test2

README.md

@@ -1,166 +1,166 @@
----
-title: 🧩 DiffuseCraft Mod (SDXL/SD1.5 Models Text-to-Image)
-emoji: 🧩🖼️📦
-colorFrom: red
-colorTo: pink
-sdk: gradio
-sdk_version: 6.10.0
-python_version: "3.12"
-app_file: app.py
-pinned: true
-header: mini
-license: mit
-duplicated_from: r3gm/DiffuseCraft
-short_description: Stunning images using stable diffusion.
-preload_from_hub:
-  - madebyollin/sdxl-vae-fp16-fix config.json,diffusion_pytorch_model.safetensors
----
-
-## Using this Space programmatically
-
-You can call this Space from Python (via `gradio_client`) or from plain `curl`.
-
-> ⚠️ Note: This README may lag behind the actual API definition shown in the Space’s “View API” page.
-> If something does not work, always double-check the latest argument list and endpoint names there.
-
-Assumptions:
-
-- Space ID: `John6666/DiffuseCraftMod`
-- You have a valid Hugging Face access token: `hf_xxx...` (read access is enough)
-- Replace `hf_xxx...` with your own token
-
----
-
-### 1. Python examples (`gradio_client`)
-
-Install:
-
-```bash
-pip install gradio_client
-````
-
-#### 1.1 Synchronous API – `generate_image`
-
-```python
-from gradio_client import Client
-
-client = Client("John6666/DiffuseCraftMod", hf_token="hf_xxx...")
-
-status, images, info = client.predict(
-    # Core text controls
-    prompt="Hello!!",
-    negative_prompt=(
-        "lowres, bad anatomy, bad hands, missing fingers, extra digit, "
-        "fewer digits, worst quality, low quality"
-    ),
-
-    # Basic generation controls
-    num_images=1,
-    num_inference_steps=28,
-    guidance_scale=7.0,
-    clip_skip=0,
-    seed=-1,
-
-    # Canvas / model / task (optional, server has defaults)
-    height=1024,
-    width=1024,
-    model_name="votepurchase/animagine-xl-3.1",
-    vae_model="None",
-    task="txt2img",
-
-    # All other arguments are optional; defaults match the UI
-    api_name="/generate_image",
-)
-
-print(status)   # e.g. "COMPLETE"
-print(images)   # list of image paths / URLs
-print(info)     # generation metadata (seed, model, etc.)
-```
-
-#### 1.2 Streaming API – `generate_image_stream`
-
-```python
-from gradio_client import Client
-
-client = Client("John6666/DiffuseCraftMod", hf_token="hf_xxx...")
-
-job = client.submit(
-    prompt="Hello!!",
-    negative_prompt=(
-        "lowres, bad anatomy, bad hands, missing fingers, extra digit, "
-        "fewer digits, worst quality, low quality"
-    ),
-    num_images=1,
-    num_inference_steps=28,
-    guidance_scale=7.0,
-    clip_skip=0,
-    seed=-1,
-    height=1024,
-    width=1024,
-    model_name="votepurchase/animagine-xl-3.1",
-    vae_model="None",
-    task="txt2img",
-    api_name="/generate_image_stream",
-)
-
-for status, images, info in job:
-    # You will see progress messages, intermediate previews, and the final result.
-    print(status, images, info)
-```
-
-You can stop iterating once you see a `"COMPLETE"` status if you only care about the final output.
-
----
-
-### 2. `curl` examples
-
-When calling from `curl`, include your HF token; anonymous calls may be rate-limited or rejected.
-
-```bash
-export HF_TOKEN="hf_xxx..."  # your Hugging Face access token
-```
-
-The `data` field is a positional array. The order must match the function signature.
-For simplicity, the examples below only send the first few arguments and rely on server defaults for the rest.
-
-#### 2.1 Synchronous API – `generate_image`
-
-```bash
-curl -X POST "https://john6666-diffusecraftmod.hf.space/call/generate_image" \
-  -H "Authorization: Bearer $HF_TOKEN" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "data": [
-      "Hello!!",  // prompt
-      "lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality", // negative_prompt
-      1,          // num_images
-      28,         // num_inference_steps
-      7.0,        // guidance_scale
-      0,          // clip_skip
-      -1          // seed
-      // All subsequent parameters will use their default values
-    ]
-  }'
-```
-
-#### 2.2 Streaming API – `generate_image_stream`
-
-```bash
-curl -X POST "https://john6666-diffusecraftmod.hf.space/call/generate_image_stream" \
-  -H "Authorization: Bearer $HF_TOKEN" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "data": [
-      "Hello!!",
-      "lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality",
-      1,
-      28,
-      7.0,
-      0,
-      -1
-    ]
-  }'
-```
-
-For full parameter coverage (all advanced options such as LoRAs, ControlNet, IP-Adapter, etc.),
-refer to the Space’s “View API” page and adapt the examples above accordingly.
+---
+title: 🧩 DiffuseCraft Mod (SDXL/SD1.5 Models Text-to-Image)
+emoji: 🧩🖼️📦
+colorFrom: red
+colorTo: pink
+sdk: gradio
+sdk_version: 5.45.0
+app_file: app.py
+pinned: true
+header: mini
+license: mit
+duplicated_from: r3gm/DiffuseCraft
+short_description: Stunning images using stable diffusion.
+preload_from_hub:
+  - madebyollin/sdxl-vae-fp16-fix config.json,diffusion_pytorch_model.safetensors
+hf_oauth: true
+---
+
+## Using this Space programmatically
+
+You can call this Space from Python (via `gradio_client`) or from plain `curl`.
+
+> ⚠️ Note: This README may lag behind the actual API definition shown in the Space’s “View API” page.
+> If something does not work, always double-check the latest argument list and endpoint names there.
+
+Assumptions:
+
+- Space ID: `John6666/DiffuseCraftMod`
+- You have a valid Hugging Face access token: `hf_xxx...` (read access is enough)
+- Replace `hf_xxx...` with your own token
+
+---
+
+### 1. Python examples (`gradio_client`)
+
+Install:
+
+```bash
+pip install gradio_client
+````
+
+#### 1.1 Synchronous API – `generate_image`
+
+```python
+from gradio_client import Client
+
+client = Client("John6666/DiffuseCraftMod", hf_token="hf_xxx...")
+
+status, images, info = client.predict(
+    # Core text controls
+    prompt="Hello!!",
+    negative_prompt=(
+        "lowres, bad anatomy, bad hands, missing fingers, extra digit, "
+        "fewer digits, worst quality, low quality"
+    ),
+
+    # Basic generation controls
+    num_images=1,
+    num_inference_steps=28,
+    guidance_scale=7.0,
+    clip_skip=0,
+    seed=-1,
+
+    # Canvas / model / task (optional, server has defaults)
+    height=1024,
+    width=1024,
+    model_name="votepurchase/animagine-xl-3.1",
+    vae_model="None",
+    task="txt2img",
+
+    # All other arguments are optional; defaults match the UI
+    api_name="/generate_image",
+)
+
+print(status)   # e.g. "COMPLETE"
+print(images)   # list of image paths / URLs
+print(info)     # generation metadata (seed, model, etc.)
+```
+
+#### 1.2 Streaming API – `generate_image_stream`
+
+```python
+from gradio_client import Client
+
+client = Client("John6666/DiffuseCraftMod", hf_token="hf_xxx...")
+
+job = client.submit(
+    prompt="Hello!!",
+    negative_prompt=(
+        "lowres, bad anatomy, bad hands, missing fingers, extra digit, "
+        "fewer digits, worst quality, low quality"
+    ),
+    num_images=1,
+    num_inference_steps=28,
+    guidance_scale=7.0,
+    clip_skip=0,
+    seed=-1,
+    height=1024,
+    width=1024,
+    model_name="votepurchase/animagine-xl-3.1",
+    vae_model="None",
+    task="txt2img",
+    api_name="/generate_image_stream",
+)
+
+for status, images, info in job:
+    # You will see progress messages, intermediate previews, and the final result.
+    print(status, images, info)
+```
+
+You can stop iterating once you see a `"COMPLETE"` status if you only care about the final output.
+
+---
+
+### 2. `curl` examples
+
+When calling from `curl`, include your HF token; anonymous calls may be rate-limited or rejected.
+
+```bash
+export HF_TOKEN="hf_xxx..."  # your Hugging Face access token
+```
+
+The `data` field is a positional array. The order must match the function signature.
+For simplicity, the examples below only send the first few arguments and rely on server defaults for the rest.
+
+#### 2.1 Synchronous API – `generate_image`
+
+```bash
+curl -X POST "https://john6666-diffusecraftmod.hf.space/call/generate_image" \
+  -H "Authorization: Bearer $HF_TOKEN" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "data": [
+      "Hello!!",  // prompt
+      "lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality", // negative_prompt
+      1,          // num_images
+      28,         // num_inference_steps
+      7.0,        // guidance_scale
+      0,          // clip_skip
+      -1          // seed
+      // All subsequent parameters will use their default values
+    ]
+  }'
+```
+
+#### 2.2 Streaming API – `generate_image_stream`
+
+```bash
+curl -X POST "https://john6666-diffusecraftmod.hf.space/call/generate_image_stream" \
+  -H "Authorization: Bearer $HF_TOKEN" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "data": [
+      "Hello!!",
+      "lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality",
+      1,
+      28,
+      7.0,
+      0,
+      -1
+    ]
+  }'
+```
+
+For full parameter coverage (all advanced options such as LoRAs, ControlNet, IP-Adapter, etc.),
+refer to the Space’s “View API” page and adapt the examples above accordingly.

app.py

@@ -199,11 +199,6 @@ class GuiSD:
         # Avoid duplicate downloads
         self.active_downloads = set()
         self.download_lock = threading.Lock()
-
-        # Anti-abuse: track new model requests.
-        self.used_models = []
-        self.new_model_history = []
-
     def update_storage_models(self, storage_floor_gb=24, required_inventory_for_purge=3):
         while get_used_storage_gb() > storage_floor_gb:
             if len(self.inventory) < required_inventory_for_purge:
@@ -228,34 +223,6 @@ class GuiSD:
         print(self.inventory)
 
     def load_new_model(self, model_name, vae_model, task, controlnet_model, progress=gr.Progress(track_tqdm=True)):
-
-        if model_name != model_list[0]:
-            # --- Anti-Abuse Check Start ---
-            if model_name in self.used_models:
-                # Move to the end to mark as the most recently used.
-                self.used_models.remove(model_name)
-                self.used_models.append(model_name)
-            else:
-                current_time = datetime.now()
-                # Retain history of new model requests from the last 20 minutes.
-                self.new_model_history = [
-                    t for t in self.new_model_history
-                    if (current_time - t).total_seconds() < 1200
-                ]
-
-                # Allow a maximum of 5 new model requests per 20 minutes.
-                if len(self.new_model_history) >= 5:
-                    yield "Rate limit exceeded: Too many new models requested."
-                    raise gr.Error("Too many new models requested. Please reuse your previously loaded models or wait a few minutes before trying new ones.")
-
-                self.new_model_history.append(current_time)
-                self.used_models.append(model_name)
-
-                # Cap the reuse list to the 5 most recent models.
-                if len(self.used_models) > 5:
-                    self.used_models.pop(0)
-            # --- Anti-Abuse Check End ---
-
         lock_key = model_name
 
         while True:
@@ -878,7 +845,7 @@ CSS ="""
 .desc [src$='#float'] { float: right; margin: 20px; }
 """
 
-with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
+with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=False, css=CSS) as app:
     gr.Markdown("# 🧩 DiffuseCraft Mod", elem_classes="title")
     gr.Markdown("This space is a modification of [r3gm's DiffuseCraft](https://huggingface.co/spaces/r3gm/DiffuseCraft).", elem_classes="info")
     with gr.Column():
@@ -923,9 +890,9 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                                     keep_tags_gui = gr.Radio(label="Remove tags leaving only the following", choices=["body", "dress", "all"], value="all")
                                 image_algorithms = gr.CheckboxGroup(["Use WD Tagger"], label="Algorithms", value=["Use WD Tagger"], visible=False)
                             generate_from_image_btn_gui = gr.Button(value="GENERATE TAGS FROM IMAGE")
-                        prompt_gui = gr.Textbox(lines=6, placeholder="1girl, solo, ...", label="Prompt", buttons=["copy"])
+                        prompt_gui = gr.Textbox(lines=6, placeholder="1girl, solo, ...", label="Prompt", show_copy_button=True)
                         with gr.Accordion("Negative prompt, etc.", open=False) as menu_negative:
-                            neg_prompt_gui = gr.Textbox(lines=3, placeholder="Enter Neg prompt", label="Negative prompt", value="lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality, very displeasing, (bad)", buttons=["copy"])
+                            neg_prompt_gui = gr.Textbox(lines=3, placeholder="Enter Neg prompt", label="Negative prompt", value="lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality, very displeasing, (bad)", show_copy_button=True)
                             translate_prompt_button = gr.Button(value="Translate prompt to English", size="sm", variant="secondary")
                             with gr.Row():
                                 insert_prompt_gui = gr.Radio(label="Insert reccomended positive / negative prompt", choices=["None", "Auto", "Animagine", "Pony"], value="Auto", interactive=True)                          
@@ -955,7 +922,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                         update_task_options,
                         [model_name_gui, task_gui],
                         [task_gui],
-                        api_visibility="undocumented",
+                        show_api=False,
                     )
 
                     load_model_gui = gr.HTML(elem_id="load_model", elem_classes="contain")
@@ -972,7 +939,8 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                         # height="auto",
                         interactive=False,
                         preview=False,
-                        buttons=["download", "fullscreen"],
+                        show_share_button=False,
+                        show_download_button=True,
                         selected_index=50,
                         format="png",
                     )
@@ -983,9 +951,9 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
 
                     with gr.Accordion("History", open=False):
                         history_files = gr.Files(interactive=False, visible=False)
-                        history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain", format="png", interactive=False, buttons=["download", "fullscreen"])
+                        history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain", format="png", interactive=False, show_share_button=False, show_download_button=True)
                         history_clear_button = gr.Button(value="Clear History", variant="secondary")
-                        history_clear_button.click(lambda: ([], []), None, [history_gallery, history_files], queue=False, api_visibility="undocumented")
+                        history_clear_button.click(lambda: ([], []), None, [history_gallery, history_files], queue=False, show_api=False)
 
                     with gr.Row(equal_height=False, variant="default"):
                         gpu_duration_gui = gr.Number(minimum=5, maximum=240, value=20, show_label=False, container=False, info="GPU time duration (seconds)")
@@ -1165,7 +1133,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                             return gr.Slider(minimum=-val_lora, maximum=val_lora, step=0.01, value=1.0, label=label, visible=visible)
                     
                         def lora_textbox(label):
-                            return gr.Textbox(label=label, info="Example of prompt:", value="None", buttons=["copy"], interactive=False, visible=False)
+                            return gr.Textbox(label=label, info="Example of prompt:", value="None", show_copy_button=True, interactive=False, visible=False)
                         
                         with gr.Row():
                             with gr.Column():
@@ -1236,7 +1204,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                             search_civitai_button_lora = gr.Button("Search on Civitai")
                             search_civitai_desc_lora = gr.Markdown(value="", visible=False, elem_classes="desc")
                             with gr.Accordion("Select from Gallery", open=False):
-                                search_civitai_gallery_lora = gr.Gallery([], label="Results", allow_preview=False, columns=5, buttons=["download", "fullscreen"], interactive=False)
+                                search_civitai_gallery_lora = gr.Gallery([], label="Results", allow_preview=False, columns=5, show_share_button=False, interactive=False)
                             search_civitai_result_lora = gr.Dropdown(label="Search Results", choices=[("", "")], value="", allow_custom_value=True, visible=False)
                             with gr.Row():
                                 text_lora = gr.Textbox(label="LoRA's download URL", placeholder="https://civitai.com/api/download/models/28907", info="It has to be .safetensors files, and you can also download them from Hugging Face.", lines=1, scale=4)
@@ -1320,8 +1288,8 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                             use_textual_inversion_gui = gr.CheckboxGroup(choices=get_embed_list(get_model_pipeline(model_name_gui.value)) if active_textual_inversion_gui.value else [], value=None, label="Use Textual Invertion in prompt")
                             def update_textual_inversion_gui(active_textual_inversion_gui, model_name_gui):
                                 return gr.update(choices=get_embed_list(get_model_pipeline(model_name_gui)) if active_textual_inversion_gui else [])
-                            active_textual_inversion_gui.change(update_textual_inversion_gui, [active_textual_inversion_gui, model_name_gui], [use_textual_inversion_gui], api_visibility="undocumented")
-                            model_name_gui.change(update_textual_inversion_gui, [active_textual_inversion_gui, model_name_gui], [use_textual_inversion_gui], api_visibility="undocumented")
+                            active_textual_inversion_gui.change(update_textual_inversion_gui, [active_textual_inversion_gui, model_name_gui], [use_textual_inversion_gui], show_api=False)
+                            model_name_gui.change(update_textual_inversion_gui, [active_textual_inversion_gui, model_name_gui], [use_textual_inversion_gui], show_api=False)
 
                         with gr.Accordion("ControlNet / Img2img / Inpaint", open=False, visible=True) as menu_i2i:
                             with gr.Row():
@@ -1359,7 +1327,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                                     change_preprocessor_choices,
                                     [task_gui],
                                     [preprocessor_name_gui],
-                                    api_visibility="undocumented",
+                                    show_api=False,
                                 )
 
                             with gr.Row():
@@ -1419,7 +1387,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                                 gr.Info(f"{len(sd_gen.model.STYLE_NAMES)} styles loaded")
                                 return gr.update(value=None, choices=sd_gen.model.STYLE_NAMES)
 
-                            style_button.click(load_json_style_file, [style_json_gui], [style_prompt_gui], api_visibility="undocumented")
+                            style_button.click(load_json_style_file, [style_json_gui], [style_prompt_gui], show_api=False)
 
                         with gr.Accordion("Other settings", open=False, visible=True) as menu_other:
                             with gr.Row():
@@ -1541,7 +1509,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
 
                     def change_visibility_canvas():
                         return gr.update(visible=True, interactive=True), gr.update(visible=False)
-                    show_canvas.click(change_visibility_canvas, [], [image_base, show_canvas], api_visibility="undocumented")
+                    show_canvas.click(change_visibility_canvas, [], [image_base, show_canvas], show_api=False)
 
                     invert_mask = gr.Checkbox(value=False, label="Invert mask")
                     btn = gr.Button("Create mask")
@@ -1555,7 +1523,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
 
                 def send_img(img_source, img_result):
                     return img_source, img_result
-                btn_send.click(send_img, [img_source, img_result], [image_control, image_mask_gui], api_visibility="undocumented")
+                btn_send.click(send_img, [img_source, img_result], [image_control, image_mask_gui], show_api=False)
 
         with gr.Tab("PNG Info"):
             with gr.Row():
@@ -1563,7 +1531,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                     image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
 
                 with gr.Column():
-                    result_metadata = gr.Textbox(label="Metadata", show_label=True, buttons=["copy"], interactive=False, container=True, max_lines=99)
+                    result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
 
                     image_metadata.change(
                         fn=extract_exif_data,
@@ -1601,11 +1569,11 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
             [menu_model, menu_from_image, menu_negative, menu_gen, menu_hires, menu_lora, menu_advanced,
               menu_example, task_gui, quick_speed_gui],
             queue=False,
-            api_visibility="undocumented",
+            show_api=False,
         )
-        model_name_gui.change(get_t2i_model_info, [model_name_gui], [model_info_gui], queue=False, api_visibility="undocumented")
-        translate_prompt_gui.click(translate_to_en, [prompt_gui], [prompt_gui], queue=False, api_visibility="undocumented")\
-        .then(translate_to_en, [neg_prompt_gui], [neg_prompt_gui], queue=False, api_visibility="undocumented")
+        model_name_gui.change(get_t2i_model_info, [model_name_gui], [model_info_gui], queue=False, show_api=False)
+        translate_prompt_gui.click(translate_to_en, [prompt_gui], [prompt_gui], queue=False, show_api=False)\
+        .then(translate_to_en, [neg_prompt_gui], [neg_prompt_gui], queue=False, show_api=False)
 
         gr.on(
             triggers=[quick_model_type_gui.change, quick_genre_gui.change, quick_speed_gui.change, quick_aspect_gui.change],
@@ -1614,7 +1582,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
             outputs=[quality_selector_gui, style_selector_gui, sampler_selector_gui, optimization_gui, insert_prompt_gui],
             queue=False,
             trigger_mode="once",
-            api_visibility="undocumented",
+            show_api=False,
         )
         gr.on(
             triggers=[quality_selector_gui.change, style_selector_gui.change, insert_prompt_gui.change],
@@ -1623,7 +1591,7 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
             outputs=[prompt_gui, neg_prompt_gui, quick_model_type_gui],
             queue=False,
             trigger_mode="once",
-            api_visibility="undocumented",
+            show_api=False,
         )
         sampler_selector_gui.change(set_sampler_settings, [sampler_selector_gui], [sampler_gui, steps_gui, cfg_gui, clip_skip_gui, img_width_gui, img_height_gui, optimization_gui], queue=False)
         optimization_gui.change(set_optimization, [optimization_gui, steps_gui, cfg_gui, sampler_gui, clip_skip_gui, lora5_gui, lora_scale_5_gui], [steps_gui, cfg_gui, sampler_gui, clip_skip_gui, lora5_gui, lora_scale_5_gui], queue=False)
@@ -1646,15 +1614,15 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                     lora7_gui, lora_scale_7_gui, lora7_info_gui, lora7_copy_gui, lora7_desc_gui],
             queue=False,
             trigger_mode="once",
-            api_visibility="undocumented",
+            show_api=False,
         )
-        lora1_copy_gui.click(apply_lora_prompt, [prompt_gui, lora1_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        lora2_copy_gui.click(apply_lora_prompt, [prompt_gui, lora2_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        lora3_copy_gui.click(apply_lora_prompt, [prompt_gui, lora3_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        lora4_copy_gui.click(apply_lora_prompt, [prompt_gui, lora4_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        lora5_copy_gui.click(apply_lora_prompt, [prompt_gui, lora5_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        lora6_copy_gui.click(apply_lora_prompt, [prompt_gui, lora6_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        lora7_copy_gui.click(apply_lora_prompt, [prompt_gui, lora7_info_gui], [prompt_gui], queue=False, api_visibility="undocumented")
+        lora1_copy_gui.click(apply_lora_prompt, [prompt_gui, lora1_info_gui], [prompt_gui], queue=False, show_api=False)
+        lora2_copy_gui.click(apply_lora_prompt, [prompt_gui, lora2_info_gui], [prompt_gui], queue=False, show_api=False)
+        lora3_copy_gui.click(apply_lora_prompt, [prompt_gui, lora3_info_gui], [prompt_gui], queue=False, show_api=False)
+        lora4_copy_gui.click(apply_lora_prompt, [prompt_gui, lora4_info_gui], [prompt_gui], queue=False, show_api=False)
+        lora5_copy_gui.click(apply_lora_prompt, [prompt_gui, lora5_info_gui], [prompt_gui], queue=False, show_api=False)
+        lora6_copy_gui.click(apply_lora_prompt, [prompt_gui, lora6_info_gui], [prompt_gui], queue=False, show_api=False)
+        lora7_copy_gui.click(apply_lora_prompt, [prompt_gui, lora7_info_gui], [prompt_gui], queue=False, show_api=False)
         gr.on(
             triggers=[search_civitai_button_lora.click, search_civitai_query_lora.submit],
             fn=search_civitai_lora,
@@ -1663,54 +1631,54 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
             outputs=[search_civitai_result_lora, search_civitai_desc_lora, search_civitai_button_lora, search_civitai_query_lora, search_civitai_gallery_lora],
             queue=True,
             scroll_to_output=True,
-            api_visibility="undocumented",
+            show_api=False,
         )
-        search_civitai_result_lora.change(select_civitai_lora, [search_civitai_result_lora], [text_lora, search_civitai_desc_lora], queue=False, scroll_to_output=True, api_visibility="undocumented")
-        search_civitai_gallery_lora.select(update_civitai_selection, None, [search_civitai_result_lora], queue=False, api_visibility="undocumented")
-        button_lora.click(get_my_lora, [text_lora, romanize_text], [lora1_gui, lora2_gui, lora3_gui, lora4_gui, lora5_gui, lora6_gui, lora7_gui, new_lora_status], scroll_to_output=True, api_visibility="undocumented")
-        upload_button_lora.upload(upload_file_lora, [upload_button_lora], [file_output_lora, upload_button_lora], api_visibility="undocumented").success(
-            move_file_lora, [file_output_lora], [lora1_gui, lora2_gui, lora3_gui, lora4_gui, lora5_gui, lora6_gui, lora7_gui], scroll_to_output=True, api_visibility="undocumented")
+        search_civitai_result_lora.change(select_civitai_lora, [search_civitai_result_lora], [text_lora, search_civitai_desc_lora], queue=False, scroll_to_output=True, show_api=False)
+        search_civitai_gallery_lora.select(update_civitai_selection, None, [search_civitai_result_lora], queue=False, show_api=False)
+        button_lora.click(get_my_lora, [text_lora, romanize_text], [lora1_gui, lora2_gui, lora3_gui, lora4_gui, lora5_gui, lora6_gui, lora7_gui, new_lora_status], scroll_to_output=True, show_api=False)
+        upload_button_lora.upload(upload_file_lora, [upload_button_lora], [file_output_lora, upload_button_lora], show_api=False).success(
+            move_file_lora, [file_output_lora], [lora1_gui, lora2_gui, lora3_gui, lora4_gui, lora5_gui, lora6_gui, lora7_gui], scroll_to_output=True, show_api=False)
 
-        use_textual_inversion_gui.change(set_textual_inversion_prompt, [use_textual_inversion_gui, prompt_gui, neg_prompt_gui, prompt_syntax_gui], [prompt_gui, neg_prompt_gui], api_visibility="undocumented")
+        use_textual_inversion_gui.change(set_textual_inversion_prompt, [use_textual_inversion_gui, prompt_gui, neg_prompt_gui, prompt_syntax_gui], [prompt_gui, neg_prompt_gui], show_api=False)
 
         generate_from_image_btn_gui.click(
-            lambda: ("", "", ""), None, [series_dbt, character_dbt, prompt_gui], queue=False, api_visibility="undocumented",
+            lambda: ("", "", ""), None, [series_dbt, character_dbt, prompt_gui], queue=False, show_api=False,
         ).success(
             predict_tags_wd,
             [input_image_gui, prompt_gui, image_algorithms, general_threshold_gui, character_threshold_gui],
             [series_dbt, character_dbt, prompt_gui, copy_button_dbt],
-            api_visibility="undocumented",
+            show_api=False,
         ).success(
-            compose_prompt_to_copy, [character_dbt, series_dbt, prompt_gui], [prompt_gui], queue=False, api_visibility="undocumented",
+            compose_prompt_to_copy, [character_dbt, series_dbt, prompt_gui], [prompt_gui], queue=False, show_api=False,
         ).success(
-            remove_specific_prompt, [prompt_gui, keep_tags_gui], [prompt_gui], queue=False, api_visibility="undocumented",
+            remove_specific_prompt, [prompt_gui, keep_tags_gui], [prompt_gui], queue=False, show_api=False,
         ).success(
-            convert_danbooru_to_e621_prompt, [prompt_gui, tag_type_gui], [prompt_gui], queue=False, api_visibility="undocumented",
+            convert_danbooru_to_e621_prompt, [prompt_gui, tag_type_gui], [prompt_gui], queue=False, show_api=False,
         ).success(
-            insert_recom_prompt, [prompt_gui, neg_prompt_gui, recom_prompt_gui], [prompt_gui, neg_prompt_gui], queue=False, api_visibility="undocumented",
+            insert_recom_prompt, [prompt_gui, neg_prompt_gui, recom_prompt_gui], [prompt_gui, neg_prompt_gui], queue=False, show_api=False,
         )
         
-        prompt_type_button.click(convert_danbooru_to_e621_prompt, [prompt_gui, prompt_type_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        random_character_gui.click(select_random_character, [series_dbt, character_dbt], [series_dbt, character_dbt], queue=False, api_visibility="undocumented")
+        prompt_type_button.click(convert_danbooru_to_e621_prompt, [prompt_gui, prompt_type_gui], [prompt_gui], queue=False, show_api=False)
+        random_character_gui.click(select_random_character, [series_dbt, character_dbt], [series_dbt, character_dbt], queue=False, show_api=False)
         generate_db_random_button.click(
             v2_random_prompt,
             [prompt_gui, series_dbt, character_dbt,
             rating_dbt, aspect_ratio_dbt, length_dbt, identity_dbt, ban_tags_dbt, model_name_dbt],
             [prompt_gui, series_dbt, character_dbt],
-            api_visibility="undocumented",
+            show_api=False,
         ).success(
-            convert_danbooru_to_e621_prompt, [prompt_gui, tag_type_gui], [prompt_gui], queue=False, api_visibility="undocumented",
+            convert_danbooru_to_e621_prompt, [prompt_gui, tag_type_gui], [prompt_gui], queue=False, show_api=False,
         )
 
-        translate_prompt_button.click(translate_prompt, [prompt_gui], [prompt_gui], queue=False, api_visibility="undocumented")
-        translate_prompt_button.click(translate_prompt, [character_dbt], [character_dbt], queue=False, api_visibility="undocumented")
-        translate_prompt_button.click(translate_prompt, [series_dbt], [series_dbt], queue=False, api_visibility="undocumented")
+        translate_prompt_button.click(translate_prompt, [prompt_gui], [prompt_gui], queue=False, show_api=False)
+        translate_prompt_button.click(translate_prompt, [character_dbt], [character_dbt], queue=False, show_api=False)
+        translate_prompt_button.click(translate_prompt, [series_dbt], [series_dbt], queue=False, show_api=False)
 
         generate_button.click(
             fn=insert_model_recom_prompt,
             inputs=[prompt_gui, neg_prompt_gui, model_name_gui, recom_prompt_gui],
             outputs=[prompt_gui, neg_prompt_gui],
-            api_visibility="private",
+            api_name=False,
             queue=False,
         ).success(
             fn=sd_gen.load_new_model,
@@ -1853,8 +1821,8 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
             api_name="sd_gen_generate_pipeline",
             queue=True,
             show_progress="full",
-        ).success(save_gallery_images, [result_images, model_name_gui], [result_images, result_images_files], queue=False, api_visibility="undocumented")\
-        .success(save_gallery_history, [result_images, result_images_files, history_gallery, history_files], [history_gallery, history_files], queue=False, api_visibility="undocumented")
+        ).success(save_gallery_images, [result_images, model_name_gui], [result_images, result_images_files], queue=False, show_api=False)\
+        .success(save_gallery_history, [result_images, result_images_files, history_gallery, history_files], [history_gallery, history_files], queue=False, show_api=False)
 
         with gr.Tab("Danbooru Tags Transformer with WD Tagger", render=True):
             with gr.Column(scale=2):
@@ -1893,60 +1861,60 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
                     generate_btn = gr.Button(value="GENERATE TAGS", size="lg", variant="primary")
                 with gr.Row():
                     with gr.Group():
-                        output_text = gr.TextArea(label="Output tags", interactive=False, buttons=["copy"])
+                        output_text = gr.TextArea(label="Output tags", interactive=False, show_copy_button=True)
                         with gr.Row():
                             copy_btn = gr.Button(value="Copy to clipboard", size="sm", interactive=False)
                             copy_prompt_btn = gr.Button(value="Copy to primary prompt", size="sm", interactive=False)
                     with gr.Group():
-                        output_text_pony = gr.TextArea(label="Output tags (Pony e621 style)", interactive=False, buttons=["copy"])
+                        output_text_pony = gr.TextArea(label="Output tags (Pony e621 style)", interactive=False, show_copy_button=True)
                         with gr.Row():
                             copy_btn_pony = gr.Button(value="Copy to clipboard", size="sm", interactive=False)
                             copy_prompt_btn_pony = gr.Button(value="Copy to primary prompt", size="sm", interactive=False)
                 description_ui()
 
-        translate_input_prompt_button.click(translate_prompt, inputs=[input_general], outputs=[input_general], queue=False, api_visibility="undocumented")
-        translate_input_prompt_button.click(translate_prompt, inputs=[input_character], outputs=[input_character], queue=False, api_visibility="undocumented")
-        translate_input_prompt_button.click(translate_prompt, inputs=[input_copyright], outputs=[input_copyright], queue=False, api_visibility="undocumented")
+        translate_input_prompt_button.click(translate_prompt, inputs=[input_general], outputs=[input_general], queue=False, show_api=False)
+        translate_input_prompt_button.click(translate_prompt, inputs=[input_character], outputs=[input_character], queue=False, show_api=False)
+        translate_input_prompt_button.click(translate_prompt, inputs=[input_copyright], outputs=[input_copyright], queue=False, show_api=False)
 
         generate_from_image_btn.click(
-            lambda: ("", "", ""), None, [input_copyright, input_character, input_general], queue=False, api_visibility="undocumented",
+            lambda: ("", "", ""), None, [input_copyright, input_character, input_general], queue=False, show_api=False,
         ).success(
             predict_tags_wd,
             [input_image, input_general, image_algorithms, general_threshold, character_threshold],
             [input_copyright, input_character, input_general, copy_input_btn],
-            api_visibility="undocumented",
+            show_api=False,
         ).success(
-            remove_specific_prompt, inputs=[input_general, keep_tags], outputs=[input_general], queue=False, api_visibility="undocumented",
+            remove_specific_prompt, inputs=[input_general, keep_tags], outputs=[input_general], queue=False, show_api=False,
         ).success(
-            convert_danbooru_to_e621_prompt, inputs=[input_general, input_tag_type], outputs=[input_general], queue=False, api_visibility="undocumented",
+            convert_danbooru_to_e621_prompt, inputs=[input_general, input_tag_type], outputs=[input_general], queue=False, show_api=False,
         ).success(
-            insert_recom_prompt, inputs=[input_general, dummy_np, recom_prompt], outputs=[input_general, dummy_np], queue=False, api_visibility="undocumented",
+            insert_recom_prompt, inputs=[input_general, dummy_np, recom_prompt], outputs=[input_general, dummy_np], queue=False, show_api=False,
         ).success(lambda: gr.update(interactive=True), None, [copy_prompt_btn_input], queue=False)
-        copy_input_btn.click(compose_prompt_to_copy, inputs=[input_character, input_copyright, input_general], outputs=[input_tags_to_copy], api_visibility="undocumented")\
-            .success(gradio_copy_text, inputs=[input_tags_to_copy], js=COPY_ACTION_JS, api_visibility="undocumented")
-        copy_prompt_btn_input.click(compose_prompt_to_copy, inputs=[input_character, input_copyright, input_general], outputs=[input_tags_to_copy], api_visibility="undocumented")\
-            .success(gradio_copy_prompt, inputs=[input_tags_to_copy], outputs=[prompt_gui], api_visibility="undocumented")
+        copy_input_btn.click(compose_prompt_to_copy, inputs=[input_character, input_copyright, input_general], outputs=[input_tags_to_copy], show_api=False)\
+            .success(gradio_copy_text, inputs=[input_tags_to_copy], js=COPY_ACTION_JS, show_api=False)
+        copy_prompt_btn_input.click(compose_prompt_to_copy, inputs=[input_character, input_copyright, input_general], outputs=[input_tags_to_copy], show_api=False)\
+            .success(gradio_copy_prompt, inputs=[input_tags_to_copy], outputs=[prompt_gui], show_api=False)
         
-        pick_random_character.click(select_random_character, [input_copyright, input_character], [input_copyright, input_character], api_visibility="undocumented")
+        pick_random_character.click(select_random_character, [input_copyright, input_character], [input_copyright, input_character], show_api=False)
 
         generate_btn.click(
             v2_upsampling_prompt,
             [model_name, input_copyright, input_character, input_general,
             input_rating, input_aspect_ratio, input_length, input_identity, input_ban_tags],
             [output_text],
-            api_visibility="undocumented",
+            show_api=False,
         ).success(
-            convert_danbooru_to_e621_prompt, inputs=[output_text, tag_type], outputs=[output_text_pony], queue=False, api_visibility="undocumented",
+            convert_danbooru_to_e621_prompt, inputs=[output_text, tag_type], outputs=[output_text_pony], queue=False, show_api=False,
         ).success(
-            insert_recom_prompt, inputs=[output_text, dummy_np, recom_animagine], outputs=[output_text, dummy_np], queue=False, api_visibility="undocumented",
+            insert_recom_prompt, inputs=[output_text, dummy_np, recom_animagine], outputs=[output_text, dummy_np], queue=False, show_api=False,
         ).success(
-            insert_recom_prompt, inputs=[output_text_pony, dummy_np, recom_pony], outputs=[output_text_pony, dummy_np], queue=False, api_visibility="undocumented",
+            insert_recom_prompt, inputs=[output_text_pony, dummy_np, recom_pony], outputs=[output_text_pony, dummy_np], queue=False, show_api=False,
         ).success(lambda: (gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True)),
-                   None, [copy_btn, copy_btn_pony, copy_prompt_btn, copy_prompt_btn_pony], queue=False, api_visibility="undocumented")
-        copy_btn.click(gradio_copy_text, inputs=[output_text], js=COPY_ACTION_JS, api_visibility="undocumented")
-        copy_btn_pony.click(gradio_copy_text, inputs=[output_text_pony], js=COPY_ACTION_JS, api_visibility="undocumented")
-        copy_prompt_btn.click(gradio_copy_prompt, inputs=[output_text], outputs=[prompt_gui], api_visibility="undocumented")
-        copy_prompt_btn_pony.click(gradio_copy_prompt, inputs=[output_text_pony], outputs=[prompt_gui], api_visibility="undocumented")
+                   None, [copy_btn, copy_btn_pony, copy_prompt_btn, copy_prompt_btn_pony], queue=False, show_api=False)
+        copy_btn.click(gradio_copy_text, inputs=[output_text], js=COPY_ACTION_JS, show_api=False)
+        copy_btn_pony.click(gradio_copy_text, inputs=[output_text_pony], js=COPY_ACTION_JS, show_api=False)
+        copy_prompt_btn.click(gradio_copy_prompt, inputs=[output_text], outputs=[prompt_gui], show_api=False)
+        copy_prompt_btn_pony.click(gradio_copy_prompt, inputs=[output_text_pony], outputs=[prompt_gui], show_api=False)
 
         from typing import Any, Dict, List, Optional, Tuple, Generator
         # 1) Helper: model loader (keeps existing behavior)
@@ -2284,9 +2252,10 @@ with gr.Blocks(elem_id="main", fill_width=True, fill_height=False) as app:
             yield from _generate_image(argv)
 
     # 5) Register two APIs with explicit signatures
-    gr.api(generate_image, api_name="generate_image", api_visibility="public", queue=True, concurrency_id="gpu")
-    gr.api(generate_image_stream, api_name="generate_image_stream", api_visibility="public", queue=True, concurrency_id="gpu")
+    gr.api(generate_image, api_name="generate_image", show_api=True, queue=True, concurrency_id="gpu")
+    gr.api(generate_image_stream, api_name="generate_image_stream", show_api=True, queue=True, concurrency_id="gpu")
 
+    gr.LoginButton()
     gr.DuplicateButton(value="Duplicate Space for private use (This demo does not work on CPU. Requires GPU Space)")
 
 
@@ -2299,7 +2268,5 @@ if __name__ == "__main__":
         ssr_mode=args.ssr,
         mcp_server=False,
         allowed_paths=[allowed_path],
-        theme=args.theme,
-        css=CSS,
     )
 ## END MOD

constants.py

@@ -19,7 +19,7 @@ DOWNLOAD_MODEL = "https://huggingface.co/zuv0/test/resolve/main/milkyWonderland_
 DOWNLOAD_VAE = "https://huggingface.co/Anzhc/Anzhcs-VAEs/resolve/main/SDXL%20Anime%20VAE%20Dec-only%20B3.safetensors, https://huggingface.co/fp16-guy/anything_kl-f8-anime2_vae-ft-mse-840000-ema-pruned_blessed_clearvae_fp16_cleaned/resolve/main/vae-ft-mse-840000-ema-pruned_fp16.safetensors?download=true"
 
 # - **Download LoRAs**
-DOWNLOAD_LORA = "https://huggingface.co/Leopain/color/resolve/main/Coloring_book_-_LineArt.safetensors, https://civitai.com/api/download/models/135867, https://huggingface.co/Linaqruf/anime-detailer-xl-lora/resolve/main/anime-detailer-xl.safetensors?download=true, https://huggingface.co/Linaqruf/style-enhancer-xl-lora/resolve/main/style-enhancer-xl.safetensors?download=true"
+DOWNLOAD_LORA = "https://huggingface.co/Leopain/color/resolve/main/Coloring_book_-_LineArt.safetensors, https://civitai.com/api/download/models/135867, https://huggingface.co/Linaqruf/anime-detailer-xl-lora/resolve/main/anime-detailer-xl.safetensors?download=true, https://huggingface.co/Linaqruf/style-enhancer-xl-lora/resolve/main/style-enhancer-xl.safetensors?download=true, https://huggingface.co/ByteDance/Hyper-SD/resolve/main/Hyper-SD15-8steps-CFG-lora.safetensors?download=true, https://huggingface.co/ByteDance/Hyper-SD/resolve/main/Hyper-SDXL-8steps-CFG-lora.safetensors?download=true"
 
 LOAD_DIFFUSERS_FORMAT_MODEL = [
     'TestOrganizationPleaseIgnore/potato_quality_anime_plzwork_sdxl',

env.py

@@ -30,8 +30,6 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'BlueDancer/Artisanica_XL',
     'neta-art/neta-noob-1.0',
     'OnomaAIResearch/Illustrious-xl-early-release-v0',
-    'martineux/bismuth7-xl',
-    'martineux/perfectdeliberate8',
     'Raelina/Rae-Diffusion-XL-V2',
     'Raelina/Raemu-XL-V4',
     'Raelina/Raemu-XL-V5',
@@ -47,12 +45,6 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Raelina/Raehoshi-illust-XL-7',
     'Raelina/Raehoshi-illust-XL-7.1',
     'Raelina/Raehoshi-illust-XL-8',
-    'Raelina/Raehoshi-illust-XL-8.1',
-    'Raelina/Raehoshi-illust-XL-9',
-    'Raelina/Raehoshi-illust-XL-9.1',
-    'Raelina/Raehoshi-illust-XL-10',
-    'Raelina/Raehoshi-illust-XL-11',
-    'Raelina/Raehoshi-illust-vpred',
     'camenduru/FLUX.1-dev-diffusers',
     'black-forest-labs/FLUX.1-schnell',
     'sayakpaul/FLUX.1-merged',

packages.txt

@@ -1,2 +1 @@
-git-lfs
-ffmpeg
+git-lfs aria2 ffmpeg

requirements.txt

@@ -1,23 +1,23 @@
-stablepy==0.6.5
-diffusers
-transformers>=4.47.1,<5,!=4.57.0
-accelerate
-huggingface_hub
-spaces
-torch==2.8.0
-numpy<2
-gdown
-opencv-python
-#dartrs
-git+https://github.com/John6666cat/dartrs
-translatepy
-timm
-rapidfuzz
-pandas
-safetensors
-sentencepiece
-unidecode
-matplotlib-inline
-mediapipe==0.10.13
-einops
-# pydantic==2.10.6
+stablepy==0.6.5
+diffusers
+transformers
+accelerate
+huggingface_hub
+hf_transfer
+hf_xet
+torch==2.5.1
+torchvision
+numpy<2
+gdown
+opencv-python
+optimum[onnxruntime]
+#dartrs
+git+https://github.com/John6666cat/dartrs
+translatepy
+timm
+rapidfuzz
+sentencepiece
+unidecode
+matplotlib-inline
+https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.4.11/flash_attn-2.8.3+cu124torch2.5-cp310-cp310-linux_x86_64.whl
+pydantic==2.10.6

utils.py

@@ -275,11 +275,11 @@ def civ_redirect_down(url, dir_, civitai_api_key, romanize, alternative_name):
     elif os.path.exists(os.path.join(dir_, filename_base)):
         return os.path.join(dir_, filename_base), filename_base
 
-    wget_command = (
-        f'wget -c -nv '
-        f'-O "{os.path.join(dir_, filename_base)}" "{redirect_url}"'
+    aria2_command = (
+        f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
+        f'-k 1M -s 16 -d "{dir_}" -o "{filename_base}" "{redirect_url}"'
     )
-    r_code = os.system(wget_command)  # noqa
+    r_code = os.system(aria2_command)  # noqa
 
     # if r_code != 0:
     #     raise RuntimeError(f"Failed to download file: {filename_base}. Error code: {r_code}")
@@ -293,32 +293,27 @@ def civ_redirect_down(url, dir_, civitai_api_key, romanize, alternative_name):
 
 def civ_api_down(url, dir_, civitai_api_key, civ_filename):
     """
-    This method is susceptible to being blocked because it generates a lot of temp redirect links with wget.
-    If an API key limit is reached, generating a new API key and using it can fix the issue. no
+    This method is susceptible to being blocked because it generates a lot of temp redirect links with aria2c.
+    If an API key limit is reached, generating a new API key and using it can fix the issue.
     """
     output_path = None
-    
+
     url_dl = url + f"?token={civitai_api_key}"
-    
     if not civ_filename:
-        wget_command = (
-            f'wget -c -nv '
-            f'-P "{dir_}" "{url_dl}"'
-        )
-        os.system(wget_command)
-    
+        aria2_command = f'aria2c -c -x 1 -s 1 -d "{dir_}" "{url_dl}"'
+        os.system(aria2_command)
     else:
         output_path = os.path.join(dir_, civ_filename)
-    
         if not os.path.exists(output_path):
-            wget_command = (
-                f'wget -c -nv '
-                f'-O "{output_path}" "{url_dl}"'
+            aria2_command = (
+                f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
+                f'-k 1M -s 16 -d "{dir_}" -o "{civ_filename}" "{url_dl}"'
             )
-            os.system(wget_command)
-    
+            os.system(aria2_command)
+
     return output_path
 
+
 def drive_down(url, dir_):
     import gdown
 
@@ -359,16 +354,10 @@ def hf_down(url, dir_, hf_token, romanize):
         url = url.replace("/blob/", "/resolve/")
 
     if hf_token:
-        os.system(
-            f'wget -c -nv '
-            f'--header="Authorization: Bearer {hf_token}" '
-            f'-O "{os.path.join(dir_, filename)}" "{url}"'
-        )
+        user_header = f'"Authorization: Bearer {hf_token}"'
+        os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {dir_}  -o {filename}")
     else:
-        os.system(
-            f'wget -c -nv '
-            f'-O "{os.path.join(dir_, filename)}" "{url}"'
-        )
+        os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {dir_}  -o {filename}")
 
     return output_path
 
@@ -381,8 +370,7 @@ def download_things(directory, url, hf_token="", civitai_api_key="", romanize=Fa
         downloaded_file_path = drive_down(url, directory)
     elif "huggingface.co" in url:
         downloaded_file_path = hf_down(url, directory, hf_token, romanize)
-    elif "civitai." in url:
-        url = url.replace("civitai.red", "civitai.com")
+    elif "civitai.com" in url:
         if not civitai_api_key:
             msg = "You need an API key to download Civitai models."
             print(f"\033[91m{msg}\033[0m")
@@ -405,10 +393,7 @@ def download_things(directory, url, hf_token="", civitai_api_key="", romanize=Fa
             gr.Warning(msg)
             downloaded_file_path = civ_api_down(url, directory, civitai_api_key, civ_filename)
     else:
-        os.system(
-            f'wget -c -nv '
-            f'-P "{directory}" "{url}"'
-        )
+        os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
 
     return downloaded_file_path
 
@@ -578,12 +563,7 @@ def create_mask_now(img, invert):
 
     time.sleep(0.5)
 
-    layers = (img.get("layers") or []) if isinstance(img, dict) else []
-    if not layers:
-        background = img.get("background") if isinstance(img, dict) else None
-        return background, None
-
-    transparent_image = layers[0]
+    transparent_image = img["layers"][0]
 
     # Extract the alpha channel
     alpha_channel = np.array(transparent_image)[:, :, 3]