Prediction

Model

pipeline-examples/tile

dch1aj4hm9rm80crq3k9axhmrg

Status

Succeeded

Source

Web

Hardware

CPU (Small)

Total duration

26.8s

Created

3 months ago

Webhook

–

Input

prompt: a network of interconnected pipes
input_image: https://replicate.delivery/pbxt/NYHmuV6SArbn0iLUqlsT9l8fBS2IBzh9515Jom1nIfxQsbKL/tmplhnm_9ui.png
model: black-forest-labs/flux-schnell
inpaint_model: ideogram
seam_percentage: 60

{
  "inpaint_model": "ideogram",
  "input_image": "https://replicate.delivery/pbxt/NYHmuV6SArbn0iLUqlsT9l8fBS2IBzh9515Jom1nIfxQsbKL/tmplhnm_9ui.png",
  "model": "black-forest-labs/flux-schnell",
  "prompt": "a network of interconnected pipes",
  "seam_percentage": 60
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_ZpA**********************************

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 pipeline-examples/tile using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  inpaint_model: "ideogram",
  input_image: "https://replicate.delivery/pbxt/NYHmuV6SArbn0iLUqlsT9l8fBS2IBzh9515Jom1nIfxQsbKL/tmplhnm_9ui.png",
  model: "black-forest-labs/flux-schnell",
  prompt: "a network of interconnected pipes",
  seam_percentage: 60
};

const output = await replicate.run("pipeline-examples/tile", { 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_ZpA**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run pipeline-examples/tile using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "pipeline-examples/tile",
    input={
        "inpaint_model": "ideogram",
        "input_image": "https://replicate.delivery/pbxt/NYHmuV6SArbn0iLUqlsT9l8fBS2IBzh9515Jom1nIfxQsbKL/tmplhnm_9ui.png",
        "model": "black-forest-labs/flux-schnell",
        "prompt": "a network of interconnected pipes",
        "seam_percentage": 60
    }
)

# 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_ZpA**********************************

This is your API token. Keep it to yourself.

Run pipeline-examples/tile 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": {
      "inpaint_model": "ideogram",
      "input_image": "https://replicate.delivery/pbxt/NYHmuV6SArbn0iLUqlsT9l8fBS2IBzh9515Jom1nIfxQsbKL/tmplhnm_9ui.png",
      "model": "black-forest-labs/flux-schnell",
      "prompt": "a network of interconnected pipes",
      "seam_percentage": 60
    }
  }' \
  https://api.replicate.com/v1/models/pipeline-examples/tile/predictions

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

Output

Generated in

26.3 seconds

Tweak it Report