Manju

What Is Spring AI? Creating the Project Configuring OpenAI Understanding ChatModel Understanding ChatClient Creating a ChatClient Basic Conversation with ChatClient Running the Application Summary AI has rapidly become a standard capability in modern applications. Whether you are building chatbots, intelligent business workflows, or AI powered assistants, Large Language Models (LLMs) can significantly enhance your applications. Until recently, Python has been the primary language for building AI applications. However, a new era has arrived for Java developers. With Spring AI, Java developers can now build AI powered applications using the familiar Spring programming model. What Is Spring AI? Building AI applications involves several challenges, such as interacting with AI providers, constructing prompts, managing conversations, parsing responses, and orchestrating AI workflows. Spring AI addresses these challenges by providing the familiar Spring programming model for AI...

Greetings! Calling an LLM Understanding Tokens and Next Token Prediction Controlling the Response with Inference Parameters Temperature Top P Maximum Output Tokens LLM Responses Are Not Guaranteed Facts Getting Structured Responses Messages and Roles Chat Conversations Conversation Memory Context Windows The LLM Does Not Know Our Data External Knowledge with RAG Accessing Live Data with Tools Combining Memory, RAG, and Tools Are We Building an Agent? Why Do We Need AI Frameworks? Summary Large Language Models (LLMs) have changed the way we build applications. Today, we can build chatbots, intelligent workflows, AI assistants, and even AI agents. There are many frameworks available to build LLM powered applications like Spring AI, Langchain. However, before jumping into a framework, it is important to understand what happens underneath. In this article, we will explore the main concepts behind LLM applications by directly interacting with OpenAI APIs. Calling an ...