In this workshop, we will build a chatbot based on OpenAI language models and implementing the Retrieval Augmented Generation (RAG) pattern.
This workshop exists in different variants:
You'll use Fastify to create a Node.js service that leverage OpenAI SDK and LangChain to build a chatbot that will answer questions based on a corpus of documents, as well as a website to test it.
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👉 See the workshop using Node.js + Azure AI Search: we will use Azure AI Search to index and search the documents.
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👉 See the workshop using Node.js + Qdrant: we will use Qdrant to index and search the documents.
You'll use 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, as well as a website to test it.
- 👉 See the workshop using Quarkus + Qdrant: we will use Qdrant to index and search the documents.
- Azure account. If you're new to Azure, get an Azure account for free to get free Azure credits to get started.
- Azure subscription with access enabled for the Azure OpenAI service. You can request access with this form.
You can use GitHub Codespaces to work on this project directly from your browser: select the Code button, then the Codespaces tab and click on Create Codespaces on main.
You can also use Docker and the Dev Containers extension for VS Code to work locally using a ready-to-use dev environment.
This project is structured as monorepo, all packages source code is located under the src/ folder.
Here's the architecture of the application:
Before deploying to Azure, you need to install the Azure Developer CLI. Once you're ready, run the following commands:
azd auth login
azd upThis 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.
This workshop is 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!
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.
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.