Stable & Affordable Google Veo 3.1 Text-to-Video API with Audio

API Examples

Submit Example

// Step 1: Submit generation request
const response = await fetch('https://api.flaq.ai/api/v1/video/task', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_API_KEY'
  },
  body: JSON.stringify({
    model_name: 'veo3.1-text-to-video',
    prompt: 'A time-lapse of a flower blooming in a garden'
  })
});

const { data } = await response.json();
const taskId = data.task_id;

Polling Example

// Step 2: Poll for results
const taskId = data.task_id;

const pollResult = async (taskId) => {
  const res = await fetch(`https://api.flaq.ai/api/v1/video/${taskId}`, {
    headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
  });
  return res.json();
};

while (true) {
  const pollResultData = await pollResult(taskId);
  const status = pollResultData.data.task_status;

  if (status === 'succeed') {
    console.log(pollResultData.data.task_result.videos[0].url);
    break;
  }

  if (status === 'failed') {
    console.error(pollResultData.data.task_status_msg);
    break;
  }

  await new Promise(resolve => setTimeout(resolve, ));
}

Submit Example

# Step 1: Submit generation request
import requests

response = requests.post(
    'https://api.flaq.ai/api/v1/video/task',
    headers={
        'Content-Type': 'application/json',
        'Authorization': 'Bearer YOUR_API_KEY'
    },
    json={
        'model_name': 'veo3.1-text-to-video',
        'prompt': 'A time-lapse of a flower blooming in a garden'
    }
)

result = response.json()
task_id = result['data']['task_id']

Polling Example

# Step 2: Poll for results
task_id = response.json()['data'][]
poll_url = 

 :
    poll_result = requests.get(poll_url, headers={: }).json()
    status = poll_result[][]
     status == :
        (poll_result[][][][][])
        
     status == :
        (poll_result[][])
        
    time.sleep()

Submit Example

# Step 1: Submit generation request
curl -X POST https://api.flaq.ai/api/v1/video/task \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model_name": "veo3.1-text-to-video",
    "prompt": "A time-lapse of a flower blooming in a garden"
  }'

Polling Example

# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/video/{task_id}" \
  -H "Authorization: Bearer YOUR_API_KEY"

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API Examples

Submit Example

Polling Example

Submit Example

Polling Example

Submit Example

Polling Example

More Articles for Veo 3.1 Text to Video

Related Veo3 1 Models

Related Models

Premium Veo 3.1 Text-to-Video API (Google's Advanced Video Generation)

Key Features of Veo 3.1 Text-to-Video API

How to Use Veo 3.1 Text-to-Video API for Professional Video Generation on Best Image AI

Best Use Cases for Veo 3.1 Text-to-Video API Integration

Veo 3.1 Text-to-Video vs Competitors: Comparative Analysis

API Examples

Submit Example

Polling Example

Submit Example

Polling Example

Submit Example

Polling Example

More Articles for Veo 3.1 Text to Video