Update app.py

app.py

@@ -1,30 +1,72 @@
 import gradio as gr
-from diffusers import StableDiffusionPipeline
-import torch
+import replicate
+import random
+import os
 
-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")
+def query(prompt, aspect_ratio="1:1", steps=28, cfg_scale=3.5, seed=-1, strength=0.95):
+    if seed == -1:
+        seed = random.randint(1, 1000000000)
+    
+    input = {
+        "prompt": prompt,
+        "hf_lora": "codermert/mert_flux",
+        "output_format": "jpg",
+        "aspect_ratio": aspect_ratio,
+        "num_inference_steps": steps,
+        "guidance_scale": cfg_scale,
+        "lora_scale": strength,
+        "seed": seed,
+        "disable_safety_checker": True
+    }
+    
+    output = replicate.run(
+        "lucataco/flux-dev-lora:a22c463f11808638ad5e2ebd582e07a469031f48dd567366fb4c6fdab91d614d",
+        input=input
+    )
 
-    # Flux LoRA modelini yükleyin
-    lora_model_id = "lucataco/flux-dev-lora"
-    base_model.load_lora_weights(lora_model_id)
+    print(output)
+    return output[0], seed
 
-    # 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()
+css = """
+#app-container {
+    max-width: 600px;
+    margin-left: auto;
+    margin-right: auto;
+}
+"""
+
+examples = [
+    "A beautiful landscape with mountains and a lake",
+    "A futuristic cityscape at night",
+    "A portrait of a smiling person in a colorful outfit",
+]
+
+with gr.Blocks(theme='default', css=css) as app:
+    gr.HTML("<center><h1>Mert Flux Image Generator</h1></center>")
+    with gr.Column(elem_id="app-container"):
+        with gr.Row():
+            text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2)
+        with gr.Row():
+            with gr.Accordion("Advanced Settings", open=False):
+                aspect_ratio = gr.Radio(label="Aspect ratio", value="1:1", choices=["1:1", "4:5", "2:3", "3:4","9:16", "4:3", "16:9"])
+                steps = gr.Slider(label="Sampling steps", value=28, minimum=1, maximum=100, step=1)
+                cfg = gr.Slider(label="CFG Scale", value=3.5, minimum=1, maximum=20, step=0.5)
+                strength = gr.Slider(label="Strength", value=0.95, minimum=0, maximum=1, step=0.001)
+                seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
+
+        with gr.Row():
+            text_button = gr.Button("Generate", variant='primary')
+        with gr.Row():
+            image_output = gr.Image(type="pil", label="Generated Image", show_download_button=True)
+        with gr.Row():
+            seed_output = gr.Textbox(label="Seed Used", show_copy_button=True)
+
+        gr.Examples(examples=examples, inputs=[text_prompt])
+
+        text_button.click(
+            query, 
+            inputs=[text_prompt, aspect_ratio, steps, cfg, seed, strength], 
+            outputs=[image_output, seed_output]
+        )
+
+app.launch(show_api=False)