Update app.py

app.py

@@ -37,7 +37,7 @@ if not os.path.exists(model_path):
 def run_command_and_save(
     prompt, mode, height, width, steps, seed, cfg_scale, strength, sampling_method,
     batch_count, schedule, clip_skip, vae_tiling, vae_on_cpu, clip_on_cpu, diffusion_fa,
-    control_net_cpu, canny, verbose, init_image=None
+    control_net_cpu, canny, verbose, init_image=None, weight_type=None
 ):
     try:
         # Lưu ảnh đầu vào nếu được cung cấp
@@ -45,7 +45,6 @@ def run_command_and_save(
         if init_image is not None:
             init_image_path = "input_image.png"
             init_image.save(init_image_path)
-
         # Tạo lệnh chạy
         command = [
             f"./{app_path}",
@@ -63,8 +62,11 @@ def run_command_and_save(
             "--schedule", schedule,
             "--clip-skip", str(clip_skip),
         ]
-
-        # Thêm tùy chọn VAE tiling
+        # Thêm tùy chọn Weight Type nếu được chỉ định
+        if weight_type:
+            command.extend(["--type", weight_type])
+        
+        # Thêm các tùy chọn khác
         if vae_tiling:
             command.append("--vae-tiling")
         if vae_on_cpu:
@@ -79,11 +81,9 @@ def run_command_and_save(
             command.append("--canny")
         if verbose:
             command.append("-v")
-
         # Thêm ảnh đầu vào nếu có
         if mode == "img2img" and init_image_path:
             command.extend(["-i", init_image_path])
-
         # Chạy lệnh và hiển thị log theo thời gian thực
         process = subprocess.Popen(
             command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True
@@ -92,7 +92,6 @@ def run_command_and_save(
         for line in process.stdout:
             logs.append(line.strip())  # Lưu log vào danh sách
             print(line, end="")  # In log ra màn hình
-
         process.wait()  # Đợi tiến trình hoàn thành
         # Kiểm tra kết quả và trả về
         if process.returncode == 0:
@@ -106,10 +105,8 @@ def run_command_and_save(
                 local_folder = os.path.join(".", folder_name)
                 os.makedirs(local_folder, exist_ok=True)
                 local_file_path = os.path.join(local_folder, file_name)
-
                 # Di chuyển file đến thư mục mới
                 os.rename(output_path, local_file_path)
-
                 # Upload file lên Hugging Face Hub
                 api = HfApi()
                 repo_id = "ArrcttacsrjksX/Deffusion"
@@ -144,7 +141,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         Generate stunning images from text or modify existing images with AI-powered tools.
         """
     )
-
     # Thiết lập giao diện
     with gr.Row():
         with gr.Column():
@@ -158,7 +154,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                 label="Drop Image (for img2img mode)", type="pil", visible=False
             )
             mode.change(toggle_image_input, inputs=mode, outputs=init_image)
-
         with gr.Column():
             height = gr.Slider(
                 128, 1024, value=512, step=64, label="Image Height (px)", interactive=True
@@ -178,7 +173,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             strength = gr.Slider(
                 0, 1, value=0.75, step=0.01, label="Strength (img2img only)", interactive=True
             )
-
     with gr.Row():
         sampling_method = gr.Dropdown(
             choices=["euler", "euler_a", "heun", "dpm2", "dpm++2s_a", "dpm++2m", "dpm++2mv2", "ipndm", "ipndm_v", "lcm"],
@@ -191,7 +185,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             choices=["discrete", "karras", "exponential", "ays", "gits"],
             value="discrete", label="Denoiser Sigma Schedule", interactive=True
         )
-
     with gr.Row():
         clip_skip = gr.Slider(
             -1, 10, value=-1, step=1, label="CLIP Skip Layers", interactive=True
@@ -203,22 +196,26 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         control_net_cpu = gr.Checkbox(label="ControlNet on CPU", value=False)
         canny = gr.Checkbox(label="Canny Preprocessor", value=False)
         verbose = gr.Checkbox(label="Verbose Logging", value=False)
-
+    with gr.Row():
+        weight_type = gr.Dropdown(
+            choices=["f32", "f16", "q4_0", "q4_1", "q5_0", "q5_1", "q8_0", "q2_K", "q3_K", "q4_K"],
+            value=None,  # Mặc định không chọn
+            label="Weight Type (Optional)",
+            interactive=True
+        )
     # Nút chạy và kết quả
     with gr.Row():
         run_button = gr.Button("🚀 Run", variant="primary")
-
     with gr.Row():
         output_image = gr.File(label="Download Image", interactive=False)
         log_output = gr.Textbox(label="Logs", interactive=False, lines=10)
-
     # Kết nối nút Run với hàm xử lý
     run_button.click(
         run_command_and_save,
         inputs=[
             prompt, mode, height, width, steps, seed, cfg_scale, strength, sampling_method,
             batch_count, schedule, clip_skip, vae_tiling, vae_on_cpu, clip_on_cpu, diffusion_fa,
-            control_net_cpu, canny, verbose, init_image
+            control_net_cpu, canny, verbose, init_image, weight_type  # Thêm weight_type
         ],
         outputs=[output_image, log_output],
     )