Video Generation

Generate videos from text prompts in minutes

Overview

Generate videos from text descriptions, reference images, or existing videos.

Minimal Example (Synchronous)

Note: Synchronous generation can take 5-15 minutes to complete for certain models, we recommend using the async queue and polling for long-running jobs (See Below).

Python

import requests

response = requests.post(
    "https://hub.oxen.ai/api/ai/videos/generate",
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json={
        "model": "kling-video-v2-6-pro-text-to-video",
        "prompt": "A red balloon floating upward through blue sky",
        "duration": 5,
    },
)

data = response.json()
print("Video URL:", data["videos"][0]["url"])

curl -X POST https://hub.oxen.ai/api/ai/videos/generate \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kling-video-v2-6-pro-text-to-video",
    "prompt": "A red balloon floating upward through blue sky",
    "duration": 5
  }'

Async Generation (Recommended)

For video generation, using the async queue avoids long-lived HTTP connections:

Python

import requests
import time

API_KEY = "YOUR_API_KEY"
MODEL = "kling-video-v2-6-pro-text-to-video"
HEADERS = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json",
}

# 1. Enqueue
response = requests.post(
    "https://hub.oxen.ai/api/ai/queue",
    headers=HEADERS,
    json={
        "model": MODEL,
        "prompt": "A sunset timelapse over the ocean",
        "duration": 5,
    },
)
generation_id = response.json()["generations"][0]["generation_id"]
print(f"Enqueued generation: {generation_id}")

# 2. Poll until done
while True:
    data = requests.get(
        f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
        headers=HEADERS,
    ).json()
    print(f"Status: {data['status']}")
    if data["status"] in {"succeeded", "failed", "cancelled"}:
        break
    time.sleep(10)

if data["status"] == "succeeded":
    print(f"Done! Result: {data['result_url']}")
else:
    print(f"Generation {data['status']}: {data.get('error_message')}")

# 1. Enqueue
curl -X POST https://hub.oxen.ai/api/ai/queue \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kling-video-v2-6-pro-text-to-video",
    "prompt": "A sunset timelapse over the ocean",
    "duration": 5
  }'

# 2. Poll until done
curl -H "Authorization: Bearer YOUR_API_KEY" \
  "https://hub.oxen.ai/api/ai/queue?model=kling-video-v2-6-pro-text-to-video"

What’s Next

• Video Generation Reference for the full parameter list
• Kling O3 Pro: Reference to Video for multi-shot video with reference images
• Async Queue Reference for batch generation