Optimized Latent Consistency (SDv1.5)

fal-ai/lcm-sd15-i2i

Inference

Commercial use

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/serverless-client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

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 * as fal from "@fal-ai/serverless-client";

const result = await fal.subscribe("fal-ai/lcm-sd15-i2i", {
  input: {
    prompt: "masterpiece, colorful, photo of a beach in hawaii, sun",
    image_url: "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});

Real-time via WebSockets#

This model has a real-time mode via websockets, this is supported via the fal.realtime client.

import * as fal from "@fal-ai/serverless-client";

const connection = fal.realtime.connect("fal-ai/lcm-sd15-i2i", {
  onResult: (result) => {
    console.log(result);
  },
  onError: (error) => {
    console.error(error);
  }
});

connection.send({
  prompt: "masterpiece, colorful, photo of a beach in hawaii, sun",
  image_url: "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png"
});

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.

import * as fal from "@fal-ai/serverless-client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API 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.

3. Files#

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.

Data URI (base64)#

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.

Hosted files (URL)#

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.

Uploading files#

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 * as fal from "@fal-ai/serverless-client";

// Upload a file (you can get a file reference from an input element or a drag-and-drop event)
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

// Use the URL in your request
const result = await fal.subscribe("fal-ai/lcm-sd15-i2i", { image_url: url });

Auto uploads

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.

4. Schema#

Input#

prompt*string

The prompt to use for generating the image. Be as descriptive as possible for best results.

image_url*string

The image to use as a base.

strengthfloat

The strength of the image. Default value: 0.8

negative_promptstring

The negative prompt to use.Use it to address details that you don't want in the image. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). Default value: ""

seedinteger

The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.

guidance_scalefloat

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: 1

num_inference_stepsinteger

The number of inference steps to use for generating the image. The more steps the better the image will be but it will also take longer to generate. Default value: 4

sync_modeboolean

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_imagesinteger

The number of images to generate. The function will return a list of images with the same prompt and negative prompt but different seeds. Default value: 1

enable_safety_checksboolean

If set to true, the resulting image will be checked whether it includes any potentially unsafe content. If it does, it will be replaced with a black image. Default value: true

request_idstring

An id bound to a request, can be used with response to identify the request itself. Default value: ""

{
  "prompt": "masterpiece, colorful, photo of a beach in hawaii, sun",
  "image_url": "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png",
  "strength": 0.8,
  "negative_prompt": "cartoon, illustration, animation. face. male, female",
  "seed": 42,
  "guidance_scale": 1,
  "num_inference_steps": 4,
  "num_images": 1,
  "enable_safety_checks": true
}

Output#

images*list<Image>

The generated image files info.

timings*Timings

seed*integer

Seed 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.