Upload app.py

app.py

@@ -120,77 +120,81 @@ with gr.Blocks(css=css, fill_width=True, elem_id="container") as demo:
                         value=28,
                     )
 
-                with gr.Group():
-                    model_name = gr.Dropdown(label="Model", info="You can enter a huggingface model repo_id to want to use.", choices=get_diffusers_model_list(), value=get_diffusers_model_list()[0], allow_custom_value=True, interactive=True)
-                    model_info = gr.Markdown(elem_id="model-info")
-                    model_detail = gr.Checkbox(label="Show detail of model in list", value=False)
+                with gr.Row():
+                    with gr.Group():
+                        model_name = gr.Dropdown(label="Model", info="You can enter a huggingface model repo_id to want to use.", choices=get_diffusers_model_list(), value=get_diffusers_model_list()[0], allow_custom_value=True, interactive=True)
+                        model_info = gr.Markdown(elem_id="model-info")
+                        model_detail = gr.Checkbox(label="Show detail of model in list", value=False)
 
-                sampler = gr.Dropdown(label="Sampler", choices=get_samplers(), value="Euler a")
+                with gr.Row():
+                    sampler = gr.Dropdown(label="Sampler", choices=get_samplers(), value="Euler a")
+                    vae_model = gr.Dropdown(label="VAE Model", choices=get_vaes(), value=get_vaes()[0])
 
-                chatbot = gr.Chatbot(likeable=False, render_markdown=False, visible=False) # component for auto-translation
+                with gr.Row():
+                    with gr.Accordion("LoRA", open=True, visible=True):
+                        with gr.Group():
+                            lora1 = gr.Dropdown(label="LoRA 1", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
+                            lora1_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 1: weight")
+                            with gr.Row():
+                                lora1_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                                lora1_copy = gr.Button(value="Copy example to prompt", visible=False)
+                            lora1_md = gr.Markdown(value="", visible=False)
+                        with gr.Group():
+                            lora2 = gr.Dropdown(label="LoRA 2", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
+                            lora2_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 2: weight")
+                            with gr.Row():
+                                lora2_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                                lora2_copy = gr.Button(value="Copy example to prompt", visible=False)
+                            lora2_md = gr.Markdown(value="", visible=False)
+                        with gr.Group():
+                            lora3 = gr.Dropdown(label="LoRA 3", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
+                            lora3_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 3: weight")
+                            with gr.Row():
+                                lora3_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                                lora3_copy = gr.Button(value="Copy example to prompt", visible=False)
+                            lora3_md = gr.Markdown(value="", visible=False)
+                        with gr.Group():
+                            lora4 = gr.Dropdown(label="LoRA 4", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
+                            lora4_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 4: weight")
+                            with gr.Row():
+                                lora4_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                                lora4_copy = gr.Button(value="Copy example to prompt", visible=False)
+                            lora4_md = gr.Markdown(value="", visible=False)
+                        with gr.Group():
+                            lora5 = gr.Dropdown(label="LoRA 5", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
+                            lora5_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 5: weight")
+                            with gr.Row():
+                                lora5_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                                lora5_copy = gr.Button(value="Copy example to prompt", visible=False)
+                            lora5_md = gr.Markdown(value="", visible=False)
+                        with gr.Accordion("From URL", open=True, visible=True):
+                            with gr.Row():
+                                lora_search_civitai_query = gr.Textbox(label="Query", placeholder="oomuro sakurako...", lines=1)
+                                lora_search_civitai_basemodel = gr.CheckboxGroup(label="Search LoRA for", choices=["Pony", "SD 1.5", "SDXL 1.0"], value=["Pony", "SDXL 1.0"])
+                                lora_search_civitai_submit = gr.Button("Search on Civitai")
+                            lora_search_civitai_result = gr.Dropdown(label="Search Results", choices=[("", "")], value="", allow_custom_value=True, visible=False)
+                            lora_search_civitai_json = gr.JSON(value={}, visible=False)
+                            lora_search_civitai_desc = gr.Markdown(value="", visible=False)
+                            lora_download_url = gr.Textbox(label="URL", placeholder="http://...my_lora_url.safetensors", lines=1)
+                            lora_download = gr.Button("Get and set LoRA and apply to prompt")
 
-                with gr.Accordion("LoRA", open=True, visible=True):
-                    with gr.Group():
-                        lora1 = gr.Dropdown(label="LoRA 1", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
-                        lora1_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 1: weight")
-                        with gr.Row():
-                            lora1_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
-                            lora1_copy = gr.Button(value="Copy example to prompt", visible=False)
-                        lora1_md = gr.Markdown(value="", visible=False)
-                    with gr.Group():
-                        lora2 = gr.Dropdown(label="LoRA 2", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
-                        lora2_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 2: weight")
-                        with gr.Row():
-                            lora2_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
-                            lora2_copy = gr.Button(value="Copy example to prompt", visible=False)
-                        lora2_md = gr.Markdown(value="", visible=False)
-                    with gr.Group():
-                        lora3 = gr.Dropdown(label="LoRA 3", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
-                        lora3_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 3: weight")
-                        with gr.Row():
-                            lora3_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
-                            lora3_copy = gr.Button(value="Copy example to prompt", visible=False)
-                        lora3_md = gr.Markdown(value="", visible=False)
-                    with gr.Group():
-                        lora4 = gr.Dropdown(label="LoRA 4", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
-                        lora4_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 4: weight")
-                        with gr.Row():
-                            lora4_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
-                            lora4_copy = gr.Button(value="Copy example to prompt", visible=False)
-                        lora4_md = gr.Markdown(value="", visible=False)
-                    with gr.Group():
-                        lora5 = gr.Dropdown(label="LoRA 5", choices=get_all_lora_tupled_list(), value="", allow_custom_value=True)
-                        lora5_wt = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA 5: weight")
-                        with gr.Row():
-                            lora5_info = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
-                            lora5_copy = gr.Button(value="Copy example to prompt", visible=False)
-                        lora5_md = gr.Markdown(value="", visible=False)
-                    with gr.Accordion("From URL", open=True, visible=True):
-                        with gr.Row():
-                            lora_search_civitai_query = gr.Textbox(label="Query", placeholder="oomuro sakurako...", lines=1)
-                            lora_search_civitai_basemodel = gr.CheckboxGroup(label="Search LoRA for", choices=["Pony", "SD 1.5", "SDXL 1.0"], value=["Pony", "SDXL 1.0"])
-                            lora_search_civitai_submit = gr.Button("Search on Civitai")
-                        lora_search_civitai_result = gr.Dropdown(label="Search Results", choices=[("", "")], value="", allow_custom_value=True, visible=False)
-                        lora_search_civitai_json = gr.JSON(value={}, visible=False)
-                        lora_search_civitai_desc = gr.Markdown(value="", visible=False)
-                        lora_download_url = gr.Textbox(label="URL", placeholder="http://...my_lora_url.safetensors", lines=1)
-                        lora_download = gr.Button("Get and set LoRA and apply to prompt")
-                
-                vae_model = gr.Dropdown(label="VAE Model", choices=get_vaes(), value=get_vaes()[0])
-                recom_prompt = gr.Checkbox(label="Recommended prompt", value=True)
-                quality_selector = gr.Radio(label="Quality Tag Presets", interactive=True, choices=list(preset_quality.keys()), value="None")
-                style_selector = gr.Radio(label="Style Presets", interactive=True, choices=list(preset_styles.keys()), value="None")
-
-                with gr.Accordion("Translation Settings", open=False):
-                    chat_model = gr.Dropdown(choices=get_dolphin_models(), value=get_dolphin_models()[0][1], allow_custom_value=True, label="Model")
-                    chat_model_info = gr.Markdown(value=get_dolphin_model_info(get_dolphin_models()[0][1]), label="Model info")
-                    chat_format = gr.Dropdown(choices=get_llm_formats(), value=get_dolphin_model_format(get_dolphin_models()[0][1]), label="Message format")
-                    chat_sysmsg = gr.Textbox(value=get_dolphin_sysprompt(), label="System message")
-                    chat_tokens = gr.Slider(minimum=1, maximum=4096, value=512, step=1, label="Max tokens")
-                    chat_temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
-                    chat_topp = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
-                    chat_topk = gr.Slider(minimum=0, maximum=100, value=40, step=1, label="Top-k")
-                    chat_rp = gr.Slider(minimum=0.0, maximum=2.0, value=1.1, step=0.1, label="Repetition penalty")
+                with gr.Row():
+                    recom_prompt = gr.Checkbox(label="Recommended prompt", value=True)
+                    quality_selector = gr.Radio(label="Quality Tag Presets", interactive=True, choices=list(preset_quality.keys()), value="None")
+                    style_selector = gr.Radio(label="Style Presets", interactive=True, choices=list(preset_styles.keys()), value="None")
+
+                with gr.Row():
+                    with gr.Accordion("Translation Settings", open=False):
+                        chatbot = gr.Chatbot(likeable=False, render_markdown=False, visible=False) # component for auto-translation
+                        chat_model = gr.Dropdown(choices=get_dolphin_models(), value=get_dolphin_models()[0][1], allow_custom_value=True, label="Model")
+                        chat_model_info = gr.Markdown(value=get_dolphin_model_info(get_dolphin_models()[0][1]), label="Model info")
+                        chat_format = gr.Dropdown(choices=get_llm_formats(), value=get_dolphin_model_format(get_dolphin_models()[0][1]), label="Message format")
+                        chat_sysmsg = gr.Textbox(value=get_dolphin_sysprompt(), label="System message")
+                        chat_tokens = gr.Slider(minimum=1, maximum=4096, value=512, step=1, label="Max tokens")
+                        chat_temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+                        chat_topp = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
+                        chat_topk = gr.Slider(minimum=0, maximum=100, value=40, step=1, label="Top-k")
+                        chat_rp = gr.Slider(minimum=0.0, maximum=2.0, value=1.1, step=0.1, label="Repetition penalty")
 
             examples = gr.Examples(
                 examples = [