Update app.py

app.py

@@ -1,72 +1,75 @@
 import gradio as gr
-import replicate
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
+import torch
+from PIL import Image
 import random
-import os
 
-def query(prompt, aspect_ratio="1:1", steps=28, cfg_scale=3.5, seed=-1, strength=0.95):
+model_id = "stabilityai/stable-diffusion-xl-base-1.0"
+lora_model_id = "codermert/tugce2-lora"  # Your LoRA model
+
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+pipe = pipe.to("cuda")
+pipe.load_lora_weights(lora_model_id)
+
+def generate_image(prompt, negative_prompt, steps, cfg_scale, seed, strength):
     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
-    }
+    generator = torch.Generator("cuda").manual_seed(seed)
     
-    output = replicate.run(
-        "lucataco/flux-dev-lora:a22c463f11808638ad5e2ebd582e07a469031f48dd567366fb4c6fdab91d614d",
-        input=input
-    )
-
-    print(output)
-    return output[0], seed
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        num_inference_steps=steps,
+        guidance_scale=cfg_scale,
+        generator=generator,
+        cross_attention_kwargs={"scale": strength},
+    ).images[0]
+    
+    return image, seed
 
 css = """
 #app-container {
-    max-width: 600px;
+    max-width: 800px;
     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",
+    ["A beautiful landscape with mountains and a lake", "ugly, deformed"],
+    ["A futuristic cityscape at night", "daytime, rural"],
+    ["A portrait of a smiling person in a colorful outfit", "monochrome, frowning"],
 ]
 
 with gr.Blocks(theme='default', css=css) as app:
-    gr.HTML("<center><h1>Mert Flux Image Generator</h1></center>")
+    gr.HTML("<center><h1>Mert Flux LoRA Explorer</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)
+            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What to avoid in the image", 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)
+            with gr.Column():
+                steps = gr.Slider(label="Sampling steps", value=30, minimum=10, maximum=100, step=1)
+                cfg_scale = gr.Slider(label="CFG Scale", value=7.5, minimum=1, maximum=20, step=0.5)
+            with gr.Column():
+                strength = gr.Slider(label="LoRA Strength", value=0.75, minimum=0, maximum=1, step=0.01)
                 seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
 
         with gr.Row():
-            text_button = gr.Button("Generate", variant='primary')
+            generate_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)
+            seed_output = gr.Number(label="Seed Used")
 
-        gr.Examples(examples=examples, inputs=[text_prompt])
+        gr.Examples(examples=examples, inputs=[text_prompt, negative_prompt])
 
-        text_button.click(
-            query, 
-            inputs=[text_prompt, aspect_ratio, steps, cfg, seed, strength], 
+        generate_button.click(
+            generate_image, 
+            inputs=[text_prompt, negative_prompt, steps, cfg_scale, seed, strength], 
             outputs=[image_output, seed_output]
         )
 
-app.launch(show_api=False)
+app.launch()