Spaces:
Paused
Paused
| import gradio as gr | |
| import os | |
| import pandas as pd | |
| from huggingface_hub import HfFileSystem | |
| import tempfile | |
| # --- CONFIGURATION --- | |
| HF_BUCKET = "hf://buckets/Krixter/storage" | |
| def get_fs(): | |
| """Initialize the Hugging Face File System. Uses a token if available, otherwise runs anonymously.""" | |
| token = os.environ.get("HF_TOKEN") | |
| # If there's no token, HfFileSystem will just run in public/anonymous mode | |
| return HfFileSystem(token=token) | |
| def format_size(size_bytes): | |
| """Convert bytes to a human-readable format.""" | |
| for unit in ['B', 'KB', 'MB', 'GB', 'TB']: | |
| if size_bytes < 1024.0: | |
| return f"{size_bytes:.2f} {unit}" | |
| size_bytes /= 1024.0 | |
| def list_files(): | |
| """Fetch files from the bucket and return a formatted DataFrame.""" | |
| try: | |
| fs = get_fs() | |
| # Fetch file list with details (size, modified date) | |
| files = fs.ls(HF_BUCKET, detail=True) | |
| data = [] | |
| for f in files: | |
| if f["type"] == "file": | |
| name = os.path.basename(f["name"]) | |
| size_str = format_size(f["size"]) | |
| last_modified = f.get("last_modified", "Unknown") | |
| data.append({ | |
| "File Name": name, | |
| "Last Modified": last_modified, | |
| "Size": size_str | |
| }) | |
| df = pd.DataFrame(data) | |
| if not df.empty: | |
| # Convert 'Last Modified' to datetime for accurate chronological sorting | |
| df["Last Modified"] = pd.to_datetime(df["Last Modified"]).dt.tz_localize(None) | |
| # Default sort by File Name (alphabetical) | |
| df = df.sort_values(by="File Name", ascending=True) | |
| file_names = df["File Name"].tolist() if not df.empty else [] | |
| return df, gr.update(choices=file_names) | |
| except Exception as e: | |
| print(f"Error fetching files: {e}") | |
| return pd.DataFrame(columns=["File Name", "Last Modified", "Size"]), gr.update(choices=[]) | |
| def download_file(filename): | |
| """Download the selected file from the bucket to a temporary local file.""" | |
| if not filename: | |
| return None | |
| try: | |
| fs = get_fs() | |
| src_path = f"{HF_BUCKET}/{filename}" | |
| # Create a temporary directory to hold the downloaded file | |
| temp_dir = tempfile.mkdtemp() | |
| dest_path = os.path.join(temp_dir, filename) | |
| # Pull the file down from the bucket | |
| print(f"📥 Downloading {filename}...") | |
| fs.get(src_path, dest_path) | |
| print("✅ Download complete!") | |
| return dest_path | |
| except Exception as e: | |
| print(f"⚠️ Error downloading {filename}: {e}") | |
| return None | |
| # --- UI LAYOUT --- | |
| with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo")) as app: | |
| gr.Markdown("# 🗄️ AudioNovel Bucket Explorer") | |
| gr.Markdown("View, sort, and download your processed audio files. **Click the column headers below to sort by Name, Date, or Size.**") | |
| with gr.Row(): | |
| refresh_btn = gr.Button("🔄 Refresh Bucket contents", variant="secondary") | |
| # Interactive table | |
| file_table = gr.Dataframe( | |
| headers=["File Name", "Last Modified", "Size"], | |
| interactive=False, | |
| label="Bucket Contents" | |
| ) | |
| gr.Markdown("---") | |
| gr.Markdown("### 📥 Download a File") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| file_dropdown = gr.Dropdown(label="Select File to Download", choices=[]) | |
| with gr.Column(scale=1): | |
| download_btn = gr.Button("🚀 Prepare Download", variant="primary") | |
| file_output = gr.File(label="Ready for Download") | |
| # --- EVENT TRIGGERS --- | |
| # Trigger refresh | |
| refresh_btn.click(fn=list_files, inputs=[], outputs=[file_table, file_dropdown]) | |
| # Trigger download | |
| download_btn.click(fn=download_file, inputs=[file_dropdown], outputs=[file_output]) | |
| # Load data automatically on startup | |
| app.load(fn=list_files, inputs=[], outputs=[file_table, file_dropdown]) | |
| if __name__ == "__main__": | |
| app.launch() |