The artificial intelligence landscape presents unprecedented opportunities for Java developers. With decades of experience building robust enterprise applications using Spring, Quarkus and Jakarta EE, Java developers are uniquely positioned to create sophisticated AI solutions. The emergence of specialized AI libraries like LangChain4j enables them to leverage their existing expertise while building secure, scalable, and maintainable AI applications.

Introducing LangChain4j: A Comprehensive Java AI Library

LangChain4j represents a significant advancement in Java-based AI development. This community-driven library, with substantial backing from Red Hat — a key Microsoft partner in the Java ecosystem — provides a comprehensive suite of abstractions and tools designed to streamline AI application development. The project offers robust support for large language models (LLMs), vector stores, and intelligent agents, drawing inspiration from the widely adopted Python LangChain framework. Microsoft’s collaboration with the Python LangChain community has already demonstrated our commitment to advancing AI security across open-source platforms, as detailed in our previous announcement on LangChain.

Microsoft’s Investment in LangChain4j

Our telemetry data indicates significant growth in LangChain4j adoption, with hundreds of Microsoft customers utilizing the framework in production environments. Recognizing the importance of this open-source initiative, Microsoft has made substantial contributions to enhance the project’s Azure and OpenAI integration capabilities.

At the time of this writing, the Java developer advocacy team at Microsoft contributed to 190 issues and pull requests to the main LangChain4j project (see the current list here).

Our early contributions include comprehensive support for azure-related services like Azure OpenAI, GitHub Models (with the Azure AI Inference API), Azure Blob Storage, Azure Cosmos DB, and Azure AI Search.

More recently, Microsoft has spearheaded the integration of the official OpenAI Java SDK, developed by OpenAI, into the LangChain4j ecosystem (see https://github.com/langchain4j/langchain4j/pull/2508 ). This effort should benefit all Java developers utilizing the OpenAI models, as well as all other models supporting the same API. It also focuses on Azure-specific functionality, emphasizing authentication mechanisms and security protocols.

Strengthening Security Through Collaborative Audit

Our partnership with LangChain4j extends beyond feature development to encompass comprehensive security initiatives. Microsoft, as part of its Secure Future Initiative (see details at https://www.microsoft.com/en-us/trust-center/security/secure-future-initiative), has conducted an extensive security audit of the LangChain4j framework in collaboration with the open-source community. Over the past quarter, our joint efforts have successfully addressed several critical security vulnerabilities, including:

• Database Security: Resolution of SQL injection vulnerabilities affecting PostgreSQL and MySQL vector store implementations (see commit here)
• Dependency Management: Systematic updates to address known vulnerabilities in third-party libraries

Beyond immediate vulnerability remediation, our collaboration has established robust security governance structures, including the implementation of a formal security policy, designated security contacts, and a structured security advisory process.

Industry Leadership Perspective

Microsoft is proud to partner with LangChain4j to enhance the security and accessibility of AI development for Java developers. Dmytro Liubarskyi, founder and project lead of LangChain4j, shares this vision for the future of Java AI development:

“Our goal with LangChain4j has always been to make advanced AI capabilities easily accessible to Java developers — without compromising on security, scalability, or developer experience. We’re especially grateful for Microsoft’s dedication to strengthening the security of the library — their close collaboration and thorough audit process have helped us build a more secure and trustworthy foundation for AI development in Java.”

Getting Started: Resources for Developers

For organizations and developers interested in implementing LangChain4j with Microsoft Azure, we have developed comprehensive documentation available on the official LangChain4j documentation portal:

• Complete guide for using LangChain4j with OpenAI’s official Java SDK: https://docs.langchain4j.dev/integrations/language-models/open-ai-official
• Detailed documentation for leveraging the Azure OpenAI SDK with LangChain4j: https://docs.langchain4j.dev/integrations/language-models/azure-open-ai
• Sample code to use Azure OpenAI SDK with LangChain4j: https://github.com/langchain4j/langchain4j-examples/tree/main/azure-open-ai-examples

If you prefer to learn using video content, our Microsoft for Java Developers YouTube channel has a dedicated playlist for LangChain4j. You’ll find videos from our Java Developer Advocacy team members who contribute to the project, as well as videos recorded during Microsoft JDConf’s conference:

https://www.youtube.com/playlist?list=PLPeZXlCR7ew8f0wgsEEj3vxvyrkLyd-Rd

Looking Forward

This partnership represents Microsoft’s continued commitment to empowering developers with secure, enterprise-ready AI tools. By combining Java’s enterprise-proven foundation with cutting-edge AI capabilities, we’re enabling organizations to build sophisticated AI solutions that meet the highest standards for security, scalability, and maintainability.

As the AI landscape continues to evolve, Microsoft remains dedicated to fostering innovation through selected open-source partnerships, ensuring that developers have access to the tools and security measures necessary for success in the AI-driven future.