/ Spring AI guide
Spring AI is a framework designed to simplify the development of applications that incorporate artificial intelligence (AI) capabilities. It is based on the design principles of the Spring ecosystem for Java and aims to make AI engineering more accessible and less complex for developers.
Brief introduction to the framework
Spring is an open-source framework for developing Java applications. Created by Rod Johnson in 2003, it quickly established itself as one of the most popular frameworks in the Java world, thanks to its flexibility, modularity and ease of use.
This very popular framework can be used for developing a wide range of Java applications, including web applications, RESTful services, batch applications, integration applications, and much more. The ecosystem of related projects (such as Spring Boot, Spring MVC etc.) simplifies and speeds up application development in different contexts.
Main features of Spring AI
The framework offers developers a set of tools and resources to build AI applications more efficiently and intuitively, following the ecosystem’s design principles and modular approach. Below are some of the main features:
- Support for a wide range of AI models, including OpenAI, Microsoft, Amazon, Google, and Huggingface.
- Support for different types of AI models, such as chat models, text-to-image, audio-to-text transcription and embedding models.
- Integration with vector databases for data management.
- Call functions to allow AI models to request additional information to improve prompt responses.
- ETL framework for data engineering, which facilitates the transfer and manipulation of documents for training AI models.
Throughout this guide, we will explore the fundamentals of this tool together and guide you in discovering this framework through practical and accessible tutorials. If you’re ready to dive into the world of AI, read on and prepare to be inspired and amazed by the incredible potential of this framework.