Update app.py

app.py

@@ -44,7 +44,12 @@ def generate_character_description(character_prompt, system_message = """
         return result
     except Exception as e:
         return f"Error generating description: {str(e)}"
-        
+    
+# Function to enable LoRA if selected
+def enable_lora(lora_add, basemodel):
+    print(f"[-] Menentukan model: LoRA {'diaktifkan' if lora_add else 'tidak diaktifkan'}, model dasar: {basemodel}")
+    return basemodel if not lora_add else lora_add
+
 # Function to generate image
 async def generate_image(prompt, model, lora_word, width, height, scales, steps, seed):
     try:
@@ -53,7 +58,7 @@ async def generate_image(prompt, model, lora_word, width, height, scales, steps,
         seed = int(seed)
 
         print(f"[-] Menerjemahkan prompt: {prompt}")
-        #text = generate_character_description(str(Translator().translate(prompt, 'English'))) + "," + lora_word
+        text = str(Translator().translate(prompt, 'English')) + "," + lora_word
         
         print(f"[-] Generating image with prompt: {text}, model: {model}")
         client = AsyncInferenceClient()
@@ -66,18 +71,18 @@ async def generate_image(prompt, model, lora_word, width, height, scales, steps,
 # Function to upscale image
 def get_upscale_finegrain(prompt, img_path, upscale_factor):
     try:
-        print(f"[-] Processing with Factor {upscale_factor} for Image {img_path}")
+        print(f"[-] Memulai proses upscaling dengan faktor {upscale_factor} untuk gambar {img_path}")
         client = Client("finegrain/finegrain-image-enhancer", hf_token=HF_TOKEN_UPSCALER)
         result = client.predict(
             input_image=handle_file(img_path), 
             prompt=prompt, 
             negative_prompt="worst quality, low quality, normal quality",
             upscale_factor=upscale_factor,
-            controlnet_scale=0.7,
+            controlnet_scale=0.6,
             controlnet_decay=1,
             condition_scale=6,
-            denoise_strength=0.33, 
-            num_inference_steps=20,
+            denoise_strength=0.35, 
+            num_inference_steps=18,
             solver="DDIM", 
             api_name="/process"
         )
@@ -112,7 +117,7 @@ async def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_fac
             print(f"[-] Proses upscaling selesai. Gambar tersimpan di: {upscale_image_path}")
             return [image_path, upscale_image_path]  # Return both images
         else:
-            print("[-] Upscaling process, select the factor.")
+            print("[-] Upscaling gagal, jalur gambar upscale tidak ditemukan.")
 
     return [image_path]
 
@@ -162,52 +167,49 @@ with gr.Blocks(css=css, theme=IndonesiaTheme()) as WallpaperFluxMaker:
             # Column 1: Input prompt, LoRA, and base model
             with gr.Column(scale=1, elem_id="col-left"):
                 prompt = gr.Textbox(
-                    label="📜 Image Description", 
-                    placeholder="Write your prompt in any language, and it will be automatically translated into English.",
+                    label="📜 Deskripsi Gambar", 
+                    placeholder="Tuliskan prompt Anda dalam bahasa apapun, yang akan langsung diterjemahkan ke bahasa Inggris.",
                     elem_id="textbox-prompt"
                 )
 
                 basemodel_choice = gr.Dropdown(
-                    label="🖼️ Select a Model", 
+                    label="🖼️ Pilih Model", 
                     choices=[
-                        "black-forest-labs/FLUX.1-schnell",
-                        "black-forest-labs/FLUX.1-dev",
-                        "black-forest-labs/FLUX.1-merged",
-                        "dataautogpt3/FLUX-SyntheticAnime",
-                        "Shakker-Labs/FLUX.1-dev-LoRA-AntiBlur"
+                        "black-forest-labs/FLUX.1-schnell", 
+                        "black-forest-labs/FLUX.1-DEV", 
+                        "enhanceaiteam/Flux-uncensored", 
                         "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro", 
                         "Shakker-Labs/FLUX.1-dev-LoRA-add-details", 
-                        "city96/FLUX.1-schnell-gguf"
+                        "city96/FLUX.1-dev-gguf"
                     ], 
                     value="black-forest-labs/FLUX.1-schnell"
                 )
 
                 lora_model_choice = gr.Dropdown(
-                    label="🎨 select a LoRA", 
+                    label="🎨 Pilih LoRA", 
                     choices=[
                         "Shakker-Labs/FLUX.1-dev-LoRA-add-details", 
                         "XLabs-AI/flux-RealismLora", 
-                        "enhanceaiteam/Flux-uncensored",
-                        "Keltezaa/female-masturbation-fingering"
-                    ]+loaded_loras, 
+                        "enhanceaiteam/Flux-uncensored"
+                    ], 
                     value="XLabs-AI/flux-RealismLora"
                 )
 
-                process_lora =gr.Checkbox(label="🎨 Use LoRA")
-                process_upscale = gr.Checkbox(label="🔍 Upscale resolution")
-                upscale_factor = gr.Radio(label="🔍 Upscale factor", choices=[2, 4, 8], value=2)
+                process_lora = gr.Checkbox(label="🎨 Aktifkan LoRA")
+                process_upscale = gr.Checkbox(label="🔍 Aktifkan Peningkatan Resolusi")
+                upscale_factor = gr.Radio(label="🔍 Faktor Peningkatan Resolusi", choices=[2, 4, 8], value=2)
 
             # Column 2: Advanced options (always open)
             with gr.Column(scale=1, elem_id="col-right"):
-                with gr.Accordion(label="⚙️ Settings", open=True):
-                    width = gr.Slider(label="Width", minimum=512, maximum=1280, step=8, value=1280)
-                    height = gr.Slider(label="Height", minimum=512, maximum=1280, step=8, value=768)
-                    scales = gr.Slider(label="Scale", minimum=1, maximum=20, step=1, value=8)
-                    steps = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=8)
+                with gr.Accordion(label="⚙️ Opsi Lanjutan", open=True):
+                    width = gr.Slider(label="Lebar", minimum=512, maximum=1280, step=8, value=1280)
+                    height = gr.Slider(label="Tinggi", minimum=512, maximum=1280, step=8, value=768)
+                    scales = gr.Slider(label="Skala", minimum=1, maximum=20, step=1, value=8)
+                    steps = gr.Slider(label="Langkah", minimum=1, maximum=100, step=1, value=8)
                     seed = gr.Number(label="Seed", value=-1)
 
         # Button to generate image
-        btn = gr.Button("🚀 Bombs away!", elem_id="generate-btn")
+        btn = gr.Button("🚀 Buat Gambar", elem_id="generate-btn")
 
         # Running the `gen` function when "Generate" button is pressed
         btn.click(fn=gen, inputs=[
@@ -215,4 +217,4 @@ with gr.Blocks(css=css, theme=IndonesiaTheme()) as WallpaperFluxMaker:
         ], outputs=output_res)
 
 # Launching the Gradio app
-WallpaperFluxMaker.queue(api_open=False).launch(show_api=True)
+WallpaperFluxMaker.queue(api_open=False).launch(show_api=False)