Luma Ray 2 Review: AI Video Generation Quality, Speed, and API Guide

import requests
import time

LUMA_API_KEY = "your-luma-api-key"
BASE_URL = "https://api.lumalabs.ai/dream-machine/v1"

headers = {
    "Authorization": f"Bearer {LUMA_API_KEY}",
    "Content-Type": "application/json"
}

# Create a generation
response = requests.post(
    f"{BASE_URL}/generations",
    headers=headers,
    json={
        "prompt": "A woman walking through a field of sunflowers at golden hour, "
                  "wind blowing through her hair, cinematic slow motion",
        "model": "ray-2",
        "resolution": "1080p",
        "duration": 5
    }
)

generation = response.json()
generation_id = generation["id"]
print(f"Generation started: {generation_id}")

def wait_for_generation(generation_id, timeout=120):
    start = time.time()
    while time.time() - start < timeout:
        resp = requests.get(
            f"{BASE_URL}/generations/{generation_id}",
            headers=headers
        )
        data = resp.json()

        if data["state"] == "completed":
            return data["assets"]["video"]
        elif data["state"] == "failed":
            raise Exception(f"Generation failed: {data.get('failure_reason')}")

        print(f"Status: {data['state']}...")
        time.sleep(3)

    raise TimeoutError("Generation timed out")

video_url = wait_for_generation(generation_id)
print(f"Video ready: {video_url}")

# Animate a reference image
response = requests.post(
    f"{BASE_URL}/generations",
    headers=headers,
    json={
        "prompt": "The woman turns her head and smiles, gentle breeze",
        "model": "ray-2",
        "keyframes": {
            "frame0": {
                "type": "image",
                "url": "https://your-bucket.s3.amazonaws.com/portrait.jpg"
            }
        },
        "duration": 5,
        "resolution": "1080p"
    }
)

# Extend an existing video
response = requests.post(
    f"{BASE_URL}/generations",
    headers=headers,
    json={
        "prompt": "She continues walking and reaches a wooden bridge",
        "model": "ray-2",
        "keyframes": {
            "frame0": {
                "type": "generation",
                "id": previous_generation_id  # Continue from last frame
            }
        },
        "duration": 5
    }
)

const axios = require('axios');

const LUMA_API_KEY = 'your-luma-api-key';

async function generateVideo(prompt) {
  const response = await axios.post(
    'https://api.lumalabs.ai/dream-machine/v1/generations',
    {
      prompt,
      model: 'ray-2',
      resolution: '1080p',
      duration: 5
    },
    {
      headers: {
        'Authorization': `Bearer ${LUMA_API_KEY}`,
        'Content-Type': 'application/json'
      }
    }
  );

  const generationId = response.data.id;

  // Poll for result
  while (true) {
    const status = await axios.get(
      `https://api.lumalabs.ai/dream-machine/v1/generations/${generationId}`,
      { headers: { 'Authorization': `Bearer ${LUMA_API_KEY}` } }
    );

    if (status.data.state === 'completed') {
      return status.data.assets.video;
    }
    if (status.data.state === 'failed') {
      throw new Error(status.data.failure_reason);
    }

    await new Promise(r => setTimeout(r, 3000));
  }
}

from openai import OpenAI

# Step 1: Generate starting frame with DALL-E via Crazyrouter
client = OpenAI(
    api_key="your-crazyrouter-key",
    base_url="https://crazyrouter.com/v1"
)

image_response = client.images.generate(
    model="dall-e-3",
    prompt="A cozy cabin in snowy mountains, warm light from windows, evening",
    size="1792x1024"
)

image_url = image_response.data[0].url

# Step 2: Animate with Luma Ray 2
video_response = requests.post(
    f"{BASE_URL}/generations",
    headers=headers,
    json={
        "prompt": "Snow falls gently, smoke rises from chimney, aurora appears in sky",
        "model": "ray-2",
        "keyframes": {"frame0": {"type": "image", "url": image_url}},
        "duration": 7
    }
)

# Generate a 30-second video by chaining 5-second clips
clips = []
prompts = [
    "A rocket launches from a desert pad, flames and smoke billow",
    "The rocket climbs through clouds, blue sky transitions to black",
    "The rocket reaches orbit, Earth visible below, stars appear",
    "Solar panels deploy, the spacecraft rotates slowly",
    "Wide shot of the spacecraft orbiting Earth, sun rising behind it",
]

previous_id = None
for prompt in prompts:
    payload = {"prompt": prompt, "model": "ray-2", "duration": 6}
    if previous_id:
        payload["keyframes"] = {"frame0": {"type": "generation", "id": previous_id}}

    resp = requests.post(f"{BASE_URL}/generations", headers=headers, json=payload)
    gen_id = resp.json()["id"]
    video_url = wait_for_generation(gen_id)
    clips.append(video_url)
    previous_id = gen_id