app.py

import gradio as gr
from diffusers import StableDiffusionPipeline
import torch

def generate_image(prompt, num_inference_steps=50):
    # Kendi modelinizi yükleyin
    base_model = StableDiffusionPipeline.from_pretrained("codermert/mert_flux", torch_dtype=torch.float16)
    base_model.to("cuda")

    # Flux LoRA modelini yükleyin
    lora_model_id = "lucataco/flux-dev-lora"
    base_model.load_lora_weights(lora_model_id)

    # Resmi oluşturun
    image = base_model(prompt, num_inference_steps=num_inference_steps).images[0]
    
    return image

iface = gr.Interface(
    fn=generate_image,
    inputs=[
        gr.Textbox(label="Prompt"),
        gr.Slider(minimum=1, maximum=100, step=1, label="Number of Inference Steps", value=50)
    ],
    outputs=gr.Image(label="Generated Image"),
    title="Mert Flux Image Generator",
    description="Generate images using Mert Flux model and Flux LoRA"
)

iface.launch()