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azure-openai-rag-workshop-java
Azure OpenAI RAG with Java, LangChain4J and Quarkus
A Java sample app that chats with your data using OpenAI.

πŸ€– Azure OpenAI RAG with Java, LangChain4j and Quarkus

Open project in GitHub Codespaces Ollama + Mistral License

⭐ If you like this sample, star it on GitHub β€” it helps a lot!

Overview β€’ Run the sample β€’ Other versions β€’ References

This sample shows how to build an AI chat experience with Retrieval-Augmented Generation (RAG) using LangChain4j and OpenAI language models. The application is hosted on Azure Static Web Apps and Azure Container Apps, with Qdrant as the vector database. You can use it as a starting point for building more complex AI applications.

Important

πŸ‘‰ Follow the full-length workshop to learn how we built this sample and how you can run and deploy it.

Overview

This sample uses Quarkus to create a Java service that leverage OpenAI SDK and LangChain4j to build a chatbot that will answer questions based on a corpus of documents, with a website to interact with the API.

This project is structured as monorepo, all packages source code is located under the src/ folder. Here's the architecture of the application:

Architecture diagram

Run the sample

You can use GitHub Codespaces to work on this project directly from your browser:

Open in GitHub Codespaces

You can also use Docker and the Dev Containers extension for VS Code to work locally using a ready-to-use dev environment:

Open in Dev Containers

If you prefer to install all the tools locally, you can follow these setup instructions.

Tip

You can run this sample entirely locally without any cost using Ollama. Follow the instructions above to setup the tools locally to get started.

Azure prerequisites

Deploy the sample

Open a terminal and run the following commands:

azd auth login
azd up

This commands will first ask you to log in into Azure. Then it will provison the Azure resources, package the services and deploy them to Azure.

Clean up

To clean up all the Azure resources created by this sample:

  1. Run azd down --purge
  2. When asked if you are sure you want to continue, enter y

The resource group and all the resources will be deleted.

Other versions

This sample and workshop exists in different versions:

References

Here are some resources to learn more about the technologies used in this sample:

You can also find more Azure AI samples here.

This sample/workshop was based on the enterprise-ready sample ChatGPT + Enterprise data with Azure OpenAI and AI Search:

If you want to go further with more advanced use-cases, authentication, history and more, you should check it out!

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.