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import os
import time
import requests
from extensions.openai.errors import *
def generations(prompt: str, size: str, response_format: str, n: int):
# Stable Diffusion callout wrapper for txt2img
# Low effort implementation for compatibility. With only "prompt" being passed and assuming DALL-E
# the results will be limited and likely poor. SD has hundreds of models and dozens of settings.
# If you want high quality tailored results you should just use the Stable Diffusion API directly.
# it's too general an API to try and shape the result with specific tags like "masterpiece", etc,
# Will probably work best with the stock SD models.
# SD configuration is beyond the scope of this API.
# At this point I will not add the edits and variations endpoints (ie. img2img) because they
# require changing the form data handling to accept multipart form data, also to properly support
# url return types will require file management and a web serving files... Perhaps later!
width, height = [int(x) for x in size.split('x')] # ignore the restrictions on size
# to hack on better generation, edit default payload.
payload = {
'prompt': prompt, # ignore prompt limit of 1000 characters
'width': width,
'height': height,
'batch_size': n,
'restore_faces': True, # slightly less horrible
}
resp = {
'created': int(time.time()),
'data': []
}
# TODO: support SD_WEBUI_AUTH username:password pair.
sd_url = f"{os.environ['SD_WEBUI_URL']}/sdapi/v1/txt2img"
response = requests.post(url=sd_url, json=payload)
r = response.json()
if response.status_code != 200 or 'images' not in r:
raise ServiceUnavailableError(r.get('detail', [{'msg': 'Unknown error calling Stable Diffusion'}])[0]['msg'], code=response.status_code)
# r['parameters']...
for b64_json in r['images']:
if response_format == 'b64_json':
resp['data'].extend([{'b64_json': b64_json}])
else:
resp['data'].extend([{'url': f'data:image/png;base64,{b64_json}'}]) # yeah it's lazy. requests.get() will not work with this
return resp