import torch
import gradio as gr
from diffusers import FluxKontextPipeline
from optimum.quanto import freeze, qfloat8, quantize
from PIL import Image

print("Loading FLUX Kontext with 8-bit quantization...")
pipe = FluxKontextPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-Kontext-dev",
    torch_dtype=torch.bfloat16,
)

print("Quantizing transformer to 8-bit...")
quantize(pipe.transformer, weights=qfloat8)
freeze(pipe.transformer)

print("Quantizing text encoder to 8-bit...")
quantize(pipe.text_encoder_2, weights=qfloat8)
freeze(pipe.text_encoder_2)

pipe.to("cuda")
print("Model ready!")

def edit_image(input_image, prompt, steps, guidance, seed, progress=gr.Progress()):
    if input_image is None:
        return None, "Please upload an image."
    if not prompt.strip():
        return None, "Please enter an edit instruction."

    progress(0.1, desc="Preparing...")
    input_image = input_image.convert("RGB")
    generator = torch.Generator().manual_seed(int(seed))

    def step_cb(pipe, i, t, kwargs):
        progress(0.1 + 0.9 * (i / steps), desc=f"Step {i}/{steps}")
        return kwargs

    result = pipe(
        image=input_image,
        prompt=prompt.strip(),
        num_inference_steps=steps,
        guidance_scale=guidance,
        generator=generator,
        callback_on_step_end=step_cb,
    ).images[0]

    progress(1.0, desc="Done!")
    return result, "Done!"

EXAMPLES = [
    ["Make the sky look like a sunset"],
    ["Remove the background and make it white"],
    ["Make it look like a watercolor painting"],
    ["Add snow to the ground"],
    ["Change the style to anime"],
]

with gr.Blocks(title="FLUX Kontext Image Editor") as demo:
    gr.Markdown("# FLUX.1 Kontext Image Editor")
    gr.Markdown("Edit images with natural language. Powered by FLUX.1 Kontext running locally.")
    with gr.Row():
        with gr.Column():
            input_img = gr.Image(type="pil", label="Upload Image")
            prompt = gr.Textbox(
                label="Edit Instruction",
                placeholder="e.g. remove the person and smooth the background",
                lines=2,
            )
            with gr.Accordion("Advanced Settings", open=False):
                steps    = gr.Slider(10, 50, value=28, step=1, label="Steps (less = faster)")
                guidance = gr.Slider(1, 10, value=2.5, step=0.5, label="Guidance Scale")
                seed     = gr.Number(value=42, label="Seed")
            run_btn = gr.Button("Edit Image", variant="primary")
            gr.Examples(examples=EXAMPLES, inputs=[prompt], label="Example Prompts")
        with gr.Column():
            output_img = gr.Image(label="Edited Image")
            status     = gr.Textbox(label="Status", interactive=False)
    run_btn.click(
        fn=edit_image,
        inputs=[input_img, prompt, steps, guidance, seed],
        outputs=[output_img, status],
    )

if __name__ == "__main__":
    demo.launch(share=False)