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Integrating OpenAI ChatGPT with Spring AI With the advent of AI-driven technologies, Spring AI now supports OpenAI's ChatGPT, a powerful language model that has significantly advanced the capabilities of text generation in software applications. In this blog, we will delve into the process of integrating ChatGPT with Spring AI, explaining key concepts and providing practical examples to help you get started. Contents [ hide ] Getting Started: Obtaining an OpenAI API Key The first step towards integrating ChatGPT into your Spring application is obtaining an API key from OpenAI, which serves as your secret key for accessing the API. Here’s how to do it: Visit the OpenAI website and sign up for an account. Once your account is set up, navigate to the API section and select the 'API Keys' page. Click on 'Create new key'. This will generate a new API key that you can use in your application. Copy this key and secure it. You will need to

Introduction to Spring AI with Ollama Welcome to a comprehensive guide on leveraging Spring AI with Ollama to develop AI-driven applications using Java. This tutorial will cover everything from setting up Ollama locally, configuring your development environment, to creating an application that utilizes large language models for text generation. Contents [ hide ] Setting Up Ollama Installing Ollama To use Ollama locally, you must first install it on your machine. This involves downloading the Ollama software from the official repository and configuring it to run without Docker. Follow the installation instructions provided in the Ollama README file available on their official GitHub page . Ollama Download link Downloading the Mistral Model After setting up Ollama, you can download the Mistral model directly from the Ollama management interface. Mistral is designed for a broad range of applications, offering robust text generation capabilities. // Run this command in cl

Welcome to this in-depth guide on the concept of graphs in computer science. Whether you're a complete novice or an advanced learner looking to refine your understanding, this tutorial will guide you through the core concepts, representations, and practical applications of graphs, ensuring a robust understanding of this fundamental concept. Contents [ hide ] Introduction to Graphs A graph is a data structure that consists of a set of nodes (also called vertices) and a set of edges that connect these nodes. Graphs are used to represent pairwise relationships between objects. In a graph, nodes can represent any type of entities such as people, cities, web pages, or even abstract concepts, while edges represent the relationships or connections between these entities. Graphs are used to model a wide variety of real-world situations, from social networks (like Facebook, LinkedIn) to computer networks (like the internet), from biological systems (like protein-protein i

Welcome to our beginner's guide to Kruskal's Algorithm in Graph Theory! Kruskal's Algorithm is a fundamental method used to find the minimum spanning tree (MST) of a connected, undirected graph. Let's explore this important algorithm together! Contents [ hide ] Understanding the Problem Statement Before delving into Kruskal's Algorithm, let's understand the problem it addresses. In graph theory, a spanning tree of an undirected graph is a subgraph that is a tree and connects all the vertices together without creating cycles. The minimum spanning tree (MST) of a graph is the spanning tree with the smallest possible sum of edge weights. The goal of Kruskal's Algorithm is to find this minimum spanning tree efficiently. What is Kruskal's Algorithm? Kruskal's Algorithm is a greedy algorithm used to find the minimum spanning tree (MST) of a connected, undirected graph. It starts with an empty graph and adds the edges with the smallest we

Welcome to our beginner's guide to Dijkstra's Algorithm in Graph Theory! Dijkstra's Algorithm is a fundamental method used to find the shortest path between nodes in a graph, particularly in graphs with non-negative edge weights. Let's explore this powerful algorithm together! Contents [ hide ] Understanding the Problem Statement Before diving into Dijkstra's Algorithm, let's understand the problem it addresses. In graph theory, finding the shortest path between two vertices is a common task. This problem is particularly important in various applications such as network routing, transportation systems, and GPS navigation. The shortest path between two vertices in a graph is defined as the path with the minimum total edge weight. Dijkstra's Algorithm efficiently finds the shortest path from a source vertex to all other vertices in the graph. What is Dijkstra's Algorithm? Dijkstra's Algorithm is a greedy algorithm used to find the sh