Generate an image from text prompt with LoRA support.
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.
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/wan/v2.2-a14b/text-to-image/lora", {
input: {
prompt: "In this breathtaking wildlife documentary, we are drawn into an intimate close-up of a majestic lion's face, framed against the backdrop of a vast African savannah at dawn. The camera captures the raw power and nobility of the creature as it gazes intently into the distance, its golden-brown fur glistening under the soft, diffused light that bathes the scene in an ethereal glow. Harsh shadows dance across its features, accentuating the deep wrinkles around its eyes and the rugged texture of its fur, each strand a testament to its age and wisdom. The static camera angle invites viewers to immerse themselves in this moment of profound stillness, where the lion's intense focus hints at an unseen presence or a distant threat. As the sun ascends, the landscape transforms into a symphony of warm hues, enhancing the serene yet tense atmosphere that envelops this extraordinary encounter with nature's untamed beauty."
},
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/wan/v2.2-a14b/text-to-image/lora", {
input: {
prompt: "In this breathtaking wildlife documentary, we are drawn into an intimate close-up of a majestic lion's face, framed against the backdrop of a vast African savannah at dawn. The camera captures the raw power and nobility of the creature as it gazes intently into the distance, its golden-brown fur glistening under the soft, diffused light that bathes the scene in an ethereal glow. Harsh shadows dance across its features, accentuating the deep wrinkles around its eyes and the rugged texture of its fur, each strand a testament to its age and wisdom. The static camera angle invites viewers to immerse themselves in this moment of profound stillness, where the lion's intense focus hints at an unseen presence or a distant threat. As the sun ascends, the landscape transforms into a symphony of warm hues, enhancing the serene yet tense atmosphere that envelops this extraordinary encounter with nature's untamed beauty."
},
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/wan/v2.2-a14b/text-to-image/lora", {
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/wan/v2.2-a14b/text-to-image/lora", {
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 text prompt to guide image generation.
negative_prompt stringNegative prompt for video generation. Default value: ""
seed integerRandom seed for reproducibility. If None, a random seed is chosen.
num_inference_steps integerNumber of inference steps for sampling. Higher values give better quality but take longer. Default value: 27
enable_safety_checker booleanIf set to true, input data will be checked for safety before processing. Disabling it requires account authorization; unauthorized requests are always checked.
enable_output_safety_checker booleanIf set to true, output video will be checked for safety after generation.
enable_prompt_expansion booleanWhether to enable prompt expansion. This will use a large language model to expand the prompt with additional details while maintaining the original meaning.
acceleration AccelerationEnumAcceleration level to use. The more acceleration, the faster the generation, but with lower quality. The recommended value is 'regular'. Default value: "regular"
Possible enum values: none, regular
guidance_scale floatClassifier-free guidance scale. Higher values give better adherence to the prompt but may decrease quality. Default value: 3.5
guidance_scale_2 floatGuidance scale for the second stage of the model. This is used to control the adherence to the prompt in the second stage of the model. Default value: 4
shift floatShift value for the image. Must be between 1.0 and 10.0. Default value: 2
LoRA weights to be used in the inference.
reverse_video booleanIf true, the video will be reversed.
The size of the generated image. Default value: square_hd
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
}image_format ImageFormatEnumThe format of the output image. Default value: "jpeg"
Possible enum values: png, jpeg
{
"prompt": "In this breathtaking wildlife documentary, we are drawn into an intimate close-up of a majestic lion's face, framed against the backdrop of a vast African savannah at dawn. The camera captures the raw power and nobility of the creature as it gazes intently into the distance, its golden-brown fur glistening under the soft, diffused light that bathes the scene in an ethereal glow. Harsh shadows dance across its features, accentuating the deep wrinkles around its eyes and the rugged texture of its fur, each strand a testament to its age and wisdom. The static camera angle invites viewers to immerse themselves in this moment of profound stillness, where the lion's intense focus hints at an unseen presence or a distant threat. As the sun ascends, the landscape transforms into a symphony of warm hues, enhancing the serene yet tense atmosphere that envelops this extraordinary encounter with nature's untamed beauty.",
"num_inference_steps": 27,
"enable_safety_checker": true,
"enable_output_safety_checker": false,
"enable_prompt_expansion": false,
"acceleration": "regular",
"guidance_scale": 3.5,
"guidance_scale_2": 4,
"shift": 2,
"loras": [],
"image_size": "square_hd",
"image_format": "jpeg"
}The generated image file.
seed integer* requiredThe seed used for generation.
{
"image": {
"url": "https://storage.googleapis.com/falserverless/example_outputs/wan/t2i-output.png"
}
}width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
path string* requiredURL or the path to the LoRA weights.
weight_name stringName of the LoRA weight. Used only if path is a Hugging Face repository, and required only if you have more than 1 safetensors file in the repo.
scale floatThe scale of the LoRA weight. This is used to scale the LoRA weight
before merging it with the base model. Default value: 1
transformer TransformerEnumSpecifies the transformer to load the lora weight into. 'high' loads into the high-noise transformer, 'low' loads it into the low-noise transformer, while 'both' loads the LoRA into both transformers. Default value: "high"
Possible enum values: high, low, both
url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.