Update app.py

app.py

@@ -58,19 +58,23 @@ def get_quantization_recipe(method, model_architecture):
         raise ValueError(f"Unsupported quantization method: {method}")
 
 # --------------------------------------------------------------------------------
-# CHANGE #1: Modified function signature to use gr.Request
+# CHANGE #1: The function no longer needs the `request` or `oauth_token` argument.
 # --------------------------------------------------------------------------------
-def compress_and_upload(model_id: str, quant_method: str, request: gr.Request):
+def compress_and_upload(model_id: str, quant_method: str):
     """
     Compresses a model using llm-compressor and uploads it to a new HF repo.
     """
-    oauth_token = request.token  # Get the token from the request object
-
     if not model_id:
         raise gr.Error("Please select a model from the search bar.")
 
-    if oauth_token is None:
-        raise gr.Error("Please log in with your Hugging Face account to continue.")
+    # Check for login status by calling whoami(). It will raise an error if not logged in.
+    try:
+        user_info = whoami()
+        if user_info is None:
+             raise gr.Error("Authentication error. Please log in to continue.")
+        username = user_info["name"]
+    except Exception as e:
+        raise gr.Error(f"Authentication error. Please log in to continue. Details: {e}")
 
     try:
         # --- 1. Load Model and Tokenizer ---
@@ -96,8 +100,8 @@ def compress_and_upload(model_id: str, quant_method: str, request: gr.Request):
         )
 
         # --- 4. Create Repo and Upload ---
-        api = HfApi(token=oauth_token)
-        username = whoami(token=oauth_token)["name"]
+        # HfApi() will automatically use the logged-in user's token.
+        api = HfApi()
         repo_id = f"{username}/{output_dir}"
 
         repo_url = api.create_repo(repo_id=repo_id, exist_ok=True)
@@ -130,7 +134,7 @@ This conversion was performed by the `llm-compressor-my-repo` Hugging Face Space
 For more details on the recipe used, refer to the `recipe.yaml` file in this repository.
 """
         card = ModelCard(card_content)
-        card.push_to_hub(repo_id, token=oauth_token)
+        card.push_to_hub(repo_id) # No token needed here either
 
         return f'<h1>✅ Success!</h1><br/>Model compressed and saved to your new repo: <a href="{repo_url}" target="_blank" style="text-decoration:underline">{repo_id}</a>'
 
@@ -164,11 +168,11 @@ with gr.Blocks(css="footer {display: none !important;}") as demo:
     output_html = gr.HTML(label="Result")
 
     # --------------------------------------------------------------------------------
-    # CHANGE #2: Removed `login_button` from the inputs list
+    # CHANGE #2: The inputs list is now simpler and matches the function signature.
     # --------------------------------------------------------------------------------
     compress_button.click(
         fn=compress_and_upload,
-        inputs=[model_input, quant_method_dropdown], # login_button removed
+        inputs=[model_input, quant_method_dropdown],
         outputs=output_html
     )