Upload 7 files

app.py

@@ -108,11 +108,14 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
     
+    progress(1, desc="Preparing Inference.")
+
     image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
     pipe.to("cpu")
-    if selected_index is not None:
+    if selected_index is not None: pipe.unload_lora_weights()
+    if is_valid_lora(lora_json):
+        pipe.unfuse_lora()
         pipe.unload_lora_weights()
-        if is_valid_lora(lora_json): pipe.unfuse_lora()
     clear_cache()
     return image, seed  
 
@@ -214,9 +217,10 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
                             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 = gr.Button("Get and set LoRA", scale=5)
-                                #lora_slot = gr.Number(label="LoRA slot to set", minimum=1, maximum=num_loras, step=1, value=1, scale=1, interactive=True)
-
+                                lora_download = [None] * num_loras
+                                for i in range(num_loras):
+                                    lora_download[i] = gr.Button(f"Get and set LoRA to {int(i+1)}")
+     
     gallery.select(
         update_selection,
         inputs=[width, height],
@@ -248,22 +252,22 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
     )
     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)
-    gr.on(
-        triggers=[lora_download.click, lora_download_url.submit],
-        fn=download_my_lora,
-        inputs=[lora_download_url, lora_repo[0]],
-        outputs=[lora_repo[0]],
-        scroll_to_output=True,
-        queue=True,
-        show_api=False,
-    )
 
     for i, l in enumerate(lora_repo):
+        gr.on(
+            triggers=[lora_download[i].click],
+            fn=download_my_lora,
+            inputs=[lora_download_url, lora_repo[i]],
+            outputs=[lora_repo[i]],
+            scroll_to_output=True,
+            queue=True,
+            show_api=False,
+        )
         gr.on(
             triggers=[lora_repo[i].change, lora_wt[i].change],
             fn=update_loras,
             inputs=[prompt, lora_repo[i], lora_wt[i]],
-            outputs=[prompt, lora_repo[i], lora_wt[i], lora_info[i], lora_copy[i], lora_md[i]],
+            outputs=[prompt, lora_repo[i], lora_wt[i], lora_info[i], lora_md[i]],
             queue=False,
             trigger_mode="once",
             show_api=False,
@@ -271,6 +275,7 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
         ).success(apply_lora_prompt, [lora_info[i]], [lora_trigger[i]], queue=False, show_api=False
         ).success(compose_lora_json, [lora_repo_json, lora_num[i], lora_repo[i], lora_wt[i], lora_weights[i], lora_trigger[i]], [lora_repo_json], queue=False, show_api=False)
 
+
     tagger_generate_from_image.click(
             lambda: ("", "", ""), None, [v2_series, v2_character, prompt], queue=False, show_api=False,
     ).success(

flux.py

@@ -286,7 +286,7 @@ def update_loras(prompt, lora, lora_wt):
     output_prompt = ", ".join(list_uniq(output_prompts + lora_prompts))
     choices = get_all_lora_tupled_list()
     return gr.update(value=output_prompt), gr.update(value=lora, choices=choices), gr.update(value=lora_wt),\
-     gr.update(value=tag, label=label, visible=on), gr.update(visible=on), gr.update(value=md, visible=on)
+     gr.update(value=tag, label=label, visible=on), gr.update(value=md, visible=on)
 
 
 def search_civitai_lora(query, base_model):