At Ensolvers, the integration of Generative AI and Large Language Models (LLMs) is a central focus across all projects. To achieve scalable and efficient AI solutions, the team has embraced Spring AI, a powerful framework that streamlines the integration of AI-driven functionalities into enterprise applications. This article explores how Spring AI can be configured and implemented to support Generative AI services.
Spring AI is designed to simplify the process of incorporating AI capabilities into Java-based applications. It provides a robust framework that allows developers to interact with AI models, including LLMs, through well-structured APIs and configuration management. Here is how we can integrate it into an existing Java application.
To begin with Spring AI, the first step involves adding the necessary dependencies to the project. This can be done by including the following in the pom.xml file for a Maven project:
Next, configure the default AI model and service properties in the application.yml file. Spring AI offers various configurations. This configuration allows the application to connect to the desired AI service and utilize specific models:
If your application uses application.properties you can configure it like this:
In this configuration, the OpenAI service is set with the API key and model specified. Note that one of the key powerful features that this library provides is the ability to change from one LLM to another just by switching the model. All these well-known LLM models are supported.
Once the configuration is in place, the next step is to create a service that leverages Generative AI. Below is an example of a simple service that generates text based on a prompt:
Here is a basic example of how the generateText inside AIService could look like:
The ChatModel class is provided by SpringAI and used to interact with the configured AI model. The generateText method takes a prompt as input and returns the generated text. In case of any exceptions, an error is logged using Logger, and an appropriate message is returned to the caller. Spring provides a sample code demonstrating how to create a service similar to AIService.
Integrating Generative AI with Spring AI offers a transformative solution for incorporating advanced artificial intelligence capabilities into Java applications. By leveraging Spring AI, developers can seamlessly configure AI models and services, enabling the integration of sophisticated language models to generate dynamic, contextually relevant content. As shown here, Spring AI simplifies the process of connecting to advanced AI services and offers the flexibility to switch between different models with ease.
