Building your recommendation engine with Spring AI
In this section, we will look at building the graph augmentation application leveraging Spring AI. This project approach is similar to what we built using LangChain4j. We will be leveraging the GraphRAG approach to generate embeddings for a transaction chain that meets our requirements. We will start with the ZIP file downloaded in the last section. We need to unzip the file we have downloaded. Once it is unzipped, we will load the project into the IntelliJ platform using these steps. This is similar to what we did in the previous section. Please follow the steps listed at the start of the Building your recommendation engine with LangChain4j section to import the project.
In contrast to LangChain4j, there are no significant steps to update Spring AI project dependencies. Let’s see why.
Spring AI: updating the project dependencies
Unlike the LangChain4j project, we don’t need to update any dependencies. We...
