import json class Request: session_id: str = "session" prompt: str = "" negative_prompt: str = "" init_image: str = None # base64 mask: str = None # base64 num_outputs: int = 1 num_inference_steps: int = 50 guidance_scale: float = 7.5 width: int = 512 height: int = 512 seed: int = 42 prompt_strength: float = 0.8 sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms" # allow_nsfw: bool = False precision: str = "autocast" # or "full" save_to_disk_path: str = None turbo: bool = True use_full_precision: bool = False use_face_correction: str = None # or "GFPGANv1.3" use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B" use_stable_diffusion_model: str = "sd-v1-4" use_vae_model: str = None use_hypernetwork_model: str = None hypernetwork_strength: float = 1 show_only_filtered_image: bool = False output_format: str = "jpeg" # or "png" output_quality: int = 75 stream_progress_updates: bool = False stream_image_progress: bool = False def json(self): return { "session_id": self.session_id, "prompt": self.prompt, "negative_prompt": self.negative_prompt, "num_outputs": self.num_outputs, "num_inference_steps": self.num_inference_steps, "guidance_scale": self.guidance_scale, "width": self.width, "height": self.height, "seed": self.seed, "prompt_strength": self.prompt_strength, "sampler": self.sampler, "use_face_correction": self.use_face_correction, "use_upscale": self.use_upscale, "use_stable_diffusion_model": self.use_stable_diffusion_model, "use_vae_model": self.use_vae_model, "use_hypernetwork_model": self.use_hypernetwork_model, "hypernetwork_strength": self.hypernetwork_strength, "output_format": self.output_format, "output_quality": self.output_quality, } def __str__(self): return f''' session_id: {self.session_id} prompt: {self.prompt} negative_prompt: {self.negative_prompt} seed: {self.seed} num_inference_steps: {self.num_inference_steps} sampler: {self.sampler} guidance_scale: {self.guidance_scale} w: {self.width} h: {self.height} precision: {self.precision} save_to_disk_path: {self.save_to_disk_path} turbo: {self.turbo} use_full_precision: {self.use_full_precision} use_face_correction: {self.use_face_correction} use_upscale: {self.use_upscale} use_stable_diffusion_model: {self.use_stable_diffusion_model} use_vae_model: {self.use_vae_model} use_hypernetwork_model: {self.use_hypernetwork_model} hypernetwork_strength: {self.hypernetwork_strength} show_only_filtered_image: {self.show_only_filtered_image} output_format: {self.output_format} output_quality: {self.output_quality} stream_progress_updates: {self.stream_progress_updates} stream_image_progress: {self.stream_image_progress}''' class Image: data: str # base64 seed: int is_nsfw: bool path_abs: str = None def __init__(self, data, seed): self.data = data self.seed = seed def json(self): return { "data": self.data, "seed": self.seed, "path_abs": self.path_abs, } class Response: request: Request images: list def json(self): res = { "status": 'succeeded', "request": self.request.json(), "output": [], } for image in self.images: res["output"].append(image.json()) return res