Add Dockerfile, main.py, model.h5, requirements, scaler

Dockerfile

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+# Gunakan base image Python yang kompatibel dengan TensorFlow di requirements.txt Anda
+# Python 3.10 atau 3.11 direkomendasikan untuk TensorFlow versi terbaru.
+FROM python:3.10-slim
+
+# Set direktori kerja di dalam container
+WORKDIR /app
+
+# Salin file requirements.txt terlebih dahulu untuk memanfaatkan cache Docker
+COPY requirements.txt .
+
+# Instal semua dependensi Python dari requirements.txt
+# --no-cache-dir digunakan untuk mengurangi ukuran image
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Salin semua file proyek lainnya (main.py, model.h5, scaler.joblib, dll.)
+# ke dalam direktori kerja (/app) di container.
+COPY . .
+
+# Ekspos port tempat aplikasi FastAPI akan berjalan (sesuai dengan CMD di bawah)
+EXPOSE 7860
+
+# Perintah untuk menjalankan aplikasi FastAPI menggunakan Uvicorn
+# "--host 0.0.0.0" membuat aplikasi dapat diakses dari luar container.
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

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+# -*- coding: utf-8 -*-
+"""main.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1BUdDfCHYR8XGZnFHDOP2QK8rR1GXqNv3
+"""
+
+import os
+import numpy as np
+import pandas as pd
+import joblib
+import tensorflow as tf
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from enum import Enum
+
+# Load model dan scaler
+model_path = "model.h5"
+scaler_path = "scaler.joblib"
+
+try:
+    model = tf.keras.models.load_model(model_path, compile=False)
+    scaler = joblib.load(scaler_path)
+except Exception as e:
+    model = None
+    scaler = None
+    print("Gagal memuat model atau scaler:", e)
+
+# Fitur yang digunakan saat pelatihan
+features = [
+    "age", "hypertension", "heart_disease", "bmi",
+    "female", "male",
+    "no_info_smoke", "current_smoke", "ever_smoke",
+    "former_smoke", "never_smoke", "no_current_smoke"
+]
+
+# Enum untuk input gender dan riwayat merokok
+class Gender(str, Enum):
+    female = "Female"
+    male = "Male"
+
+class Smoke(str, Enum):
+    never = "never"
+    no_info = "No Info"
+    current = "current"
+    ever = "ever"
+    former = "former"
+    not_current = "not current"
+
+# Skema input
+class InputData(BaseModel):
+    age: int
+    hypertension: int
+    heart_disease: int
+    bmi: float
+    gender: Gender
+    smoking_history: Smoke
+
+# Inisialisasi FastAPI
+app = FastAPI(title="Simple Diabetes Predictor")
+
+@app.get("/")
+def home():
+    return {"message": "API siap digunakan"}
+
+@app.post("/predict/")
+def predict(data: InputData):
+    if model is None or scaler is None:
+        raise HTTPException(status_code=500, detail="Model belum dimuat.")
+
+    df = pd.DataFrame([data.dict()])
+
+    # One-hot encoding manual
+    df["female"] = int(data.gender == "Female")
+    df["male"] = int(data.gender == "Male")
+
+    for col in ["no_info_smoke", "current_smoke", "ever_smoke", "former_smoke", "never_smoke", "no_current_smoke"]:
+        df[col] = 0
+
+    smoke_map = {
+        "No Info": "no_info_smoke",
+        "current": "current_smoke",
+        "ever": "ever_smoke",
+        "former": "former_smoke",
+        "never": "never_smoke",
+        "not current": "no_current_smoke"
+    }
+    smoke_col = smoke_map.get(data.smoking_history.value, None)
+    if smoke_col:
+        df[smoke_col] = 1
+
+    df = df[features]  # urutkan kolom
+    scaled = scaler.transform(df)
+    pred = model.predict(scaled)[0]
+
+    if len(pred) == 1:
+        prob = float(pred[0])
+        label = int(prob > 0.5)
+        return {"diabetes_probability": round(prob, 4), "prediction": label}
+    else:
+        prob = float(pred[1])
+        return {"diabetes_probability": round(prob, 4), "prediction": int(np.argmax(pred))}

model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:410846166ffcb5ee46577a4871e3f59f1b81ffb072ab571dd016db75d65f297c
+size 17960

scaler.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2843a8c45446955abb8d70dad272bb71de19f6f26469024bcb788bb1938af0ac
+size 903