12345678910111213141516171819202122232425262728293031323334353637383940414243444546 |
- #!/usr/bin/env python3
- import asyncio
- import functools
- import io
- from typing import Callable
- import replicate # very nice API to run AI models; see https://replicate.com/
- from nicegui import ui
- from nicegui.events import UploadEventArguments
- async def io_bound(callback: Callable, *args: any, **kwargs: any):
- '''Makes a blocking function awaitable; pass function as first parameter and its arguments as the rest'''
- return await asyncio.get_event_loop().run_in_executor(None, functools.partial(callback, *args, **kwargs))
- async def transcribe(e: UploadEventArguments):
- transcription.text = 'Transcribing...'
- model = replicate.models.get('openai/whisper')
- version = model.versions.get('30414ee7c4fffc37e260fcab7842b5be470b9b840f2b608f5baa9bbef9a259ed')
- prediction = await io_bound(version.predict, audio=io.BytesIO(e.content.read()))
- text = prediction.get('transcription', 'no transcription')
- transcription.set_text(f'result: "{text}"')
- async def generate_image():
- image.source = 'https://dummyimage.com/600x400/ccc/000000.png&text=building+image...'
- model = replicate.models.get('stability-ai/stable-diffusion')
- version = model.versions.get('db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf')
- prediction = await io_bound(version.predict, prompt=prompt.value)
- image.source = prediction[0]
- # User Interface
- with ui.row().style('gap:10em'):
- with ui.column():
- ui.label('OpenAI Whisper (voice transcription)').classes('text-2xl')
- ui.upload(on_upload=transcribe, auto_upload=True).style('width: 20em')
- transcription = ui.label().classes('text-xl')
- with ui.column():
- ui.label('Stable Diffusion (image generator)').classes('text-2xl')
- prompt = ui.input('prompt').style('width: 20em')
- ui.button('Generate', on_click=generate_image).style('width: 15em')
- image = ui.image().style('width: 60em')
- ui.run()
|