curl --request POST \
  --url https://api.example.com/v1/projects/{project_id}/extract \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --header 'x-selected-account-id: <api-key>' \
  --data @- <<EOF
{
  "parameters": {
    "extraction_schema": {
      "properties": {
        "invoice_id": {
          "description": "The unique invoice identifier.",
          "type": "string"
        },
        "total_amount": {
          "description": "The final amount due.",
          "type": "number"
        }
      },
      "required": [
        "invoice_id",
        "total_amount"
      ],
      "type": "object"
    },
    "generate_citations": true,
    "model": "openai/gpt-4",
    "system_prompt": "You are an expert financial analyst. Extract data with high precision.",
    "user_prompt": "The invoice total can be found near the bottom right. Pay close attention to the 'Total Due' label."
  },
  "source_id": "job_parse_xyz..."
}
EOF

import requests

url = "https://api.example.com/v1/projects/{project_id}/extract"

payload = {
    "parameters": {
        "extraction_schema": {
            "properties": {
                "invoice_id": {
                    "description": "The unique invoice identifier.",
                    "type": "string"
                },
                "total_amount": {
                    "description": "The final amount due.",
                    "type": "number"
                }
            },
            "required": ["invoice_id", "total_amount"],
            "type": "object"
        },
        "generate_citations": True,
        "model": "openai/gpt-4",
        "system_prompt": "You are an expert financial analyst. Extract data with high precision.",
        "user_prompt": "The invoice total can be found near the bottom right. Pay close attention to the 'Total Due' label."
    },
    "source_id": "job_parse_xyz..."
}
headers = {
    "x-api-key": "<api-key>",
    "x-selected-account-id": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {
    'x-api-key': '<api-key>',
    'x-selected-account-id': '<api-key>',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    parameters: {
      extraction_schema: {
        properties: {
          invoice_id: {description: 'The unique invoice identifier.', type: 'string'},
          total_amount: {description: 'The final amount due.', type: 'number'}
        },
        required: ['invoice_id', 'total_amount'],
        type: 'object'
      },
      generate_citations: true,
      model: 'openai/gpt-4',
      system_prompt: 'You are an expert financial analyst. Extract data with high precision.',
      user_prompt: 'The invoice total can be found near the bottom right. Pay close attention to the \'Total Due\' label.'
    },
    source_id: 'job_parse_xyz...'
  })
};

fetch('https://api.example.com/v1/projects/{project_id}/extract', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/v1/projects/{project_id}/extract",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'parameters' => [
        'extraction_schema' => [
                'properties' => [
                                'invoice_id' => [
                                                                'description' => 'The unique invoice identifier.',
                                                                'type' => 'string'
                                ],
                                'total_amount' => [
                                                                'description' => 'The final amount due.',
                                                                'type' => 'number'
                                ]
                ],
                'required' => [
                                'invoice_id',
                                'total_amount'
                ],
                'type' => 'object'
        ],
        'generate_citations' => true,
        'model' => 'openai/gpt-4',
        'system_prompt' => 'You are an expert financial analyst. Extract data with high precision.',
        'user_prompt' => 'The invoice total can be found near the bottom right. Pay close attention to the \'Total Due\' label.'
    ],
    'source_id' => 'job_parse_xyz...'
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-api-key: <api-key>",
    "x-selected-account-id: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/v1/projects/{project_id}/extract"

	payload := strings.NewReader("{\n  \"parameters\": {\n    \"extraction_schema\": {\n      \"properties\": {\n        \"invoice_id\": {\n          \"description\": \"The unique invoice identifier.\",\n          \"type\": \"string\"\n        },\n        \"total_amount\": {\n          \"description\": \"The final amount due.\",\n          \"type\": \"number\"\n        }\n      },\n      \"required\": [\n        \"invoice_id\",\n        \"total_amount\"\n      ],\n      \"type\": \"object\"\n    },\n    \"generate_citations\": true,\n    \"model\": \"openai/gpt-4\",\n    \"system_prompt\": \"You are an expert financial analyst. Extract data with high precision.\",\n    \"user_prompt\": \"The invoice total can be found near the bottom right. Pay close attention to the 'Total Due' label.\"\n  },\n  \"source_id\": \"job_parse_xyz...\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-api-key", "<api-key>")
	req.Header.Add("x-selected-account-id", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/v1/projects/{project_id}/extract")
  .header("x-api-key", "<api-key>")
  .header("x-selected-account-id", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"parameters\": {\n    \"extraction_schema\": {\n      \"properties\": {\n        \"invoice_id\": {\n          \"description\": \"The unique invoice identifier.\",\n          \"type\": \"string\"\n        },\n        \"total_amount\": {\n          \"description\": \"The final amount due.\",\n          \"type\": \"number\"\n        }\n      },\n      \"required\": [\n        \"invoice_id\",\n        \"total_amount\"\n      ],\n      \"type\": \"object\"\n    },\n    \"generate_citations\": true,\n    \"model\": \"openai/gpt-4\",\n    \"system_prompt\": \"You are an expert financial analyst. Extract data with high precision.\",\n    \"user_prompt\": \"The invoice total can be found near the bottom right. Pay close attention to the 'Total Due' label.\"\n  },\n  \"source_id\": \"job_parse_xyz...\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/v1/projects/{project_id}/extract")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["x-selected-account-id"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"parameters\": {\n    \"extraction_schema\": {\n      \"properties\": {\n        \"invoice_id\": {\n          \"description\": \"The unique invoice identifier.\",\n          \"type\": \"string\"\n        },\n        \"total_amount\": {\n          \"description\": \"The final amount due.\",\n          \"type\": \"number\"\n        }\n      },\n      \"required\": [\n        \"invoice_id\",\n        \"total_amount\"\n      ],\n      \"type\": \"object\"\n    },\n    \"generate_citations\": true,\n    \"model\": \"openai/gpt-4\",\n    \"system_prompt\": \"You are an expert financial analyst. Extract data with high precision.\",\n    \"user_prompt\": \"The invoice total can be found near the bottom right. Pay close attention to the 'Total Due' label.\"\n  },\n  \"source_id\": \"job_parse_xyz...\"\n}"

response = http.request(request)
puts response.read_body

{
  "id": "<string>",
  "project_id": "<string>",
  "operation": "parse",
  "status": "pending",
  "created_at": "2023-11-07T05:31:56Z",
  "object": "job",
  "source_id": "<string>",
  "correlation_id": "<string>",
  "started_at": "2023-11-07T05:31:56Z",
  "completed_at": "2023-11-07T05:31:56Z",
  "result": {},
  "progress": {
    "total": 123,
    "succeeded": 123,
    "failed": 123,
    "cancelled": 123,
    "pending": 123,
    "child_jobs": [
      {
        "source_document_id": "<string>",
        "job_id": "<string>",
        "status": "pending",
        "parse_result_id": "<string>",
        "error": "<string>"
      }
    ]
  },
  "error": "<string>",
  "history": [
    {
      "step": "<string>",
      "timestamp": "2023-11-07T05:31:56Z",
      "duration_ms": 123,
      "status": "<string>",
      "details": {}
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}