If you have looked into building an AI-powered application recently, you have probably noticed that there are a lot of frameworks and libraries out there that expect you to be running Python and JavaScript on the back end. In today’s video, we will take a look at how we can build an AI-powered chatbot using Spring Boot on the back end.
We will be working with Langchain, a library that helps us orchestrate between different AI actions and chain together things and call agents. We will use this library to help us build an AI application using Spring Boot on the back end.
To get started, we will create a new service class called ChatService. This service will act as the intermediary between OpenAI and our front end. We will use the OpenAI API to get chat responses and send them to our client.
Next, we will create a chat view in our front-end folder. This view will have components for displaying a list of messages and allowing users to input and send new messages. We will use the OpenAI API to generate responses and display them in real-time.
To improve the user experience, we will implement streaming chat. This means that as the AI is writing its response, we will display it to the user instantaneously. We will use the Langchain streaming chat model and convert it to a Flux, a data type that allows us to subscribe to new data as it comes in.
In conclusion, building an AI-powered chatbot with Spring Boot allows us to leverage the power of AI while using a familiar and powerful framework. By implementing streaming chat, we can provide a more seamless and interactive user experience.
If you are interested in learning more about AI-powered applications or Spring Boot, stay tuned for future videos where we will cover other tools and topics in more detail.
