import gradio as gr
from diffusers import StableDiffusionPipeline
from PIL import Image

# Load the Stable Diffusion model (replace with your desired model)
model_id = "runwayml/stable-diffusion-v1-5"  # Example: Stable Diffusion v1.5
pipe = StableDiffusionPipeline.from_pretrained(model_id)
pipe.to("cuda") # If you have a CUDA-enabled GPU, use it for faster generation
# otherwise, remove this line to use your CPU (slower)

def generate_image(prompt):
    """
    Generates an image from a text prompt using Stable Diffusion.

    Args:
        prompt (str): The text prompt to guide image generation.

    Returns:
        PIL.Image.Image: The generated image.
    """
    try:
        image = pipe(prompt).images[0]  # Get the first image from the pipeline output
        return image
    except Exception as e:
        print(f"Error generating image: {e}")
        return None # Or return a default image if desired


# Gradio Interface
def gradio_interface(prompt):
    """
    Generates an image using the Stable Diffusion model and returns it for the Gradio interface.

    Args:
        prompt (str): The text prompt for image generation.

    Returns:
        PIL.Image.Image or str: The generated image or an error message.
    """
    image = generate_image(prompt)
    if image:
        return image
    else:
        return "Error: Image generation failed. Please try a different prompt or check the console for details."



if __name__ == "__main__":
    # Create the Gradio interface
    iface = gr.Interface(
        fn=gradio_interface,
        inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."),
        outputs=gr.Image(label="Generated Image"),
        title="Text-to-Image Generator",
        description="Enter a text prompt and let the AI generate an image for you. Uses Stable Diffusion (or your specified model).",
        examples=[
            ["A photo of a cat wearing a hat"],
            ["A futuristic cityscape at sunset"],
            ["An abstract painting with vibrant colors"],
        ]
    )

    # Launch the interface
    iface.launch()