ตัวแปลง AI เป็น DXF

# 1. Create job
curl -X POST https://api.runconvert.com/v3/jobs \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "tag": "ai-to-dxf",
    "tasks": {
      "upload-file": {
        "operation": "import/direct/upload"
      },
      "convert": {
        "operation": "convert",
        "input": "upload-file",
        "input_format": "ai",
        "output_format": "dxf"
      },
      "export-result": {
        "operation": "export/url",
        "input": "convert"
      }
    }
  }'

# 2. Upload your file (upload_url of the upload-file task in the response)
curl -X PUT "$UPLOAD_URL&filename=input.ai" --upload-file input.ai

# 3. Poll for result
curl https://api.runconvert.com/v3/jobs/$JOB_ID?include=tasks \
  -H "Authorization: Bearer YOUR_API_KEY"

const API_KEY = 'YOUR_API_KEY';
const BASE = 'https://api.runconvert.com/v3';

// 1. Create job
const { data: job } = await fetch(`${BASE}/jobs`, {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    tag: 'ai-to-dxf',
    tasks: {
      'upload-file': { operation: 'import/direct/upload' },
      convert: {
        operation: 'convert',
        input: 'upload-file',
        input_format: 'ai',
        output_format: 'dxf',
      },
      'export-result': { operation: 'export/url', input: 'convert' },
    },
  }),
}).then((r) => r.json());

// 2. Upload file
const uploadTask = job.tasks.find((t) => t.name === 'upload-file');
await fetch(`${uploadTask.upload_url}&filename=input.ai`, { method: 'PUT', body: fileBlob });

// 3. Poll until finished
let downloadUrl;
while (!downloadUrl) {
  await new Promise((r) => setTimeout(r, 1000));
  const { data } = await fetch(
    `${BASE}/jobs/${job.id}?include=tasks`,
    { headers: { Authorization: `Bearer ${API_KEY}` } },
  ).then((r) => r.json());

  if (data.status === 'error') throw new Error(`Job ${job.id} failed`);
  if (data.status === 'finished') {
    const exportTask = data.tasks.find((t) => t.name === 'export-result');
    downloadUrl = exportTask.result.files[0].url;
  }
}
console.log('Download URL:', downloadUrl);

import requests, time

API_KEY = 'YOUR_API_KEY'
BASE = 'https://api.runconvert.com/v3'
HEADERS = {'Authorization': f'Bearer {API_KEY}'}

# 1. Create job
job = requests.post(f'{BASE}/jobs', headers=HEADERS, json={
    'tag': 'ai-to-dxf',
    'tasks': {
        'upload-file': {'operation': 'import/direct/upload'},
        'convert': {
            'operation': 'convert',
            'input': 'upload-file',
            'input_format': 'ai',
            'output_format': 'dxf',
        },
        'export-result': {'operation': 'export/url', 'input': 'convert'},
    },
}).json()['data']

# 2. Upload file
upload_task = next(t for t in job['tasks'] if t['name'] == 'upload-file')
with open('input.ai', 'rb') as f:
    requests.put(upload_task['upload_url'] + '&filename=input.ai', data=f)

# 3. Poll until finished
while True:
    data = requests.get(
        f"{BASE}/jobs/{job['id']}?include=tasks",
        headers=HEADERS,
    ).json()['data']
    if data['status'] == 'error':
        raise RuntimeError(f"Job {job['id']} failed")
    if data['status'] == 'finished':
        export_task = next(t for t in data['tasks'] if t['name'] == 'export-result')
        print('Download URL:', export_task['result']['files'][0]['url'])
        break
    time.sleep(1)