Prerequisites

• An Azure subscription.Create one for free.
• Python 3.8 or later version. We recommend using Python 3.10 or later, but having at least Python 3.8 is required. If you don't have a suitable version of Python installed, you can follow the instructions in theVS Code Python Tutorial for the easiest way of installing Python on your operating system.
• An Azure OpenAI resource created in one of the supported regions. For more information about region availability, see themodels and versions documentation.
• Then, you need to deploy asora model with your Azure OpenAI resource. For more information, seeCreate a resource and deploy a model with Azure OpenAI.

Microsoft Entra ID prerequisites

For the recommended keyless authentication with Microsoft Entra ID, you need to:

• Install theAzure CLI used for keyless authentication with Microsoft Entra ID.
• Assign theCognitive Services User role to your user account. You can assign roles in the Azure portal underAccess control (IAM) >Add role assignment.

Set up

1. Create a new foldervideo-generation-quickstart and go to the quickstart folder with the following command:

   mkdir video-generation-quickstart && cd video-generation-quickstart

2. Create a virtual environment. If you already have Python 3.10 or higher installed, you can create a virtual environment using the following commands:

   • Windows
   • Linux
   • macOS

   py -3 -m venv .venv.venv\scripts\activate

   Activating the Python environment means that when you runpython orpip from the command line, you then use the Python interpreter contained in the.venv folder of your application. You can use thedeactivate command to exit the python virtual environment, and can later reactivate it when needed.

   Tip

   We recommend that you create and activate a new Python environment to use to install the packages you need for this tutorial. Don't install packages into your global python installation. You should always use a virtual or conda environment when installing python packages, otherwise you can break your global installation of Python.

3. For therecommended keyless authentication with Microsoft Entra ID, install theazure-identity package with:

   pip install azure-identity

Retrieve resource information

You need to retrieve the following information to authenticate your application with your Azure OpenAI resource:

Generate video with Sora

You can generate a video with the Sora model by creating a video generation job, polling for its status, and retrieving the generated video. The following code shows how to do this via the REST API using Python.

1. Create thesora-quickstart.py file and add the following code to authenticate your resource:

   • Microsoft Entra ID
   • API key

   import requestsimport base64 import osfrom azure.identity import DefaultAzureCredential# Set environment variables or edit the corresponding values here.endpoint = os.environ['AZURE_OPENAI_ENDPOINT']# Keyless authenticationcredential = DefaultAzureCredential()token = credential.get_token("https://cognitiveservices.azure.com/.default")api_version = 'preview'headers= { "Authorization": f"Bearer {token.token}", "Content-Type": "application/json" }

2. Create the video generation job. You can create it from a text prompt only, or from an input image and text prompt.

   • Text prompt
   • Image prompt
   • Video prompt

   # 1. Create a video generation jobcreate_url = f"{endpoint}/openai/v1/video/generations/jobs?api-version={api_version}"body = {    "prompt": "A cat playing piano in a jazz bar.",    "width": 480,    "height": 480,    "n_seconds": 5,    "model": "sora"}response = requests.post(create_url, headers=headers, json=body)response.raise_for_status()print("Full response JSON:", response.json())job_id = response.json()["id"]print(f"Job created: {job_id}")# 2. Poll for job statusstatus_url = f"{endpoint}/openai/v1/video/generations/jobs/{job_id}?api-version={api_version}"status=Nonewhile status not in ("succeeded", "failed", "cancelled"):    time.sleep(5)  # Wait before polling again    status_response = requests.get(status_url, headers=headers).json()    status = status_response.get("status")    print(f"Job status: {status}")# 3. Retrieve generated video if status == "succeeded":    generations = status_response.get("generations", [])    if generations:        print(f"✅ Video generation succeeded.")        generation_id = generations[0].get("id")        video_url = f"{endpoint}/openai/v1/video/generations/{generation_id}/content/video?api-version={api_version}"        video_response = requests.get(video_url, headers=headers)        if video_response.ok:            output_filename = "output.mp4"            with open(output_filename, "wb") as file:                file.write(video_response.content)                print(f'Generated video saved as "{output_filename}"')    else:        raise Exception("No generations found in job result.")else:    raise Exception(f"Job didn't succeed. Status: {status}")

3. Run the Python file.

   python sora-quickstart.py

   Wait a few moments to get the response.

Output

The output will show the full response JSON from the video generation job creation request, including the job ID and status.

{    "object": "video.generation.job",    "id": "task_01jwcet0eje35tc5jy54yjax5q",    "status": "queued",    "created_at": 1748469875,    "finished_at": null,    "expires_at": null,    "generations": [],    "prompt": "A cat playing piano in a jazz bar.",    "model": "sora",    "n_variants": 1,    "n_seconds": 5,    "height": 480,    "width": 480,    "failure_reason": null}

The generated video will be saved asoutput.mp4 in the current directory.

Job created: task_01jwcet0eje35tc5jy54yjax5qJob status: preprocessingJob status: runningJob status: processingJob status: succeeded✅ Video generation succeeded.Generated video saved as "output.mp4"

Prerequisites

• An Azure subscription.Create one for free.
• An Azure OpenAI resource created in a supported region. SeeRegion availability. For more information, seeCreate a resource and deploy a model with Azure OpenAI.

Go to Microsoft Foundry portal

Browse to theFoundry portal and sign in with the credentials associated with your Azure OpenAI resource. During or after the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.

From the Foundry landing page, create or select a new project. Navigate to theModels + endpoints page on the left nav. SelectDeploy model and then choose the Sora video generation model from the list. Complete the deployment process.

On the model's page, selectOpen in playground.

Try out video generation

Start exploring Sora video generation with a no-code approach through theVideo playground. Enter your prompt into the text box and selectGenerate. When the AI-generated video is ready, it appears on the page.

In theVideo playground, you can also view Python and cURL code samples, which are prefilled according to your settings. Select the code button at the top of your video playback pane. You can use this code to write an application that completes the same task.