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

# Load the model
model_id = "models/black-forest-labs/FLUX.1-dev"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

def generate_image(prompt, negative_prompt, num_inference_steps, guidance_scale, width, height):
    image = pipe(
        prompt=prompt,
        negative_prompt=negative_prompt,
        num_inference_steps=num_inference_steps,
        guidance_scale=guidance_scale,
        width=width,
        height=height
    ).images[0]
    return image

def edit_image(image, brightness, contrast, saturation):
    edited = Image.fromarray(image)
    edited = edited.convert('RGB')
    edited = edited.point(lambda p: p * brightness)
    edited = edited.point(lambda p: 128 + (p - 128) * contrast)
    edited = edited.convert('HSV')
    h, s, v = edited.split()
    s = s.point(lambda p: p * saturation)
    edited = Image.merge('HSV', (h, s, v)).convert('RGB')
    return edited

with gr.Blocks(css="style.css") as demo:
    gr.Markdown("# FLUX.1 Image Generator")
    
    with gr.Tab("Generate"):
        with gr.Row():
            with gr.Column():
                prompt = gr.Textbox(label="Prompt")
                negative_prompt = gr.Textbox(label="Negative Prompt")
                steps = gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Inference Steps")
                guidance = gr.Slider(minimum=1, maximum=20, value=7.5, step=0.1, label="Guidance Scale")
                width = gr.Slider(minimum=256, maximum=1024, value=512, step=64, label="Width")
                height = gr.Slider(minimum=256, maximum=1024, value=512, step=64, label="Height")
                generate_btn = gr.Button("Generate")
            with gr.Column():
                output = gr.Image(label="Generated Image")
    
    with gr.Tab("Edit"):
        with gr.Row():
            with gr.Column():
                input_image = gr.Image(label="Input Image")
                brightness = gr.Slider(minimum=0.5, maximum=1.5, value=1.0, step=0.1, label="Brightness")
                contrast = gr.Slider(minimum=0.5, maximum=1.5, value=1.0, step=0.1, label="Contrast")
                saturation = gr.Slider(minimum=0.5, maximum=1.5, value=1.0, step=0.1, label="Saturation")
                edit_btn = gr.Button("Apply Edits")
            with gr.Column():
                edited_output = gr.Image(label="Edited Image")
    
    generate_btn.click(generate_image, inputs=[prompt, negative_prompt, steps, guidance, width, height], outputs=output)
    edit_btn.click(edit_image, inputs=[input_image, brightness, contrast, saturation], outputs=edited_output)

demo.launch()