Stepx Edit2 | Image to Image

fal-ai/stepx-edit2

Image-to-image editing with Step1X-Edit v2 from StepFun. Reasoning-enhanced modifications through a thinking–editing–reflection loop with MLLM world knowledge for abstract instruction comprehension.

Inference

Commercial use

Schema

LLMs

Playground API

About

Generate image using Step1X-Edit v1.2 model with thinking and reflection capabilities.

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

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.

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/stepx-edit2", {
  input: {
    prompt: "make head band red",
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/girl_2.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);

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"
});

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. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

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/stepx-edit2", {
  input: {
    prompt: "make head band red",
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/girl_2.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/stepx-edit2", {
  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/stepx-edit2", {
  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);

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.

5. Schema#

Input#

prompt string* required

The prompt to generate an image from.

image_url string* required

The image URL to generate an image from. Needs to match the dimensions of the mask.

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 the model will output the same image every time.

guidance_scale float

The true CFG scale. Controls how closely the model follows the prompt. Default value: 6

num_inference_steps integer

The number of inference steps to perform. Recommended: 50. Default value: 50

enable_thinking_mode boolean

Enable thinking mode. Uses multimodal language model knowledge to interpret abstract editing instructions. Default value: true

enable_reflection_mode boolean

Enable reflection mode. Reviews outputs, corrects unintended changes, and determines when editing is complete. Default value: true

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

enable_safety_checker boolean

If set to true, the safety checker will be enabled. Default value: true

output_format OutputFormatEnum

The format of the generated image. Default value: "jpeg"

Possible enum values: jpeg, png

{
  "prompt": "make head band red",
  "image_url": "https://storage.googleapis.com/falserverless/example_inputs/girl_2.png",
  "negative_prompt": "",
  "guidance_scale": 6,
  "num_inference_steps": 50,
  "enable_thinking_mode": true,
  "enable_reflection_mode": true,
  "enable_safety_checker": true,
  "output_format": "jpeg"
}

Output#

images list<Image>* required

The generated images

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.

has_nsfw_concepts list<boolean>* required

Whether the generated images contain NSFW concepts.

prompt string* required

The prompt used for generating the image.

reformat_prompt string

The model's interpretation of your instruction (only available when thinking mode is enabled).

think_info list<string>

Reasoning process details (only available when thinking mode is enabled).

best_info list<object>

Reflection analysis (only available when reflection mode is enabled).

{
  "images": [
    {
      "height": 1024,
      "content_type": "image/jpeg",
      "url": "https://v3.fal.media/files/kangaroo/kFPr5gC_Rr9JZbTTakEMd.jpeg",
      "width": 672
    }
  ],
  "prompt": ""
}

Other types#

Image#

url string* required

width integer* required

height integer* required

content_type string

Default value: "image/jpeg"

Stepx Edit2 Image to Image

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

Image#