MIF_E31232435/ml_model/app.py

597 lines
18 KiB
Python

"""
Flask API untuk Prediksi Permintaan Stok Bahan
Menggunakan Random Forest Model
"""
from flask import Flask, request, jsonify
from flask_cors import CORS
import joblib
import pandas as pd
import numpy as np
import logging
from datetime import datetime
import mysql.connector
from mysql.connector import Error
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
app = Flask(__name__)
CORS(app)
# ============================================================================
# DATABASE CONFIGURATION
# ============================================================================
DB_HOST = 'localhost'
DB_USER = 'root'
DB_PASSWORD = '' # Ganti dengan password MySQL Anda jika ada
DB_NAME = 'prediksi_stok_db'
def get_db_connection():
"""Get MySQL database connection"""
try:
connection = mysql.connector.connect(
host=DB_HOST,
user=DB_USER,
password=DB_PASSWORD,
database=DB_NAME
)
return connection
except Error as e:
logger.error(f"Database connection error: {e}")
return None
# ============================================================================
# LOAD MODELS AT STARTUP
# ============================================================================
try:
model = joblib.load('model_prediksi.pkl')
encoders = joblib.load('encoders.pkl')
feature_columns = joblib.load('feature_columns.pkl')
metadata = joblib.load('model_metadata.pkl')
logger.info("Models loaded successfully")
logger.info(f"Model Type: {metadata['model_type']}")
logger.info(f"R² Score: {metadata['r2_score']:.4f}")
except Exception as e:
logger.error(f"Failed to load models: {e}")
raise
# ============================================================================
# ROUTES
# ============================================================================
@app.route('/health', methods=['GET'])
def health():
"""Health check endpoint"""
return jsonify({
'status': 'healthy',
'model_type': metadata['model_type'],
'r2_score': round(metadata['r2_score'], 4),
'timestamp': datetime.now().isoformat()
}), 200
@app.route('/metadata', methods=['GET'])
def get_metadata():
"""Get model metadata"""
return jsonify({
'status': 'success',
'model_info': {
'type': metadata['model_type'],
'r2_score': round(metadata['r2_score'], 4),
'mae': round(metadata['mae'], 4),
'rmse': round(metadata['rmse'], 4),
'features': feature_columns,
'target': metadata['target_column'],
'total_samples': metadata['total_samples']
}
}), 200
@app.route('/prediksi', methods=['POST'])
def prediksi():
"""
Predict stock demand
Body: {
"tahun": 2024,
"bulan": 4,
"hari": 4,
"hari_dalam_minggu": 3,
"harga_satuan_update": 50000,
"total_harga_update": 250000,
"produk_encoded": 2,
"nama_produk_encoded": 2,
"kategori_produk_encoded": 1,
"hari_minggu": 3
}
"""
try:
data = request.json
# Validate required fields
required_fields = feature_columns
missing_fields = [f for f in required_fields if f not in data]
if missing_fields:
return jsonify({
'status': 'error',
'message': f'Missing fields: {", ".join(missing_fields)}',
'required_fields': required_fields
}), 400
# Create feature array
X_pred = np.array([[data[f] for f in feature_columns]])
# Predict
prediksi_raw = model.predict(X_pred)[0]
prediksi = max(1, round(prediksi_raw))
# Return result
return jsonify({
'status': 'success',
'input': data,
'prediksi': {
'jumlah_unit': prediksi,
'nilai_raw': round(prediksi_raw, 2)
},
'model_accuracy': {
'r2_score': round(metadata['r2_score'], 4),
'mae': round(metadata['mae'], 4),
'rmse': round(metadata['rmse'], 4)
}
}), 200
except Exception as e:
logger.error(f"Prediction error: {str(e)}")
return jsonify({
'status': 'error',
'message': f'Prediction failed: {str(e)}'
}), 500
@app.route('/batch-prediksi', methods=['POST'])
def batch_prediksi():
"""
Batch prediction for multiple items
Body: {
"items": [
{"tahun": 2024, "bulan": 4, ...},
{"tahun": 2024, "bulan": 5, ...}
]
}
"""
try:
data = request.json
if 'items' not in data or not isinstance(data['items'], list):
return jsonify({
'status': 'error',
'message': 'Body harus berisi "items" array'
}), 400
results = []
for i, item in enumerate(data['items']):
try:
# Check required fields
missing_fields = [f for f in feature_columns if f not in item]
if missing_fields:
results.append({
'index': i,
'status': 'error',
'message': f'Missing fields: {", ".join(missing_fields)}'
})
continue
# Create feature array
X_pred = np.array([[item[f] for f in feature_columns]])
# Predict
prediksi_raw = model.predict(X_pred)[0]
prediksi = max(1, round(prediksi_raw))
results.append({
'index': i,
'status': 'success',
'prediksi': prediksi,
'nilai_raw': round(prediksi_raw, 2)
})
except Exception as e:
results.append({
'index': i,
'status': 'error',
'message': str(e)
})
return jsonify({
'status': 'success',
'total_items': len(data['items']),
'results': results
}), 200
except Exception as e:
logger.error(f"Batch prediction error: {str(e)}")
return jsonify({
'status': 'error',
'message': f'Batch prediction failed: {str(e)}'
}), 500
@app.route('/info', methods=['GET'])
def info():
"""Get API information"""
return jsonify({
'api_name': 'Prediksi Permintaan Stok Bahan',
'version': '2.0',
'model': metadata['model_type'],
'endpoints': {
'GET /health': 'API health check',
'GET /metadata': 'Get model metadata',
'GET /info': 'Get API info',
'POST /prediksi': 'Single prediction',
'POST /batch-prediksi': 'Batch prediction',
'GET /products': 'Get all products',
'POST /transactions': 'Save transaction',
'GET /transactions': 'Get transaction history'
},
'required_features': feature_columns
}), 200
# ============================================================================
# DATABASE ENDPOINTS - PRODUCTS & TRANSACTIONS
# ============================================================================
@app.route('/products', methods=['GET'])
def get_products():
"""Get all products from database"""
try:
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor(dictionary=True)
cursor.execute("SELECT * FROM products ORDER BY name")
products = cursor.fetchall()
cursor.close()
connection.close()
return jsonify({
'status': 'success',
'total': len(products),
'products': products
}), 200
except Exception as e:
logger.error(f"Get products error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
@app.route('/products/<int:product_id>', methods=['GET'])
def get_product(product_id):
"""Get specific product by ID"""
try:
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor(dictionary=True)
cursor.execute("SELECT * FROM products WHERE id = %s", (product_id,))
product = cursor.fetchone()
cursor.close()
connection.close()
if not product:
return jsonify({'status': 'error', 'message': 'Product not found'}), 404
return jsonify({
'status': 'success',
'product': product
}), 200
except Exception as e:
logger.error(f"Get product error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
@app.route('/transactions', methods=['POST'])
def save_transaction():
"""
Save transaction to database
Body: {
"product_name": "Tepung Terigu 1kg",
"category": "Tepung",
"quantity": 5,
"unit_price": 15000,
"total_price": 75000,
"transaction_date": "2024-04-05"
}
"""
try:
data = request.json
# Validate required fields
required_fields = ['product_name', 'category', 'quantity', 'unit_price', 'total_price', 'transaction_date']
missing_fields = [f for f in required_fields if f not in data]
if missing_fields:
return jsonify({
'status': 'error',
'message': f'Missing fields: {", ".join(missing_fields)}',
'required_fields': required_fields
}), 400
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor()
cursor.execute("""
INSERT INTO transactions
(product_name, category, quantity, unit_price, total_price, transaction_date)
VALUES (%s, %s, %s, %s, %s, %s)
""", (
data['product_name'],
data['category'],
data['quantity'],
data['unit_price'],
data['total_price'],
data['transaction_date']
))
connection.commit()
transaction_id = cursor.lastrowid
cursor.close()
connection.close()
logger.info(f"Transaction saved: ID={transaction_id}")
return jsonify({
'status': 'success',
'message': 'Transaction saved successfully',
'transaction_id': transaction_id
}), 201
except Exception as e:
logger.error(f"Save transaction error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
@app.route('/transactions', methods=['GET'])
def get_transactions():
"""Get transaction history"""
try:
# Get optional query parameters
limit = request.args.get('limit', 100, type=int)
offset = request.args.get('offset', 0, type=int)
product_name = request.args.get('product_name', None)
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor(dictionary=True)
# Build query
query = "SELECT * FROM transactions WHERE 1=1"
params = []
if product_name:
query += " AND product_name LIKE %s"
params.append(f"%{product_name}%")
query += " ORDER BY created_at DESC LIMIT %s OFFSET %s"
params.extend([limit, offset])
cursor.execute(query, params)
transactions = cursor.fetchall()
# Get total count
cursor.execute("SELECT COUNT(*) as total FROM transactions" +
(" WHERE product_name LIKE %s" if product_name else ""),
([f"%{product_name}%"] if product_name else []))
total = cursor.fetchone()['total']
cursor.close()
connection.close()
return jsonify({
'status': 'success',
'total': total,
'limit': limit,
'offset': offset,
'transactions': transactions
}), 200
except Exception as e:
logger.error(f"Get transactions error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
@app.route('/predictions', methods=['POST'])
def save_prediction():
"""
Save prediction result to database
Body: {
"product_name": "Tepung Terigu 1kg",
"category": "Tepung",
"unit_price": 15000,
"prediction_date": "2024-04-05",
"predicted_quantity": 45,
"raw_value": 44.8,
"estimated_total_price": 672000,
"accuracy_r2": 0.9964,
"error_mae": 2.51
}
"""
try:
data = request.json
required_fields = ['product_name', 'category', 'unit_price', 'prediction_date', 'predicted_quantity']
missing_fields = [f for f in required_fields if f not in data]
if missing_fields:
return jsonify({
'status': 'error',
'message': f'Missing fields: {", ".join(missing_fields)}'
}), 400
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor()
cursor.execute("""
INSERT INTO predictions
(product_name, category, unit_price, prediction_date, predicted_quantity,
raw_value, estimated_total_price, accuracy_r2, error_mae)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
""", (
data['product_name'],
data['category'],
data['unit_price'],
data['prediction_date'],
data['predicted_quantity'],
data.get('raw_value'),
data.get('estimated_total_price'),
data.get('accuracy_r2'),
data.get('error_mae')
))
connection.commit()
prediction_id = cursor.lastrowid
cursor.close()
connection.close()
logger.info(f"Prediction saved: ID={prediction_id}")
return jsonify({
'status': 'success',
'message': 'Prediction saved successfully',
'prediction_id': prediction_id
}), 201
except Exception as e:
logger.error(f"Save prediction error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
# ============================================================================
# RECIPES ENDPOINTS
# ============================================================================
@app.route('/recipes', methods=['GET'])
def get_recipes():
"""Get all recipes with their ingredients"""
try:
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor(dictionary=True)
# Get all recipes
cursor.execute("SELECT id, recipe_name, description FROM recipes ORDER BY recipe_name")
recipes = cursor.fetchall()
# Get ingredients for each recipe
for recipe in recipes:
cursor.execute("""
SELECT product_name, quantity_needed, unit
FROM recipe_ingredients
WHERE recipe_id = %s
ORDER BY product_name
""", (recipe['id'],))
recipe['ingredients'] = cursor.fetchall()
cursor.close()
connection.close()
return jsonify({
'status': 'success',
'total': len(recipes),
'recipes': recipes
}), 200
except Exception as e:
logger.error(f"Get recipes error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
@app.route('/recipes/<int:recipe_id>', methods=['GET'])
def get_recipe(recipe_id):
"""Get specific recipe with ingredients"""
try:
connection = get_db_connection()
if not connection:
return jsonify({'status': 'error', 'message': 'Database connection failed'}), 500
cursor = connection.cursor(dictionary=True)
# Get recipe
cursor.execute("SELECT id, recipe_name, description FROM recipes WHERE id = %s", (recipe_id,))
recipe = cursor.fetchone()
if not recipe:
cursor.close()
connection.close()
return jsonify({'status': 'error', 'message': 'Recipe not found'}), 404
# Get ingredients
cursor.execute("""
SELECT product_name, quantity_needed, unit
FROM recipe_ingredients
WHERE recipe_id = %s
ORDER BY product_name
""", (recipe_id,))
recipe['ingredients'] = cursor.fetchall()
cursor.close()
connection.close()
return jsonify({
'status': 'success',
'recipe': recipe
}), 200
except Exception as e:
logger.error(f"Get recipe error: {str(e)}")
return jsonify({'status': 'error', 'message': str(e)}), 500
@app.errorhandler(404)
def not_found(error):
return jsonify({'status': 'error', 'message': 'Endpoint tidak ditemukan'}), 404
@app.errorhandler(500)
def internal_error(error):
return jsonify({'status': 'error', 'message': 'Internal server error'}), 500
# ============================================================================
# MAIN
# ============================================================================
if __name__ == '__main__':
logger.info("=" * 80)
logger.info("Starting Prediksi Stok API")
logger.info("=" * 80)
logger.info(f"Model: {metadata['model_type']}")
logger.info(f"Accuracy (R²): {metadata['r2_score']:.4f}")
logger.info(f"Features: {len(feature_columns)}")
logger.info("Endpoints: /health, /metadata, /info, /prediksi, /batch-prediksi, /products, /transactions, /predictions, /recipes")
logger.info("Access API at: http://localhost:5000")
logger.info("=" * 80)
app.run(
debug=False,
host='0.0.0.0',
port=5000,
threaded=True
)