fix: update packages

README.md

@@ -4,7 +4,7 @@ emoji: 🐐
 colorFrom: gray
 colorTo: green
 sdk: gradio
-sdk_version: 4.44.1
+sdk_version: 5.50.0
 hf_oauth: true
 hf_oauth_scopes:
   - read-repos

app.py

@@ -1,13 +1,17 @@
 import os
+import shutil
 import tempfile
+import traceback
 
 os.environ["HF_HUB_CACHE"] = "cache"
+os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
 os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
 import gradio as gr
 
 from huggingface_hub import HfApi
 from huggingface_hub import whoami
 from huggingface_hub import ModelCard
+from huggingface_hub import model_info
 from huggingface_hub import scan_cache_dir
 from huggingface_hub import logging
 
@@ -32,15 +36,6 @@ QUANT_PARAMS = {
     "Q8": 8,
 }
 
-def list_files_in_folder(folder_path):
-    # List all files and directories in the specified folder
-    all_items = os.listdir(folder_path)
-    
-    # Filter out only files
-    files = [item for item in all_items if os.path.isfile(os.path.join(folder_path, item))]
-    
-    return files
-
 def clear_hf_cache_space():
     scan = scan_cache_dir()
     to_delete = []
@@ -89,29 +84,42 @@ def upload_to_hub(path, upload_repo, hf_path, oauth_token):
 
     api = HfApi(token=oauth_token.token)
     api.create_repo(repo_id=upload_repo, exist_ok=True)
+    api.upload_folder(folder_path=path, repo_id=upload_repo)
 
-    files = list_files_in_folder(path)
-    print(files)
-    for file in files:
-        file_path = os.path.join(path, file)
-        print(f"Uploading file: {file_path}")
-        api.upload_file(
-            path_or_fileobj=file_path,
-            path_in_repo=file,
-            repo_id=upload_repo,
-        )
-        
-    print(f"Upload successful, go to https://huggingface.co/{upload_repo} for details.")    
+    print(f"Upload successful, go to https://huggingface.co/{upload_repo} for details.")
 
 def process_model(model_id, q_method, oauth_token: gr.OAuthToken | None):
-    if oauth_token.token is None:
+    if oauth_token is None or oauth_token.token is None:
         raise ValueError("You must be logged in to use MLX-my-repo")
-    
+
+    # Set token for mlx_lm.convert which doesn't accept a token parameter
+    os.environ["HF_TOKEN"] = oauth_token.token
+
     model_name = model_id.split('/')[-1]
     username = whoami(oauth_token.token)["name"]
     try:
+        # Check model size vs available disk (need ~2x for download + conversion)
+        info = model_info(model_id, token=oauth_token.token)
+        if info.safetensors and info.safetensors.total:
+            model_bytes = info.safetensors.total
+        elif info.siblings:
+            model_bytes = sum(s.size or 0 for s in info.siblings)
+        else:
+            model_bytes = 0
+        if model_bytes > 0:
+            free_bytes = shutil.disk_usage(".").free
+            required_bytes = model_bytes * 2
+            if free_bytes < required_bytes:
+                model_gb = model_bytes / (1024**3)
+                free_gb = free_bytes / (1024**3)
+                raise ValueError(
+                    f"Not enough disk space. Model is ~{model_gb:.1f}GB, "
+                    f"need ~{model_gb * 2:.1f}GB for conversion, "
+                    f"but only {free_gb:.1f}GB available."
+                )
+
         # Fail early if the tokenizer requires custom code
-        _ = AutoTokenizer.from_pretrained(model_id, trust_remote_code=False)
+        _ = AutoTokenizer.from_pretrained(model_id, token=oauth_token.token, trust_remote_code=False)
 
         if q_method == "FP16":
             upload_repo = f"{username}/{model_name}-mlx-fp16"
@@ -137,17 +145,20 @@ def process_model(model_id, q_method, oauth_token: gr.OAuthToken | None):
             "llama.png",
         )
     except Exception as e:
-        return (f"Error: {e}", "error.png")
+        traceback.print_exc()
+        error_type = type(e).__name__
+        error_msg = str(e) or "No details available"
+        return (f"**{error_type}**: {error_msg}", "error.png")
     finally:
         clear_hf_cache_space()
         print("Folder cleaned up successfully!")
 
-css="""/* Custom CSS to allow scrolling */
+CSS = """/* Custom CSS to allow scrolling */
 .gradio-container {overflow-y: auto;}
 """
 
 # Create Gradio interface
-with gr.Blocks(css=css) as demo: 
+with gr.Blocks(css=CSS) as demo:
     gr.Markdown("You must be logged in to use MLX-my-repo.")
     gr.LoginButton(min_width=250)
 
@@ -165,7 +176,7 @@ with gr.Blocks(css=css) as demo:
         filterable=False,
         visible=True
     )
-    
+
     iface = gr.Interface(
         fn=process_model,
         inputs=[
@@ -182,7 +193,7 @@ with gr.Blocks(css=css) as demo:
     )
 
 def restart_space():
-    HfApi().restart_space(repo_id="mlx-community/mlx-my-repo", token=HF_TOKEN, factory_reboot=True)
+    HfApi().restart_space(repo_id="smcleod/mlx-my-repo", token=HF_TOKEN, factory_reboot=True)
 
 scheduler = BackgroundScheduler()
 scheduler.add_job(restart_space, "interval", seconds=21600)

requirements.txt

@@ -1,6 +1,7 @@
 hf-transfer
-gradio[oauth]>=4.28.0 
-gradio_huggingfacehub_search==0.0.7 
+audioop-lts
+gradio[oauth]>=5.50.0,<6.0.0
+gradio_huggingfacehub_search>=0.0.12
 APScheduler
 mlx[cpu]
-mlx-lm==0.29.1
+mlx-lm>=0.31.2