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Optimized Latent Consistency (SDv1.5) Image to Image

Optimized Latent Consistency (SDv1.5)
fal-ai/lcm-sd15-i2i
Inference
Commercial use

About

Generate Image

1. Calling the API#

Install the client#

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

npm install --save @fal-ai/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 { fal } from "@fal-ai/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);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

Real-time via WebSockets#

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

import { fal } from "@fal-ai/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 { fal } from "@fal-ai/client";

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

3. Queue#

Submit a request#

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/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"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

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/lcm-sd15-i2i", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

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/lcm-sd15-i2i", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. 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 { 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.

5. Schema#

Input#

prompt string* required

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

image_url string* required

The image to use as a base.

strength float

The strength of the image. Default value: 0.8

negative_prompt string

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: ""

seed integer

The same seed and the same prompt given to the same version of Stable Diffusion 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: 1

num_inference_steps integer

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

enable_safety_checks boolean

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_id string

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>* required

The generated image files info.

timings Timings* required
seed integer* required

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.

num_inference_steps integer

Number of inference steps used to generate the image. It will be the same value of the one passed in the input or the default one in case none was passed. Default value: 4

request_id string

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

nsfw_content_detected list<boolean>* required

A list of booleans indicating whether the generated image contains any potentially unsafe content. If the safety check is disabled, this field will have a false for each generated image.

{
  "images": [
    {
      "url": "",
      "content_type": "image/jpeg"
    }
  ],
  "num_inference_steps": 4
}

Other types#

Image#

url string* required
width integer* required
height integer* required
content_type string

Default value: "image/jpeg"

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