U9 AI · INSIGHTS
Video API integration: from a scoped test to a downloadable result
A practical U9 AI workflow for checking a model, running one bounded test, tracking an asynchronous task and retrieving its result.
The short answer#
Treat a video integration as an asynchronous workflow, not as a single request. First verify the enabled model and its protocol, then submit one intentionally small test, retain its request or task identifier, query the task until it reaches a terminal state, and obtain the returned resource from the documented result field. A catalog entry alone is not proof that every parameter, account or protocol is available.
1. Define one testable outcome#
Before sending a request, write down the exact outcome that would make the test useful: the input type, the expected aspect ratio or duration, whether audio is required, and where the finished asset must be delivered. Keep the first test narrow. It is much easier to diagnose one known input and one expected result than several changing variables at once.
For a user-facing workflow, decide what the product should show while the task is still running: a pending state, a safe retry message, and a result area that remains available after completion. Do not call a result "successful" merely because a request was accepted.
2. Verify the model and contract separately#
Start with the model catalogue and the API compatibility guide. Confirm the model identifier exposed to your account, its generation mode, and the protocol that the configuration uses. Then use the model-specific public contract for creation fields, status values and result fields.
This distinction matters: a model can be visible in a catalogue while a particular tool, account permission, input form or optional setting is not compatible. Never guess an endpoint or silently substitute a different model when a contract is incomplete.
3. Bound the first paid test#
Use an input you are allowed to submit. Pick the smallest configuration that can answer your question, set a single-attempt budget, and record the displayed price before submission. Keep the resulting request ID, task ID and selected configuration together in your own log.
If the request times out after it may have reached the provider, mark its submission state as unknown and investigate it by identifier. Re-sending an asynchronous paid request blindly can create duplicate tasks and duplicate charges.
4. Query until a terminal task state#
Video work normally finishes later than the creation call. Poll or receive status updates only through the documented query method, using a modest interval and a bounded timeout. Preserve the provider status and any error code. A terminal failure is useful evidence for support; repeated immediate submissions are not a remedy.
When the task completes, read the documented output URL or media field. Keep that URL separate from the task status: a completed task and a downloadable asset are two checks. Your application should clearly show a failed download instead of masking it as a generation failure.
5. Make the result usable and traceable#
Present a preview and a direct resource action when the returned media format supports it. Store only the references and records your product needs, and do not expose API keys, prompts or private source media in public logs. For each test, retain the model, settings, request or task ID, timestamps, final status and the wallet/request record that explains any charge.
For the public Seedance V2 flow, use the Seedance 2.0 V2 video API guide. For a broader checklist, read model testing. If the documented contract and the observed response disagree, open a private support ticket with the identifier and a redacted response excerpt—never a secret key.