We are happy to announce the 1.0.0 Milestone 3 release of Spring AI.

This release brings significant enhancements and new features across various areas.

Observability

This release introduces many refinements to the observability stack, particularly for streaming responses from Chat Models. Many thanks to Thomas Vitale and Dariusz Jedrzejczyk for all their help in this area!

Observability covers the ChatClient, ChatModel, Embedding Models and Vector stores enabling you to view all touchpoints with your AI infrstructure in fine grained detail..

In the M2 release we introduced observability…

We are happy to announce the 1.0.0 Milestone 2 release of Spring AI.

This release brings significant enhancements and new features across various areas.

Key Focus: Observability

A major emphasis for this release has been on observability functionality, crucial for monitoring, debugging, and optimizing AI applications. Comprehensive observability features have been introduced for:

• ChatClient (including Advisors)
• Chat Models (OpenAI, Ollama, Mistral, Anthropic)
• Embedding Models
• Image Generation Models
• Vector Stores

Note: Support for additional ChatModel implementation will be added in future…

We are happy to announce the 1.0.0 Milestone 1 release of Spring AI.

This release has the following new features an improvements.

ChatClient Fluent API

The fluent API provides methods to construct a Prompt, which is then passed as input to the AI model. You create a ChatClient using the ChatClient.Builder object. You can obtain an auto-configured ChatClient.Builder from Spring Boot autoconfiguration or create one programmatically.

If you're familiar with other Spring client classes like WebClient, RestClient, and JdbcClient, this will feel familiar.

Here is a simple usage example

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We are happy to announce the milestone 0.8.1 release of Spring AI. Thanks for all the community contributions and great discussion on GitHub issues.

This release has the following new features and improvements.

Google Gemini

Google recently released its Gemini AI Model. It has many exciting features and functionalities; check their release blog for an overview.

Features supported in Spring AI are:

• One of Gemini's marquee features is its multimodal support. This lets you chat with the model using images, videos, and text. For example, you can send the model a photo of a plate of cookies and ask it to give you a recipe for those cookies. Spring AI supports this feature; read more about it here and take a look at the sample application that showcases many Gemini features.
• Streaming and Non-Streaming chat clients
• Function Calling
• Native compilation of Gemini applications
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We are happy to announce the first milestone release of Spring AI, version 0.8.0. A big thanks to the over 50 community members and employees in other companies who have contributed to the project. Your work is very much appreciated!

The Spring AI project was founded based on the realization that creating AI applications was no longer the sole domain of Machine Learning or AI Specialists, who typically use Python. With the meteoric rise in popularity of ChatGPT, which provides a simple Web API to access pre-trained models, creating compelling AI applications has become accessible to software…

On behalf of the Java CFEnv community I am happy to announce the release of Java CFEnv 1.1 GA.

This release add support for the following services:

• Volume Services

• Pivotal Single Sign-On Service

• Pivotal Redis Service

It also adds the following functionality:

• Checks the classpath to correctly determine setting of MySQL or MariaDB driver class name.

• When using the Spring Boot support, an exception is thrown if the Spring Cloud Connector library is on the classpath. This applies only for the following services: DataSource, RabbitMQ, Cassandra, MongoDB, and Redis. The exception message indicates to set the environment variable JBP_CONFIG_SPRING_AUTO_RECONFIGURATION '{enabled: false}'

• Support for Boot 1.5.x by copying a logging utility class into the project.

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Introduction

On behalf of the community I am happy to announce the release of Java CFEnv 1.1 RC1.

The RC1 release adds the following functionality:

• Checks the classpath to correctly determine setting of MySQL or MariaDB driver class name.

• When using the Boot support, an exception is thrown if the Spring Cloud Connector library is on the classpath. This applies only for the following services: DataSource, RabbitMQ, Cassandra, MongoDB, and Redis. The exception message indicates to set the environment variable JBP_CONFIG_SPRING_AUTO_RECONFIGURATION '{enabled: false}'

• Support for Boot 1.5.x by copying a logging utility class into the project.

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Introduction

On behalf of the community I am happy to announce the release of Java CFEnv 1.1 M1.

This release brings in contributions from several teams

• EMC Volume Service

• Pivotal Single Sign-On Service

• Pivotal Redis Service

Support for Volume Services is a new feature. Single Sign-On functionality has been improved to set Spring Security auto-configuration properties for Spring Security 5’s OAuth support. The Redis support has been improved to support auto-configuration of TLS.

The project README has more information.

A release candidate is going out next week, followed quickly by a GA release. Please try it out and give feedback on our github issues…

The Spring Cloud Data Flow team is pleased to announce the release of 2.1 of Data Flow.

We have a brand new website with great new content, which is where you can find our getting started guide for use on Cloud Foundry and Kubernetes and your Local Machine.

Here are the highlights:

New Dedicated Data Flow Website

The Data Flow team takes pride is openly communicating with the community in various forums including StackOverflow, Gitter, GitHub, Twitter, and at times in Email and Zoom calls even.

However, we realized that we could provide a much better experience to answer common questions and provide an easier on-ramp to using Data Flow if we focused on improving the online documentation. The reference guide was not the ideal format to achieve that goal, so we embarked on creating a new website - https://dataflow.spring.io…

The Spring Cloud Data Flow team is pleased to announce the release of 2.0 of Data Flow. Follow the Getting Started guides for running on Local, Cloud Foundry, and Kubernetes.

Hand in hand is the 2.0 release of Spring Cloud Skipper. The getting started section in the reference guide is the best place to start if you want to use Skipper separately from Data Flow.

Here are the highlights for Data Flow

• Stream deployment always delegates to Skipper

• Single server that runs on all supported platforms

• Launch tasks against multiple platforms

• UI improvements

• Standardize on OAuth2 and OpenID Connect for Security

• Revamped metrics and monitoring of deployed applications

• Updated analytics using micrometer

• Database migration support

• Update to Boot 2.1

• Update internals to use JPA

• Task/Job Execution and Performance improvements

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