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v1

latestOpenAPI 3.0.2Apache-2.02026-07-142963051.0 MB
AI

Extract metadata (structured)

Sends an AI request to supported Large Language Models (LLMs) and returns extracted metadata as a set of key-value pairs.

To define the extraction structure, provide either a metadata template or a list of fields. To learn more about creating templates, see Creating metadata templates in the Admin Console or use the metadata template API.

This endpoint also supports Enhanced Extract Agent.

For information about supported file formats and languages, see the Extract metadata from file (structured) API guide.

post/ai/extract_structured

Request body

include_confidence_scoreboolean

A flag to indicate whether confidence scores for every extracted field should be returned.

include_referenceboolean

A flag to indicate whether references for every extracted field should be returned.

Example request

{
  "items": [
    {
      "id": "123",
      "type": "file",
      "content": "This is file content."
    }
  ],
  "metadata_template": {
    "template_key": "invoiceTemplate",
    "type": "metadata_template",
    "scope": "enterprise_12345"
  },
  "fields": [
    {
      "key": "name",
      "description": "The name of the person.",
      "displayName": "Name",
      "prompt": "Name is the first and last name from the email address",
      "type": "enum",
      "options": [
        {
          "key": "First Name"
        },
        {
          "key": "Last Name"
        }
      ],
      "fields": [
        {
          "key": "street_name",
          "description": "The street name of the address.",
          "displayName": "Street Name",
          "prompt": "The street name from the address section",
          "type": "string",
          "options": [
            {
              "key": "First Name"
            }
          ]
        }
      ],
      "taxonomy_key": "certification_taxonomy",
      "namespace": "enterprise_123",
      "options_rules": {
        "multi_select": true,
        "selectable_levels": [
          1
        ]
      }
    }
  ],
  "ai_agent": {
    "type": "ai_agent_id",
    "id": "14031"
  },
  "include_confidence_score": true,
  "include_reference": true,
  "taxonomy_sources": [
    {
      "type": "taxonomy",
      "taxonomy_key": "certification_taxonomy",
      "namespace": "enterprise_123"
    },
    {
      "type": "file",
      "taxonomy_key": "industry_taxonomy",
      "id": "1234567890"
    }
  ]
}

Response

A successful response including the answer from the LLM.

answerAiExtractResponse required

AI extract response. The content of this response may vary depending on the requested configuration.

created_atstring date-time required

The ISO date formatted timestamp of when the answer to the prompt was created.

completion_reasonstring

The reason the response finishes.

confidence_scoreobject

The confidence score levels and numeric values for each extracted field as a JSON dictionary. This can be empty if no field could be extracted.

referenceobject

The reference for each extracted field as a JSON dictionary. This can be empty if no field could be extracted.

Example response

{
  "created_at": "2012-12-12T10:53:43-08:00",
  "completion_reason": "done",
  "ai_agent_info": {
    "models": [
      {
        "name": "azure__openai__text_embedding_ada_002",
        "provider": "azure",
        "supported_purpose": "embedding"
      }
    ],
    "processor": "basic_text"
  }
}