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POST
/
v2
/
extract
cURL
curl -X POST 'https://api.ade.landing.ai/v2/extract' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -F 'markdown=@parse-output.md' \
  -F 'schema={"type":"object","properties":{"revenue":{"type":"string","description":"Q1 2024 revenue"}}}'
import json
import requests

url = 'https://api.ade.landing.ai/v2/extract'
headers = {'Authorization': 'Bearer YOUR_API_KEY'}

files = {'markdown': open('parse-output.md', 'rb')}
data = {
    'schema': json.dumps({
        'type': 'object',
        'properties': {
            'revenue': {'type': 'string', 'description': 'Q1 2024 revenue'}
        }
    })
}

response = requests.post(url, headers=headers, files=files, data=data)
print(response.json())
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

const form = new FormData();
form.append('markdown', fs.createReadStream('parse-output.md'));
form.append('schema', JSON.stringify({
  type: 'object',
  properties: {
    revenue: { type: 'string', description: 'Q1 2024 revenue' }
  }
}));

axios.post('https://api.ade.landing.ai/v2/extract', form, {
  headers: { 'Authorization': 'Bearer YOUR_API_KEY', ...form.getHeaders() }
})
  .then(response => console.log(response.data))
  .catch(error => console.error(error));
{
  "extraction": {},
  "extraction_metadata": {},
  "markdown": "<string>",
  "metadata": {
    "job_id": "<string>",
    "version": "<string>",
    "duration_ms": 123,
    "doc_id": "<string>",
    "credit_usage": 0,
    "billing": {
      "total_credits": 123
    }
  }
}
{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

Body

Input to V2ExtractOperationWorkflow.

Provide the markdown as an inline markdown string, as a multipart file part named markdown (for large inputs — the gateway stages the upload internally), or via a public markdown_url. Exactly one source must be supplied.

​
schema
Schema · object
required

JSON Schema describing the fields to extract. The schema must be an object type with a properties map of field names to their types and descriptions.

Example:
{
  "properties": {
    "revenue": {
      "description": "Q1 revenue figure",
      "type": "string"
    },
    "summary": {
      "description": "Executive summary",
      "type": "string"
    }
  },
  "type": "object"
}
​
markdown
string | null

Markdown string to extract from, or a multipart FILE part carrying the markdown (large inputs — uploads are staged by the gateway). Can come from any source — LandingAI parse output, a third-party parser, or hand-authored text. When the markdown was produced by POST /v2/parse, it ends with a <!-- doc_id=<id> --> comment that the service reads automatically and echoes as metadata.doc_id.

​
markdown_url
string | null

URL to fetch the markdown from. Must be a public http(s) URL; private/loopback IPs are rejected at submit time.

​
model
string | null

The version of the model to use for extraction. Use extract-latest to use the latest version.

​
options
V2ExtractOptions · object | null

Extraction options (strict). Omit for defaults.

Response

v2-extract result

Result returned by V2ExtractOperationWorkflow — the /v2/extract response body (docs/extract-v2-proposal.md → Response).

extraction and extraction_metadata mirror each other structurally: leaf values in extraction are replaced by ExtractionFieldMetadata objects in extraction_metadata.

​
extraction
Extraction · object
required

Extracted values conforming to the request schema.

​
extraction_metadata
Extraction Metadata · object
required

Per-field metadata, mirroring extraction with leaf values replaced by {value, spans} objects.

​
markdown
string
required

Echoed input markdown.

​
metadata
V2ExtractMetadata · object
required

Request metadata (job_id, version, duration_ms, doc_id, credit_usage).