# 🐍 Python Conversion Summary

Vico telah dikonversi dari Node.js menjadi Python dengan menggunakan library resmi `huggingface_hub`.

## ✨ Perubahan Utama

### File Python Baru
- **`server.py`** - Flask API server (menggantikan server.js)
- **`hf_uploader.py`** - Utility upload dengan `huggingface_hub` library
- **`requirements.txt`** - Dependencies Python
- **`examples/upload-file.py`** - Contoh upload via API (Python)
- **`examples/direct-hf-upload.py`** - Contoh direct upload ke HF

### Fitur Baru
✅ Menggunakan library resmi `huggingface_hub`  
✅ Support direct upload dengan `upload_file()` dan `upload_folder()`  
✅ Better error handling  
✅ Support upload folder (tidak hanya file)  
✅ Path structure: `/u/` untuk semua file  

## 🚀 Quick Start

### 1. Install Dependencies
```bash
pip install -r requirements.txt
```

### 2. Setup Environment
```bash
cp .env.example .env
# Edit .env dan set HF_TOKEN dan HF_REPO_ID
```

### 3. Run Server
```bash
python3 server.py
```

### 4. Upload File

**Via API:**
```bash
curl -X POST http://localhost:3000/api/upload \
  -F "file=@data.csv"
```

**Via Python (Direct):**
```python
from huggingface_hub import login, upload_file

login(token='hf_...')
upload_file(
    path_or_fileobj='data.csv',
    path_in_repo='u/data.csv',
    repo_id='username/dataset',
    repo_type='dataset'
)
```

## 📝 API Endpoints

### POST /api/upload
Upload single file ke Hugging Face dataset

**Params:**
- `file` - File untuk di-upload
- `repo_id` - Target dataset (atau dari .env)
- `token` - HF token (atau dari .env)
- `subfolder` - Optional subfolder

**Response:**
```json
{
  "success": true,
  "data": {
    "url": "https://huggingface.co/datasets/.../blob/main/u/...",
    "file_path": "u/...",
    "file_size": 12345,
    "upload_timestamp": "2024-06-24T..."
  }
}
```

## 🔄 Migration Guide

### Dari Node.js (Old)
```javascript
// Old: Node.js
npm start
```

### Ke Python (New)
```bash
# New: Python
python3 server.py
```

## 📚 Library: huggingface_hub

Dokumentasi: https://huggingface.co/docs/hub/security-tokens

### Contoh Penggunaan

```python
from huggingface_hub import login, upload_file, upload_folder

# Authenticate
login(token='hf_...')

# Upload single file
upload_file(
    path_or_fileobj='path/to/file.csv',
    path_in_repo='u/file.csv',
    repo_id='username/dataset-name',
    repo_type='dataset',
    commit_message='Upload data'
)

# Upload entire folder
upload_folder(
    folder_path='path/to/folder',
    repo_id='username/dataset-name',
    repo_type='dataset',
    path_in_repo='u/folder',
    commit_message='Upload folder'
)
```

## 🔑 Environment Variables

Setup di `.env`:
```env
HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxxxx
HF_REPO_ID=username/dataset-name
PORT=3000
NODE_ENV=development
```

## 📦 Dependencies

```
Flask==2.3.3          # Web framework
python-dotenv==1.0.0  # Environment variables
huggingface-hub==0.16.4  # Official HF library
requests==2.31.0      # HTTP client
```

## 🧪 Testing

### Test server health
```bash
curl http://localhost:3000
```

### Test upload (dengan .env set)
```bash
python3 examples/upload-file.py
```

### Test direct upload
```bash
python3 examples/direct-hf-upload.py
```

## ✅ Checklist

- [x] Server berjalan di port 3000
- [x] API endpoint `/api/upload` working
- [x] Environment variables support
- [x] Response format JSON
- [x] Error handling
- [x] Direct upload support
- [x] Folder upload support
- [x] Docker support

## 📖 File Reference

| File | Purpose |
|------|---------|
| `server.py` | Flask web server |
| `hf_uploader.py` | Upload utility dengan HF library |
| `requirements.txt` | Python dependencies |
| `examples/upload-file.py` | Upload via API |
| `examples/direct-hf-upload.py` | Direct upload |
| `Dockerfile` | Docker image |

## 🚀 Production Deployment

### Dengan Gunicorn
```bash
pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:3000 server:app
```

### Dengan Docker
```bash
docker build -t vico-api .
docker run -p 3000:3000 \
  -e HF_TOKEN=your_token \
  -e HF_REPO_ID=username/dataset \
  vico-api
```

---

**Note:** Old Node.js files (server.js, package.json) masih ada untuk referensi tapi tidak lagi digunakan. 
Gunakan Python files untuk development baru.