Emu 3.5 Image | Text to Image

fal-ai/emu-3.5-image/text-to-image

Generate images from text using Emu 3.5 Image

Inference

Commercial use

Streaming

Schema

LLMs

Playground API

About

Generate an image based on a text description using Emu3.5 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

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/emu-3.5-image/text-to-image", {
  input: {
    prompt: "Capture an intimate close-up bathed in warm, soft, late-afternoon sunlight filtering into a quintessential 1960s kitchen. The focal point is a charmingly designed vintage package of all-purpose flour, resting invitingly on a speckled Formica countertop. The packaging itself evokes pure nostalgia: perhaps thick, slightly textured paper in a warm cream tone, adorned with simple, bold typography (a friendly serif or script) in classic red and blue \"ALL-PURPOSE FLOUR\", featuring a delightful illustration like a stylized sheaf of wheat or a cheerful baker character. In smaller bold print at the bottom of the package: \"NET WT 5 LBS (80 OZ) 2.27kg\". Focus sharply on the package details – the slightly soft edges of the paper bag, the texture of the vintage printing, the inviting \"All-Purpose Flour\" text. Subtle hints of the 1960s kitchen frame the shot – the chrome edge of the counter gleaming softly, a blurred glimpse of a pastel yellow ceramic tile backsplash, or the corner of a vintage metal canister set just out of focus. The shallow depth of field keeps attention locked on the beautifully designed package, creating an aesthetic rich in warmth, authenticity, and nostalgic appeal."
  },
  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);

Streaming#

This model supports streaming requests. You can stream data directly to the model and get the result in real-time.

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

const stream = await fal.stream("fal-ai/emu-3.5-image/text-to-image", {
  input: {
    prompt: "Capture an intimate close-up bathed in warm, soft, late-afternoon sunlight filtering into a quintessential 1960s kitchen. The focal point is a charmingly designed vintage package of all-purpose flour, resting invitingly on a speckled Formica countertop. The packaging itself evokes pure nostalgia: perhaps thick, slightly textured paper in a warm cream tone, adorned with simple, bold typography (a friendly serif or script) in classic red and blue \"ALL-PURPOSE FLOUR\", featuring a delightful illustration like a stylized sheaf of wheat or a cheerful baker character. In smaller bold print at the bottom of the package: \"NET WT 5 LBS (80 OZ) 2.27kg\". Focus sharply on the package details – the slightly soft edges of the paper bag, the texture of the vintage printing, the inviting \"All-Purpose Flour\" text. Subtle hints of the 1960s kitchen frame the shot – the chrome edge of the counter gleaming softly, a blurred glimpse of a pastel yellow ceramic tile backsplash, or the corner of a vintage metal canister set just out of focus. The shallow depth of field keeps attention locked on the beautifully designed package, creating an aesthetic rich in warmth, authenticity, and nostalgic appeal."
  }
});

for await (const event of stream) {
  console.log(event);
}

const result = await stream.done();

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/emu-3.5-image/text-to-image", {
  input: {
    prompt: "Capture an intimate close-up bathed in warm, soft, late-afternoon sunlight filtering into a quintessential 1960s kitchen. The focal point is a charmingly designed vintage package of all-purpose flour, resting invitingly on a speckled Formica countertop. The packaging itself evokes pure nostalgia: perhaps thick, slightly textured paper in a warm cream tone, adorned with simple, bold typography (a friendly serif or script) in classic red and blue \"ALL-PURPOSE FLOUR\", featuring a delightful illustration like a stylized sheaf of wheat or a cheerful baker character. In smaller bold print at the bottom of the package: \"NET WT 5 LBS (80 OZ) 2.27kg\". Focus sharply on the package details – the slightly soft edges of the paper bag, the texture of the vintage printing, the inviting \"All-Purpose Flour\" text. Subtle hints of the 1960s kitchen frame the shot – the chrome edge of the counter gleaming softly, a blurred glimpse of a pastel yellow ceramic tile backsplash, or the corner of a vintage metal canister set just out of focus. The shallow depth of field keeps attention locked on the beautifully designed package, creating an aesthetic rich in warmth, authenticity, and nostalgic appeal."
  },
  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/emu-3.5-image/text-to-image", {
  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/emu-3.5-image/text-to-image", {
  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 create the image.

resolution ResolutionEnum

The resolution of the output image. Default value: "720p"

Possible enum values: 480p, 720p

aspect_ratio AspectRatioEnum

The aspect ratio of the output image. Default value: "1:1"

Possible enum values: 21:9, 16:9, 4:3, 3:2, 1:1, 2:3, 3:4, 9:16, 9:21

enable_safety_checker boolean

Whether to enable the safety checker. Default value: true

seed integer

The seed for the inference.

output_format OutputFormatEnum

The format of the output image. Default value: "png"

Possible enum values: jpeg, png, webp

sync_mode boolean

Whether to return the image in sync mode.

{
  "prompt": "Capture an intimate close-up bathed in warm, soft, late-afternoon sunlight filtering into a quintessential 1960s kitchen. The focal point is a charmingly designed vintage package of all-purpose flour, resting invitingly on a speckled Formica countertop. The packaging itself evokes pure nostalgia: perhaps thick, slightly textured paper in a warm cream tone, adorned with simple, bold typography (a friendly serif or script) in classic red and blue \"ALL-PURPOSE FLOUR\", featuring a delightful illustration like a stylized sheaf of wheat or a cheerful baker character. In smaller bold print at the bottom of the package: \"NET WT 5 LBS (80 OZ) 2.27kg\". Focus sharply on the package details – the slightly soft edges of the paper bag, the texture of the vintage printing, the inviting \"All-Purpose Flour\" text. Subtle hints of the 1960s kitchen frame the shot – the chrome edge of the counter gleaming softly, a blurred glimpse of a pastel yellow ceramic tile backsplash, or the corner of a vintage metal canister set just out of focus. The shallow depth of field keeps attention locked on the beautifully designed package, creating an aesthetic rich in warmth, authenticity, and nostalgic appeal.",
  "resolution": "720p",
  "aspect_ratio": "1:1",
  "enable_safety_checker": true,
  "output_format": "png"
}

Output#

images list<ImageFile>* required

The edited image.

seed integer* required

The seed for the inference.

{
  "images": [
    {
      "height": 880,
      "file_name": "2_gRhwfsnmNKYtZ_dveyV.jpg",
      "content_type": "image/jpeg",
      "url": "https://v3b.fal.media/files/b/koala/UFe9ES9IGdp0N90JmCyd4.jpg",
      "width": 1184
    }
  ],
  "seed": 1815037768
}

Other types#

ImageFile#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

file_data string

File data

width integer

The width of the image

height integer

The height of the 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#

Streaming#

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#

ImageFile#

Related Models

Emu 3.5 Image Text 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#

Streaming#

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#

ImageFile#

Related Models