gpt_academic/autogpt/commands/image_gen.py

""" Image Generation Module for AutoGPT."""
import io
import json
import time
import uuid
from base64 import b64decode
from typing import TYPE_CHECKING

import openai
import requests
from PIL import Image

from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.logs import logger

if TYPE_CHECKING:
    from autogpt.config import Config


@command(
    "generate_image",
    "Generate Image",
    '"prompt": "<prompt>"',
    lambda config: config.image_provider,
    "Requires a image provider to be set.",
)
def generate_image(prompt: str, config: Config, 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"{config.workspace_path}/{str(uuid.uuid4())}.jpg"

    # DALL-E
    if config.image_provider == "dalle":
        return generate_image_with_dalle(prompt, filename, size, config)
    # HuggingFace
    elif config.image_provider == "huggingface":
        return generate_image_with_hf(prompt, filename, config)
    # SD WebUI
    elif config.image_provider == "sdwebui":
        return generate_image_with_sd_webui(prompt, filename, config, size)
    return "No Image Provider Set"


def generate_image_with_hf(prompt: str, filename: str, config: Config) -> 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/{config.huggingface_image_model}"
    )
    if config.huggingface_api_token is None:
        raise ValueError(
            "You need to set your Hugging Face API token in the config file."
        )
    headers = {
        "Authorization": f"Bearer {config.huggingface_api_token}",
        "X-Use-Cache": "false",
    }

    retry_count = 0
    while retry_count < 10:
        response = requests.post(
            API_URL,
            headers=headers,
            json={
                "inputs": prompt,
            },
        )

        if response.ok:
            try:
                image = Image.open(io.BytesIO(response.content))
                logger.info(f"Image Generated for prompt:{prompt}")
                image.save(filename)
                return f"Saved to disk:{filename}"
            except Exception as e:
                logger.error(e)
                break
        else:
            try:
                error = json.loads(response.text)
                if "estimated_time" in error:
                    delay = error["estimated_time"]
                    logger.debug(response.text)
                    logger.info("Retrying in", delay)
                    time.sleep(delay)
                else:
                    break
            except Exception as e:
                logger.error(e)
                break

        retry_count += 1

    return f"Error creating image."


def generate_image_with_dalle(
    prompt: str, filename: str, size: int, config: Config
) -> str:
    """Generate an image with DALL-E.

    Args:
        prompt (str): The prompt to use
        filename (str): The filename to save the image to
        size (int): The size of the image

    Returns:
        str: The filename of the image
    """

    # Check for supported image sizes
    if size not in [256, 512, 1024]:
        closest = min([256, 512, 1024], key=lambda x: abs(x - size))
        logger.info(
            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",
        api_key=config.openai_api_key,
    )

    logger.info(f"Image Generated for prompt:{prompt}")

    image_data = b64decode(response["data"][0]["b64_json"])

    with open(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,
    config: Config,
    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 config.sd_webui_auth:
        username, password = config.sd_webui_auth.split(":")
        s.auth = (username, password or "")

    # Generate the images
    response = requests.post(
        f"{config.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,
        },
    )

    logger.info(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(filename)

    return f"Saved to disk:{filename}"