Introduction to Spring AI and Azure OpenAI

  • 5 minutes

Spring AI is a powerful framework that simplifies the integration of AI capabilities into Java applications. In this module, you learn how to build an AI-powered application and AI agents, using Spring AI with Azure OpenAI, and deploy to Azure Container Apps.

What is Spring AI?

Spring AI provides the following abstractions and tools that make it easy to work with various AI models and services:

  • The ChatClient API: a core abstraction for interacting with large language models (LLMs).
  • Multiple AI model providers: support for all major AI model providers, including Azure OpenAI.
  • Embeddings: generate vector embeddings for semantic search.
  • Vector storage integration: built-in support for vector databases, such as pgvector.
  • Advisors API: encapsulates generative AI patterns - for example, to implement retrieval-augmented generation (RAG).

RAG implementation

A RAG application typically has the following capabilities:

  • Converts user questions into vector embeddings.
  • Finds similar previous prompts and responses using vector similarity search.
  • Uses found responses as context for generating responses.
  • Stores interactions for future reference.

Agents and workflows

Spring AI also empowers you to build dynamic AI agents and orchestrated workflows. Although various patterns exist - like chain, parallelization and routing - this module focuses exclusively on the Evaluator-Optimizer workflow.

This pattern iteratively refines outputs through a generator-evaluator loop, ensuring high-quality and adaptive AI responses.

Why use Azure OpenAI and Container Apps?

Azure OpenAI provides a secure and scalable platform for deploying AI models with enterprise-grade features. It ensures data privacy and compliance, making it suitable for sensitive applications, and integrates seamlessly with other Azure services.

Azure Container Apps offers a serverless environment for running containerized applications with automatic scaling based on demand, simplifying microservice deployment and management.

Azure PostgreSQL is a fully managed database service that supports advanced features like vector search, providing high availability, security, and performance for large datasets used in AI models.

Learning objectives

After completing this module, you'll be able to:

  • Understand Spring AI's core abstractions and Azure OpenAI integration.
  • Create and configure Azure PostgreSQL for vector storage.
  • Implement an end-to-end AI application and AI Agents with Spring AI.
  • Deploy and scale your application on Azure Container Apps.