Update app.py

app.py

@@ -1,37 +1,109 @@
 import os
 import requests
-from huggingface_hub import HfApi
+import gradio as gr
+from huggingface_hub import HfApi, hf_hub_download
+from pathlib import Path
 
-# 1. Configuration
-token = os.getenv("HF_TOKEN")
-dest_repo = "AIDev07/AIModelsLoaded"
-filename = "starcoder2-15b-instruct-v0.1-Q4_K_M.gguf"
+# Initialize HF API
+# Ensure you have set 'HF_TOKEN' in your Space Secrets
+HF_TOKEN = os.environ.get("HF_TOKEN")
+api = HfApi(token=HF_TOKEN)
 
-# Manually defined clean URL to avoid f-string errors
-source_url = "https://huggingface.co"
-
-if not token:
-    print("❌ ERROR: Set 'HF_TOKEN' in Space Secrets!")
-else:
-    api = HfApi(token=token)
-    print(f"🚀 Starting Transfer for: {filename}")
+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')
 
+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."
+    
     try:
-        # 2. Use the 'run_as_future' or standard upload with the stream
-        with requests.get(source_url, stream=True) as r:
+        # 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:
             r.raise_for_status()
+            total_size = int(r.headers.get('content-length', 0))
+            downloaded = 0
             
-            # 3. Upload using the raw stream
-            api.upload_file(
-                path_or_fileobj=r.raw,
-                path_in_repo=filename,
-                repo_id=dest_repo,
-                repo_type="dataset",
-                commit_message=f"Direct cloud transfer of {filename}"
-            )
-            
-        print(f"✅ DONE! File is now in {dest_repo}")
+            with open(local_path, 'wb') as f:
+                for chunk in r.iter_content(chunk_size=8192):
+                    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)}%")
+        
+        # 4. Upload to Hugging Face
+        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"
+        )
         
+        # 5. Cleanup
+        if local_path.exists():
+            os.remove(local_path)
+            
+        return f"✅ Success! File '{filename}' uploaded to {repo_id}"
+
     except Exception as e:
-        print(f"❌ Transfer Failed: {e}")
-        print("Tip: If it says 'Connection Reset', the file is too big for a basic stream.")
+        return f"❌ Error: {str(e)}"
+
+# --- 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.**
+        """
+    )
+    
+    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)
+
+    upload_btn.click(
+        fn=download_and_upload,
+        inputs=[dataset_link, download_link],
+        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.
+        """
+    )
+
+if __name__ == "__main__":
+    demo.launch()