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README.md

@@ -4,9 +4,9 @@ emoji: 🏆😻
 colorFrom: red
 colorTo: pink
 sdk: gradio
-sdk_version: 4.40.0
+sdk_version: 4.41.0
 app_file: app.py
-pinned: false
+pinned: true
 license: mit
 duplicated_from:
 - multimodalart/flux-lora-the-explorer

app.py

@@ -365,26 +365,28 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css) as app:
                             lora_copy = [None] * num_loras
                             lora_md = [None] * num_loras
                             lora_num = [None] * num_loras
-                            for i in range(num_loras):
-                                with gr.Group():
-                                    with gr.Row():
-                                        lora_repo[i] = gr.Dropdown(label=f"LoRA {int(i+1)} Repo", choices=get_all_lora_tupled_list(), info="Input LoRA Repo ID", value="", allow_custom_value=True)
-                                        lora_weights[i] = gr.Dropdown(label=f"LoRA {int(i+1)} Filename", choices=[], info="Optional", value="", allow_custom_value=True)
-                                        lora_trigger[i] = gr.Textbox(label=f"LoRA {int(i+1)} Trigger Prompt", lines=1, max_lines=4, value="")
-                                        lora_wt[i] = gr.Slider(label=f"LoRA {int(i+1)} Scale", minimum=-2, maximum=2, step=0.01, value=1.00)
-                                    with gr.Row():
-                                        lora_info[i] = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
-                                        lora_copy[i] = gr.Button(value="Copy example to prompt", visible=False)
-                                        lora_md[i] = gr.Markdown(value="", visible=False)
-                                        lora_num[i] = gr.Number(i, visible=False)
+                            with gr.Row():
+                                for i in range(num_loras):
+                                    with gr.Column():
+                                        with gr.Row():
+                                            lora_repo[i] = gr.Dropdown(label=f"LoRA {int(i+1)} Repo", choices=get_all_lora_tupled_list(), info="Input LoRA Repo ID", value="", allow_custom_value=True)
+                                            lora_weights[i] = gr.Dropdown(label=f"LoRA {int(i+1)} Filename", choices=[], info="Optional", value="", allow_custom_value=True)
+                                            lora_trigger[i] = gr.Textbox(label=f"LoRA {int(i+1)} Trigger Prompt", lines=1, max_lines=4, value="")
+                                            lora_wt[i] = gr.Slider(label=f"LoRA {int(i+1)} Scale", minimum=-2, maximum=2, step=0.01, value=1.00)
+                                        with gr.Row():
+                                            lora_info[i] = gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
+                                            lora_copy[i] = gr.Button(value="Copy example to prompt", visible=False)
+                                            lora_md[i] = gr.Markdown(value="", visible=False)
+                                            lora_num[i] = gr.Number(i, visible=False)
                             with gr.Accordion("From URL", open=True, visible=True):
                                 with gr.Row():
                                     lora_search_civitai_query = gr.Textbox(label="Query", placeholder="flux", lines=1)
                                     lora_search_civitai_submit = gr.Button("Search on Civitai")
                                     lora_search_civitai_basemodel = gr.CheckboxGroup(label="Search LoRA for", choices=["Flux.1 D", "Flux.1 S"], value=["Flux.1 D", "Flux.1 S"])
                                 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)
+                                with gr.Row():
+                                    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)
                                 with gr.Row():
                                     lora_download = [None] * num_loras
@@ -399,16 +401,17 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css) as app:
                             cn_image_ref = [None] * num_cns
                             cn_res = [None] * num_cns
                             cn_num = [None] * num_cns
-                            for i in range(num_cns):
-                                with gr.Group():
-                                    with gr.Row():
-                                        cn_mode[i] = gr.Dropdown(label=f"ControlNet {int(i+1)} Mode", choices=get_control_union_mode(), value=get_control_union_mode()[0], allow_custom_value=False)
-                                        cn_scale[i] = gr.Slider(label=f"ControlNet {int(i+1)} Weight", minimum=0.0, maximum=1.0, step=0.01, value=0.75)
-                                        cn_res[i] = gr.Slider(label=f"ControlNet {int(i+1)} Preprocess resolution", minimum=128, maximum=512, value=384, step=1)
-                                        cn_num[i] = gr.Number(i, visible=False)
-                                    with gr.Row():
-                                        cn_image_ref[i] = gr.Image(label="Image Reference", type="pil", format="png", height=256, sources=["upload", "clipboard"], show_share_button=False)
-                                        cn_image[i] = gr.Image(label="Control Image", type="pil", format="png", height=256, show_share_button=False, interactive=False)
+                            with gr.Row():
+                                for i in range(num_cns):
+                                    with gr.Column():
+                                        with gr.Row():
+                                            cn_mode[i] = gr.Dropdown(label=f"ControlNet {int(i+1)} Mode", choices=get_control_union_mode(), value=get_control_union_mode()[0], allow_custom_value=False)
+                                            cn_scale[i] = gr.Slider(label=f"ControlNet {int(i+1)} Weight", minimum=0.0, maximum=1.0, step=0.01, value=0.75)
+                                            cn_res[i] = gr.Slider(label=f"ControlNet {int(i+1)} Preprocess resolution", minimum=128, maximum=512, value=384, step=1)
+                                            cn_num[i] = gr.Number(i, visible=False)
+                                        with gr.Row():
+                                            cn_image_ref[i] = gr.Image(label="Image Reference", type="pil", format="png", height=256, sources=["upload", "clipboard"], show_share_button=False)
+                                            cn_image[i] = gr.Image(label="Control Image", type="pil", format="png", height=256, show_share_button=False, interactive=False)
 
     gallery.select(
         update_selection,

mod.py

@@ -32,6 +32,9 @@ models = [
     "John6666/iniverse-mix-xl-sfwnsfw-fluxdfp8v10-fp8-flux",
     "John6666/the-araminta-flux1a1-fp8-flux",
     "John6666/acorn-is-spinning-flux-v11-fp8-flux",
+    "John6666/real-horny-v2-v2unet-fp8-flux",
+    "John6666/centerfold-flux-v20fp8e5m2-fp8-flux",
+    "John6666/jib-mix-flux-v208stephyper-fp8-flux",
     "John6666/fluxescore-dev-v10fp16-fp8-flux",
     # "",
 ]