typetext
{
"aspect_ratio": "1:1",
"output_format": "webp",
"output_quality": 80,
"prompt": "486 computer with CRT monitor, displaying programmer code in monochrome green, smoky dark bedroom, photo taken in the early 90's, photorealistic",
"prompt_upsampling": true,
"safety_tolerance": 2
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_Jq0**********************************
This is your API token. Keep it to yourself.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run black-forest-labs/flux-1.1-pro using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = {
aspect_ratio: "1:1",
output_format: "webp",
output_quality: 80,
prompt: "486 computer with CRT monitor, displaying programmer code in monochrome green, smoky dark bedroom, photo taken in the early 90's, photorealistic",
prompt_upsampling: true,
safety_tolerance: 2
};
const output = await replicate.run("black-forest-labs/flux-1.1-pro", { 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.
pip install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_Jq0**********************************
This is your API token. Keep it to yourself.
import replicate
Run black-forest-labs/flux-1.1-pro using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"black-forest-labs/flux-1.1-pro",
input={
"aspect_ratio": "1:1",
"output_format": "webp",
"output_quality": 80,
"prompt": "486 computer with CRT monitor, displaying programmer code in monochrome green, smoky dark bedroom, photo taken in the early 90's, photorealistic",
"prompt_upsampling": True,
"safety_tolerance": 2
}
)
# 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.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_Jq0**********************************
This is your API token. Keep it to yourself.
Run black-forest-labs/flux-1.1-pro 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": "1:1",
"output_format": "webp",
"output_quality": 80,
"prompt": "486 computer with CRT monitor, displaying programmer code in monochrome green, smoky dark bedroom, photo taken in the early 90\'s, photorealistic",
"prompt_upsampling": true,
"safety_tolerance": 2
}
}' \
https://api.replicate.com/v1/models/black-forest-labs/flux-1.1-pro/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "ajfrva4p4hrge0cjaf3bncfwn4",
"model": "black-forest-labs/flux-1.1-pro",
"version": "hidden",
"input": {
"aspect_ratio": "1:1",
"output_format": "webp",
"output_quality": 80,
"prompt": "486 computer with CRT monitor, displaying programmer code in monochrome green, smoky dark bedroom, photo taken in the early 90's, photorealistic",
"prompt_upsampling": true,
"safety_tolerance": 2
},
"logs": "Using seed: 34810\nRunning prediction... \nGenerating image...",
"output": "https://replicate.delivery/czjl/qmOBEyKh0qaMBNGHbQAOnX519XdmT26ktIhVqvCTvVXSdy4E/output.webp",
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2024-10-03T19:06:16.484Z",
"started_at": "2024-10-03T19:06:16.495753Z",
"completed_at": "2024-10-03T19:06:49.636051Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/ajfrva4p4hrge0cjaf3bncfwn4/cancel",
"get": "https://api.replicate.com/v1/predictions/ajfrva4p4hrge0cjaf3bncfwn4",
"web": "https://replicate.com/p/ajfrva4p4hrge0cjaf3bncfwn4"
},
"metrics": {
"image_count": 1,
"predict_time": 33.140297629,
"total_time": 33.152051
}
}