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README.md

@@ -4,8 +4,8 @@ emoji: 🖼🖼️📦
 colorFrom: purple
 colorTo: red
 sdk: gradio
-sdk_version: 5.45.0
-python_version: "3.10"
+sdk_version: 6.17.3
+python_version: "3.12"
 app_file: app.py
 license: mit
 short_description: Text-to-Image

app.py

@@ -54,7 +54,7 @@ css = """
 .image { margin: 0px auto; object-fit: contain; }
 """
 
-with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
+with gr.Blocks(fill_width=True, elem_id="container") as demo:
     gr.Markdown("# Votepurchase Multiple Model", elem_classes="title")
     state = gr.State(value={})
     with gr.Tab("Image Generator"):
@@ -68,20 +68,19 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                 auto_trans = gr.Checkbox(label="Auto translate to English", value=False, scale=2)
 
             result = gr.Image(label="Result", elem_id="result", format="png", type="filepath", show_label=False, interactive=False,
-                              show_download_button=True, show_share_button=False, container=True)
+                              buttons=["download", "fullscreen"], container=True)
 
             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, show_share_button=False,
-                show_download_button=True)
+                history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain", format="png", interactive=False, buttons=["download", "fullscreen"])
                 history_clear_button = gr.Button(value="Clear History", variant="secondary")
-                history_clear_button.click(lambda: ([], []), None, [history_gallery, history_files], queue=False, show_api=False)
+                history_clear_button.click(lambda: ([], []), None, [history_gallery, history_files], queue=False, api_visibility="undocumented")
 
             with gr.Accordion("Advanced Settings", open=True):
                 task = gr.Dropdown(label="Task", choices=SDXL_TASK, value=TASK_MODEL_LIST[0])
                 with gr.Tab("Generation Settings"):
                     with gr.Row():
-                        negative_prompt = gr.Text(label="Negative prompt", lines=1, max_lines=6, placeholder="Enter a negative prompt", show_copy_button=True,
+                        negative_prompt = gr.Text(label="Negative prompt", lines=1, max_lines=6, placeholder="Enter a negative prompt", buttons=["copy"],
                                                 value="(low quality, worst quality:1.2), very displeasing, watermark, signature, ugly")
                     with gr.Accordion("Prompt Settings", open=False):
                         with gr.Row():
@@ -131,7 +130,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                         return gr.Slider(minimum=-val_lora, maximum=val_lora, step=0.01, value=1.0, label=label, visible=visible)
                     
                     def lora_textbox():
-                        return gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                        return gr.Textbox(label="", info="Example of prompt:", value="", buttons=["copy"], interactive=False, visible=False)
                     
                     with gr.Row():
                         with gr.Column():
@@ -204,7 +203,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                             lora_search_civitai_json = gr.JSON(value={}, visible=False)
                             lora_search_civitai_desc = gr.Markdown(value="", visible=False, elem_classes="desc")
                         with gr.Accordion("Select from Gallery", open=False):
-                            lora_search_civitai_gallery = gr.Gallery([], label="Results", allow_preview=False, columns=5, show_share_button=False, interactive=False)
+                            lora_search_civitai_gallery = gr.Gallery([], label="Results", allow_preview=False, columns=5, buttons=["download", "fullscreen"], interactive=False)
                         lora_search_civitai_result = gr.Dropdown(label="Search Results", choices=[("", "")], value="", allow_custom_value=True, visible=False)
                         lora_download_url = 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)
                         lora_download = gr.Button("Get and set LoRA and apply to prompt")
@@ -215,10 +214,10 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                         with gr.Column():
                             #image_control = gr.Image(label="Image ControlNet / Inpaint / Img2img", type="filepath", height=384, sources=["upload", "clipboard", "webcam"], show_share_button=False)
                             image_control = gr.ImageEditor(label="Image ControlNet / Inpaint / Img2img", type="filepath", sources=["upload", "clipboard", "webcam"], image_mode='RGB',
-                                                        show_share_button=False, show_fullscreen_button=False, layers=False, canvas_size=(384, 384), width=384, height=512,
+                                                        buttons=["download"], layers=False, canvas_size=(384, 384), width=384, height=512,
                                                         brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed", default_size=32), eraser=gr.Eraser(default_size="32"), elem_classes="image")
                             result_to_ic_button = gr.Button("Get image from generated result")
-                        image_mask = gr.Image(label="Image Mask", type="filepath", height=384, sources=["upload", "clipboard"], show_share_button=False, elem_classes="image")
+                        image_mask = gr.Image(label="Image Mask", type="filepath", height=384, sources=["upload", "clipboard"], buttons=["download", "fullscreen"], elem_classes="image")
                     with gr.Row():
                         strength = gr.Slider(minimum=0.01, maximum=1.0, step=0.01, value=0.55, label="Strength",
                                             info="This option adjusts the level of changes for img2img, repaint and inpaint.")
@@ -248,10 +247,10 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                             with gr.Column():
                                 #image_ip1 = gr.Image(label="IP Image", type="filepath", height=384, sources=["upload", "clipboard"], show_share_button=False)
                                 image_ip1 = gr.ImageEditor(label="IP Image", type="filepath", sources=["upload", "clipboard", "webcam"], image_mode='RGB',
-                                                        show_share_button=False, show_fullscreen_button=False, layers=False, canvas_size=(384, 384), width=384, height=512,
+                                                        buttons=["download"], layers=False, canvas_size=(384, 384), width=384, height=512,
                                                         brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed", default_size=32), eraser=gr.Eraser(default_size="32"), elem_classes="image")
                                 result_to_ip1_button = gr.Button("Get image from generated result")
-                            mask_ip1 = gr.Image(label="IP Mask (optional)", type="filepath", height=384, sources=["upload", "clipboard"], show_share_button=False, elem_classes="image")
+                            mask_ip1 = gr.Image(label="IP Mask (optional)", type="filepath", height=384, sources=["upload", "clipboard"], buttons=["download", "fullscreen"], elem_classes="image")
                         with gr.Row():
                             model_ip1 = gr.Dropdown(value="plus_face", label="Model", choices=IP_MODELS)
                             mode_ip1 = gr.Dropdown(value="original", label="Mode", choices=MODE_IP_OPTIONS)
@@ -261,10 +260,10 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                             with gr.Column():
                                 #image_ip2 = gr.Image(label="IP Image", type="filepath", height=384, sources=["upload", "clipboard"], show_share_button=False)
                                 image_ip2 = gr.ImageEditor(label="IP Image", type="filepath", sources=["upload", "clipboard", "webcam"], image_mode='RGB',
-                                                        show_share_button=False, show_fullscreen_button=False, layers=False, canvas_size=(384, 384), width=384, height=512,
+                                                        buttons=["download"], layers=False, canvas_size=(384, 384), width=384, height=512,
                                                         brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed", default_size=32), eraser=gr.Eraser(default_size="32"), elem_classes="image")
                                 result_to_ip2_button = gr.Button("Get image from generated result")
-                            mask_ip2 = gr.Image(label="IP Mask (optional)", type="filepath", height=384, sources=["upload", "clipboard"], show_share_button=False, elem_classes="image")
+                            mask_ip2 = gr.Image(label="IP Mask (optional)", type="filepath", height=384, sources=["upload", "clipboard"], buttons=["download", "fullscreen"], elem_classes="image")
                         with gr.Row():
                             model_ip2 = gr.Dropdown(value="base", label="Model", choices=IP_MODELS)
                             mode_ip2 = gr.Dropdown(value="style", label="Mode", choices=MODE_IP_OPTIONS)
@@ -275,24 +274,24 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                         with gr.Column():
                             image_base = gr.ImageEditor(sources=["upload", "clipboard", "webcam"],
                                 brush=gr.Brush(default_size="32", color_mode="fixed", colors=["rgba(0, 0, 0, 1)", "rgba(0, 0, 0, 0.1)", "rgba(255, 255, 255, 0.1)"]),
-                                eraser=gr.Eraser(default_size="32"), show_share_button=False, show_fullscreen_button=False,
+                                eraser=gr.Eraser(default_size="32"), buttons=["download"],
                                 canvas_size=(384, 384), width=384, height=512, elem_classes="image")
                             result_to_cm_button = gr.Button("Get image from generated result")
                             invert_mask = gr.Checkbox(value=False, label="Invert mask")
                             cm_btn = gr.Button("Create mask")
                         with gr.Column():
-                            img_source = gr.Image(interactive=False, height=384, show_share_button=False, elem_classes="image")
-                            img_result = gr.Image(label="Mask image", show_label=True, interactive=False, height=384, show_share_button=False, elem_classes="image")
+                            img_source = gr.Image(interactive=False, height=384, buttons=["download", "fullscreen"], elem_classes="image")
+                            img_result = gr.Image(label="Mask image", show_label=True, interactive=False, height=384, buttons=["download", "fullscreen"], elem_classes="image")
                             cm_btn_send = gr.Button("Send to ControlNet / Img2img / Inpaint")
                             with gr.Row():
                                 cm_btn_send_ip1 = gr.Button("Send to IP-Adapter 1")
                                 cm_btn_send_ip2 = gr.Button("Send to IP-Adapter 2")
-                        cm_btn.click(create_mask_now, [image_base, invert_mask], [img_source, img_result], show_api=False)
+                        cm_btn.click(create_mask_now, [image_base, invert_mask], [img_source, img_result], api_visibility="undocumented")
                         def send_img(img_source, img_result):
                             return img_source, img_result
-                        cm_btn_send.click(send_img, [img_source, img_result], [image_control, image_mask], queue=False, show_api=False)
-                        cm_btn_send_ip1.click(send_img, [img_source, img_result], [image_ip1, mask_ip1], queue=False, show_api=False)
-                        cm_btn_send_ip2.click(send_img, [img_source, img_result], [image_ip2, mask_ip2], queue=False, show_api=False)
+                        cm_btn_send.click(send_img, [img_source, img_result], [image_control, image_mask], queue=False, api_visibility="undocumented")
+                        cm_btn_send_ip1.click(send_img, [img_source, img_result], [image_ip1, mask_ip1], queue=False, api_visibility="undocumented")
+                        cm_btn_send_ip2.click(send_img, [img_source, img_result], [image_ip2, mask_ip2], queue=False, api_visibility="undocumented")
 
                 with gr.Tab("Hires fix / Detailfix / Face restoration"):
                     with gr.Accordion("Hires fix", open=True):
@@ -355,7 +354,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                             face_restoration_weight = gr.Slider(minimum=0., maximum=1., step=0.001, value=.5, label="Weight", info="(0 = maximum effect, 1 = minimum effect)")
 
                 with gr.Tab("Translation Settings"):
-                    chatbot = gr.Chatbot(type="messages", render_markdown=False, visible=False) # component for auto-translation
+                    chatbot = gr.Chatbot(render_markdown=False, visible=False) # component for auto-translation
                     chat_model = gr.Dropdown(choices=get_dolphin_models(), value=get_dolphin_models()[0], allow_custom_value=True, label="Model")
                     chat_model_info = gr.Markdown(value=get_dolphin_model_info(get_dolphin_models()[0]), label="Model info")
                     chat_format = gr.Dropdown(choices=get_llm_formats(), value=get_dolphin_model_format(get_dolphin_models()[0]), label="Message format")
@@ -382,18 +381,18 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
             cache_examples=False,
         )
 
-    model_name.change(update_task_options, [model_name, task], [task], queue=False, show_api=False)\
-    .success(update_task_options, [model_name, task_sel], [task_sel], queue=False, show_api=False)\
-    .success(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, show_api=False)
-    task_sel.select(lambda x: x, [task_sel], [task], queue=False, show_api=False)
-    task.change(change_preprocessor_choices, [task], [preprocessor_name], queue=False, show_api=False)\
-    .success(lambda x: x, [task], [task_sel], queue=False, show_api=False)
-    active_textual_inversion.change(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, show_api=False)
+    model_name.change(update_task_options, [model_name, task], [task], queue=False, api_visibility="undocumented")\
+    .success(update_task_options, [model_name, task_sel], [task_sel], queue=False, api_visibility="undocumented")\
+    .success(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, api_visibility="undocumented")
+    task_sel.select(lambda x: x, [task_sel], [task], queue=False, api_visibility="undocumented")
+    task.change(change_preprocessor_choices, [task], [preprocessor_name], queue=False, api_visibility="undocumented")\
+    .success(lambda x: x, [task], [task_sel], queue=False, api_visibility="undocumented")
+    active_textual_inversion.change(update_textual_inversion, [active_textual_inversion, model_name], [use_textual_inversion], queue=False, api_visibility="undocumented")
     use_textual_inversion.change(set_textual_inversion_prompt, [use_textual_inversion, prompt, negative_prompt, prompt_syntax], [prompt, negative_prompt])
-    result_to_cm_button.click(lambda x: x, [result], [image_base], queue=False, show_api=False)
-    result_to_ic_button.click(lambda x: x, [result], [image_control], queue=False, show_api=False)
-    result_to_ip1_button.click(lambda x: x, [result], [image_ip1], queue=False, show_api=False)
-    result_to_ip2_button.click(lambda x: x, [result], [image_ip2], queue=False, show_api=False)
+    result_to_cm_button.click(lambda x: x, [result], [image_base], queue=False, api_visibility="undocumented")
+    result_to_ic_button.click(lambda x: x, [result], [image_control], queue=False, api_visibility="undocumented")
+    result_to_ip1_button.click(lambda x: x, [result], [image_ip1], queue=False, api_visibility="undocumented")
+    result_to_ip2_button.click(lambda x: x, [result], [image_ip2], queue=False, api_visibility="undocumented")
 
     gr.on( #lambda x: None, inputs=None, outputs=result).then(
         triggers=[run_button.click, prompt.submit],
@@ -420,7 +419,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         outputs=[result],
         queue=True,
         show_progress="full",
-        show_api=True,
+        api_visibility="public",
     )
 
     gr.on( #lambda x: None, inputs=None, outputs=result).then(
@@ -447,7 +446,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                 active_textual_inversion, face_restoration_model, face_restoration_visibility, face_restoration_weight, gpu_duration, auto_trans, recom_prompt],
         outputs=[result],
         queue=False,
-        show_api=True,
+        api_visibility="public",
         api_name="infer_translate",
     ).success(
         fn=dolphin_respond_auto,
@@ -455,13 +454,13 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         outputs=[chatbot, result, prompt],
         queue=True,
         show_progress="full",
-        show_api=False,
+        api_visibility="undocumented",
     ).success(
         fn=dolphin_parse_simple,
         inputs=[prompt, chatbot, state],
         outputs=[prompt],
         queue=False,
-        show_api=False,
+        api_visibility="undocumented",
     ).success(
         fn=infer,
         inputs=[prompt, negative_prompt, seed, randomize_seed, width, height,
@@ -486,11 +485,11 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         outputs=[result],
         queue=True,
         show_progress="full",
-        show_api=False,
-    ).success(lambda: None, None, chatbot, queue=False, show_api=False)\
-    .success(pass_result, [result], [result], queue=False, show_api=False) # dummy fn for api
+        api_visibility="undocumented",
+    ).success(lambda: None, None, chatbot, queue=False, api_visibility="undocumented")\
+    .success(pass_result, [result], [result], queue=False, api_visibility="undocumented") # dummy fn for api
 
-    result.change(save_image_history, [result, history_gallery, history_files, model_name], [history_gallery, history_files], queue=False, show_api=False)
+    result.change(save_image_history, [result, history_gallery, history_files, model_name], [history_gallery, history_files], queue=False, api_visibility="undocumented")
 
     gr.on(
         triggers=[lora1.change, lora1_wt.change, lora2.change, lora2_wt.change, lora3.change, lora3_wt.change,
@@ -503,15 +502,15 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                  lora6, lora6_wt, lora6_info, lora6_copy, lora6_md, lora7, lora7_wt, lora7_info, lora7_copy, lora7_md],
         queue=False,
         trigger_mode="once",
-        show_api=False,
+        api_visibility="undocumented",
     )
-    lora1_copy.click(apply_lora_prompt, [prompt, lora1_info], [prompt], queue=False, show_api=False)
-    lora2_copy.click(apply_lora_prompt, [prompt, lora2_info], [prompt], queue=False, show_api=False)
-    lora3_copy.click(apply_lora_prompt, [prompt, lora3_info], [prompt], queue=False, show_api=False)
-    lora4_copy.click(apply_lora_prompt, [prompt, lora4_info], [prompt], queue=False, show_api=False)
-    lora5_copy.click(apply_lora_prompt, [prompt, lora5_info], [prompt], queue=False, show_api=False)
-    lora6_copy.click(apply_lora_prompt, [prompt, lora6_info], [prompt], queue=False, show_api=False)
-    lora7_copy.click(apply_lora_prompt, [prompt, lora7_info], [prompt], queue=False, show_api=False)
+    lora1_copy.click(apply_lora_prompt, [prompt, lora1_info], [prompt], queue=False, api_visibility="undocumented")
+    lora2_copy.click(apply_lora_prompt, [prompt, lora2_info], [prompt], queue=False, api_visibility="undocumented")
+    lora3_copy.click(apply_lora_prompt, [prompt, lora3_info], [prompt], queue=False, api_visibility="undocumented")
+    lora4_copy.click(apply_lora_prompt, [prompt, lora4_info], [prompt], queue=False, api_visibility="undocumented")
+    lora5_copy.click(apply_lora_prompt, [prompt, lora5_info], [prompt], queue=False, api_visibility="undocumented")
+    lora6_copy.click(apply_lora_prompt, [prompt, lora6_info], [prompt], queue=False, api_visibility="undocumented")
+    lora7_copy.click(apply_lora_prompt, [prompt, lora7_info], [prompt], queue=False, api_visibility="undocumented")
 
     gr.on(
         triggers=[lora_search_civitai_submit.click, lora_search_civitai_query.submit],
@@ -520,10 +519,10 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         outputs=[lora_search_civitai_result, lora_search_civitai_desc, lora_search_civitai_submit, lora_search_civitai_query, lora_search_civitai_gallery],
         scroll_to_output=True,
         queue=True,
-        show_api=False,
+        api_visibility="undocumented",
     )
-    lora_search_civitai_json.change(search_civitai_lora_json, [lora_search_civitai_query, lora_search_civitai_basemodel], [lora_search_civitai_json], queue=True, show_api=True)  # fn for api
-    lora_search_civitai_result.change(select_civitai_lora, [lora_search_civitai_result], [lora_download_url, lora_search_civitai_desc], scroll_to_output=True, queue=False, show_api=False)
+    lora_search_civitai_json.change(search_civitai_lora_json, [lora_search_civitai_query, lora_search_civitai_basemodel], [lora_search_civitai_json], queue=True, api_visibility="public")  # fn for api
+    lora_search_civitai_result.change(select_civitai_lora, [lora_search_civitai_result], [lora_download_url, lora_search_civitai_desc], scroll_to_output=True, queue=False, api_visibility="undocumented")
     gr.on(
         triggers=[lora_download.click, lora_download_url.submit],
         fn=download_my_lora,
@@ -531,9 +530,9 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         outputs=[lora1, lora2, lora3, lora4, lora5, lora6, lora7],
         scroll_to_output=True,
         queue=True,
-        show_api=False,
+        api_visibility="undocumented",
     )
-    lora_search_civitai_gallery.select(update_civitai_selection, None, [lora_search_civitai_result], queue=False, show_api=False)
+    lora_search_civitai_gallery.select(update_civitai_selection, None, [lora_search_civitai_result], queue=False, api_visibility="undocumented")
 
     #recom_prompt.change(enable_model_recom_prompt, [recom_prompt], [recom_prompt], queue=False, show_api=False)
     gr.on(
@@ -543,18 +542,18 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
         outputs=[prompt, negative_prompt],
         queue=False,
         trigger_mode="once",
-        show_api=False,
+        api_visibility="undocumented",
     )
 
-    model_detail.change(enable_diffusers_model_detail, [model_detail, model_name, state], [model_detail, model_name, state], queue=False, show_api=False)
-    model_name.change(get_t2i_model_info, [model_name], [model_info], queue=False, show_api=False)
+    model_detail.change(enable_diffusers_model_detail, [model_detail, model_name, state], [model_detail, model_name, state], queue=False, api_visibility="undocumented")
+    model_name.change(get_t2i_model_info, [model_name], [model_info], queue=False, api_visibility="undocumented")
 
-    chat_model.change(select_dolphin_model, [chat_model, state], [chat_model, chat_format, chat_model_info, state], queue=True, show_progress="full", show_api=False)\
-    .success(lambda: None, None, chatbot, queue=False, show_api=False)
-    chat_format.change(select_dolphin_format, [chat_format, state], [chat_format, state], queue=False, show_api=False)\
-    .success(lambda: None, None, chatbot, queue=False, show_api=False)
+    chat_model.change(select_dolphin_model, [chat_model, state], [chat_model, chat_format, chat_model_info, state], queue=True, show_progress="full", api_visibility="undocumented")\
+    .success(lambda: None, None, chatbot, queue=False, api_visibility="undocumented")
+    chat_format.change(select_dolphin_format, [chat_format, state], [chat_format, state], queue=False, api_visibility="undocumented")\
+    .success(lambda: None, None, chatbot, queue=False, api_visibility="undocumented")
     chat_lora.change(select_dolphin_lora, [chat_lora, state], [chat_lora, state], queue=True, show_progress="full")\
-    .success(lambda: None, None, chatbot, queue=False, show_api=False)
+    .success(lambda: None, None, chatbot, queue=False, api_visibility="undocumented")
 
     # Tagger
     with gr.Tab("Tags Transformer with Tagger"):
@@ -594,61 +593,61 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                     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, show_copy_button=True)
+                        output_text = gr.TextArea(label="Output tags", interactive=False, buttons=["copy"])
                         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, show_copy_button=True)
+                        output_text_pony = gr.TextArea(label="Output tags (Pony e621 style)", interactive=False, buttons=["copy"])
                         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)
 
-        random_character.click(select_random_character, [input_copyright, input_character], [input_copyright, input_character], queue=False, show_api=False)
+        random_character.click(select_random_character, [input_copyright, input_character], [input_copyright, input_character], queue=False, api_visibility="undocumented")
 
-        translate_input_prompt_button.click(translate_prompt, [input_general], [input_general], queue=False, show_api=False)
-        translate_input_prompt_button.click(translate_prompt, [input_character], [input_character], queue=False, show_api=False)
-        translate_input_prompt_button.click(translate_prompt, [input_copyright], [input_copyright], queue=False, show_api=False)
+        translate_input_prompt_button.click(translate_prompt, [input_general], [input_general], queue=False, api_visibility="undocumented")
+        translate_input_prompt_button.click(translate_prompt, [input_character], [input_character], queue=False, api_visibility="undocumented")
+        translate_input_prompt_button.click(translate_prompt, [input_copyright], [input_copyright], queue=False, api_visibility="undocumented")
 
         generate_from_image_btn.click(
-            lambda: ("", "", ""), None, [input_copyright, input_character, input_general], queue=False, show_api=False,
+            lambda: ("", "", ""), None, [input_copyright, input_character, input_general], queue=False, api_visibility="undocumented",
         ).success(
             predict_tags_wd,
             [input_image, input_general, image_algorithms, general_threshold, character_threshold],
             [input_copyright, input_character, input_general, copy_input_btn],
-            show_api=False,
+            api_visibility="undocumented",
         ).success(
-            predict_tags_fl2_sd3, [input_image, input_general, image_algorithms], [input_general], show_api=False,
+            predict_tags_fl2_sd3, [input_image, input_general, image_algorithms], [input_general], api_visibility="undocumented",
         ).success(
-            remove_specific_prompt, [input_general, keep_tags], [input_general], queue=False, show_api=False,
+            remove_specific_prompt, [input_general, keep_tags], [input_general], queue=False, api_visibility="undocumented",
         ).success(
-            convert_danbooru_to_e621_prompt, [input_general, input_tag_type], [input_general], queue=False, show_api=False,
+            convert_danbooru_to_e621_prompt, [input_general, input_tag_type], [input_general], queue=False, api_visibility="undocumented",
         ).success(
-            insert_recom_prompt, [input_general, dummy_np, recom_prompt], [input_general, dummy_np], queue=False, show_api=False,
-        ).success(lambda: gr.update(interactive=True), None, [copy_prompt_btn_input], queue=False, show_api=False)
-        copy_input_btn.click(compose_prompt_to_copy, [input_character, input_copyright, input_general], [input_tags_to_copy], show_api=False)\
-            .success(gradio_copy_text, [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], show_api=False)
+            insert_recom_prompt, [input_general, dummy_np, recom_prompt], [input_general, dummy_np], queue=False, api_visibility="undocumented",
+        ).success(lambda: gr.update(interactive=True), None, [copy_prompt_btn_input], queue=False, api_visibility="undocumented")
+        copy_input_btn.click(compose_prompt_to_copy, [input_character, input_copyright, input_general], [input_tags_to_copy], api_visibility="undocumented")\
+            .success(gradio_copy_text, [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], api_visibility="undocumented")
         
         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],
-            show_api=False,
+            api_visibility="undocumented",
         ).success(
-            convert_danbooru_to_e621_prompt, [output_text, tag_type], [output_text_pony], queue=False, show_api=False,
+            convert_danbooru_to_e621_prompt, [output_text, tag_type], [output_text_pony], queue=False, api_visibility="undocumented",
         ).success(
-            insert_recom_prompt, [output_text, dummy_np, recom_animagine], [output_text, dummy_np], queue=False, show_api=False,
+            insert_recom_prompt, [output_text, dummy_np, recom_animagine], [output_text, dummy_np], queue=False, api_visibility="undocumented",
         ).success(
-            insert_recom_prompt, [output_text_pony, dummy_np, recom_pony], [output_text_pony, dummy_np], queue=False, show_api=False,
+            insert_recom_prompt, [output_text_pony, dummy_np, recom_pony], [output_text_pony, dummy_np], queue=False, api_visibility="undocumented",
         ).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, show_api=False)
-        copy_btn.click(gradio_copy_text, [output_text], js=COPY_ACTION_JS, show_api=False)
-        copy_btn_pony.click(gradio_copy_text, [output_text_pony], js=COPY_ACTION_JS, show_api=False)
-        copy_prompt_btn.click(gradio_copy_prompt, inputs=[output_text], outputs=[prompt], show_api=False)
-        copy_prompt_btn_pony.click(gradio_copy_prompt, inputs=[output_text_pony], outputs=[prompt], show_api=False)
+                  None, [copy_btn, copy_btn_pony, copy_prompt_btn, copy_prompt_btn_pony], queue=False, api_visibility="undocumented")
+        copy_btn.click(gradio_copy_text, [output_text], js=COPY_ACTION_JS, api_visibility="undocumented")
+        copy_btn_pony.click(gradio_copy_text, [output_text_pony], js=COPY_ACTION_JS, api_visibility="undocumented")
+        copy_prompt_btn.click(gradio_copy_prompt, inputs=[output_text], outputs=[prompt], api_visibility="undocumented")
+        copy_prompt_btn_pony.click(gradio_copy_prompt, inputs=[output_text_pony], outputs=[prompt], api_visibility="undocumented")
 
     with gr.Tab("PNG Info"):
         with gr.Row():
@@ -656,7 +655,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
                 image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
 
             with gr.Column():
-                result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
+                result_metadata = gr.Textbox(label="Metadata", show_label=True, buttons=["copy"], interactive=False, container=True, max_lines=99)
 
                 image_metadata.change(
                     fn=extract_exif_data,
@@ -687,4 +686,4 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
 
 if __name__ == "__main__":
     demo.queue()
-    demo.launch(show_error=True, share=False, debug=True, ssr_mode=False, mcp_server=False)
+    demo.launch(show_error=True, share=False, debug=True, ssr_mode=False, mcp_server=False, css=css)

env.py

@@ -80,6 +80,8 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     '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',

modutils.py

@@ -218,6 +218,8 @@ CIVITAI_RESOLVE_NEGATIVE_CACHE: dict[str, str] = {}
 CIVITAI_VERSION_JSON_CACHE: dict[str, dict] = {}
 CIVITAI_VERSION_NEGATIVE_CACHE: dict[str, str] = {}
 CIVITAI_WGET_FRESH_RETRY_LIMIT = 1
+CIVITAI_METADATA_RECONNECT_ATTEMPTS = 3
+CIVITAI_METADATA_RECONNECT_BACKOFF = 0.8
 CIVITAI_API_PROBE_TIMEOUT = (3.0, 8.0)
 CIVITAI_API_RETRYABLE_STATUSES = frozenset([404, 405, 429, 500, 502, 503, 504])
 CIVITAI_ACTIVE_API_ORIGIN = ""
@@ -492,6 +494,20 @@ def extract_civitai_model_version_id(url: str):
         return ""
     return ""
 
+def extract_civitai_file_id(url: str):
+    try:
+        parts = get_civitai_url_parts(url)
+        qs = urllib.parse.parse_qs(parts.query)
+        for key, values in qs.items():
+            if str(key).casefold() != "fileid" or not values:
+                continue
+            value = str(values[0] or "").strip()
+            if value.isdigit():
+                return value
+    except Exception:
+        return ""
+    return ""
+
 def get_civitai_query_filters(url: str):
     try:
         parts = get_civitai_url_parts(url)
@@ -706,6 +722,16 @@ def pick_civitai_file_from_version_json(json_data, source_url: str = ""):
     files = json_data.get("files", []) if isinstance(json_data, dict) else []
     if not isinstance(files, list) or not files:
         return {}
+    explicit_file_id = extract_civitai_file_id(source_url)
+    if explicit_file_id:
+        for file_info in files:
+            if not isinstance(file_info, dict):
+                continue
+            candidate_id = str(file_info.get("id") or file_info.get("fileId") or "").strip()
+            if candidate_id == explicit_file_id:
+                return dict(file_info)
+        print(f"[civitai] explicit fileId={explicit_file_id} not present in model version metadata")
+        return {}
     version_id = str((json_data or {}).get("id") or "")
     filters = get_civitai_query_filters(source_url)
     candidates = []
@@ -786,41 +812,61 @@ def request_json_data(url, api_key: str = ""):
         return None
 
     endpoint_path = f"/model-versions/{model_version_id}"
-    headers = get_civitai_headers(effective_api_key)
-    session = create_retry_session()
+    last_error = None
+    for attempt in range(1, CIVITAI_METADATA_RECONNECT_ATTEMPTS + 1):
+        session = create_retry_session()
+        headers = get_civitai_headers(effective_api_key)
+        if attempt > 1:
+            headers["Connection"] = "close"
+        endpoint_url = ""
+        try:
+            json_data, endpoint_url, result = request_civitai_api_json(
+                endpoint_path,
+                headers=headers,
+                timeout=CIVITAI_METADATA_TIMEOUT,
+                api_key=effective_api_key,
+                session=session,
+                stream=True,
+                allow_not_found=True,
+            )
+            if result.status_code == 404:
+                print(f"Civitai metadata lookup status=404: {endpoint_url}")
+                cache_put(CIVITAI_VERSION_NEGATIVE_CACHE, model_version_id, "status=404")
+                return None
+            if not json_data:
+                print(f"Civitai metadata lookup returned empty JSON: {endpoint_url}")
+                cache_put(CIVITAI_VERSION_NEGATIVE_CACHE, model_version_id, "empty_json")
+                return None
+            cache_put(CIVITAI_VERSION_JSON_CACHE, model_version_id, copy.deepcopy(json_data))
+            if normalized_url and normalized_url != raw_url:
+                cache_put(CIVITAI_RESOLVE_CACHE, raw_url, normalized_url)
+            return json_data
+        except Exception as e:
+            last_error = e
+            print(
+                f"[civitai] metadata reconnect attempt={attempt}/{CIVITAI_METADATA_RECONNECT_ATTEMPTS} "
+                f"url={sanitize_url_for_log(endpoint_url or endpoint_path)} "
+                f"error={type(e).__name__}: {sanitize_sensitive_log_text(e)}"
+            )
+        finally:
+            try:
+                session.close()
+            except Exception:
+                pass
+        if attempt < CIVITAI_METADATA_RECONNECT_ATTEMPTS:
+            time.sleep(min(2.5, CIVITAI_METADATA_RECONNECT_BACKOFF * attempt))
 
-    try:
-        json_data, endpoint_url, result = request_civitai_api_json(
-            endpoint_path,
-            headers=headers,
-            timeout=CIVITAI_METADATA_TIMEOUT,
-            api_key=effective_api_key,
-            session=session,
-            stream=True,
-            allow_not_found=True,
-        )
-        if result.status_code == 404:
-            print(f"Civitai metadata lookup status=404: {endpoint_url}")
-            cache_put(CIVITAI_VERSION_NEGATIVE_CACHE, model_version_id, "status=404")
-            return None
-        if not json_data:
-            print(f"Civitai metadata lookup returned empty JSON: {endpoint_url}")
-            cache_put(CIVITAI_VERSION_NEGATIVE_CACHE, model_version_id, "empty_json")
-            return None
-        cache_put(CIVITAI_VERSION_JSON_CACHE, model_version_id, copy.deepcopy(json_data))
-        if normalized_url and normalized_url != raw_url:
-            cache_put(CIVITAI_RESOLVE_CACHE, raw_url, normalized_url)
-        return json_data
-    except Exception as e:
-        print(f"Civitai metadata lookup failed: {endpoint_url} {type(e).__name__}: {sanitize_sensitive_log_text(e)}")
-        return None
+    if last_error is not None:
+        print(f"Civitai metadata lookup failed after reconnects: {type(last_error).__name__}: {sanitize_sensitive_log_text(last_error)}")
+    return None
 
 class ModelInformation:
     def __init__(self, json_data, source_url: str = ""):
         selected_file = pick_civitai_file_from_version_json(json_data, source_url=source_url)
+        explicit_file_id = extract_civitai_file_id(source_url)
         self.model_version_id = json_data.get("id", "")
         self.model_id = json_data.get("modelId", "")
-        self.download_url = selected_file.get("downloadUrl", "") or json_data.get("downloadUrl", "")
+        self.download_url = selected_file.get("downloadUrl", "") or ("" if explicit_file_id else json_data.get("downloadUrl", ""))
         self.model_url = f"{get_civitai_canonical_web_origin()}/models/{self.model_id}?modelVersionId={self.model_version_id}"
         self.filename_url = selected_file.get("name", "") or ""
         self.description = json_data.get("description", "")
@@ -1005,7 +1051,41 @@ def guess_downloaded_file_path(directory, before_files, expected_filename=""):
 
     return None
 
-def get_existing_completed_download_path(directory, expected_filename=""):
+def get_civitai_expected_size_bytes(file_info):
+    if not isinstance(file_info, dict):
+        return 0
+    raw_size_kb = file_info.get("sizeKB")
+    if raw_size_kb is None:
+        raw_size_kb = file_info.get("sizeKb")
+    try:
+        size_kb = float(raw_size_kb)
+    except (TypeError, ValueError):
+        return 0
+    if size_kb <= 0:
+        return 0
+    return max(1, int(round(size_kb * 1024.0)))
+
+def is_civitai_file_complete(path, file_info=None, *, log_mismatch=False):
+    candidate = Path(path)
+    if not candidate.exists() or not candidate.is_file():
+        return False
+    expected_size = get_civitai_expected_size_bytes(file_info)
+    if expected_size <= 0:
+        return True
+    try:
+        actual_size = int(candidate.stat().st_size)
+    except OSError:
+        return False
+    tolerance = 4096
+    complete = abs(actual_size - expected_size) <= tolerance
+    if not complete and log_mismatch:
+        print(
+            f"[civitai] existing file size mismatch; treating as incomplete "
+            f"path={candidate} actual={actual_size} expected={expected_size}"
+        )
+    return complete
+
+def get_existing_completed_download_path(directory, expected_filename="", file_info=None):
     expected_name = str(expected_filename or "").strip()
     if not expected_name:
         return ""
@@ -1021,7 +1101,7 @@ def get_existing_completed_download_path(directory, expected_filename=""):
             candidate_paths.append(legacy_nested_path)
 
     for candidate_path in candidate_paths:
-        if candidate_path.exists() and candidate_path.is_file():
+        if is_civitai_file_complete(candidate_path, file_info=file_info, log_mismatch=True):
             return str(candidate_path)
 
     return ""
@@ -1064,6 +1144,7 @@ def download_things(directory, url, hf_token="", civitai_api_key="", romanize=Fa
         if normalized_url != url:
             print(f"Civitai download URL normalized: {sanitize_url_for_log(url)} -> {sanitize_url_for_log(normalized_url)}")
         model_profile = retrieve_model_info(normalized_url, api_key=civitai_api_key)
+        selected_file = model_profile.selected_file if model_profile else {}
         if model_profile and model_profile.download_url:
             url = model_profile.download_url
             filename = model_profile.filename_url or ""
@@ -1087,7 +1168,7 @@ def download_things(directory, url, hf_token="", civitai_api_key="", romanize=Fa
         print(f"Filename: {filename}")
         print(f"[civitai] resolved signed host={signed_host or '-'} url={sanitize_url_for_log(url)}")
 
-        existing_completed_path = get_existing_completed_download_path(directory, expected_filename=filename)
+        existing_completed_path = get_existing_completed_download_path(directory, expected_filename=filename, file_info=selected_file)
         if existing_completed_path:
             print(f"[civitai] using existing completed file path={existing_completed_path}")
             downloaded_file_path = existing_completed_path
@@ -1139,10 +1220,14 @@ def download_things(directory, url, hf_token="", civitai_api_key="", romanize=Fa
             if download_status != 0:
                 log_download_error("civitai", "command_failed", url=url, status=download_status)
 
+        if not downloaded_file_path and download_status == 0:
+            candidate_path = guess_downloaded_file_path(directory, before_files, expected_filename=filename)
+            if candidate_path and is_civitai_file_complete(candidate_path, file_info=selected_file, log_mismatch=True):
+                downloaded_file_path = candidate_path
+            elif candidate_path:
+                log_download_error("civitai", "size_mismatch", url=url, detail=f"path={candidate_path}")
         if not downloaded_file_path:
-            downloaded_file_path = guess_downloaded_file_path(directory, before_files, expected_filename=filename)
-        if not downloaded_file_path:
-            existing_completed_path = get_existing_completed_download_path(directory, expected_filename=filename)
+            existing_completed_path = get_existing_completed_download_path(directory, expected_filename=filename, file_info=selected_file)
             if existing_completed_path:
                 print(f"[civitai] using existing completed file path={existing_completed_path}")
                 downloaded_file_path = existing_completed_path
@@ -1773,7 +1858,6 @@ def get_lora_info(lora_path: str):
     label = ""
     md = "None"
     if not lora_path or lora_path == "None":
-        print("LoRA file not found.")
         return is_valid, label, tag, md
     path = Path(lora_path)
     new_path = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')

requirements.txt

@@ -1,6 +1,6 @@
 stablepy==0.6.5
 diffusers
-transformers
+transformers>=4.47.1,<5,!=4.57.0
 accelerate
 torch==2.8.0
 numpy<2
@@ -8,12 +8,11 @@ gdown
 opencv-python
 huggingface_hub
 spaces
-scikit-build-core
-https://github.com/John6666cat/llama-cpp-python/releases/download/v0.3.35-cu128-Basic-linux-20260412/llama_cpp_python-0.3.35+cu128.basic-cp310-cp310-linux_x86_64.whl
+https://github.com/JamePeng/llama-cpp-python/releases/download/v0.3.46-cu128-linux-20260808/llama_cpp_python-0.3.46+cu128-cp312-cp312-linux_x86_64.whl
 git+https://github.com/John6666cat/llama-cpp-agent
-pybind11>=2.12
 rapidfuzz
-optimum[onnxruntime]
+pandas
+safetensors
 #dartrs
 git+https://github.com/John6666cat/dartrs
 translatepy
@@ -22,6 +21,6 @@ wrapt-timeout-decorator
 sentencepiece
 unidecode
 matplotlib-inline
-mediapipe==0.10.5
+mediapipe==0.10.13
 einops
 # pydantic==2.10.6