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OpenAIImageGenerationToolSpec #

Bases: BaseToolSpec

OpenAI Image Generation tool spec.

Source code in llama-index-integrations/tools/llama-index-tools-openai/llama_index/tools/openai/image_generation/base.py 
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class OpenAIImageGenerationToolSpec(BaseToolSpec):
    """OpenAI Image Generation tool spec."""

    spec_functions = ["image_generation"]

    def __init__(
        self, api_key: Optional[str] = None, cache_dir: Optional[str] = None
    ) -> None:
        try:
            from openai import OpenAI
        except ImportError:
            raise ImportError(
                "Please install openai with `pip install openai` to use this tool"
            )

        """Initialize with parameters."""
        self.client = OpenAI(api_key=api_key)
        self.cache_dir = cache_dir or DEFAULT_CACHE_DIR

    def get_cache_dir(self):
        return self.cache_dir

    def save_base64_image(self, base64_str, image_name):
        try:
            from io import BytesIO

            from PIL import Image
        except ImportError:
            raise ImportError(
                "Please install Pillow with `pip install Pillow` to use this tool"
            )
        cache_dir = self.cache_dir

        # Create cache directory if it doesn't exist
        if not os.path.exists(cache_dir):
            os.makedirs(cache_dir)

        # Decode the base64 string
        image_data = base64.b64decode(base64_str)

        # Create an image from the decoded bytes and save it
        image_path = os.path.join(cache_dir, image_name)
        with Image.open(BytesIO(image_data)) as img:
            img.save(image_path)

        return image_path

    def image_generation(
        self,
        text: str,
        model: Optional[str] = "dall-e-3",
        quality: Optional[str] = "standard",
        num_images: Optional[int] = 1,
        size: Optional[str] = DEFAULT_SIZE,
        style: Optional[str] = "vivid",
        timeout: Optional[int] = None,
        download: Optional[bool] = False,
    ) -> str:
        """
        This tool accepts a natural language string and will use OpenAI's DALL-E model to generate an image.

        Args:
            text: The text to generate an image from.

            model: The model to use for image generation. Defaults to `dall-e-3`.
                Must be one of `dall-e-2` or `dall-e-3`.

            num_images: The number of images to generate. Defaults to 1.
                Must be between 1 and 10. For `dall-e-3`, only `n=1` is supported.

            quality: The quality of the image that will be generated. Defaults to `standard`.
                Must be one of `standard` or `hd`. `hd` creates images with finer
                details and greater consistency across the image. This param is only supported
                for `dall-e-3`.

            size: The size of the generated images. Defaults to `1024x1024`.
                Must be one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`.
                Must be one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3` models.

            style: The style of the generated images. Defaults to `vivid`.
                Must be one of `vivid` or `natural`.
                Vivid causes the model to lean towards generating hyper-real and dramatic images.
                Natural causes the model to produce more natural, less hyper-real looking images.
                This param is only supported for `dall-e-3`.

            timeout: Override the client-level default timeout for this request, in seconds. Defaults to `None`.

            download: If `True`, the image will be downloaded to the cache directory. Defaults to `True`.
        """
        if size not in valid_sizes[model]:
            raise Exception(f"Invalid size for {model}: {size}")

        response = self.client.images.generate(
            prompt=text,
            n=num_images,
            model=model,
            quality=quality,
            size=size,
            response_format="b64_json" if download else "url",
            style=style,
            timeout=timeout,
        )
        if download:
            image_bytes = response.data[0].b64_json
            ext = get_extension(image_bytes)
            filename = f"{time.time()}.{ext}"

            return (self.save_base64_image(image_bytes, filename),)

        return response.data[0].url

image_generation #

image_generation(text: str, model: Optional[str] = 'dall-e-3', quality: Optional[str] = 'standard', num_images: Optional[int] = 1, size: Optional[str] = DEFAULT_SIZE, style: Optional[str] = 'vivid', timeout: Optional[int] = None, download: Optional[bool] = False) -> str

This tool accepts a natural language string and will use OpenAI's DALL-E model to generate an image.

Parameters:

Name Type Description Default
text str

The text to generate an image from.

 required
model Optional[str]

The model to use for image generation. Defaults to dall-e-3. Must be one of dall-e-2 or dall-e-3.

 'dall-e-3'
num_images Optional[int]

The number of images to generate. Defaults to 1. Must be between 1 and 10. For dall-e-3, only n=1 is supported.

 1
quality Optional[str]

The quality of the image that will be generated. Defaults to standard. Must be one of standard or hd. hd creates images with finer details and greater consistency across the image. This param is only supported for dall-e-3.

 'standard'
size Optional[str]

The size of the generated images. Defaults to 1024x1024. Must be one of 256x256, 512x512, or 1024x1024 for dall-e-2. Must be one of 1024x1024, 1792x1024, or 1024x1792 for dall-e-3 models.

 DEFAULT_SIZE
style Optional[str]

The style of the generated images. Defaults to vivid. Must be one of vivid or natural. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images. This param is only supported for dall-e-3.

 'vivid'
timeout Optional[int]

Override the client-level default timeout for this request, in seconds. Defaults to None.

 None
download Optional[bool]

If True, the image will be downloaded to the cache directory. Defaults to True.

 False
Source code in llama-index-integrations/tools/llama-index-tools-openai/llama_index/tools/openai/image_generation/base.py 
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def image_generation(
    self,
    text: str,
    model: Optional[str] = "dall-e-3",
    quality: Optional[str] = "standard",
    num_images: Optional[int] = 1,
    size: Optional[str] = DEFAULT_SIZE,
    style: Optional[str] = "vivid",
    timeout: Optional[int] = None,
    download: Optional[bool] = False,
) -> str:
    """
    This tool accepts a natural language string and will use OpenAI's DALL-E model to generate an image.

    Args:
        text: The text to generate an image from.

        model: The model to use for image generation. Defaults to `dall-e-3`.
            Must be one of `dall-e-2` or `dall-e-3`.

        num_images: The number of images to generate. Defaults to 1.
            Must be between 1 and 10. For `dall-e-3`, only `n=1` is supported.

        quality: The quality of the image that will be generated. Defaults to `standard`.
            Must be one of `standard` or `hd`. `hd` creates images with finer
            details and greater consistency across the image. This param is only supported
            for `dall-e-3`.

        size: The size of the generated images. Defaults to `1024x1024`.
            Must be one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`.
            Must be one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3` models.

        style: The style of the generated images. Defaults to `vivid`.
            Must be one of `vivid` or `natural`.
            Vivid causes the model to lean towards generating hyper-real and dramatic images.
            Natural causes the model to produce more natural, less hyper-real looking images.
            This param is only supported for `dall-e-3`.

        timeout: Override the client-level default timeout for this request, in seconds. Defaults to `None`.

        download: If `True`, the image will be downloaded to the cache directory. Defaults to `True`.
    """
    if size not in valid_sizes[model]:
        raise Exception(f"Invalid size for {model}: {size}")

    response = self.client.images.generate(
        prompt=text,
        n=num_images,
        model=model,
        quality=quality,
        size=size,
        response_format="b64_json" if download else "url",
        style=style,
        timeout=timeout,
    )
    if download:
        image_bytes = response.data[0].b64_json
        ext = get_extension(image_bytes)
        filename = f"{time.time()}.{ext}"

        return (self.save_base64_image(image_bytes, filename),)

    return response.data[0].url