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Spring AI with Open Ai

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 t

Spring AI with Ollama

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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 c

Graph Data Structure

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

Kruskal's Algorithm in Graph

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

Dijkstra's Algorithm in Graph

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

Prim's Algorithm in Graph

Welcome to our beginner's guide to Prim's Algorithm in Graph Theory! Prim'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 Prim'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 Prim's Algorithm is to find this minimum spanning tree efficiently. What is Prim's Algorithm? Prim's Algorithm is a greedy algorithm used to find the minimum spanning tree (MST) of a connected, undirected graph. It starts with an arbitrary vertex and grows the spanning tree by adding the shortest e

Topological Sort in Graph

Welcome to our beginner's guide to Topological Sort in Graph Theory! Topological Sort is an essential algorithm used to order the vertices of a directed graph such that for every directed edge uv from vertex u to vertex v, u comes before v in the ordering. Let's explore this important concept together! Contents [ hide ] Understanding the Problem Statement Before delving into Topological Sort, let's understand the problem it addresses. Consider a scenario where tasks depend on one another; for example, in a project where certain tasks must be completed before others can begin. Such dependencies can be modeled using directed graphs, where nodes represent tasks and directed edges represent dependencies between tasks. The goal of Topological Sort is to find a linear ordering of the vertices of the graph such that for every directed edge uv, the vertex u comes before the vertex v in the ordering. This ordering provides a sequence in which the tasks can be perf

Union-Find Algorithm in Graph

Welcome to our beginner's guide to the Union-Find Algorithm in Graph Theory! Union-Find is a fundamental algorithm used to efficiently manage disjoint sets, often applied in graph theory for tasks like determining connected components and detecting cycles. Let's explore this powerful algorithm together! Contents [ hide ] Understanding the Problem Statement Before diving into the Union-Find Algorithm, let's understand the problem it aims to solve. In many graph-related scenarios, we encounter the need to group elements into sets and perform operations like merging sets and finding whether two elements belong to the same set. Consider a scenario where we have a graph with several nodes and edges connecting them. We want to efficiently answer questions like: Are two nodes connected? Which nodes are part of the same connected component? Is there a cycle in the graph? The Union-Find Algorithm provides an elegant solution to address these que

Depth-First Search (DFS) in Graph

Welcome to our beginner's guide to Depth-First Search (DFS) in Graph Theory! DFS is another fundamental algorithm used to traverse or search through the nodes of a graph in a systematic manner. Let's explore this fascinating algorithm together! Contents [ hide ] What is Depth-First Search (DFS)? Depth-First Search is an algorithm used to traverse or search through the nodes of a graph in a depthward motion. It starts at a specific node (often referred to as the "source" node) and explores as far as possible along each branch before backtracking. Imagine you're exploring a maze again. DFS would explore as far as possible along one path before backtracking and exploring another path. How does DFS Work? DFS employs a simple strategy of exploring nodes as deeply as possible along each branch before backtracking. The algorithm proceeds as follows: Start with the source node and mark it as visited. Explore one of the unvisited neighbors