let's build our simple frontend, which is just an input to collect the question, a submit button that will hit our backend to get the answer, and an API call when a user hits “submit.” Let’s download the new LangChain JS package. Let’s get started!įirst, let’s create our Next.js app: npx create-next-app So, we can ask the bot questions about the collapse and hopefully get some clarity around the situation. Now we can easily integrate LangChain into our Next.js apps.įor this bot, I’ve loaded a Wikipedia document about the recent Silicon Valley Bank collapse. For a while, you had to use Python with LangChain, but that changed when they launched LangChain JS last month. LangChain launched last year, and the library helps build custom chatbots, agents, and has wrappers to help us with things like prompt templates, chunking (to break up long documents), and more. There’s no easy way to load a large amount of custom data, and it doesn’t have any data after 2021, so it needs custom data for it to be knowledgeable about current events.
Part of the point of this is to show how easy and fast it is to create something powerful.įirst off, why is this even needed when we have a great chatbot in ChatGPT? Well, ChatGPT doesn’t work well with proprietary and custom data. In this tutorial, I will build a customized AI chatbot using Next.js (React) and LangChain JS.
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