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F5 TTS Text to Audio

fal-ai/f5-tts
F5 TTS
Inference
Commercial use

About

Text To Speech

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/f5-tts", {
  input: {
    gen_text: "I don't really care what you call me. I've been a silent spectator, watching species evolve, empires rise and fall. But always remember, I am mighty and enduring. Respect me and I'll nurture you; ignore me and you shall face the consequences.",
    ref_audio_url: "https://github.com/SWivid/F5-TTS/raw/21900ba97d5020a5a70bcc9a0575dc7dec5021cb/tests/ref_audio/test_en_1_ref_short.wav",
    model_type: "F5-TTS"
  },
  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"
});

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/f5-tts", {
  input: {
    gen_text: "I don't really care what you call me. I've been a silent spectator, watching species evolve, empires rise and fall. But always remember, I am mighty and enduring. Respect me and I'll nurture you; ignore me and you shall face the consequences.",
    ref_audio_url: "https://github.com/SWivid/F5-TTS/raw/21900ba97d5020a5a70bcc9a0575dc7dec5021cb/tests/ref_audio/test_en_1_ref_short.wav",
    model_type: "F5-TTS"
  },
  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/f5-tts", {
  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/f5-tts", {
  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#

gen_text string* required

The text to be converted to speech.

ref_audio_url string* required

The URL of the reference audio file.

ref_text string

The reference text to be used for TTS. If not provided, an ASR (Automatic Speech Recognition) model will be used to generate the reference text. Default value: ""

model_type ModelTypeEnum* required

The name of the model to be used for TTS.

Possible enum values: F5-TTS, E2-TTS

remove_silence boolean

Whether to remove the silence from the audio file. Default value: true

{
  "gen_text": "I don't really care what you call me. I've been a silent spectator, watching species evolve, empires rise and fall. But always remember, I am mighty and enduring. Respect me and I'll nurture you; ignore me and you shall face the consequences.",
  "ref_audio_url": "https://github.com/SWivid/F5-TTS/raw/21900ba97d5020a5a70bcc9a0575dc7dec5021cb/tests/ref_audio/test_en_1_ref_short.wav",
  "ref_text": "Some call me nature, others call me mother nature.",
  "model_type": "F5-TTS",
  "remove_silence": true
}

Output#

audio_url AudioFile* required

The audio file containing the generated speech.

{
  "audio_url": {
    "url": "https://v2.fal.media/files/8535dd59e911496a947daa35c07e67a3_tmplkcy6tut.wav",
    "content_type": "audio/wav",
    "file_name": "8535dd59e911496a947daa35c07e67a3_tmplkcy6tut.wav",
    "file_size": 4404019
  }
}

Other types#

AudioFile#

url string* required
content_type string

Default value: "audio/wav"

file_name string

Default value: "8535dd59e911496a947daa35c07e67a3_tmplkcy6tut.wav"

file_size integer | null

The size of the file in bytes.

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