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OpenAI Developers

API deployment checklist | OpenAI API Sora 2 Prompting Guide Codex Prompting Guide Docs MCP | OpenAI Developers Gpt-image-1.5 Prompting Guide GPT-5.2 Prompting Guide Transcribing User Audio with a Separate Realtime Request Modernizing your Codebase with Codex GitHub - openai/openai-apps-sdk-examples: Example apps for the Apps SDK GitHub - openai/openai-chatkit-advanced-samples: Starter app to build with OpenAI ChatKit SDK GitHub - openai/openai-chatkit-starter-app: Starter app to build with OpenAI ChatKit + Agent Builder Rate limits | OpenAI API Web search | OpenAI API Getting started with datasets | OpenAI API Prompt optimizer | OpenAI API Verifying gpt-oss implementations How to run gpt-oss locally with LM Studio Fine-tuning with gpt-oss and Hugging Face Transformers How to run gpt-oss locally with Ollama Function calling | OpenAI API Models | OpenAI API Reasoning best practices | OpenAI API Reasoning models | OpenAI API Background mode | OpenAI API Batch API | OpenAI API Conversation state | OpenAI API File search | OpenAI API Flex processing | OpenAI API MCP and Connectors | OpenAI API Code Interpreter | OpenAI API Quickstart - OpenAI Agents SDK Build Hour: Agentic Tool Calling Build Hour: Built-In Tools Reasoning best practices | OpenAI API Graders | OpenAI API Evaluation best practices | OpenAI API Working with evals | OpenAI API Guardrails - OpenAI Agents SDK Latency optimization | OpenAI API Optimizing LLM Accuracy | OpenAI API Agent orchestration - OpenAI Agents SDK Production best practices | OpenAI API Realtime transcription | OpenAI API Optimizing LLM Accuracy | OpenAI API Realtime and audio | OpenAI API Realtime conversations | OpenAI API Responses guide Migrate to the Responses API | OpenAI API Speech to text | OpenAI API Supervised fine-tuning | OpenAI API Tracing - OpenAI Agents SDK Vision fine-tuning | OpenAI API Audio and speech | OpenAI API GitHub - openai/openai-cs-agents-demo: Demo of a customer service use case implemented with the OpenAI Agents SDK Voice agents | OpenAI API Fine-tuning best practices | OpenAI API GitHub - openai/openai-agents-python: A lightweight, powerful framework for multi-agent workflows GitHub - openai/openai-agents-js: A lightweight, powerful framework for multi-agent workflows and voice agents Agents SDK | OpenAI API Using tools | OpenAI API Computer use | OpenAI API GitHub - openai/openai-cua-sample-app: Learn how to use CUA (our Computer Using Agent) via the API on multiple computer environments. GitHub - openai/openai-testing-agent-demo: Demo of a UI testing agent using the OpenAI CUA model and the Responses API. Model optimization | OpenAI API GitHub - openai/openai-fm: Code for openai.fm, a demo for the OpenAI Speech API Predicted Outputs | OpenAI API GitHub - openai/openai-realtime-console: React app for inspecting, building and debugging with the Realtime API Building Voice Agents GitHub - openai/openai-realtime-solar-system: Demo showing how to use the OpenAI Realtime API to navigate a 3D scene via tool calling GitHub - openai/openai-realtime-twilio-demo Reinforcement fine-tuning | OpenAI API GitHub - openai/openai-responses-starter-app: Starter app to build with the OpenAI Responses API Structured model outputs | OpenAI API GitHub - openai/openai-structured-outputs-samples: Sample apps to help developers get started with Structured Outputs Voice agents | OpenAI API Model optimization | OpenAI API GitHub - openai/openai-realtime-agents: This is a simple demonstration of more advanced, agentic patterns built on top of the Realtime API. GitHub - openai/openai-support-agent-demo: Demo of a customer support agent interface using NextJS and the OpenAI Responses API with File Search Building Voice Agents Generate images with high input fidelity AI app development: Concept to production Model optimization Building agents Eval Driven System Design - From Prototype to Production Multi-Agent Portfolio Collaboration with OpenAI Agents SDK o3/o4-mini Function Calling Guide Exploring Model Graders for Reinforcement Fine-Tuning Guide to Using the Responses API Reinforcement Fine-Tuning for Conversational Reasoning with the OpenAI API Evals API Use-case - Responses Evaluation Comparing Speech-to-Text Methods with the OpenAI API Generate images with GPT Image Multi-Tool Orchestration with RAG approach using OpenAI Multi-Language One-Way Translation with the Realtime API Doing RAG on PDFs using File Search in the Responses API How to use the Usage API and Cost API to monitor your OpenAI usage Leveraging model distillation to fine-tune a model Orchestrating Agents: Routines and Handoffs Prompt Caching 101 Developing Hallucination Guardrails
GitHub - openai/openai-sora-sample-app: Sample app to get started using the Video API with Sora
2025-10-15 · via OpenAI Developers

MIT License NextJS Sora Video API

This repository contains a NextJS sample app built on top of the Sora Video API and OpenAI SDK. It provides a simple UI for experimentation, using text prompts and optionally image inputs to generate and remix videos.

Sora demo visual

Features:

  • Generate new videos or remix existing runs through the /videos endpoints.
  • Queue multiple variations in one click with Versions Count and follow progress via automatic polling.
  • Auto-title runs so finished clips stay recognizable.
  • Automatically optimize prompts.
  • Generate starter imagery with gpt-image-1 to use as image inputs.
  • Preview, download, remix, or retry completed runs directly from the history panel.
  • Persist preferences and run history in localStorage so refreshes do not wipe context.

This app is meant to be used as a starting point to build Sora-powered video experiences that you can customize to your needs.

How to use

  1. Get access to the Sora Video API:

    • Sora is currently in limited availability. Request access through your OpenAI account team or the Video API waitlist.
    • Once approved, review the video generation guide to understand supported parameters and limits.
  2. Set the OpenAI API key:

    2 options:

    • Export the OPENAI_API_KEY environment variable globally on your machine.
    • Create a .env.local file at the project root (see below)
    OPENAI_API_KEY="your-openai-api-key"
  3. Clone the repository:

    git clone https://github.com/openai/sora-starter-app.git
  4. Install dependencies:

    Run in the project root:

  5. Run the app:

    The app will be available at http://localhost:3000.

Video helpers

This sample app highlights common Sora workflows and wraps each one in a small UI helper to speed up iteration.

Generate new videos

  • Fill in your prompt, choose a Sora model (sora-2 or sora-2-pro), aspect ratio, and duration (4s, 8s, or 12s).
  • Optionally upload an image; the app crops it to the chosen aspect ratio before sending it along as input_reference.
  • Submit one or many variations at once via Versions Count. The sidebar polls /videos/{id} until each job completes.

Remix existing runs

  • Paste an existing video_id into the Remix section or click Remix on a completed run.
  • Adjust prompt, model, size, or duration and resubmit. The history keeps both parent and remix entries linked for fast comparison.

Prompt optimization

Use Generate prompt to call the Responses API to optimize your prompt for the selected model, size, and duration.

Image ideation

  • Let gpt-image-1 propose stills aligned with your prompt. Choose the one you like and send it as the next input_reference.
  • Swap between generated and uploaded imagery without losing form state.

Run management

  • Preview, download, remix, or retry finished runs without leaving the page.
  • Remove unwanted runs from the history and bulk download completed clips.

Demo flows

Try a fresh generation

  • Enter a descriptive prompt such as A sweeping drone shot over neon-drenched Kyoto at night.
  • Select sora-2-pro, set duration to 8 seconds, and bump Versions Count to 3.
  • Click Generate. Watch each run stream through queued → processing → completed states, then preview the outputs inline.

Try a remix

  • Pick your favorite completed clip and hit Remix.
  • Add guidance like with a vintage film grain feel and submit. Compare the remix to the original using the preview overlay navigation.

Try prompt and image suggestions

  • Click Suggest prompt after entering a rough idea—e.g., A playful golden retriever in the snow—and apply the refined version.
  • Ask for image ideas, select one of the generated stills, and run a new generation to see how the reference shapes the motion.

Contributing

You are welcome to open issues or submit PRs to improve this app, however, please note that we may not review all suggestions.

License

This project is licensed under the MIT License. See the LICENSE file for details.