
JSON schema for AI video output: 5 templates to copy
Copyable JSON Schemas for AI video output on Sume: one video, video plus copy, a poster, aspect ratios, and caption cues, all in the strict subset.
Sume Formats over the API: create and version a Format, call it, run bulk batches, get structured output, take webhooks, and debug failed runs.
Start with: What is a Sume Format? Turn an agent thread into one API call

Copyable JSON Schemas for AI video output on Sume: one video, video plus copy, a poster, aspect ratios, and caption cues, all in the strict subset.

To regenerate one scene of an AI video, continue the Sume Format run with previous_run_id and name the scene. It can redo that clip and leave the rest alone.

A failed Sume Format run names its cause in error.code. Here is each code with its details fields, what gets billed, and whether to continue or retry.

Put customer text in a Sume run's input object, not its instruction. The agent is told to read it as data; the docs call that a trust boundary, not a sandbox.

A Sume Format recipe is a SKILL.md file plus references. Keep SKILL.md a short index, move detail into references/, and follow the package rules.

Before you count a Sume run as delivered, check status and primary_output_url, read filled_by, and probe the file. Here is what Sume checks, and what it skips.

A failed Sume Format run still reports the scenes it made if your output schema allows a partial. Use nullable fields, skip minItems, and name a primary key.

Edit a Sume Format's files over the API without overwriting another writer: each write carries the file's blob sha, and If-Match guards the whole package.

Create a Sume Format with POST /v1/formats, then write its SKILL.md recipe through the Contents API. The fields, the slug rules, and the errors to handle.

Share a Sume team Format with another team workspace. Once the grant is live, that team calls the owner's address with its own team key and pays for its runs.

The documented Sume Format API limits in one place: request and input sizes, attachments, schemas, spend caps, queues, run deadlines, webhooks, rate limits.

Sume rejects an output_schema outside the OpenAI strict-mode subset with 400 output_schema_invalid. Read each violation's rule, then port oneOf and nullable.

GET /v1/formats lists the Formats your key can call. Address one by {handle}/{slug} or by its permanent skl_ id, and list its runs newest first.

A checklist for a Sume Format run that did something unexpected: the composed first message, the carried instruction, the version, events, and output.

Every Sume Format edit bumps its version, and each run receipt records the version that ran. Runs cannot be pinned to a version, and there is no rollback API.

When a Sume bulk queue completes, read counts.failed, then continue each failed child that left work behind or resubmit it under a new Idempotency-Key.

Make a UGC-style ad over the Sume API: call a catalog UGC Format at the sume handle, or render an Avatar 1.0 talking video with your script and product image.

Bind a JSON Schema as output_schema and a Sume Format run returns output in that shape, with each media URL checked against what the run made.

A Sume bulk request queues 1 to 100 ordinary Format runs on the server and keeps 1 to 16 in flight. Poll one queue URL; read each child as a normal run.

A Sume Format run goes from queued to processing to a terminal status. Learn the outcome from one signed format.run.terminal webhook, by polling, or both.

To embed AI video generation, your server holds one Sume API key and runs a Format per customer, with a derived Idempotency-Key, spend cap, and webhook.

A Sume Format is a saved video recipe your backend calls by handle and slug. One POST runs it in a fresh sandbox and returns media plus optional typed JSON.

Sume ships ready-made Formats for product and UGC-style video and images, each callable from your backend with one HTTP request at the reserved sume handle.