This is a LlamaIndex project using Next.js bootstrapped with create-llama. It uses Azure Container Apps as a serverless deployment platform and Azure Dymanic Session as a tool for code interpretation.
This template, the application code and configuration it contains, has been built to showcase Microsoft Azure specific services and tools. We strongly advise our customers not to make this code part of their production environments without implementing or enabling additional security features.
- A full-stack chat application written in Next.js
- Support for file uploads, code highlighting, and pdf rendering
- Azure OpenAI using gpt-4o-mini (by default)
- Azure Container Apps for deployment
- Azure Dynamic Sessions Tool for code interpretation (Python runtime)
- Azure Managed Identity for secure access to Azure services
To deploy this template, you need an Azure subscription. If you don't have an Azure subscription, create a free account before you begin.
You have a few options for getting started with this template. The quickest way to get started is GitHub Codespaces, since it will setup all the tools for you, but you can also set it up locally. You can also use a VS Code dev container
This template uses gpt-4o-mini which may not be available in all Azure regions. Check for up-to-date region availability and select a region during deployment accordingly
- We recommend using
eastus
You can run this template virtually by using GitHub Codespaces. The button will open a web-based VS Code instance in your browser:
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Open the template (this may take several minutes)
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Open a terminal window
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Sign into your Azure account:
azd auth login --use-device-code
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Provision the Azure resources and deploy your code:
azd up
You will be prompted to select some details about your deployed resources, including location. As a reminder we recommend eastus as the region for this project. Once the deployment is complete you should be able to scroll up in your terminal and see the url that the app has been deployed to. It should look similar to this Ingress Updated. Access your app at https://env-name.codespacesname.eastus.azurecontainerapps.io/. Navigate to the link to try out the app straight away!
A related option is VS Code Dev Containers, which will open the project in your local VS Code using the Dev Containers extension:
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Start Docker Desktop (install it if not already installed)
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Open the project:
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In the VS Code window that opens, once the project files show up (this may take several minutes), open a terminal window.
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Sign into your Azure account:
azd auth login
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Provision the Azure resources and deploy your code:
azd up
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Install the app dependencies:
npm install
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Configure a CI/CD pipeline:
azd pipeline config
To start the web app, run the following command:
npm run devOpen the URL http://localhost:3000 in your browser to interact with the bot.
You need to install following tools to work on your local machine:
- Install azd
- Windows:
winget install microsoft.azd - Linux:
curl -fsSL https://aka.ms/install-azd.sh | bash - MacOS:
brew tap azure/azd && brew install azd
- Windows:
- Docker Desktop (for Mac M1 M2 M3, use Docker Desktop for Apple Silicon 4.34.2 or later)
- Node.js (v20 LTS)
- Git
Then you can get the project code:
- Fork the project to create your own copy of this repository.
- On your forked repository, select the Code button, then the Local tab, and copy the URL of your forked repository.
- Open a terminal and run this command to clone the repo:
git clone <your-repo-url>
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Bring down the template code:
azd init --template llama-index-azure-code-interpreter
This will perform a git clone
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Sign into your Azure account:
azd auth login
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Install all dependencies:
npm install
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Provision and deploy the project to Azure:
azd up
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Configure a CI/CD pipeline:
azd pipeline config
Once your deployment is complete, you should see a .env file at the root of the project. This file contains the environment variables needed to run the application using Azure resources.
First, install the dependencies:
npm install
Second, generate the embeddings of the documents in the ./data directory (if this folder exists - otherwise, skip this step):
npm run generate
Third, run the development server:
npm run dev
Open http://localhost:3000 with your browser to see the result.
- Build an image for the Next.js app:
docker build -t <your_app_image_name> .
- Generate embeddings:
Parse the data and generate the vector embeddings if the ./data folder exists - otherwise, skip this step:
docker run \
--rm \
-v $(pwd)/.env:/app/.env \ # Use ENV variables and configuration from your file-system
-v $(pwd)/config:/app/config \
-v $(pwd)/data:/app/data \
-v $(pwd)/cache:/app/cache \ # Use your file system to store the vector database
<your_app_image_name> \
npm run generate
- Start the app:
docker run \
--rm \
-v $(pwd)/.env:/app/.env \ # Use ENV variables and configuration from your file-system
-v $(pwd)/config:/app/config \
-v $(pwd)/cache:/app/cache \ # Use your file system to store gea vector database
-p 3000:3000 \
<your_app_image_name>
This template uses gpt-4o-mini which may not be available in all Azure regions. Check for up-to-date region availability and select a region during deployment accordingly
- We recommend using
eastus
You can estimate the cost of this project's architecture with Azure's pricing calculator
- Azure Container Apps: Consumption plan, Free for the first 2M executions. Pricing per execution and memory used. Pricing
- Azure OpenAI: Standard tier, GPT and Ada models. Pricing per 1K tokens used, and at least 1K tokens are used per question. Pricing
Warning
To avoid unnecessary costs, remember to take down your app if it's no longer in use, either by deleting the resource group in the Portal or running azd down --purge.
This template has Managed Identity built in to eliminate the need for developers to manage these credentials. Applications can use managed identities to obtain Microsoft Entra tokens without having to manage any credentials. Additionally, we have added a GitHub Action tool that scans the infrastructure-as-code files and generates a report containing any detected issues. To ensure best practices in your repo we recommend anyone creating solutions based on our templates ensure that the Github secret scanning setting is enabled in your repos.
Here are some resources to learn more about the technologies used in this sample:
- LlamaIndexTS Documentation - learn about LlamaIndex (Typescript features).
- Generative AI For Beginners
- Azure OpenAI Service
- Azure OpenAI Assistant Builder
- Chat + Enterprise data with Azure OpenAI and Azure AI Search
You can also find more Azure AI samples here.
If you can't find a solution to your problem, please open an issue in this repository.
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 [email protected] 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.