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The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientSet 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/sensenova-u1-infographic", {
input: {
prompt: "A flat-design infographic titled 'The Lifecycle of a Tree' with five labeled stages laid out left-to-right (seed, sapling, young tree, mature tree, decomposition), soft pastel green-and-brown palette, minimal sans-serif headings, hand-drawn vector illustrations, white background, subtle drop-shadow on cards."
},
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"
});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/sensenova-u1-infographic", {
input: {
prompt: "A flat-design infographic titled 'The Lifecycle of a Tree' with five labeled stages laid out left-to-right (seed, sapling, young tree, mature tree, decomposition), soft pastel green-and-brown palette, minimal sans-serif headings, hand-drawn vector illustrations, white background, subtle drop-shadow on cards."
},
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/sensenova-u1-infographic", {
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/sensenova-u1-infographic", {
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);Read more about file handling in our file upload guide.
prompt string* requiredText prompt describing the infographic to generate. Detailed prompts that specify layout, sections, color palette, typography, and the data being visualized work best.
aspect_ratio AspectRatioEnumAspect ratio for the generated image. Maps to the trained resolution buckets — using ratios outside this set is not supported. Defaults to 16:9, which fits most poster / presentation-style infographics. Default value: "16:9"
Possible enum values: 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 1:2, 2:1
num_inference_steps integerNumber of flow-matching denoising steps. Default value: 50
guidance_scale floatClassifier-free guidance scale. Higher values follow the prompt more strictly. Default value: 4
timestep_shift floatTimestep shifting factor for the flow-matching sampler. Higher values bias sampling towards earlier timesteps. Default value: 3
use_thinking booleanIf True, run chain-of-thought before image generation. Improves complex-prompt fidelity but is slower and billed at 1.2x.
seed integerThe same seed and the same prompt given to the same version of the model will output the same image every time.
enable_safety_checker booleanIf set to true, the safety checker will be enabled. Default value: true
output_format OutputFormatEnumThe format of the generated image. Default value: "jpeg"
Possible enum values: jpeg, png
sync_mode booleanIf True, the media will be returned as a data URI and the output data won't be available in the request history.
{
"prompt": "A flat-design infographic titled 'The Lifecycle of a Tree' with five labeled stages laid out left-to-right (seed, sapling, young tree, mature tree, decomposition), soft pastel green-and-brown palette, minimal sans-serif headings, hand-drawn vector illustrations, white background, subtle drop-shadow on cards.",
"aspect_ratio": "16:9",
"num_inference_steps": 50,
"guidance_scale": 4,
"timestep_shift": 3,
"enable_safety_checker": true,
"output_format": "jpeg"
}The generated image(s).
seed integer* requiredThe seed used for the generation.
Whether the generated images contain NSFW concepts.
prompt string* requiredThe prompt used for the generation.
thinking stringChain-of-thought trace emitted when use_thinking is True, else null.
Per-stage timings in seconds.
{
"images": [
{
"url": "",
"content_type": "image/jpeg"
}
],
"prompt": ""
}url string* requiredwidth integer* requiredheight integer* requiredcontent_type stringDefault value: "image/jpeg"