import os import base64 import requests from dotenv import load_dotenv from typing import List load_dotenv() class StableDiffusion: """ A class to interact with the Stable Diffusion API for image generation. Attributes: ----------- api_key : str The API key for accessing the Stable Diffusion API. api_host : str The host URL of the Stable Diffusion API. engine_id : str The ID of the Stable Diffusion engine. headers : dict The headers for the API request. output_dir : str Directory where generated images will be saved. Methods: -------- generate_image(prompt: str, cfg_scale: int, height: int, width: int, samples: int, steps: int) -> List[str]: Generates images based on a text prompt and returns a list of file paths to the generated images. """ def __init__(self, api_key: str, api_host: str = "https://api.stability.ai"): """ Initializes the StableDiffusion class with the provided API key and host. Parameters: ----------- api_key : str The API key for accessing the Stable Diffusion API. api_host : str The host URL of the Stable Diffusion API. Default is "https://api.stability.ai". """ self.api_key = api_key self.api_host = api_host self.engine_id = "stable-diffusion-v1-6" self.headers = { "Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", "Accept": "application/json" } self.output_dir = "images" os.makedirs(self.output_dir, exist_ok=True) def generate_image(self, prompt: str, cfg_scale: int = 7, height: int = 1024, width: int = 1024, samples: int = 1, steps: int = 30) -> List[str]: """ Generates images based on a text prompt. Parameters: ----------- prompt : str The text prompt based on which the image will be generated. cfg_scale : int CFG scale parameter for image generation. Default is 7. height : int Height of the generated image. Default is 1024. width : int Width of the generated image. Default is 1024. samples : int Number of images to generate. Default is 1. steps : int Number of steps for the generation process. Default is 30. Returns: -------- List[str]: A list of paths to the generated images. Raises: ------- Exception: If the API response is not 200 (OK). """ response = requests.post( f"{self.api_host}/v1/generation/{self.engine_id}/text-to-image", headers=self.headers, json={ "text_prompts": [{"text": prompt}], "cfg_scale": cfg_scale, "height": height, "width": width, "samples": samples, "steps": steps, }, ) if response.status_code != 200: raise Exception(f"Non-200 response: {response.text}") data = response.json() image_paths = [] for i, image in enumerate(data["artifacts"]): image_path = os.path.join(self.output_dir, f"v1_txt2img_{i}.png") with open(image_path, "wb") as f: f.write(base64.b64decode(image["base64"])) image_paths.append(image_path) return image_paths # Usage example: # sd = StableDiffusion("your-api-key") # images = sd.generate_image("A scenic landscape with mountains") # print(images)