Async image generation is easy to demo and surprisingly easy to ship badly. The missing piece is usually not the generation request itself, but a reliable way to ask: “Is this task done, and what exactly happened?”
This guide walks through a practical polling workflow using the Flux Tasks API on Ace Data Cloud. The API is designed to query the execution status of task IDs returned by Flux image or video generation requests. We will focus on image-style task records because the documentation example is built around the Flux Images Generation API.
The goal is to build the boring but important part of an image product: tracking task state, reading the final response, showing useful errors, and avoiding duplicate work.
What you can do
The Flux Tasks API lets you retrieve task details after a Flux generation request has already returned a platform task ID.
The key details are:
- Base URL:
- Endpoint:
- Authentication:
- Headers: and
- Single task action:
- Batch task action:
For a single task, the request body contains:
- uid=1000(sandbox) gid=1000(sandbox) groups=1000(sandbox): the generated task ID
- : the operation method, set to
For multiple tasks, the request body contains:
- : an array of task IDs
- : set to
The returned task object can include , , , , the original , and the final . A task that is not complete may not include or yet.
Poll one task first
Start with a single task polling endpoint in your backend. Even if your UI will eventually show many images at once, single-task polling is easier to reason about and test.
{"error": {"message": "The token is invalid, please make sure your token is correct.", "code": "invalid_token"}, "trace_id": "37dbc369-cef6-46c3-b12f-f1730be9d856"}
The documented response includes both execution metadata and the final generation result:
For a product backend, the most important rule is simple: do not treat a task as done until is present and the is available. Before that, keep it in a pending or running state.
Store task records like you will debug them later
A good polling workflow stores more than the image URL. At minimum, keep:
- the platform task uid=1000(sandbox) gid=1000(sandbox) groups=1000(sandbox)
- your internal user or project ID
- the original prompt or request summary
- , , , and when available
- the final
- if returned
The field is especially useful because it records what started the task. In the docs, it contains fields such as , , and . When a user says “the wrong image came back,” this gives you the exact generation request without searching through logs.
Batch polling when the UI has many cards
Once the single-task version is solid, add batch polling. This is useful for gallery pages, dashboards, or multi-image generation flows where the frontend needs to refresh many task cards at once.
{"error": {"message": "The token is invalid, please make sure your token is correct.", "code": "invalid_token"}, "trace_id": "7451fbf0-bdbd-47e6-941a-19bcbe576441"}
The batch response contains and . Each item follows the same structure as a single task result, so your parser can share most of the same code path.
A practical approach is to poll pending tasks every few seconds on the server, update your database, and let the frontend read your own normalized task state. That keeps API tokens out of the browser and prevents every open tab from polling the upstream API independently.
Turn API errors into product states
The docs list several common error codes:
- : missing or invalid parameters
- : invalid or unsupported request path
- : missing or invalid authorization token
- : rate limit exceeded
- : server-side failure
The error shape includes , an object, and :
Do not show all of these as the same generic failure. A is an integration or configuration problem. A should trigger backoff. A usually means your request builder needs attention. A should be logged with so you can investigate or report it.
A simple polling loop design
Here is the shape I usually use:
- Generation request returns a task ID.
- Save the task as .
- Poll with .
- If is absent, keep the task pending.
- If is true, save and mark it complete.
- If an error is returned, save , , and .
For batch views, replace step 3 with , but keep the same state transitions for each returned item.
Final thoughts
Task polling is not glamorous, but it is where image-generation products start feeling dependable. The Flux Tasks API gives you the fields you need: task IDs, timestamps, elapsed time, original request data, final response data, and trace IDs for failures.
If you want the full reference examples, read the Flux Tasks API documentation: https://platform.acedata.cloud/documents/flux-tasks-integration
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