""" Image Generation Module for AutoGPT.""" import io import os.path import uuid from base64 import b64decode import openai import requests from PIL import Image from autogpt.config import Config from autogpt.workspace import path_in_workspace CFG = Config() def generate_image(prompt: str, size: int = 256) -> str: """Generate an image from a prompt. Args: prompt (str): The prompt to use size (int, optional): The size of the image. Defaults to 256. (Not supported by HuggingFace) Returns: str: The filename of the image """ filename = f"{str(uuid.uuid4())}.jpg" # DALL-E if CFG.image_provider == "dalle": return generate_image_with_dalle(prompt, filename, size) # HuggingFace elif CFG.image_provider == "huggingface": return generate_image_with_hf(prompt, filename) # SD WebUI elif CFG.image_provider == "sdwebui": return generate_image_with_sd_webui(prompt, filename, size) return "No Image Provider Set" def generate_image_with_hf(prompt: str, filename: str) -> str: """Generate an image with HuggingFace's API. Args: prompt (str): The prompt to use filename (str): The filename to save the image to Returns: str: The filename of the image """ API_URL = ( f"https://api-inference.huggingface.co/models/{CFG.huggingface_image_model}" ) if CFG.huggingface_api_token is None: raise ValueError( "You need to set your Hugging Face API token in the config file." ) headers = { "Authorization": f"Bearer {CFG.huggingface_api_token}", "X-Use-Cache": "false", } response = requests.post( API_URL, headers=headers, json={ "inputs": prompt, }, ) image = Image.open(io.BytesIO(response.content)) print(f"Image Generated for prompt:{prompt}") image.save(path_in_workspace(filename)) return f"Saved to disk:{filename}" def generate_image_with_dalle(prompt: str, filename: str) -> str: """Generate an image with DALL-E. Args: prompt (str): The prompt to use filename (str): The filename to save the image to Returns: str: The filename of the image """ openai.api_key = CFG.openai_api_key # Check for supported image sizes if size not in [256, 512, 1024]: closest = min([256, 512, 1024], key=lambda x: abs(x - size)) print( f"DALL-E only supports image sizes of 256x256, 512x512, or 1024x1024. Setting to {closest}, was {size}." ) size = closest response = openai.Image.create( prompt=prompt, n=1, size=f"{size}x{size}", response_format="b64_json", ) print(f"Image Generated for prompt:{prompt}") image_data = b64decode(response["data"][0]["b64_json"]) with open(path_in_workspace(filename), mode="wb") as png: png.write(image_data) return f"Saved to disk:{filename}" def generate_image_with_sd_webui( prompt: str, filename: str, size: int = 512, negative_prompt: str = "", extra: dict = {}, ) -> str: """Generate an image with Stable Diffusion webui. Args: prompt (str): The prompt to use filename (str): The filename to save the image to size (int, optional): The size of the image. Defaults to 256. negative_prompt (str, optional): The negative prompt to use. Defaults to "". extra (dict, optional): Extra parameters to pass to the API. Defaults to {}. Returns: str: The filename of the image """ # Create a session and set the basic auth if needed s = requests.Session() if CFG.sd_webui_auth: username, password = CFG.sd_webui_auth.split(":") s.auth = (username, password or "") # Generate the images response = requests.post( f"{CFG.sd_webui_url}/sdapi/v1/txt2img", json={ "prompt": prompt, "negative_prompt": negative_prompt, "sampler_index": "DDIM", "steps": 20, "cfg_scale": 7.0, "width": size, "height": size, "n_iter": 1, **extra, }, ) print(f"Image Generated for prompt:{prompt}") # Save the image to disk response = response.json() b64 = b64decode(response["images"][0].split(",", 1)[0]) image = Image.open(io.BytesIO(b64)) image.save(path_in_workspace(filename)) return f"Saved to disk:{filename}"