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This document introduces how to create review tasks via REST API. Creating a review task requires specifying a rule repository and a list of extraction task IDs. The system will automatically match rules in the rule repository with extraction tasks and execute review for matched rules.
A review task is one execution of applying a rule repository to extraction tasks. After creating a review task, the system will automatically execute the review and generate review results.

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Create Review Task

Submit a review task to review specified extraction tasks: 
# Using extract_task_ids
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>",
    "name": "Review Task 1",
    "repo_id": "31415926",
    "extract_task_ids": ["1234567890", "1234567891"]
  }' \
  "https://docflow.textin.com/api/app-api/sip/platform/v2/review/task/submit"

# Using batch_number
# 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>",
#     "name": "Review Task 1",
#     "repo_id": "31415926",
#     "batch_number": "202412190001"
#   }' \
#   "https://docflow.textin.com/api/app-api/sip/platform/v2/review/task/submit"
Request Parameters:
  • workspace_id (required): Workspace ID
  • name (required): Task name, max length 100
  • repo_id (required): Review rule repository ID
  • extract_task_ids (optional): Array of extraction task IDs, list of extraction task IDs that need to be reviewed
  • batch_number (optional): Batch number. The system will retrieve all tasks under this batch and merge them with extract_task_ids (with deduplication)
Response Example: 
{
  "code": 200,
  "msg": "success",
  "result": {
    "task_id": "31415926"
  }
}

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Parameter Description

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Rule Repository ID (repo_id)

The rule repository ID is the identifier of the review rule repository you created. The system will use all rules in this repository to review extraction tasks. Getting Rule Repository ID:
  • Returned when creating a rule repository via the Create Rule Repository interface
  • Obtained by viewing the rule repository list in the interface

​
Extraction Task ID (extract_task_ids)

Extraction task ID is the identifier of a task that has completed document extraction. Only tasks that have completed extraction can be used as review objects. Important Notes:
  • If a parent task ID is provided (e.g., a parent task generated by file split or multi-image crop), the system will automatically retrieve all child tasks of that parent task as input
  • If both batch_number and extract_task_ids are provided, the system will merge all tasks from the batch with extract_task_ids (with automatic deduplication)
Getting Extraction Task ID:
  • From the task_id returned by the file upload interface
  • From the file query interface (/api/app-api/sip/platform/v2/file/fetch) to get file information, where task_id is the extraction task ID

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Batch Number (batch_number)

Batch number is used to specify tasks for review in batches. When batch_number is provided, the system will retrieve all tasks under that batch for review. Use Cases:
  • Batch review of all files uploaded in the same batch
  • Combined with extract_task_ids for more flexible task selection
Example: Get Extraction Task ID
Python
import requests

ti_app_id = "<your-app-id>"
ti_secret_code = "<your-secret-code>"
workspace_id = "<your-workspace-id>"
batch_number = "<your-batch-number>"

host = "https://docflow.textin.com"
url = "/api/app-api/sip/platform/v2/file/fetch"

resp = requests.get(
    url=f"{host}{url}",
    params={
        "workspace_id": workspace_id,
        "batch_number": batch_number
    },
    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:
    files = result.get("result", {}).get("files", [])
    extract_task_ids = []
    for file in files:
        # Ensure file has completed extraction (recognition_status == 1)
        if file.get("recognition_status") == 1:
            task_id = file.get("task_id")
            if task_id:
                extract_task_ids.append(task_id)
    
    print(f"Available extraction task IDs: {extract_task_ids}")

​
Review Task Execution Flow

After creating a review task, the system will execute the review according to the following flow:
  1. Rule Matching: The system matches rules in the rule repository with extraction task categories
    • Check if the rule’s category_ids contain the extraction task’s categories
    • Check if the extraction task contains fields referenced by the rule
  2. Field Association: For matched rules, the system retrieves field values referenced by the rule from extraction results
  3. AI Review: Based on rule prompts and field values, AI makes review judgments
  4. Result Generation: Generate review results, including review status, reasoning, position anchors, and other information

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Complete Example

Complete review task creation flow:
Python
import requests
import time

ti_app_id = "<your-app-id>"
ti_secret_code = "<your-secret-code>"
workspace_id = "<your-workspace-id>"
host = "https://docflow.textin.com"

# 1. Get extraction task IDs
fetch_url = "/api/app-api/sip/platform/v2/file/fetch"
fetch_resp = requests.get(
    url=f"{host}{fetch_url}",
    params={
        "workspace_id": workspace_id,
        "batch_number": "<your-batch-number>"
    },
    headers={
        "x-ti-app-id": ti_app_id,
        "x-ti-secret-code": ti_secret_code,
    },
    timeout=60,
)

fetch_result = fetch_resp.json()
if fetch_result.get("code") != 200:
    print(f"Failed to get file list: {fetch_result.get('msg')}")
    exit(1)

files = fetch_result.get("result", {}).get("files", [])
extract_task_ids = []
for file in files:
    if file.get("recognition_status") == 1:  # Ensure extraction is completed
        task_id = file.get("task_id")
        if task_id:
            extract_task_ids.append(task_id)

if not extract_task_ids:
    print("No available extraction tasks")
    exit(1)

print(f"Found {len(extract_task_ids)} extraction tasks: {extract_task_ids}")

# 2. Create review task
submit_url = "/api/app-api/sip/platform/v2/review/task/submit"
submit_payload = {
    "workspace_id": workspace_id,
    "name": f"Review Task_{int(time.time())}",
    "repo_id": "31415926",  # Rule repository ID
    "extract_task_ids": extract_task_ids
}

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

submit_result = submit_resp.json()
if submit_result.get("code") == 200:
    task_id = submit_result.get("result", {}).get("task_id")
    print(f"Review task created successfully, Task ID: {task_id}")
    print("Please use the task ID to query review results")
else:
    print(f"Failed to create review task: {submit_result.get('msg')}")

​
Delete Review Task

If you need to delete a review task: 
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_ids": ["31415926", "31415927"]
  }' \
  "https://docflow.textin.com/api/app-api/sip/platform/v2/review/task/delete"
Request Parameters:
  • workspace_id (required): Workspace ID
  • task_ids (required): Array of review task IDs

​
Notes

  1. Extraction Task Status: Only tasks that have completed extraction (recognition_status == 1) can be used as review objects
  2. Parent Task Handling: If a parent task ID is provided (e.g., a parent task generated by file split or multi-image crop), the system will automatically retrieve all child tasks of that parent task as input for review
  3. Batch Number and Task ID Combination: If both batch_number and extract_task_ids are provided, the system will merge all tasks from the batch with extract_task_ids (with automatic deduplication)
  4. Rule Matching: The system will match rules based on the rule’s category_ids and the extraction task’s categories. Only matched rules will execute review
  5. Field Association: Ensure that fields referenced by rules exist in extraction results, otherwise it may affect review accuracy
  6. Asynchronous Execution: Review tasks are executed asynchronously. After creating a task, you need to query review status and results via the Get Review Results interface