QUICKSTART.md

Vico - Quick Start Guide (Python)

🎯 Setup Cepat (5 Menit)

1. Install Dependencies

pip install -r requirements.txt

2. Jalankan Server

# Production mode
python3 server.py

# Development mode
export FLASK_APP=server.py
export FLASK_ENV=development
flask run --reload

Server akan berjalan di http://localhost:3000

3. Test Upload

Cara 1: Dengan Environment Variables (Recommended)

Setup .env:

# Copy dari .env.example
cp .env.example .env

# Edit .env dan set:
# HF_TOKEN=hf_your_token_here
# HF_REPO_ID=username/my-dataset

Kemudian upload hanya dengan file:

# cURL
curl -X POST http://localhost:3000/api/upload \
  -F "file=@test.csv"

# atau
bash examples/env-upload.sh

Cara 2: Via cURL (Terminal)

# Siapkan file test
echo "id,name,value" > test.csv
echo "1,Alice,100" >> test.csv

# Upload
curl -X POST http://localhost:3000/api/upload \
  -F "file=@test.csv" \
  -F "repo_id=username/my-dataset" \
  -F "token=hf_your_token_here"

Via Browser

1. Buka http://localhost:3000
2. Redirect ke file examples/index.html
3. Atau buka langsung: examples/index.html

Via Node.js

node examples/nodejs-axios.js

Via Python

python3 examples/upload-file.py

---

📌 Langkah-langkah Detail

A. Siapkan Hugging Face Token

1. Buka https://huggingface.co/settings/tokens
2. Klik "New token"
3. Beri nama: "Vico Upload"
4. Pilih tipe: "Write"
5. Salin token (format: hf_...)

B. Buat Dataset di Hugging Face

1. Buka https://huggingface.co/datasets/create
2. Isi form:
   • Name: my-dataset
   • Organization: Pilih account Anda
   • Visibility: Public (atau Private)
3. Klik "Create dataset"
4. Catat ID: username/my-dataset

C. Upload File

Gunakan salah satu metode di atas dengan:

• repo_id: ID dataset yang dibuat
• token: Token yang disalin
• file: File yang ingin diupload

D. Cek Hasil

File akan langsung muncul di:

https://huggingface.co/datasets/username/my-dataset/tree/main

---

🔧 Konfigurasi Lanjutan

Setup Environment Variables

cp .env.example .env
# Edit .env dan set PORT, NODE_ENV, dll

Deploy dengan Docker

docker build -t vico-api .
docker run -p 3000:3000 vico-api

Deploy dengan PM2

npm install -g pm2
pm2 start server.js --name "vico"
pm2 save
pm2 startup

---

📝 API Response Format

✅ Success (200)

{
  "success": true,
  "message": "File berhasil di-upload ke Hugging Face",
  "data": {
    "file_name": "test.csv",
    "file_size": 123,
    "repo_id": "username/my-dataset",
    "subfolder": "root",
    "url": "https://huggingface.co/datasets/username/my-dataset/blob/main/test.csv",
    "upload_timestamp": "2024-06-24T14:35:00.000Z"
  }
}

❌ Error (400/500)

{
  "success": false,
  "error": "Error message here",
  "required_fields": ["field1", "field2"]
}

---

🐛 Troubleshooting

Error	Solusi
Connection refused	Pastikan server running (npm start)
Token tidak valid	Cek token di https://huggingface.co/settings/tokens
Repository tidak ditemukan	Cek format: username/dataset-name (lowercase)
File too large	Max 100MB, ubah di server.js jika perlu
Timeout	File besar, tingkatkan timeout di hfUploader.js

---

📚 Contoh Lengkap

cURL dengan file

curl -X POST http://localhost:3000/api/upload \
  -F "file=@data.json" \
  -F "repo_id=john/datasets" \
  -F "token=hf_abc123xyz" \
  -F "subfolder=raw-data"

Node.js

const FormData = require('form-data');
const axios = require('axios');
const fs = require('fs');

const form = new FormData();
form.append('file', fs.createReadStream('data.json'));
form.append('repo_id', 'john/datasets');
form.append('token', 'hf_abc123xyz');
form.append('subfolder', 'raw-data');

axios.post('http://localhost:3000/api/upload', form, {
  headers: form.getHeaders()
}).then(res => console.log(res.data));

Python

import requests

files = {'file': open('data.json', 'rb')}
data = {
    'repo_id': 'john/datasets',
    'token': 'hf_abc123xyz',
    'subfolder': 'raw-data'
}

r = requests.post('http://localhost:3000/api/upload', files=files, data=data)
print(r.json())

---

📞 Support

Untuk bantuan lebih lanjut, lihat README.md untuk dokumentasi lengkap.

Happy uploading! 🚀