🤖 azure-openai-rag-workshop

In this workshop, we will build a chatbot based on OpenAI language models and implementing the Retrieval Augmented Generation (RAG) pattern. 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.

This workshop exists in different variants:

👉 See the workshop using Azure AI Search: we will use Azure AI Search to index and search the documents.
👉 See the workshop using Qdrant: we will use Qdrant to index and search the documents.

👉 See the completed solution and workshop source

Prerequisites

Node.js v20+
Docker v20+
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 the Dev Containers extension for VS Code to work locally using a ready-to-use dev environment.

Project details

This project is structured as monorepo and makes use of NPM Workspaces.

Here's the architecture of the application:

How to run locally

npm install
npm start

This command will start the frontend and backend services. For these services to work, you need to have a .env file at the root of the project with at least the following content:

AZURE_SEARCH_SERVICE=<your_azure_ai_search_instance_name>
AZURE_OPENAI_URL=<you_openai_instance_url>

The application will then be available at http://localhost:8000.

How to build Docker images

npm run docker:build

This command will build the container images for all services.

How deploy to Azure

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.

References

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!

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.

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