Spring AI

What is Spring AI?

• Spring AI is a project within the Spring Framework that brings the power of artificial intelligence (AI) to Java developers.

• It’s a spring module that lets you to create Java-based AI applications without complexity.

💡 Spring AI is currently in a pre-1.0 release version, specifically at 0.8.0 snapshot. As a snapshot version, it is still under development, which means you might encounter unexpected behavior or code-breaking changes. 🌱🤖

Generative Ai terms to know:

Let’s Explore Generative AI that is used under the hood by Spring AI:

Generative AI, also known as GenAI, is a fascinating field within artificial intelligence (AI) that focuses on creating new content in response to input prompts. Let’s break it down:

What Is Generative AI?

• Generative AI allows users to input various prompts to generate fresh content across different media types, including:
• Code: Generating code snippets or entire programs.
• Text: Generating stories, poems, or other written content.
• Sounds: Creating music, sound effects, or audio snippets.
• Videos: Generating video clips or animations.
• 3D Designs: Creating 3D models or structures.
• Images: Creating visual art, illustrations, or designs.
• Prompt: In the AI world, a prompt is a text message given to the AI model. It includes context and a question.
• What happens underneath: Prompts are tokenized i.e. breaking the text string into simple units. These units can be words or even characters depending on the model’s design. This token is then processed by the model to understand and generate responses based on the input it receives.

💡 In the case of Spring AI – it makes an API call to openAI and presents the response back.

What Spring AI Offers

1. Text-Based Generative AI:

At its core, Spring AI offers a text-based generative AI system. Users input text, and it responds with relevant text output. This basic yet powerful functionality allows for a wide array of text-based interactions and solutions tailored to meet diverse needs.

2. Integration with Industry-Leading Generative AI Models:

Spring AI collaborates with several of the tech industry’s most prominent generative AI models, including OpenAI, Azure Open AI, Bedrock (Amazon), Ollama, and Vertex AI (Google). By leveraging the unique capabilities of these platforms, Spring AI enhances its offerings, providing users with access to cutting-edge AI technology and a broad range of functionalities.

4. Document Reader:

Spring AI also features document readers, which are among the standout offerings from the Spring AI development team. These document readers are particularly useful in the context of Retrieval Augmented Generation (RAG).

• RAG provides your prompts with a specific context, ensuring that the AI doesn’t rely on its entire extensive training knowledge. Instead, it can concentrate on particular documents you’ve supplied, containing the information you’re interested in. This focus enhances the relevance and accuracy of the AI’s responses.
• Spring AI’s document reader supports various formats, including simple text, JSON, and Tika, with notable support for PDFs. This versatility ensures that developers can seamlessly integrate documents in these formats into their workflows, enabling the AI to extract and utilize the contained information effectively.

6. Prompt Templates:

Crafting an effective prompt involves more than merely posing a question and expecting an accurate response. This approach may suffice for straightforward inquiries, but for more complex scenarios, it’s essential to employ refined templates. These templates are structured in a way that allows you to insert specific details about the question or instructions you’re providing to the AI. Spring AI includes support for these prompt templates, enabling users to tailor their prompts more precisely and enhance the likelihood of obtaining relevant and accurate answers.

We will delve into some of Spring AI’s key features in detail by demonstrating their implementation through code in the later part of this article.

What can we request/response from Spring AI?

1. Conversational question-and-answer sessions, mimicking a human-like interaction by remembering past context and responding accordingly.
2. Questions based on specific documents, provided they are supplied.
3. Questions related to coding and programming data.