Migrate to @fal-ai/client
The @fal-ai/serverless-client
package has been deprecated in favor of @fal-ai/client
. Please check the migration guide for more information.
Generate Image
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/client
The @fal-ai/serverless-client
package has been deprecated in favor of @fal-ai/client
. Please check the migration guide for more information.
Set FAL_KEY
as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"
The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.
import { fal } from "@fal-ai/client";
const result = await fal.subscribe("fal-ai/flux-realism", {
input: {
prompt: "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation."
},
logs: true,
onQueueUpdate: (update) => {
if (update.status === "IN_PROGRESS") {
update.logs.map((log) => log.message).forEach(console.log);
}
},
});
console.log(result.data);
console.log(result.requestId);
The API uses an API Key for authentication. It is recommended you set the FAL_KEY
environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_KEY"
});
When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY
. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.
The client API provides a convenient way to submit requests to the model.
import { fal } from "@fal-ai/client";
const { request_id } = await fal.queue.submit("fal-ai/flux-realism", {
input: {
prompt: "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation."
},
webhookUrl: "https://optional.webhook.url/for/results",
});
You can fetch the status of a request to check if it is completed or still in progress.
import { fal } from "@fal-ai/client";
const status = await fal.queue.status("fal-ai/flux-realism", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});
Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.
import { fal } from "@fal-ai/client";
const result = await fal.queue.result("fal-ai/flux-realism", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);
Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.
You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.
You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.
We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.
import { fal } from "@fal-ai/client";
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);
The client will auto-upload the file for you if you pass a binary object (e.g. File
, Data
).
Read more about file handling in our file upload guide.
prompt
string
* requiredThe prompt to generate an image from.
The size of the generated image. Default value: landscape_4_3
Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
Note: For custom image sizes, you can pass the width
and height
as an object:
"image_size": {
"width": 1280,
"height": 720
}
num_inference_steps
integer
The number of inference steps to perform. Default value: 28
seed
integer
The same seed and the same prompt given to the same version of the model will output the same image every time.
guidance_scale
float
The CFG (Classifier Free Guidance) scale is a measure of how close you want
the model to stick to your prompt when looking for a related image to show you. Default value: 3.5
sync_mode
boolean
If set to true, the function will wait for the image to be generated and uploaded before returning the response. This will increase the latency of the function but it allows you to get the image directly in the response without going through the CDN.
num_images
integer
The number of images to generate. Default value: 1
enable_safety_checker
boolean
If set to true, the safety checker will be enabled. Default value: true
strength
float
The strength of the model. Default value: 1
output_format
OutputFormatEnum
The output image format. Default value: "jpeg"
Possible enum values: jpeg, png
{
"prompt": "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation.",
"image_size": "landscape_4_3",
"num_inference_steps": 28,
"guidance_scale": 3.5,
"num_images": 1,
"enable_safety_checker": true,
"strength": 1,
"output_format": "jpeg"
}
The generated image files info.
seed
integer
* requiredSeed of the generated Image. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed.
Whether the generated images contain NSFW concepts.
prompt
string
* requiredThe prompt used for generating the image.
{
"images": [
{
"url": "",
"content_type": "image/jpeg"
}
],
"prompt": ""
}
width
integer
The width of the generated image. Default value: 512
height
integer
The height of the generated image. Default value: 512
url
string
* requiredwidth
integer
* requiredheight
integer
* requiredcontent_type
string
Default value: "image/jpeg"