Panduan Pembangunan AI SaaS

Spesifikasi Server:

• Database Name: ao
• Database User: ao
• Database Pass: ap123
• Area Private: /www/wwwroot/app-collection/ao (Berisi kode Python, Model ML, Venv, Logs).
• Area Public: /www/wwwroot/ao.baktimakmur.com (Berisi HTML/JS/CSS dan Uploads).

cd /www/wwwroot/app-collection/ao

# Membuat virtual environment dengan nama 'venv'
python3 -m venv venv

# Mengaktifkan environment
source venv/bin/activate

Jika prompt terminal Anda berubah menjadi (venv) user@server:...$, berarti venv aktif.

# Framework Web & ASGI Server
fastapi==0.104.1
uvicorn[standard]==0.24.0
pydantic==2.5.0
pydantic-settings==2.1.0

# Database
psycopg2-binary==2.9.9
sqlalchemy==2.0.23
alembic==1.13.0

# Machine Learning
scikit-learn==1.3.2
pandas==2.1.3
numpy==1.26.2
joblib==1.3.2

# Utilities
python-dotenv==1.0.0
python-multipart==0.0.6

-- Koneksi ke database: ao (User: ao, Pass: ap123)

CREATE TABLE IF NOT EXISTS users (
    id SERIAL PRIMARY KEY,
    username VARCHAR(50) UNIQUE NOT NULL,
    email VARCHAR(100) UNIQUE NOT NULL,
    api_key VARCHAR(255) UNIQUE NOT NULL,
    is_active BOOLEAN DEFAULT TRUE,
    created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);

-- Dummy Data Insert (User Production)
INSERT INTO users (username, email, api_key, is_active) VALUES
('admin_saas', 'admin@ao.baktimakmur.com', 'prod-sk-88219238-x98', TRUE);

-- Tabel untuk queue proses ML
CREATE TABLE IF NOT EXISTS ml_jobs (
    id SERIAL PRIMARY KEY,
    user_id INTEGER REFERENCES users(id) ON DELETE CASCADE,
    job_type VARCHAR(50) NOT NULL, -- Contoh: 'sentiment_analysis', 'prediction'
    status VARCHAR(20) DEFAULT 'pending', -- pending, processing, completed, failed
    input_params JSONB, -- Data input fleksibel
    result_path VARCHAR(255), -- Path file hasil di area public
    error_message TEXT,
    created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);

-- Trigger untuk update timestamp (PostgreSQL Standard)
CREATE OR REPLACE FUNCTION update_updated_at_column()
RETURNS TRIGGER AS $$ BEGIN
    NEW.updated_at = CURRENT_TIMESTAMP;
    RETURN NEW;
END;
 $$ language 'plpgsql';

CREATE TRIGGER update_ml_jobs_updated_at BEFORE UPDATE ON ml_jobs
    FOR EACH ROW EXECUTE FUNCTION update_updated_at_column();

# Database Configuration
DB_HOST=localhost
DB_PORT=5432
DB_NAME=ao
DB_USER=ao
DB_PASS=ap123

# App Configuration
APP_NAME="AO ML SaaS"
APP_ENV=production
DEBUG=false
SECRET_KEY=ubah_ini_dengan_random_string_panjang_untuk_jwt

# Paths
PUBLIC_ROOT=/www/wwwroot/ao.baktimakmur.com
UPLOAD_DIR=/www/wwwroot/ao.baktimakmur.com/uploads
MODEL_DIR=/www/wwwroot/app-collection/ao/ml_models

from pydantic_settings import BaseSettings
from functools import lru_cache

class Settings(BaseSettings):
    # Database
    DB_HOST: str
    DB_PORT: str
    DB_NAME: str
    DB_USER: str
    DB_PASS: str

    # App Security
    SECRET_KEY: str
    ALGORITHM: str = "HS256"
    ACCESS_TOKEN_EXPIRE_MINUTES: int = 30
    
    # App Info
    APP_NAME: str
    APP_ENV: str
    DEBUG: bool = False

    # Directories
    PUBLIC_ROOT: str
    UPLOAD_DIR: str
    MODEL_DIR: str

    @property
    def DATABASE_URL(self) -> str:
        return f"postgresql://{self.DB_USER}:{self.DB_PASS}@{self.DB_HOST}:{self.DB_PORT}/{self.DB_NAME}"

    class Config:
        env_file = ".env"
        case_sensitive = True

@lru_cache()
def get_settings() -> Settings:
    return Settings()

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from core.config import get_settings

settings = get_settings()

# Engine Database
engine = create_engine(settings.DATABASE_URL, pool_pre_ping=True)

# Session Local Factory
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Base Model
Base = declarative_base()

# Dependency Injection untuk FastAPI
def get_db():
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()