Custom API

Supported labeling types: Span labeling, row labeling, bounding box labeling, and document labeling.

We also support a Custom API option for using your own model in ML-assisted labeling by providing an API URL. Your API must follow the required request structure to integrate with the Datasaur platform. Here’s how to set it up:

Set up custom API for ML-assisted labeling

1. Build an API for your model that follows the required request and response format compatible with Datasaur. For guidance, refer to the API creation example.

   1. You can find example request and response bodies near the API URL input field or in the Examples section below.

2. Once your API is ready, enter the API URL in the designated field in the extension.

3. For span labeling project

   1. Sentences per request (0 = all): Define how many sentences are sent in a single API request.

4. For row labeling project

   1. Target text: Select the input text used as reference.

   2. Target question: Select the output column to predict.

   3. Faster prediction speed: Enables faster predictions by processing requests on the backend.

5. Confidence score: Adjust the value according to your needs.

6. Click Predict labels.

Examples

Custom API for span labeling

ML-assisted labeling with Custom API for span labeling

Request Body

{
    "id": "[project_id]",
    "name": "[project_name]",
    "documents": [
      {
        "id": "[document_id_1]",
        "sentences": [
          {
            "id": 0, // zero-based line number of the document
            "text": "first message",
            "metadata": []
          },
          {
            "id": 1,
            "text": "first message",
            "metadata": []
          },
        ]
      }
    ]
  }

Response Body

{
  "id": "[project_id]",
  "documents": [
    {
      "id": "[document_id_1]",
      "labels": [
        {
          "id": 0,
          "entities": [
            {
              "label": "LOCATION",
              "start_char": 10,
              "end_char": 18,
              "layer": 0
            },
            {
              "label": "PERSON",
              "start_char": 20,
              "end_char": 29,
              "layer": 1
            },
          ]
        },
        {
          "id": 1,
          "entities": []
        }
      ]
    }
  ]
}

Custom API for row labeling

ML-assisted labeling with Custom API for row labeling

Request Body

[
  { "id": 0, "text": "I feel good." },
  { "id": 1, "text": "I don't like it." }
]

Response Body

[
  { "id": 0, "label": "POSITIVE" },
  { "id": 1, "label": "NEGATIVE" }
]

Custom API for bounding box labeling

ML-assisted labeling with Custom API for bounding box labeling

Request Body

{
    "document": {
      "id": "[document_id_1]",
      "presignedURL": "[document_presigned_url]",
    },
    "readingResult": [
      {
        "id":"[bbox_id_1]",
        "label": "O",
        "caption": "First"
        "shapes": [
          {
            "pageIndex": 0,
            "points": [
                {
                  "x": 211.51411561127316,
                  "y": 99.08677657682311
                },
                {
                  "x": 266.385241834969,
                  "y": 99.08677657682311
                },
                {
                  "x": 266.385241834969,
                  "y": 105.74680188808318
                },
                {
                  "x": 211.51411561127316,
                  "y": 105.74680188808318
                }
              ]
            }
          }
        ]
      },
      {
        "id":"[bbox_id_2]",
        "label": "O",
        "caption": "Message"
        "shapes": [
          {
            "pageIndex": 0,
            "points": [
                {
                  "x": 269.38763779813405,
                  "y": 99.09397660418664
                },
                {
                  "x": 318.98117111775315,
                  "y": 99.09397660418664
                },
                {
                  "x": 318.98117111775315,
                  "y": 105.73240183335614
                },
                {
                  "x": 269.38763779813405,
                  "y": 105.73240183335614
                }
              ]
            }
          }
        ]
      }
    ]
  }

Response Body

{
    "id": "[document_id_1]",
    "labels": [
      {
        "id":"[bbox_id_1]",
        "label": "LOCATION",
        "caption": "First",
        "confidence_score": 0.90,
        "shapes": [
          {
            "pageIndex": 0,
            "points": [
              {
                "x": 211.51411561127316,
                "y": 99.08677657682311
              },
              {
                "x": 266.385241834969,
                "y": 99.08677657682311
              },
              {
                "x": 266.385241834969,
                "y": 105.74680188808318
              },
              {
                "x": 211.51411561127316,
                "y": 105.74680188808318
              }
            ]
          }
        ]
      },
      {
        "id":"[bbox_id_2]",
        "label": "PERSON",
        "caption": "Message",
        "confidence_score": 0.90,
        "shapes": [
          {
            "pageIndex": 0,
            "points": [
              {
                "x": 269.38763779813405,
                "y": 99.09397660418664
              },
              {
                "x": 318.98117111775315,
                "y": 99.09397660418664
              },
              {
                "x": 318.98117111775315,
                "y": 105.73240183335614
              },
              {
                "x": 269.38763779813405,
                "y": 105.73240183335614
              }
            ]
          }
        ]
      }
    ]
  }

Custom API for document labeling

ML-assisted labeling with Custom API for document labeling

Request Body

{
  "document": {
    "id": "[document_id_1]",
    "presignedURL": "[document_presigned_url]"
  }
}

Response Body

{
  "id": "[document_id_1]",
  "[your_document_question_a]": "POSITIVE",
  "[your_document_question_b_with_multiple_answer]": ["NEWS", "ARTICLE"]
}