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For tasks that have completed extraction, you can use the extract specific fields API to extract additional fields or re-extract individual existing fields for the task. This API returns the complete extraction results of all fields.

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Features

  • Extract Additional Fields: Add new field extraction for tasks that have completed extraction
  • Re-extract Fields: Re-extract existing fields, which can be used to correct or optimize extraction results
  • Support Table Fields: Can extract specific fields from tables
  • Return Complete Results: Returns complete extraction results of all fields, with the same structure as /api/app-api/sip/platform/v2/file/fetch

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Field Extraction Rules

The API adopts different extraction strategies based on whether the field exists in the original classification configuration:

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Additional Fields (Fields Not in Original Results)

For fields that do not exist in the original extraction results (additional fields), the system will use the prompt provided in the request for extraction:
  • If a prompt is provided in the request, it will be used to guide field extraction
  • If no prompt is provided in the request, the default extraction logic will be used
Use Case: When you need to extract new fields for documents that are not defined in the classification configuration.

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Configured Fields (Fields Already in Original Classification)

For fields that already exist in the original classification configuration, the system will prioritize using the settings from the classification configuration for extraction:
  • Use the prompt from the classification configuration (if configured)
  • Apply post-processing rules from the classification configuration
  • Ignore the prompt parameter passed in the request
Use Case: Re-extracting existing fields to ensure unified classification configuration rules are used, maintaining consistency in extraction results.

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Usage Recommendations

  • Extract New Fields: Provide a prompt in the request, and the system will use that prompt for extraction
  • Re-extract Existing Fields: Simply specify the key, and the system will automatically use the rules from the classification configuration; no need to provide a prompt in the request

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API Endpoint

Endpoint: POST /api/app-api/sip/platform/v2/file/extract_fields Request Parameters:
ParameterTypeRequiredDescription
workspace_idstringYesWorkspace ID
task_idstringYesTask ID
fieldsarrayNoList of fields to extract, each field contains key (field name) and prompt (field hint, optional)
tablesarrayNoList of table fields to extract, each table contains name (table name) and fields (field list)

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Field Structure

ExtractFieldReqVO: 
{
  "key": "Invoice Code",        // Field name
  "prompt": "Keep only the year part"  // Field hint (optional)
}
Table Structure: 
{
  "name": "Table1",        // Table name
  "fields": [              // Field list
    {
      "key": "Goods Name",
      "prompt": "Extract full product name"
    }
  ]
}

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Example Code

import requests
import json

def extract_specific_fields(workspace_id, task_id, app_id, secret_code):
    """Extract specific fields"""
    
    host = "https://docflow.textin.com"
    url = "/api/app-api/sip/platform/v2/file/extract_fields"
    
    # Request body
    payload = {
        "workspace_id": workspace_id,
        "task_id": task_id,
        "fields": [
            {
                "key": "Invoice Code",
                "prompt": "Extract complete invoice code"
            },
            {
                "key": "Invoice Date",
                "prompt": "Keep only the year part"
            }
        ],
        "tables": [
            {
                "name": "Table1",
                "fields": [
                    {
                        "key": "Goods Name",
                        "prompt": "Extract full product name"
                    },
                    {
                        "key": "Unit Price"
                    }
                ]
            }
        ]
    }
    
    resp = requests.post(
        f"{host}{url}",
        json=payload,
        headers={
            "x-ti-app-id": app_id,
            "x-ti-secret-code": secret_code,
            "Content-Type": "application/json"
        },
        timeout=60,
    )
    
    if resp.status_code != 200:
        print(f"Request failed: {resp.status_code}")
        print(f"Error message: {resp.text}")
        return None
    
    data = resp.json()
    
    if data.get("code") != 200:
        print(f"API returned error: {data.get('message')}")
        return None
    
    # Process returned results
    result = data.get("result", {})
    files = result.get("files", [])
    
    for file in files:
        print(f"File name: {file.get('name')}")
        print(f"Task ID: {file.get('task_id')}")
        
        # Extract field information
        file_data = file.get("data", {})
        fields = file_data.get("fields", [])
        
        if fields:
            print("\n=== Field Information ===")
            for field in fields:
                key = field.get("key", "")
                value = field.get("value", "")
                positions = field.get("position", [])
                
                print(f"Field: {key}")
                print(f"Value: {value}")
                
                # Display position information
                for i, pos in enumerate(positions):
                    page = pos.get("page", 0)
                    vertices = pos.get("vertices", [])
                    print(f"  Position {i+1} (Page {page+1}): {vertices}")
                print("-" * 30)
        
        # Extract table information
        tables = file_data.get("tables", [])
        if tables:
            print("\n=== Table Information ===")
            for table in tables:
                table_name = table.get("tableName", "")
                print(f"Table name: {table_name}")
                items = table.get("items", [])
                for row_idx, row in enumerate(items):
                    print(f"  Row {row_idx + 1}:")
                    for cell in row:
                        print(f"    {cell.get('key')}: {cell.get('value')}")
    
    return data

# Usage example
if __name__ == "__main__":
    workspace_id = "<your-workspace-id>"
    task_id = "<your-task-id>"
    app_id = "<your-app-id>"
    secret_code = "<your-secret-code>"
    
    result = extract_specific_fields(workspace_id, task_id, app_id, secret_code)

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Request Examples

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Extract Basic Fields Only

{
  "workspace_id": "1234567890",
  "task_id": "202412190001",
  "fields": [
    {
      "key": "Invoice Code"
    },
    {
      "key": "Invoice Date",
      "prompt": "Keep only the year part"
    }
  ]
}

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Extract Table Fields Only

{
  "workspace_id": "1234567890",
  "task_id": "202412190001",
  "tables": [
    {
      "name": "Table1",
      "fields": [
        {
          "key": "Goods Name"
        },
        {
          "key": "Unit Price"
        },
        {
          "key": "Quantity"
        }
      ]
    }
  ]
}

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Extract Both Basic Fields and Table Fields

{
  "workspace_id": "1234567890",
  "task_id": "202412190001",
  "fields": [
    {
      "key": "Invoice Code"
    },
    {
      "key": "Invoice Date"
    }
  ],
  "tables": [
    {
      "name": "Table1",
      "fields": [
        {
          "key": "Goods Name",
          "prompt": "Extract full product name"
        },
        {
          "key": "Unit Price"
        }
      ]
    }
  ]
}

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Return Data Example

{
  "code": 200,
  "message": "success",
  "result": {
    "total": 1,
    "page": 1,
    "page_size": 20,
    "files": [
      {
        "id": "202412190001",
        "task_id": "202412190001",
        "name": "invoice.pdf",
        "recognition_status": 1,
        "data": {
          "fields": [
            {
              "key": "Invoice Code",
              "value": "3100231130",
              "position": [
                {
                  "page": 0,
                  "vertices": [100, 150, 200, 150, 200, 180, 100, 180]
                }
              ]
            },
            {
              "key": "Invoice Date",
              "value": "2024",
              "position": [
                {
                  "page": 0,
                  "vertices": [400, 150, 500, 150, 500, 180, 400, 180]
                }
              ]
            }
          ],
          "tables": [
            {
              "tableName": "Table1",
              "tableType": "0",
              "items": [
                [
                  {
                    "key": "Goods Name",
                    "value": "Electronic Computer Microcomputer Host",
                    "position": [
                      {
                        "page": 0,
                        "vertices": [100, 300, 400, 300, 400, 330, 100, 330]
                      }
                    ]
                  },
                  {
                    "key": "Unit Price",
                    "value": "5000.00",
                    "position": [
                      {
                        "page": 0,
                        "vertices": [500, 300, 600, 300, 600, 330, 500, 330]
                      }
                    ]
                  }
                ]
              ]
            }
          ]
        }
      }
    ]
  }
}

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Notes

  1. Task Status: This API is only applicable to tasks that have completed extraction (recognition_status is 1 or 2)
  2. Field Name: The key field name needs to match the field name in the configured field template (for configured fields) or use a custom name (for additional fields)
  3. Field Hint (prompt):
    • For additional fields (not in original results), prompt will take effect and can be used to guide extraction logic
    • For configured fields (already in original classification), prompt will be ignored, and the system will use rules from the classification configuration
  4. Return Results: The API returns complete extraction results of all fields, including previously extracted fields and newly extracted fields
  5. Table Name: The name in tables needs to match the actual table name in the document