Pixar style superhero, 4k, 8k, unreal engine, octane render photorealistic by cosmicwonder,
hdr, photography by cosmicwonder, high definition, symmetrical face, volumetric lighting, dusty haze,
photo, octane render, 24mm, 4k, 24mm, DSLR, high quality, 60 fps, ultra realistic

prompt_template = ("Pixar style {subject}, 4k, 8k, unreal engine, octane render photorealistic by cosmicwonder, "
    "hdr, photography by cosmicwonder, high definition, symmetrical face, volumetric lighting, dusty haze, "
    "photo, octane render, 24mm, 4k, 24mm, DSLR, high quality, 60 fps, ultra realistic")
 
prompt = prompt_template.format(subject="penguin")

class PixarStyleTool(ImageGeneratorTool):
    name: str = "PixarStyleTool"
    human_description: str = "Generates a Pixar-style image from text."
    agent_description = (
        "Used to generate a Pixar-style image of something. "
        "Only use if the user has asked directly for a Pixar-style image of something. "
        "Input: the subject of the image "
        "Output: the Pixar-style image."
    )
 
    prompt_template = ("Pixar style {subject}, 4k, 8k, unreal engine, octane render photorealistic by cosmicwonder, "
        "hdr, photography by cosmicwonder, high definition, symmetrical face, volumetric lighting, dusty haze, "
        "photo, octane render, 24mm, 4k, 24mm, DSLR, high quality, 60 fps, ultra realistic")
 
    def run(self, tool_input: List[Block], context: AgentContext) -> Union[List[Block], Task[Any]]:
        # Modify the tool inputs by interpolating them with stored prompt here
        modified_inputs = [Block(text=self.prompt_template.format(subject=block.text)) for block in tool_input]
 
        # Create the Stable Diffusion tool we want to wrap
        stable_diffusion_tool = StableDiffusionTool()
 
        # Now return the results of running Stable Diffusion on those modified prompts.
        return stable_diffusion_tool.run(modified_inputs, context)