An asynchronous library for interacting with the FakeYou Text-to-Speech API.
Project description
AsyncFakeYou
AsyncFakeYou is an asynchronous Python library for interacting with the FakeYou Text-to-Speech API. It allows you to submit TTS requests, track their status, and download the resulting audio files, all in an asynchronous manner using asyncio, aiohttp and aiofiles.
Features
- Asynchronous requests to FakeYou TTS API.
- Generation with parallel execution control
- Handle user authentication with session cookies
Installation
pip install asyncfakeyou
Simple usage
You can obtain a direct URL to the generated audio file.
from asyncfakeyou import AsyncAudioGen
import asyncio
async def text_to_speech():
gen = AsyncAudioGen(cookies="your_cookie_string")
audio_url = await gen.fetch_audio("model_token_here", "sample_text")
print(audio_url)
asyncio.run(text_to_speech())
Or you can download the generated audio file to a specified directory.
from asyncfakeyou import AsyncAudioGen
import asyncio
async def text_to_speech():
gen = AsyncAudioGen(cookies="your_cookie_string")
audio_url = await gen.fetch_and_save_audio("model_token_here", "sample_text",
output_path="./audio",
filename="generated_audio.wav")
print(audio_url)
asyncio.run(text_to_speech())
How to obtain cookies?
The cookies parameter of the AsyncAudioGen class is optional. However, I recommend setting it as it will give you higher queue priority, even without a paid subscription. If you have a premium account, you will be able to take advantage of all its benefits through this API.
from asyncfakeyou import receive_cookies
import asyncio
async def get_my_cookies():
cookies = await receive_cookies("your_username_or_email", "your_password")
print(cookies)
asyncio.run(get_my_cookies())
Parallel execution
If you need to generate multiple audio files, you can speed up the process by using fetch_tasks and fetch_and_save_tasks. These methods handle a fixed number of tasks in parallel (concurrent_tasks parameter) and automatically retry failed requests. The default value for concurrent_tasks is 3, but you can tweak this parameter.
You can iterate through the direct URLs to the generated audio files.
from asyncfakeyou import AsyncAudioGen
import asyncio
async def multiple_text_to_speech():
gen = AsyncAudioGen(cookies="your_cookie_string")
audio_tasks = [
("model_token_1", "sample_text_1"),
("model_token_2", "sample_text_2"),
("model_token_3", "sample_text_3")
]
async for audio_url in gen.fetch_tasks(audio_tasks):
print(audio_url)
asyncio.run(execute_tasks())
Or you can download the generated audio files to a specified directory.
from asyncfakeyou import AsyncAudioGen
import asyncio
async def multiple_text_to_speech():
gen = AsyncAudioGen(cookies="your_cookie_string")
audio_tasks = [
("model_token_1", "sample_text_1", "filename1.wav"),
("model_token_2", "sample_text_2", "filename2.wav"),
("model_token_3", "sample_text_3", "filename3.wav")
]
await gen.fetch_and_save_tasks(audio_tasks, output_path="./audio")
asyncio.run(execute_tasks())
Contributing
Contributions are welcome! Please fork the repository and create a pull request with your improvements.
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