Luma AI Text-to-Video

Generate Videos from Text or Images

Overview

The Luma AI Dream Machine API allows developers to generate, retrieve, and extend AI-generated content using a variety of inputs. This API is particularly useful for creative applications, such as generating visual content from text prompts.

Authentication

All API requests require a Bearer token for authentication. Include your token in the Authorization header of each request.

Pricing

Each generation costs 500 000 AI/ML Tokens

API Reference

Ensure you replace "your-api-key" with your actual API key before running the code.

Generate a video using Luma AI.

Generates a video based on a prompt using Luma AI, allowing for video creation from textual descriptions.

POSThttps://api.aimlapi.com/luma-ai/generations

Body

application/json

aspect_ratio*string

The aspect ratio of the image

Example: "16:9"

expand_prompt*boolean

Whether to expand the prompt

Example: true

image_end_url*string

The URL for the end of the image

Example: "https://example.com/image-end.jpg"

image_url*string

The URL of the main image

Example: "https://example.com/main-image.jpg"

user_prompt*string

The user-provided prompt for image generation

Example: "A beautiful sunset over the ocean"

Response

200

Body

application/json

created_at*string

estimate_wait_seconds*string

id*string

liked*string

prompt*string

state*string

video*VideoDTO (object)

Request

JavaScriptCurlPython

const response = await fetch('https://api.aimlapi.com/luma-ai/generations', {
    method: 'POST',
    headers: {
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      "aspect_ratio": "16:9",
      "expand_prompt": true,
      "image_end_url": "https://example.com/image-end.jpg",
      "image_url": "https://example.com/main-image.jpg",
      "user_prompt": "A beautiful sunset over the ocean"
    }),
});
const data = await response.json();

Response

200

{
  "created_at": "text",
  "estimate_wait_seconds": "text",
  "id": "text",
  "liked": "text",
  "prompt": "text",
  "state": "text",
  "video": {
    "height": 0,
    "width": 0,
    "thumbnail": "text",
    "url": "text"
  }
}

Example

Python

import requests

url = "https://api.aimlapi.com/luma-ai/generations"

payload = {
  "aspect_ratio": "16:9",
  "expand_prompt": True,
  "user_prompt": "Flying jellyfish"
}
headers = {
  "Authorization": "Bearer your-api-key",
  "content-type": "application/json"
}

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

print(response.json())

JS

const axios = require('axios');

const url = "https://api.aimlapi.com/luma-ai/generations";

const payload = {
  aspect_ratio: "16:9",
  expand_prompt: true,
  user_prompt: "Flying jellyfish"
};

const headers = {
  "Authorization": "Bearer your-api-key",
  "content-type": "application/json"
};

axios.post(url, payload, { headers })
  .then(response => console.log(response.data))
  .catch(error => console.error(error));

List video generations by IDs in Luma AI.

Returns a list of video generations by their IDs in Luma AI.

GEThttps://api.aimlapi.com/luma-ai/generation

Query parameters

Response

200

Body

application/json

created_at*string

estimate_wait_seconds*string

id*string

liked*string

prompt*string

state*string

video*VideoDTO (object)

Request

JavaScriptCurlPython

const response = await fetch('https://api.aimlapi.com/luma-ai/generation?ids=text', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

[
  {
    "created_at": "text",
    "estimate_wait_seconds": "text",
    "id": "text",
    "liked": "text",
    "prompt": "text",
    "state": "text",
    "video": {
      "height": 0,
      "width": 0,
      "thumbnail": "text",
      "url": "text"
    }
  }
]

Example

Python

import requests

url = "https://api.aimlapi.com/luma-ai/generation"

querystring = {"ids[0]":"4c9126f3-d9a6-4eaf-aa4c-b64b634f65bd"}

headers = {
  "Authorization": "Bearer your-api-key",
  "content-type": "application/json"
}

response = requests.get(url, headers=headers, params=querystring)

print(response.json())

JS

const axios = require('axios');

const url = "https://api.aimlapi.com/luma-ai/generation";

const params = {
  "ids[0]": "4c9126f3-d9a6-4eaf-aa4c-b64b634f65bd"
};

const headers = {
  "Authorization": "Bearer your-api-key",
  "content-type": "application/json"
};

axios.get(url, { headers, params })
  .then(response => console.log(response.data))
  .catch(error => console.error(error));

Extend a video using Luma AI.

Extends an existing video using Luma AI, creating additional content for video projects.

POSThttps://api.aimlapi.com/luma-ai/generations/{taskId}/extend

Path parameters

taskId*string

Body

application/json

aspect_ratio*string

The aspect ratio of the image

Example: "16:9"

expand_prompt*boolean

Whether to expand the prompt

Example: true

image_end_url*string

The URL for the end of the image

Example: "https://example.com/image-end.jpg"

image_url*string

The URL of the main image

Example: "https://example.com/main-image.jpg"

user_prompt*string

The user-provided prompt for image generation

Example: "A beautiful sunset over the ocean"

Response

200

Body

application/json

id*string

created_at*string

estimate_wait_seconds*string

liked*string

prompt*string

state*string

video*VideoDTO (object)

Request

JavaScriptCurlPython

const response = await fetch('https://api.aimlapi.com/luma-ai/generations/{taskId}/extend', {
    method: 'POST',
    headers: {
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      "aspect_ratio": "16:9",
      "expand_prompt": true,
      "image_end_url": "https://example.com/image-end.jpg",
      "image_url": "https://example.com/main-image.jpg",
      "user_prompt": "A beautiful sunset over the ocean"
    }),
});
const data = await response.json();

Response

200

{
  "id": "text",
  "created_at": "text",
  "estimate_wait_seconds": "text",
  "liked": "text",
  "prompt": "text",
  "state": "text",
  "video": {
    "height": 0,
    "width": 0,
    "thumbnail": "text",
    "url": "text"
  }
}

Example

Python

import requests

url = "https://api.aimlapi.com/luma-ai/generations/57a6cb80-6da0-49bd-b29a-3f089b9e55e4/extend"

payload = {
  "aspect_ratio": "16:9",
  "expand_prompt": True,
  "user_prompt": "Flying jellyfish with a hat"
}
headers = {
  "Authorization": "Bearer your-api-key",
  "content-type": "application/json"
}

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

print(response.json())

JS

const axios = require('axios');

const url = "https://api.aimlapi.com/luma-ai/generations/57a6cb80-6da0-49bd-b29a-3f089b9e55e4/extend";

const payload = {
  aspect_ratio: "16:9",
  expand_prompt: true,
  user_prompt: "Flying jellyfish with a hat"
};

const headers = {
  "Authorization": "Bearer your-api-key",
  "content-type": "application/json"
};

axios.post(url, payload, { headers })
  .then(response => console.log(response.data))
  .catch(error => console.error(error));