# Task Lifecycle

All generation APIs in the Tripo API use an asynchronous task pattern. After you submit a request, the API returns a `task_id`. You can then poll the task status and result.

## State Machine

```
queued -> running -> success
                 -> failed
                 -> cancelled
```

## Status Descriptions

| Status | Description | progress |
| :-: | :-: | :-: |
| `queued` | The task has been created and is waiting in the queue | 0 |
| `running` | The task is being processed | 0-100 |
| `success` | The task is complete, and the `output` field is available | 100 |
| `failed` | The task failed, usually due to a server-side issue. Contact support | - |
| `banned` | The input content violates the content policy | - |
| `expired` | The task has expired, and output files are no longer available | - |
| `cancelled` | The task has been cancelled | - |

## Task Flow

```
1. Create a task (POST /v3/generation/*)
   |
   v
2. Return task_id
   |
   v
3. Poll status (GET /v3/tasks/{task_id})
   |
   v
4a. status=success -> Get download links from output
4b. status=failed  -> Check error details and contact support
4c. status=banned  -> Modify the input content and submit again
```

## Credit Freeze Model

Tripo uses a credit "freeze-then-deduct" model to ensure users are not charged for failed tasks:

| Stage | Credit Change | Description |
| :-: | :-: | :-: |
| Task creation | Freeze the required credits | Credits are pre-authorized from the available balance and moved into a frozen state |
| Task succeeds | Frozen credits become consumed credits | Credits are formally deducted |
| Task fails | Frozen credits are released | Credits are returned to the available balance |
| Task is cancelled | Frozen credits are released | Credits are returned to the available balance |

Query the current balance and frozen credits:

```bash
curl -X GET https://openapi.tripo3d.ai/v3/account/balance \
  -H "Authorization: Bearer {api_key}"
```

```json
{
  "code": 0,
  "data": {
    "balance": 10000,
    "frozen": 200
  }
}
```

## Polling Recommendations

- **Polling interval**: Query once every 1-2 seconds
- **Use the `progress` field to display progress**: The value is an integer from 0 to 100
- **Set a timeout**: We recommend setting a maximum polling duration, such as 5 minutes. If it times out, tell the user to check again later
- **Use `POST /v3/tasks/list` for batch tasks**: Reduce the number of requests

### Python Polling Example

```python
import time
import requests

def wait_for_task(task_id, api_key, interval=2, timeout=300):
    url = f"https://openapi.tripo3d.ai/v3/tasks/{task_id}"
    headers = {"Authorization": f"Bearer {api_key}"}
    start = time.time()

    while time.time() - start < timeout:
        response = requests.get(url, headers=headers)
        task = response.json()["data"]
        status = task["status"]
        progress = task.get("progress", 0)

        print(f"[{task_id}] {status} ({progress}%)")

        if status == "success":
            return task["output"]
        if status in ("failed", "cancelled", "banned"):
            raise Exception(f"Task terminated: {status}")

        time.sleep(interval)

    raise TimeoutError(f"Task {task_id} timed out")
```

### JavaScript Polling Example

```javascript
async function waitForTask(taskId, apiKey, interval = 2000, timeout = 300000) {
  const url = `https://openapi.tripo3d.ai/v3/tasks/${taskId}`;
  const headers = { "Authorization": `Bearer ${apiKey}` };
  const start = Date.now();

  while (Date.now() - start < timeout) {
    const response = await fetch(url, { headers });
    const { data: task } = await response.json();
    const { status, progress = 0 } = task;

    console.log(`[${taskId}] ${status} (${progress}%)`);

    if (status === "success") return task.output;
    if (["failed", "cancelled", "banned"].includes(status)) {
      throw new Error(`Task terminated: ${status}`);
    }

    await new Promise(resolve => setTimeout(resolve, interval));
  }

  throw new Error(`Task ${taskId} timed out`);
}
```