Prediction

Official model

luma/ray

qnjvm3qyqxrge0ckqeyrts7cg4

Status

Succeeded

Source

Web

Total duration

38.4s

Created

about 1 year ago

Webhook

–

Input

prompt: This video shows the majestic beauty of a waterfall cascading down a cliff into a serene lake. The waterfall, with its powerful flow, is the central focus of the video. The surrounding landscape is lush and green, with trees and foliage adding to the natural beauty of the scene
aspect_ratio: 16:9
loop: false

{
  "aspect_ratio": "16:9",
  "loop": false,
  "prompt": "This video shows the majestic beauty of a waterfall cascading down a cliff into a serene lake. The waterfall, with its powerful flow, is the central focus of the video. The surrounding landscape is lush and green, with trees and foliage adding to the natural beauty of the scene"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_RhK**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run luma/ray using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  aspect_ratio: "16:9",
  loop: false,
  prompt: "This video shows the majestic beauty of a waterfall cascading down a cliff into a serene lake. The waterfall, with its powerful flow, is the central focus of the video. The surrounding landscape is lush and green, with trees and foliage adding to the natural beauty of the scene"
};

const output = await replicate.run("luma/ray", { input });

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_RhK**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run luma/ray using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray",
    input={
        "aspect_ratio": "16:9",
        "loop": False,
        "prompt": "This video shows the majestic beauty of a waterfall cascading down a cliff into a serene lake. The waterfall, with its powerful flow, is the central focus of the video. The surrounding landscape is lush and green, with trees and foliage adding to the natural beauty of the scene"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_RhK**********************************

This is your API token. Keep it to yourself.

Run luma/ray using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "input": {
      "aspect_ratio": "16:9",
      "loop": false,
      "prompt": "This video shows the majestic beauty of a waterfall cascading down a cliff into a serene lake. The waterfall, with its powerful flow, is the central focus of the video. The surrounding landscape is lush and green, with trees and foliage adding to the natural beauty of the scene"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Generated in

38.3 seconds

Tweak it Upscale Iterate in playground Report