Update app.py

app.py

@@ -3,7 +3,6 @@ from asgiref.wsgi import WsgiToAsgi
 from flask import Flask, render_template, request, jsonify
 import pickle
 import numpy as np
-import requests
 import pandas as pd
 from fastapi.middleware.wsgi import WSGIMiddleware
 
@@ -16,14 +15,18 @@ with open('model.pkl', 'rb') as model_file:
 with open('scaler.pkl', 'rb') as scaler_file:
     scaler = pickle.load(scaler_file)
 
-# Data contoh untuk windowed_data dan normalized_df, bisa diganti sesuai data nyata
-windowed_data = pd.DataFrame()  # Pastikan windowed_data ada
-normalized_df = pd.DataFrame()  # Pastikan normalized_df ada
-
 # Fungsi prediksi untuk 7 hari ke depan
-def predict_7_days(windowed_data, normalized_df, linear_model, scaler):
+def predict_7_days(sell_features, buy_features, linear_model, scaler):
+    # Data dari frontend
+    windowed_data = pd.DataFrame({
+        'sell': sell_features,
+        'buy': buy_features
+    })
+    
+    normalized_df = scaler.transform(windowed_data)
+    
     predictions = []
-    last_row = windowed_data.drop(columns=['sell', 'buy']).iloc[-1].values.reshape(1, -1)
+    last_row = normalized_df[-1].reshape(1, -1)
 
     # Iterasi untuk 7 hari ke depan
     for _ in range(7):
@@ -42,11 +45,11 @@ def predict_7_days(windowed_data, normalized_df, linear_model, scaler):
     predictions_df = pd.DataFrame(
         predictions, 
         columns=['sell', 'buy'], 
-        index=pd.date_range(start=normalized_df.index[-1] + pd.Timedelta(days=1), periods=7)
+        index=pd.date_range(start=pd.Timestamp.today(), periods=7)
     )
 
     # Harga terakhir
-    last_price = scaler.inverse_transform(normalized_df[['sell', 'buy']].iloc[-1].values.reshape(-1, 2))
+    last_price = scaler.inverse_transform(normalized_df[-1].reshape(-1, 2))
 
     # Hitung persentase perubahan harian
     predictions_df['sell_change'] = predictions_df['sell'].pct_change().fillna(0) * 100
@@ -58,7 +61,6 @@ def predict_7_days(windowed_data, normalized_df, linear_model, scaler):
 
     return predictions_df, total_sell_change, total_buy_change, last_price
 
-
 # Halaman utama
 @flask_app.route('/')
 def home():
@@ -66,8 +68,14 @@ def home():
 
 @flask_app.route('/predict', methods=['POST'])
 def predict():
+    data = request.get_json()  # Mengambil data dari request JSON
+
+    # Ambil fitur sell dan buy yang dikirim dari frontend
+    sell_features = data['sell_features']
+    buy_features = data['buy_features']
+
     # Prediksi harga untuk 7 hari ke depan
-    predictions_df, total_sell_change, total_buy_change, last_price = predict_7_days(windowed_data, normalized_df, linear_model, scaler)
+    predictions_df, total_sell_change, total_buy_change, last_price = predict_7_days(sell_features, buy_features, linear_model, scaler)
 
     # Membuat hasil prediksi untuk respons JSON
     predictions_result = []
@@ -95,6 +103,6 @@ def predict():
 
     return jsonify(result)
 
-# Menjalankan aplikasi Flask
+# Menjalankan aplikasi FastAPI yang memanggil aplikasi Flask
 app = FastAPI()
 app.mount("/", WSGIMiddleware(flask_app))