SivaLabs

If you ever worked with Spring Boot, then you are probably aware of Spring Initializr. The Spring Initializr is a web application that you can use to create a Spring Boot application.

Do you know Spring Initializr itself is an open-source Spring Boot application? You can fork it, customize it, deploy on your infrastructure and use it to generate Spring Boot applications.

As a software developer, at the beginning of my career, I thought it was more important to learn one more programming language or framework or library. But as years passed by, I realized it is also equally important to learn how to interact with people. Now remote work is becoming new normal and social media platforms like Twitter, LinkedIn, etc. are a common place to interact with people across the globe.

Spring Boot is the most popular framework in the Java world to build enterprise applications. Also, Spring Boot is the most sought-after skill to get hired as a Java developer.

Here is my recommended approach to learn Spring Boot.

Typically, in Spring Boot + Thymeleaf applications, we use thymeleaf-layout-dialect to define the common layout of the web pages and it works fine.

But when we compile the Spring Boot application to GraalVM native image, it is failing due to this error. I tried many suggestions mentioned in the above issue, but none of them worked for me.

In this article, we will explore the following:

• Introduction to Embedding Models.
• Loading data using DocumentReaders.
• Storing embeddings in VectorStores.
• Implementing RAG (Retrieval-Augmented Generation), a.k.a. Prompt Stuffing.

Let’s get started.

In this article, we will explore the following:

• Introduction to Spring AI.
• Interacting with Open AI using Spring AI.
• Using PromptTemplates.
• Using OutputConverters.

Let’s get started.

In this article, we will explore the following:

• Understand the need for Retrieval-Augmented Generation (RAG).
• Understand EmbeddingModel, EmbeddingStore, DocumentLoaders, EmbeddingStoreIngestor.
• Working with different EmbeddingModels and EmbeddingStores.
• Ingesting data into EmbeddingStore.
• Querying LLMs with data from EmbeddingStore.

Let’s get started.

In this article, we will explore the following:

• Using LangChain4j AiServices to interact with LLMs.
• How to ask questions and map responses to different formats?
• Summarizing the given text in different formats.
• Analyzing the sentiment of the given text.

Let’s get started.

In this article, we will explore the following:

• How to use LangChain4j ChatMemory and ConversationalChain to implement conversation style interaction?
• How to ask questions using PromptTemplate?

In the previous article, we have seen how to interact with OpenAI using Java and LangChain4j.

Let’s get started.

In this article, we will explore the following:

• Brief introduction to Generative AI?
• How to interact with Open AI APIs using Java?
• How to use LangChain4j to interact with OpenAI?
• How to run a LLM model locally using Ollama?
• Working with Ollama using LangChain4j and Testcontainers.

Let’s get started.