Update app.py

app.py

@@ -1,95 +1,85 @@
 import os
 import requests
 import gradio as gr
-from huggingface_hub import HfApi, hf_hub_download
+from huggingface_hub import HfApi
 from pathlib import Path
 
-# Initialize HF API
-# Ensure you have set 'HF_TOKEN' in your Space Secrets
+# Get token from Space Secrets
 HF_TOKEN = os.environ.get("HF_TOKEN")
 api = HfApi(token=HF_TOKEN)
 
 def get_repo_info(url):
     """Extracts repo_id and repo_type from a standard HF URL."""
-    parts = url.split("huggingface.co/")[1].split("/")
-    repo_type = parts[0] # 'datasets' or 'models'
-    repo_id = f"{parts[1]}/{parts[2]}"
-    return repo_id, repo_type.rstrip('s')
+    try:
+        parts = url.strip().split("huggingface.co/")[1].split("/")
+        if parts[0] == "datasets":
+            return f"{parts[1]}/{parts[2]}", "dataset"
+        else:
+            return f"{parts[0]}/{parts[1]}", "model"
+    except:
+        return None, None
 
 def download_and_upload(dataset_url, download_url, progress=gr.Progress()):
     if not HF_TOKEN:
-        return "❌ Error: HF_TOKEN not found in Secrets. Please add it to your Space settings."
+        return "❌ Error: HF_TOKEN not found in Secrets."
     
+    repo_id, repo_type = get_repo_info(dataset_url)
+    if not repo_id:
+        return "❌ Error: Invalid Dataset/Repo URL format."
+
+    filename = download_url.split("/")[-1].split("?")[0]
+    local_path = Path(filename)
+
     try:
-        # 1. Parse Target Repo
-        progress(0, desc="Parsing repository info...")
-        repo_id, repo_type = get_repo_info(dataset_url)
-        
-        # 2. Prepare File Info
-        filename = download_url.split("/")[-1].split("?")[0]
-        local_path = Path(filename)
-        
-        # 3. Download with Progress
-        progress(0.1, desc=f"Starting download: {filename}")
-        with requests.get(download_url, stream=True) as r:
+        # Step 1: Download with status updates
+        progress(0, desc="Initializing stream...")
+        with requests.get(download_url, stream=True, timeout=60) as r:
             r.raise_for_status()
             total_size = int(r.headers.get('content-length', 0))
             downloaded = 0
             
             with open(local_path, 'wb') as f:
-                for chunk in r.iter_content(chunk_size=8192):
+                for chunk in r.iter_content(chunk_size=1024*1024): # 1MB chunks
                     if chunk:
                         f.write(chunk)
                         downloaded += len(chunk)
                         if total_size > 0:
                             done = downloaded / total_size
-                            progress(0.1 + (done * 0.4), desc=f"Downloading... {int(done*100)}%")
+                            # Update every few MBs to keep the connection alive
+                            progress(done * 0.5, desc=f"Downloading: {downloaded/(1024**3):.2f}GB / {total_size/(1024**3):.2f}GB")
         
-        # 4. Upload to Hugging Face
+        # Step 2: Upload to HF
         progress(0.6, desc="Uploading to Hugging Face...")
         api.upload_file(
             path_or_fileobj=str(local_path),
             path_in_repo=filename,
             repo_id=repo_id,
             repo_type=repo_type,
-            commit_message=f"Uploaded {filename} via UpDownUrl"
+            commit_message=f"Uploaded {filename} via UpDownUrl",
+            # This is key for large files:
+            run_as_future=False 
         )
         
-        # 5. Cleanup
-        if local_path.exists():
-            os.remove(local_path)
-            
-        return f"✅ Success! File '{filename}' uploaded to {repo_id}"
+        return f"✅ Done! '{filename}' is now in {repo_id}"
 
     except Exception as e:
         return f"❌ Error: {str(e)}"
+    finally:
+        if local_path.exists():
+            os.remove(local_path)
 
-# --- Professional UI Design ---
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown(
-        """
-        # 🚀 UpDownUrl (v1.0)
-        **Transfer files directly from the web to your Hugging Face Repositories.**
-        """
-    )
+# --- UI Setup ---
+with gr.Blocks() as demo:
+    gr.Markdown("# 🚀 UpDownUrl v1.1")
     
     with gr.Row():
-        with gr.Column(scale=2):
-            dataset_link = gr.Textbox(
-                label="Target Dataset/Repo Link", 
-                placeholder="https://huggingface.co/datasets/USER/REPO",
-                info="The URL of the repo where the file will be saved."
-            )
-            download_link = gr.Textbox(
-                label="File Download URL", 
-                placeholder="https://.../model.gguf",
-                info="Direct link to the file you want to download."
-            )
-            upload_btn = gr.Button("Start Transfer", variant="primary")
-            
-        with gr.Column(scale=1):
-            gr.Markdown("### Status & Logs")
-            output_log = gr.Code(label="Console Output", interactive=False)
+        with gr.Column():
+            dataset_link = gr.Textbox(label="Target Repo Link", placeholder="https://huggingface.co/datasets/AIDev07/AIModelsLoaded")
+            download_link = gr.Textbox(label="Download URL", placeholder="Direct link to file")
+            upload_btn = gr.Button("Boom! Upload", variant="primary")
+        
+        with gr.Column():
+            output_log = gr.Textbox(label="Status", interactive=False)
 
     upload_btn.click(
         fn=download_and_upload,
@@ -97,13 +87,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         outputs=output_log
     )
 
-    gr.Markdown(
-        """
-        ---
-        **Note:** This Space uses your `HF_TOKEN`. Larger files (up to 15GB) are supported depending on the Space's disk quota. 
-        If it crashes, consider using a 'Large' hardware tier.
-        """
-    )
-
+# Fixed Gradio 6.0 syntax: Theme goes here
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(theme=gr.themes.Soft())