Update app.py

app.py

@@ -3,6 +3,8 @@ from huggingface_hub.hf_api import create_repo
 from huggingface_hub.repository import Repository
 import gradio as gr
 import pandas as pd
+import subprocess
+import os
 import tempfile
 
 token = gr.Textbox(label = "Your Hugging Face Token")
@@ -10,26 +12,31 @@ username = gr.Textbox(label = "Your Hugging Face User name")
 dataset_name = gr.Textbox(label = "Dataset Name")
 dataset = gr.File(label = "Dataset")
 output_text = gr.Textbox(label = "Status")
-title = "Dataset Profiler 🪄✨"
-description = "Drag and drop any dataset you want to get a detailed profile on, and this Space will profile and push it to your Hub profile as a new Space. 🌟✨"
 
 def profile_dataset(dataset, username, token, dataset_name):
 
     df = pd.read_csv(dataset.name)
     profile = pp.ProfileReport(df, title=f"{dataset_name} Report")
     
-    url = create_repo(f"{username}/{dataset_name}", repo_type = "space", token = token, space_sdk = "static")
+    repo_url = create_repo(f"{username}/{dataset_name}", repo_type = "space", token = token, space_sdk = "static")
+    
+    subprocess.run(
+    f"git clone {repo_url}".split(),
+    encoding="utf-8",
+    cwd= os.getcwd(),
+    check=True,
+    env=os.environ.copy(),
+    )
+
     repo = Repository(
-        local_dir = f"{username}/{dataset_name}",
-        clone_from=url,
-        use_auth_token=token,
-        repo_type = "space"
+    clone_from = repo_url,
+    local_dir=f"{username}/{dataset_name}"
     )
-    repo.git_pull(rebase=True)
+    
     profile.to_file(f"{username}/{dataset_name}/index.html")
     repo.git_add()
     repo.git_commit(commit_message = "Dataset report")
     repo.git_push()
-    return f"Your dataset report will be ready at {url}"
+    return f"Your dataset report will be ready at {repo_url}"
 
-gr.Interface(profile_dataset, inputs = [dataset, username, token, dataset_name], description = description, title = title, outputs=[output_text], enable_queue = True).launch(debug=True)
+gr.Interface(profile_dataset, inputs = [dataset, username, token, dataset_name], outputs=[output_text], enable_queue = True).launch(debug=True)