Update app.py (#18)

- Update app.py (ed734c18d4564c9f50b0ffd4168fc692c2ee5239)

app.py

@@ -15,8 +15,9 @@ import hashlib
 from datetime import datetime
 from typing import Dict, List, Optional
 from huggingface_hub import login, HfApi, hf_hub_download
-from huggingface_hub.utils import validate_repo_id, HFValidationError #Removed get_from_cache
+from huggingface_hub.utils import validate_repo_id, HFValidationError  # Removed get_from_cache
 from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE
+from huggingface_hub.utils import HfHubHTTPError
 
 
 # ---------------------- DEPENDENCIES ----------------------
@@ -66,7 +67,7 @@ def create_model_repo(api, user, orgs_name, model_name, make_private=False):
     try:
         api.create_repo(repo_id=repo_id, repo_type="model", private=make_private)
         print(f"Model repo '{repo_id}' created.")
-    except HfHubHTTPError:
+    except HfHubHTTPError:  # Corrected the exception name
         print(f"Model repo '{repo_id}' already exists.")
     return repo_id
 
@@ -82,7 +83,7 @@ def download_model(model_path_or_url):
             local_path = hf_hub_download(repo_id=model_path_or_url)
             return local_path
         except HFValidationError:
-            pass  # Not a simple repo ID. Might be repo ID + filename, or a URL.
+            pass  # Not a simple repo ID.  Might be repo ID + filename, or a URL.
 
         # 2. Check if it's a URL
         if model_path_or_url.startswith("http://") or model_path_or_url.startswith(
@@ -177,7 +178,11 @@ def load_sdxl_checkpoint(checkpoint_path):
 
 
 def build_diffusers_model(
-    text_encoder1_state, text_encoder2_state, vae_state, unet_state, reference_model_path=None
+    text_encoder1_state,
+    text_encoder2_state,
+    vae_state,
+    unet_state,
+    reference_model_path=None,
 ):
     """Builds the Diffusers pipeline components from the loaded state dicts."""
 
@@ -253,21 +258,33 @@ def convert_and_save_sdxl_to_diffusers(
 # ---------------------- UPLOAD FUNCTION ----------------------
 def upload_to_huggingface(model_path, hf_token, orgs_name, model_name, make_private):
     """Uploads a model to the Hugging Face Hub."""
-    login(hf_token, add_to_git_credential=True)
+    login(token=hf_token, add_to_git_credential=True)
     api = HfApi()
-    user = api.whoami(hf_token)
+    user = api.whoami(token=hf_token)
     model_repo = create_model_repo(api, user, orgs_name, model_name, make_private)
     api.upload_folder(folder_path=model_path, repo_id=model_repo)
     print(f"Model uploaded to: https://huggingface.co/{model_repo}")
 
 
 # ---------------------- GRADIO INTERFACE ----------------------
-def main(model_to_load, reference_model, output_path, hf_token, orgs_name, model_name, make_private):
+def main(
+    model_to_load,
+    reference_model,
+    output_path,
+    hf_token,
+    orgs_name,
+    model_name,
+    make_private,
+):
     """Main function: SDXL checkpoint to Diffusers, always fp16."""
 
     try:
-        convert_and_save_sdxl_to_diffusers(model_to_load, output_path, reference_model)
-        upload_to_huggingface(output_path, hf_token, orgs_name, model_name, make_private)
+        convert_and_save_sdxl_to_diffusers(
+            model_to_load, output_path, reference_model
+        )
+        upload_to_huggingface(
+            output_path, hf_token, orgs_name, model_name, make_private
+        )
         return "Conversion and upload completed successfully!"
     except Exception as e:
         return f"An error occurred: {e}"  # Return the error message
@@ -277,14 +294,14 @@ css = """
 #main-container {
     display: flex;
     flex-direction: column;
-    height: 100vh;
-    justify-content: space-between;
+    /* Removed height: 100vh; */
+    /* Removed justify-content: space-between; */
     font-family: 'Arial', sans-serif;
     font-size: 16px;
     color: #333;
 }
 #convert-button {
-    margin-top: auto;
+    margin-top: 1em; /* Adds some space above the button */
 }
 """
 
@@ -317,44 +334,48 @@ with gr.Blocks(css=css) as demo:
     """
     )
 
-    with gr.Column(elem_id="main-container"):  # Use a Column for layout
-        model_to_load = gr.Textbox(
-            label="SDXL Checkpoint (Path, URL, or HF Repo)",
-            placeholder="Path, URL, or Hugging Face Repo ID (e.g., my-org/my-model or my-org/my-model/file.safetensors)",
-        )
-        reference_model = gr.Textbox(
-            label="Reference Diffusers Model (Optional)",
-            placeholder="e.g., stabilityai/stable-diffusion-xl-base-1.0 (Leave blank for default)",
-        )
-        output_path = gr.Textbox(
-            label="Output Path (Diffusers Format)", value="output"
-        )  # Default changed to "output"
-        hf_token = gr.Textbox(
-            label="Hugging Face Token", placeholder="Your Hugging Face write token"
-        )
-        orgs_name = gr.Textbox(
-            label="Organization Name (Optional)", placeholder="Your organization name"
-        )
-        model_name = gr.Textbox(
-            label="Model Name", placeholder="The name of your model on Hugging Face"
-        )
-        make_private = gr.Checkbox(label="Make Repository Private", value=False)
-
-        convert_button = gr.Button("Convert and Upload", elem_id="convert-button")
-        output = gr.Markdown()
-
-        convert_button.click( #NOW IT IS INSIDE
-            fn=main,
-            inputs=[
-                model_to_load,
-                reference_model,
-                output_path,
-                hf_token,
-                orgs_name,
-                model_name,
-                make_private,
-            ],
-            outputs=output,
-        )
+    with gr.Row():  # Use gr.Row for horizontal layout
+        with gr.Column():  # Group input components in a Column
+
+            model_to_load = gr.Textbox(
+                label="SDXL Checkpoint (Path, URL, or HF Repo)",
+                placeholder="Path, URL, or Hugging Face Repo ID (e.g., my-org/my-model or my-org/my-model/file.safetensors)",
+            )
+            reference_model = gr.Textbox(
+                label="Reference Diffusers Model (Optional)",
+                placeholder="e.g., stabilityai/stable-diffusion-xl-base-1.0 (Leave blank for default)",
+            )
+            output_path = gr.Textbox(
+                label="Output Path (Diffusers Format)", value="output"
+            )  # Default changed to "output"
+            hf_token = gr.Textbox(
+                label="Hugging Face Token", placeholder="Your Hugging Face write token", type="password"
+            )
+            orgs_name = gr.Textbox(
+                label="Organization Name (Optional)", placeholder="Your organization name"
+            )
+            model_name = gr.Textbox(
+                label="Model Name", placeholder="The name of your model on Hugging Face"
+            )
+            make_private = gr.Checkbox(label="Make Repository Private", value=False)
+
+            convert_button = gr.Button("Convert and Upload")
+
+        with gr.Column():
+            output = gr.Markdown() #Output is in its own column
+
+    convert_button.click(
+        fn=main,
+        inputs=[
+            model_to_load,
+            reference_model,
+            output_path,
+            hf_token,
+            orgs_name,
+            model_name,
+            make_private,
+        ],
+        outputs=output,
+    )
 
 demo.launch()