revert custom

app.py

@@ -303,7 +303,7 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
     last_lora = repo_name
     return image
     
-def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, sdxl_loras, custom_lora_path, progress=gr.Progress(track_tqdm=True)):
+def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, sdxl_loras, progress=gr.Progress(track_tqdm=True)):
     selected_state_index = selected_state.index
     st = time.time()
     face_image = center_crop_image_as_square(face_image)
@@ -334,17 +334,13 @@ def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_stre
     print(sdxl_loras[selected_state_index]["repo"])
     if negative == "":
         negative = None
+
+    if not selected_state:
+        raise gr.Error("You must select a LoRA")
+    repo_name = sdxl_loras[selected_state_index]["repo"]
+    weight_name = sdxl_loras[selected_state_index]["weights"]
     
-    if not selected_state and not custom_loaded_lora:
-        raise gr.Error("You must select a style")
-    elif custom_loaded_lora:
-        repo_name = "Loaded custom LoRA"
-        full_path_lora = custom_lora_path
-    else:
-        repo_name = sdxl_loras[selected_state_index]["repo"]
-        weight_name = sdxl_loras[selected_state_index]["weights"]
-        full_path_lora = state_dicts[repo_name]["saved_name"]
-    
+    full_path_lora = state_dicts[repo_name]["saved_name"]
     #loaded_state_dict = copy.deepcopy(state_dicts[repo_name]["state_dict"])
     cross_attention_kwargs = None
     et = time.time()
@@ -372,92 +368,6 @@ def swap_gallery(order, sdxl_loras):
 def deselect():
   return gr.Gallery(selected_index=None)
 
-lora_archive = "/data"
-
-def get_huggingface_safetensors(link):
-  split_link = link.split("/")
-  if(len(split_link) == 2):
-            model_card = ModelCard.load(link)
-            image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
-            
-            print(image_path)
-            image_url = f"https://huggingface.co/{link}/resolve/main/{image_path}" if image_path else None
-            fs = HfFileSystem()
-            try:
-                list_of_files = fs.ls(link, detail=False)
-                for file in list_of_files:
-                    if(file.endswith(".safetensors")):
-                        safetensors_name = file.replace("/", "_")
-                        if(not os.path.exists(f"{lora_archive}/{safetensors_name}")):
-                          fs.get_file(file, lpath=f"{lora_archive}/{safetensors_name}")
-                    if (not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp"))):
-                      image_url = f"https://huggingface.co/{link}/resolve/main/{image_url}"
-            except:
-              raise gr.Error("You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA")
-            return split_link[1], f"{lora_archive}/{safetensors_name}", image_url
-
-def get_civitai_safetensors(link):
-  link_split = link.split("civitai.com/")
-  pattern = re.compile(r'models\/(\d+)')
-  regex_match = pattern.search(link_split[1])
-  if(regex_match):
-    civitai_model_id = regex_match.group(1)
-  
-  else:
-    raise gr.Error("No CivitAI model id found in your URL")
-  model_request_url = f"https://civitai.com/api/v1/models/{civitai_model_id}?token=dc9537afe3dcbbfb4696dd79ee8c23d7"
-  x = requests.get(model_request_url)
-  model_data = x.json()
-  if(model_data["nsfw"] == True):
-    raise gr.Error("The model is tagged by CivitAI as adult content and cannot be used in this shared environment.")
-  elif(model_data["type"] != "LORA"):
-    raise gr.Error("The model isn't tagged at CivitAI as a LoRA")
-  model_link_download = None
-  image_url = None
-  for model in model_data["modelVersions"]:
-    if(model["baseModel"] == "SDXL 1.0"):
-      model_link_download = f"{model['downloadUrl']}/?token=dc9537afe3dcbbfb4696dd79ee8c23d7"
-      safetensors_name = model["files"][0]["name"]
-      if(not os.path.exists(f"{lora_archive}/{safetensors_name}")):
-        safetensors_file_request = requests.get(model_link_download)
-        with open(f"{lora_archive}/{safetensors_name}", 'wb') as file:
-            file.write(safetensors_file_request.content)
-      for image in model["images"]:
-        if(image["nsfwLevel"] == 1):
-          image_url = image["url"]
-          break
-      break
-  return model_data["name"], f"{lora_archive}/{safetensors_name}", image_url
-  if(not model_link_download):
-    raise gr.Error("We couldn't find a SDXL LoRA on the model you've sent")
-def check_custom_model(link):
-    if(link.startswith("https://")):
-        if(link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co")):
-            link_split = link.split("huggingface.co/")
-            return get_huggingface_safetensors(link_split[1])
-        elif(link.startswith("https://civitai.com") or link.startswith("https://www.civitai.com")):
-            return get_civitai_safetensors(link)
-    else: 
-        return get_huggingface_safetensors(link)
-
-def show_loading_widget():
-    return gr.update(visible=True)
-
-def load_custom_lora(link):
-    title, path, image = check_custom_model(link)
-    card = f'''
-    <div class="custom_lora_card">
-      <span>Loaded custom LoRA:</span>
-      <div class="card_internal">
-        <h3>{title}</h3>
-        <img src="{image}" />
-      </div>
-    </div>
-    '''
-    return gr.update(visible=True), card, gr.update(visible=True), path, gr.Gallery(selected_index=None)
-
-def remove_custom_lora():
-    return "", gr.update(visible=False), gr.update(visible=False), None
 with gr.Blocks(css="custom.css") as demo:
     gr_sdxl_loras = gr.State(value=sdxl_loras_raw)
     title = gr.HTML(
@@ -471,7 +381,6 @@ with gr.Blocks(css="custom.css") as demo:
         elem_id="title",
     )
     selected_state = gr.State()
-    custom_loaded_lora = gr.State()
     with gr.Row(elem_id="main_app"):
         with gr.Column(scale=4):
             with gr.Group(elem_id="gallery_box"):
@@ -492,9 +401,7 @@ with gr.Blocks(css="custom.css") as demo:
                     show_share_button=False,
                     height=550
                 )
-                custom_model = gr.Textbox(label="Enter a custom Hugging Face or CivitAI SDXL LoRA", placeholder="Paste Hugging Face or CivitAI model path...")
-                custom_model_card = gr.HTML(visible=False)
-                custom_model_button = gr.Button("Remove custom LoRA", visible=False)
+                custom_model = gr.Textbox(label="Enter a custom Hugging Face or CivitAI SDXL LoRA", interactive=False, placeholder="Coming soon...")
         with gr.Column(scale=5):
             with gr.Row():
                 prompt = gr.Textbox(label="Prompt", show_label=False, lines=1, max_lines=1, info="Describe your subject (optional)", value="a person", elem_id="prompt")
@@ -524,19 +431,6 @@ with gr.Blocks(css="custom.css") as demo:
     #    outputs=[gallery, gr_sdxl_loras],
     #    queue=False
     #)
-    custom_model.change(
-        fn=show_loading_widget,
-        outputs=[custom_model_card]
-    ).then(
-        fn=load_custom_lora,
-        inputs=[custom_model],
-        outputs=[custom_model_card, custom_model_card, custom_model_button, custom_loaded_lora, gallery],
-        queue=False
-    )
-    custom_model_button.click(
-        fn=remove_custom_lora,
-        outputs=[custom_model, custom_loaded_lora, custom_model_card, custom_loaded_lora]
-    )
     gallery.select(
         fn=update_selection,
         inputs=[gr_sdxl_loras, face_strength, image_strength, weight, depth_control_scale, negative],
@@ -558,7 +452,7 @@ with gr.Blocks(css="custom.css") as demo:
         show_progress=False
     ).success(
         fn=run_lora,
-        inputs=[photo, prompt, negative, weight, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, gr_sdxl_loras, custom_loaded_lora],
+        inputs=[photo, prompt, negative, weight, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, gr_sdxl_loras],
         outputs=[result, share_group],
     )
     button.click(
@@ -568,7 +462,7 @@ with gr.Blocks(css="custom.css") as demo:
         show_progress=False
     ).success(
         fn=run_lora,
-        inputs=[photo, prompt, negative, weight, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, gr_sdxl_loras, custom_loaded_lora],
+        inputs=[photo, prompt, negative, weight, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, gr_sdxl_loras],
         outputs=[result, share_group],
     )
     share_button.click(None, [], [], js=share_js)