Perform document extraction inference on the service

POST /_inference/document_extraction/{inference_id}

Auth

Extract the content of documents, such as PDFs or images of documents, into a textual format.

Required privileges

Cluster privileges monitor_inference

Path parameters

inference_id string required: The unique identifier for the inference endpoint.

Query parameters

timeout union oneOf · default: 120s: The amount of time to wait for the inference request to complete.; Values: -1 0

Request body

input union oneOf required

The documents to extract the content from. Either a content object or an array of content objects.

content object example:

"input": {
  "content": {
    "type": "pdf",
    "format": "base64",
    "value": "data:application/pdf;base64,..."
  }
}

content object array example:

"input": [
  {
    "content": {
      "type": "pdf",
      "format": "base64",
      "value": "data:application/pdf;base64,..."
    }
  },
  {
    "content": {
      "type": "image",
      "format": "url",
      "value": "https://example.com/scanned-page.png"
    }
  }
]

object or object[]

content object required: The document to extract the content from.

task_settings object

Task settings for the individual inference request. These settings are specific to the task type you specified and override the task settings specified when initializing the service.

Response

application/json

document_extraction object[] required

View as Markdown

Examples

Request Console 1 / 7 languages

Run POST _inference/document_extraction/my-document-extraction-endpoint to extract the content of the example PDF document

Console Kibana Dev Tools

POST _inference/document_extraction/my-document-extraction-endpoint
{
  "input": [
    {
      "content": {
        "type": "pdf",
        "format": "base64",
        "value": "data:application/pdf;base64,..."
      }
    }
  ]
}

JavaScript Elasticsearch JavaScript Client

const response = await client.inference.documentExtraction({
  inference_id: "my-document-extraction-endpoint",
  input: [
    {
      content: {
        type: "pdf",
        format: "base64",
        value: "data:application/pdf;base64,...",
      },
    },
  ],
});

Python Elasticsearch Python Client

resp = client.inference.document_extraction(
    inference_id="my-document-extraction-endpoint",
    input=[
        {
            "content": {
                "type": "pdf",
                "format": "base64",
                "value": "data:application/pdf;base64,..."
            }
        }
    ],
)

curl Shell

curl -X POST "$ELASTICSEARCH_URL/_inference/document_extraction/my-document-extraction-endpoint" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": [
      {
        "content": {
          "type": "pdf",
          "format": "base64",
          "value": "data:application/pdf;base64,..."
        }
      }
    ]
  }'

C# Elasticsearch .NET Client

var response = await client.Inference
    .DocumentExtractionAsync(inferenceId: "my-document-extraction-endpoint", d1 => d1
        .Input(d2 => d2
            .Content(d3 => d3
                .Format(DocumentExtractionContentFormat.Base64)
                .Type(DocumentExtractionContentType.Pdf)
                .Value("data:application/pdf;base64,...")
            )
        )
    );

PHP Elasticsearch PHP Client

$resp = $client->inference()->documentExtraction([
    "inference_id" => "my-document-extraction-endpoint",
    "body" => [
        "input" => array(
            [
                "content" => [
                    "type" => "pdf",
                    "format" => "base64",
                    "value" => "data:application/pdf;base64,...",
                ],
            ],
        ),
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.inference.document_extraction(
  inference_id: "my-document-extraction-endpoint",
  body: {
    "input": [
      {
        "content": {
          "type": "pdf",
          "format": "base64",
          "value": "data:application/pdf;base64,..."
        }
      }
    ]
  }
)

Response

An abbreviated response from POST _inference/document_extraction/my-document-extraction-endpoint.

{
  "document_extraction": [
    {
      "content": "# Annual Report 2025\n\n...",
      "format": "markdown",
      "metadata": {
        "title": "Annual Report 2025"
      }
    }
  ]
}

Request Console 1 / 7 languages

Run POST _inference/document_extraction/my-document-extraction-endpoint to extract the content of an image of a document referenced by URL as markdown.

Console Kibana Dev Tools

POST _inference/document_extraction/my-document-extraction-endpoint
{
  "input": {
    "content": {
      "type": "image",
      "format": "url",
      "value": "https://example.com/scanned-page.png"
    }
  },
  "task_settings": {
    "output_format": "markdown"
  }
}

JavaScript Elasticsearch JavaScript Client

const response = await client.inference.documentExtraction({
  inference_id: "my-document-extraction-endpoint",
  input: {
    content: {
      type: "image",
      format: "url",
      value: "https://example.com/scanned-page.png",
    },
  },
  task_settings: {
    output_format: "markdown",
  },
});

Python Elasticsearch Python Client

resp = client.inference.document_extraction(
    inference_id="my-document-extraction-endpoint",
    input={
        "content": {
            "type": "image",
            "format": "url",
            "value": "https://example.com/scanned-page.png"
        }
    },
    task_settings={
        "output_format": "markdown"
    },
)

curl Shell

curl -X POST "$ELASTICSEARCH_URL/_inference/document_extraction/my-document-extraction-endpoint" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": {
      "content": {
        "type": "image",
        "format": "url",
        "value": "https://example.com/scanned-page.png"
      }
    },
    "task_settings": {
      "output_format": "markdown"
    }
  }'

C# Elasticsearch .NET Client

var response = await client.Inference
    .DocumentExtractionAsync(inferenceId: "my-document-extraction-endpoint", d1 => d1
        .Input(d2 => d2
            .Content(d3 => d3
                .Format(DocumentExtractionContentFormat.Url)
                .Type(DocumentExtractionContentType.Image)
                .Value("https://example.com/scanned-page.png")
            )
        )
        .TaskSettings(d2 => d2
            .OutputFormat(DocumentExtractionOutputFormat.Markdown)
        )
    );

PHP Elasticsearch PHP Client

$resp = $client->inference()->documentExtraction([
    "inference_id" => "my-document-extraction-endpoint",
    "body" => [
        "input" => [
            "content" => [
                "type" => "image",
                "format" => "url",
                "value" => "https://example.com/scanned-page.png",
            ],
        ],
        "task_settings" => [
            "output_format" => "markdown",
        ],
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.inference.document_extraction(
  inference_id: "my-document-extraction-endpoint",
  body: {
    "input": {
      "content": {
        "type": "image",
        "format": "url",
        "value": "https://example.com/scanned-page.png"
      }
    },
    "task_settings": {
      "output_format": "markdown"
    }
  }
)

Response

No example