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