To generate a video with an API, choose a provider and model that support your input and output needs, submit a prompt and any required reference media, track the resulting asynchronous job, and retrieve the finished video. The request fields and capabilities are provider-specific: a text-to-video example for one model is not automatically valid for another.
Choose the right workflow before writing code
Start with the video you need to produce and the inputs you can provide. Some workflows are text-to-video; others use a still image to guide the result, specify beginning and ending frames, extend an existing clip, or support conversational editing. Audio, aspect ratios, duration, and other controls depend on the selected model.
- Text-to-video: Supply a written prompt. Runway documents both text-to-video and image-to-video workflows.
- Image-directed video: Provide a reference image alongside a prompt when the chosen model supports it. Runway’s getting-started example uses an image with its gen4.5 model.
- Frame and reference control: Google’s Veo 3.1 guide describes first- and last-frame direction and support for up to three reference images.
- Audio or editing: Google’s documentation distinguishes Veo 3.1, which it describes with native audio, extension, and frame-specific generation, from Gemini Omni Flash, which it describes as supporting multimodal generation and conversational editing.
These are documented capabilities, not a guarantee that every account, model version, region, or API request can use them. Check the provider’s current guide before designing around a feature.
Pick an API with a live, suitable model
Provider documentation and model status can change. As of Google’s Veo guide update on September 17, 2026, its listed Veo 3.1 model identifiers are preview variants; treat those names and capabilities as subject to change. Google’s video-generation overview was last updated June 30, 2026.
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OpenAI’s current Videos API reference describes video resources and schema values, but labels video listing, remix, and retrieval operations deprecated. That reference alone is not enough to establish that a new Sora integration is viable. Runway’s page about Sora states that serving for sora-2 and sora-2-pro stopped on September 24, 2026; that date is Runway’s report, not a direct OpenAI announcement. Confirm current status with OpenAI directly before relying on Sora.
Before committing to any provider, verify its current model status, account and geographic availability, rate limits, supported duration and dimensions, accepted input formats, and pricing. The cited provider materials do not establish a complete apples-to-apples cost or availability comparison.
Understand the request-and-job lifecycle
Video generation typically takes longer than an ordinary API request. Your application submits a request; the provider returns or tracks a task or operation; your application waits for completion or failure; and only then does it retrieve the resulting media. Runway’s guide demonstrates waiting for task output and handling task failure. OpenAI’s video resource schema describes queued, in-progress, completed, and failed states.
- Authenticate. Create credentials with the selected provider and keep them on the server or in a secrets manager. Do not put a private API key in browser code, a public repository, or a mobile app bundle.
- Submit a model-specific request. Use the exact field names and allowed values in the provider’s current documentation. Depending on the model, the request may include a model identifier, prompt, reference image, ratio, or duration.
- Record the task or operation identifier. Preserve it with your application’s job record so a worker can resume checking after a restart.
- Wait for a terminal state. Poll according to the provider’s contract or use its documented waiting helper. Apply a deadline and increasing delays rather than polling continuously.
- Handle failure explicitly. Surface a useful error to the caller, retain diagnostic details safely, and retry only when the provider’s error and your own idempotency strategy make retrying appropriate.
- Retrieve and validate the output. Save the media to storage you control if it must persist, then verify that the downloaded object is non-empty and has the expected format before marking the application job complete.
Do not assume that a provider-hosted output URL lasts indefinitely. OpenAI’s resource schema includes an optional asset expiry time, so check retention and deletion behavior for whichever service you use.
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Runway example: what the documented workflow establishes
Runway’s API Getting Started guide demonstrates a JavaScript SDK workflow using @runwayml/sdk and its imageToVideo.create operation. The example uses the gen4.5 model, a prompt image, prompt text, a 1280:720 ratio, and a duration of 5, then waits for task output. The guide also shows a Python SDK example and describes text-to-video without an input image.
Those values describe that guide’s example, not universal API defaults or limits. The available evidence does not provide the complete SDK syntax, authentication setup, or output-download code, so copying an invented snippet would risk giving you a request that does not run. Follow Runway’s current guide for the exact install command, credential configuration, request syntax, and output handling; use the fields and values documented for the model you actually select.
Build polling and failure handling for production
Polling without wasting requests
Use the provider’s documented status endpoint or SDK wait helper. If implementing polling yourself, set a maximum elapsed time, increase the interval between checks, and stop immediately on a terminal success or failure state. Avoid assuming a fixed rendering time: the cited guides do not establish a universal latency or service-level guarantee.
Retries and duplicate work
A network timeout after submission does not necessarily mean the provider did not accept the job. Before resubmitting, check whether the original task can be found or whether the provider documents idempotency support. Otherwise, automatic retries can create duplicate generation jobs and cost. Retry transient status checks separately from generation submissions.
Persist enough state to recover
Store the provider name, model identifier, task ID, submission time, application job status, and any output location. Keep prompts and user-provided media only as long as your product needs them, and apply your own access controls to generated files.
Validate constraints, performance, and cost
Before launch, check current per-job or per-second pricing, quotas, rate limits, duration and resolution limits, supported aspect ratios, input constraints, and availability for your account and region. These values are provider- and model-specific and are not established as a comparable matrix in the documentation covered here.
- Control scope: Start with a short representative generation and the intended input type; then verify the result and request settings before running a large batch.
- Budget for asynchronous work: Design your application so users can leave a page and return to job status rather than holding a web request open for the entire render.
- Measure your own workload: Record queue time, generation time, failures, output size, and actual provider charges. Do not infer performance from a sample in documentation.
- Plan for model changes: Keep model identifiers configurable and monitor provider notices, especially when a model is in preview or an operation is marked deprecated.
Troubleshooting common failures
The request is rejected
Check authentication, the exact model identifier, required fields, allowed value formats, and whether the selected model is enabled for your account. A ratio, duration, or input mode accepted by another model may be invalid here.
The job stays queued or in progress
Keep checking through the documented task or operation flow, but enforce a deadline and report that the job is still processing rather than treating it as complete. The available provider documentation does not establish a universal completion-time threshold.
The job fails after acceptance
Capture the provider’s task error and request identifier for diagnosis. Correct the prompt or inputs if the error indicates an unsupported request; retry a transient failure only after considering duplicate-job risk.
The job completes but the video cannot be retrieved
Check the provider’s output retrieval instructions and any asset expiry information. Download or copy results to durable storage promptly when your application needs longer retention, and validate the saved file before discarding the provider reference.
A documented operation or model is unavailable
Recheck the live API reference and model lifecycle. OpenAI’s current reference marks several video operations deprecated, and preview model identifiers can change; do not assume an older example remains supported.
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ScreenshotNeo is a website screenshot API, not a video-generation API, so it does not create generated video. If your workflow also needs clean website screenshots, it can capture a URL with one GET request. See the ScreenshotNeo API documentation.
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Frequently Asked Questions
Can a video-generation API return the finished video immediately?
Usually you should expect a task or operation to finish asynchronously; check the selected provider’s documented lifecycle.
Can I use a screenshot API to generate video?
No. ScreenshotNeo captures website screenshots; video generation requires a video-generation provider and model.
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