Authored by Thasmika Gokal, this article explores the video playground within Azure AI Foundry and its integration with the Sora video generation model, providing insights and guidance for developers looking to experiment and deploy AI-generated video workflows.

Go from Prompt to Playback with Sora from Azure OpenAI in the Video Playground in Azure AI Foundry

Author: Thasmika Gokal

Introducing Sora and the Video Playground in Azure AI Foundry

The video playground in Azure AI Foundry serves as a high-fidelity testbed for developers to rapidly prototype with advanced video generation models like Sora from Azure OpenAI. This tool is purpose-built to enable safe experimentation, prompt engineering, and iteration, providing a robust environment for evaluating video model behaviors before committing to a production framework or infrastructure.

For more context, see the Tech Community launch blog covering gpt-image-1 and Sora.

The Need for Controlled Prototyping Environments

Modern development often spans multiple APIs, services, and SDKs. Before formalizing frameworks, writing tests, or setting up infrastructure, developers seek lightweight environments for quick validation. The video playground in Azure AI Foundry fulfills this need by offering a controlled and consistent space for safely testing out ideas and workflow components.

Key Capabilities for Developers

  • Rapid Prototyping: A frictionless, on-demand setup for experimenting with prompt variations, video output controls (aspect ratio, resolution, duration), and model parameters.
  • Prompt Engineering: Tools for debugging, tuning, and rewriting prompt syntax. Includes visual comparison of test outputs and a library of prebuilt industry prompts.
  • API Consistency: The playground mirrors the model’s API structure, ensuring that practices tested here translate predictably to your actual codebase.
  • VS Code Integration: After prototyping, developers can seamlessly scale into VS Code using the model’s API for further development.

Platform Features

  • Model-Specific Controls: Tweak generation settings such as aspect ratio and duration to better understand model strengths, weaknesses, and responsiveness.
  • Prebuilt Prompts and Curated Content: The playground offers nine curated example videos and templates from Microsoft to help developers get started.
  • Multi-Lingual Code Export: Automatically generate code samples (Python, JavaScript, Go, cURL) representing your configurations and prompts. These samples can be ported directly into VS Code for scaled deployments.
  • Side-By-Side Comparisons: Use a grid view to observe outcomes across different prompt or parameter permutations.
  • Azure AI Content Safety: The system integrates with Azure AI Content Safety, filtering out harmful or unsafe video generations.
  • Version-Awareness: The platform manages model versions and API updates, reducing development friction as new models become available.

Visuals and Demos

  • The playground interface offers direct visual feedback for prompt changes and model parameters (see included screenshots and demo video from Microsoft Build 2025).

What to Test in Video Playground

To maximize productive experimentation, consider the following evaluation areas while prototyping videos with Sora and similar models:

  1. Prompt-to-Motion Translation: Assess logical and temporal coherence of motion in response to prompts; tune prompts using AI-assisted rewriting.
  2. Frame Consistency: Monitor style, object, and character consistency across frames for artifact detection.
  3. Scene Control: Test the level of control available for scene composition, behaviors, camera angles, and transitions.
  4. Length and Timing: Examine the effect of prompt variations on pacing and video length; identify optimal timing.
  5. Multimodal Inputs: Explore model responses to reference images, pose data, audio, and options like lip-sync to voiceovers.
  6. Post-Processing Needs: Determine editable fidelity, need for upscaling, stabilization, or retouching.
  7. Latency and Performance: Track generation speed and cost across clips of varying length and resolution.

Azure AI Foundry enables running Sora and other models at scale, omitting the need for backend infrastructure management.

Getting Started with Azure AI Foundry Video Playground

  1. Sign in or create an account at Azure AI Foundry.
  2. Set up a Foundry Hub and/or Project.
  3. Deploy Azure OpenAI Sora via the Foundry Model Catalog or start directly from the video playground.
  4. Prototype with the provided tools, optimize your use-case, and fine-tune prompts.
  5. When ready, transfer your workflow into VS Code using the generated API integration and code samples.

Additional Resources

Azure AI Foundry’s video playground, with integrated access to Sora and robust API-to-code workflows, lets developers safely experiment and transition seamlessly to production-grade AI-powered video generation within the Microsoft ecosystem.

This post appeared first on “Microsoft DevBlog”. Read the entire article here