> ## Documentation Index
> Fetch the complete documentation index at: https://docs-docflow.textin.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Retry Review Task

> Retry review tasks or specific rules in review tasks via REST API

<Tip>
  This document introduces how to retry review tasks via REST API. When a review task execution fails or needs to be reviewed again, you can retry the entire review task or retry a specific rule in the review task.
</Tip>

Review tasks support two retry methods:

1. **Retry entire review task**: Re-execute all rules in the entire review task
2. **Retry a specific rule**: Re-execute only a specific rule in the review task

## Retry Entire Review Task

Re-execute the entire review task, which will re-review all rules in the task:

<CodeGroup>
  ```bash curl icon=terminal wrap theme={null}
  curl -X POST \
    -H "Content-Type: application/json" \
    -H "x-ti-app-id: <your-app-id>" \
    -H "x-ti-secret-code: <your-secret-code>" \
    -d '{
      "workspace_id": "<your-workspace-id>",
      "task_id": "31415926"
    }' \
    "https://docflow.textin.ai/api/app-api/sip/platform/v2/review/task/retry"
  ```

  ```python Python expandable icon=python lines theme={null}
  import requests

  ti_app_id = "<your-app-id>"
  ti_secret_code = "<your-secret-code>"
  workspace_id = "<your-workspace-id>"
  task_id = "31415926"

  host = "https://docflow.textin.ai"
  url = "/api/app-api/sip/platform/v2/review/task/retry"

  payload = {
      "workspace_id": workspace_id,
      "task_id": task_id
  }

  resp = requests.post(
      url=f"{host}{url}",
      json=payload,
      headers={
          "x-ti-app-id": ti_app_id,
          "x-ti-secret-code": ti_secret_code,
      },
      timeout=60,
  )

  result = resp.json()
  if result.get("code") == 200:
      print("Review task retry successful")
  else:
      print(f"Retry failed: {result.get('msg')}")
  ```
</CodeGroup>

**Request Parameters:**

* `workspace_id` (required): Workspace ID
* `task_id` (required): Review task ID

**Response Example:**

```json theme={null}
{
  "code": 200,
  "msg": "success"
}
```

## Retry a Specific Rule in Review Task

Re-execute only a specific rule in the review task, suitable for cases where only a specific rule needs to be reviewed again:

<CodeGroup>
  ```bash curl icon=terminal wrap theme={null}
  curl -X POST \
    -H "Content-Type: application/json" \
    -H "x-ti-app-id: <your-app-id>" \
    -H "x-ti-secret-code: <your-secret-code>" \
    -d '{
      "workspace_id": "<your-workspace-id>",
      "task_id": "31415926",
      "rule_id": "31415926"
    }' \
    "https://docflow.textin.ai/api/app-api/sip/platform/v2/review/task/rule/retry"
  ```

  ```python Python expandable icon=python lines theme={null}
  import requests

  ti_app_id = "<your-app-id>"
  ti_secret_code = "<your-secret-code>"
  workspace_id = "<your-workspace-id>"
  task_id = "31415926"
  rule_id = "31415926"

  host = "https://docflow.textin.ai"
  url = "/api/app-api/sip/platform/v2/review/task/rule/retry"

  payload = {
      "workspace_id": workspace_id,
      "task_id": task_id,
      "rule_id": rule_id
  }

  resp = requests.post(
      url=f"{host}{url}",
      json=payload,
      headers={
          "x-ti-app-id": ti_app_id,
          "x-ti-secret-code": ti_secret_code,
      },
      timeout=60,
  )

  result = resp.json()
  if result.get("code") == 200:
      print("Rule retry successful")
  else:
      print(f"Retry failed: {result.get('msg')}")
  ```
</CodeGroup>

**Request Parameters:**

* `workspace_id` (required): Workspace ID
* `task_id` (required): Review task ID
* `rule_id` (required): Review rule ID

**Response Example:**

```json theme={null}
{
  "code": 200,
  "msg": "success"
}
```

## Parameter Description

### Review Task ID (task\_id)

The review task ID is the identifier of a created review task. You can obtain it through:

* Returned when creating a task via the [Create Review Task](./create_task) API
* Obtained when querying tasks via the [Get Review Result](./get_result) API

### Review Rule ID (rule\_id)

The review rule ID is the identifier of a specific rule in the review task. You can obtain it through:

* Querying task results via the [Get Review Result](./get_result) API, from the `groups[].review_tasks[].rule_id` field
* Obtaining rule IDs from the rule repository via the [Rule Management](./rule_management) API

**Example: Get Rule ID from Review Result**

```python Python icon=python expandable theme={null}
import requests

ti_app_id = "<your-app-id>"
ti_secret_code = "<your-secret-code>"
workspace_id = "<your-workspace-id>"
task_id = "31415926"

host = "https://docflow.textin.ai"
url = "/api/app-api/sip/platform/v2/review/task/result"

# Get review result
payload = {
    "workspace_id": workspace_id,
    "task_id": task_id
}

resp = requests.post(
    url=f"{host}{url}",
    json=payload,
    headers={
        "x-ti-app-id": ti_app_id,
        "x-ti-secret-code": ti_secret_code,
    },
    timeout=60,
)

result = resp.json()
if result.get("code") == 200:
    review_result = result.get("result", {})
    groups = review_result.get("groups", [])
    
    # Iterate through all rules to get rule IDs
    rule_ids = []
    for group in groups:
        review_tasks = group.get("review_tasks", [])
        for review_task in review_tasks:
            rule_id = review_task.get("rule_id")
            rule_name = review_task.get("rule_name")
            if rule_id:
                rule_ids.append({
                    "rule_id": rule_id,
                    "rule_name": rule_name
                })
    
    print(f"Found {len(rule_ids)} rules:")
    for rule in rule_ids:
        print(f"  Rule ID: {rule['rule_id']}, Rule Name: {rule['rule_name']}")
```

## Use Cases

### Retry Entire Review Task

Suitable for the following scenarios:

1. **Review task execution failure**: When the entire review task execution fails, you can retry the entire task
2. **After rule repository update**: When rules in the rule repository are updated, you can retry the entire review task to apply the new rules
3. **After extraction result update**: When the associated extraction task results are updated, you can retry the review task to re-review based on the new extraction results

### Retry a Specific Rule

Suitable for the following scenarios:

1. **Single rule execution failure**: When a specific rule execution fails, you can retry only that rule without affecting other rules
2. **After rule configuration adjustment**: When a specific rule's configuration is adjusted, you can retry only that rule
3. **Improve efficiency**: When only a specific rule needs to be reviewed again, retrying a single rule is more efficient than retrying the entire task

## Notes

1. **Asynchronous execution**: Retry operations are executed asynchronously. After retrying, you need to query the review status via the [Get Review Result](./get_result) API
2. **Task status**: Ensure the review task exists and can be retried. Deleted tasks cannot be retried
3. **Rule status**: When retrying a rule, ensure the rule ID is correct and belongs to the specified review task
4. **Retry frequency**: It is recommended to control retry frequency to avoid excessive system load from frequent retries
5. **Result overwrite**: Retrying will regenerate review results, and the original review results will be overwritten

## Related Pages

* [Create Review Task](./create_task) - Learn how to create review tasks
* [Get Review Result](./get_result) - Learn how to get review results
* [Rule Management](./rule_management) - Learn how to manage review rule repositories