# ============================================================================
# Script 3: Run API Server
# ============================================================================

# -------------------------------------------------------------------------
# 🟢 PENYESUAIAN HUGGING FACE: Penarikan Model & File Pendukung
# -------------------------------------------------------------------------

library(plumber)

if (!dir.exists("models")) {
  dir.create("models")
}

# Fungsi pembantu agar tidak menulis kode download berulang-ulang
download_from_hf <- function(file_name) {
  hf_url <- paste0("https://huggingface.co/aephidayatuloh/mpg_highway_model/resolve/main/", file_name)
  local_path <- paste0("models/", file_name)
  
  if (!file.exists(local_path)) {
    message(paste("--- Menarik", file_name, "dari Hugging Face... ---"))
    tryCatch({
      download.file(hf_url, local_path, mode = "wb")
    }, error = function(e) {
      message(paste("⚠️ Gagal mengunduh", file_name, ":", e$message))
    })
  }
}

# Tarik semua file yang dibutuhkan API dan Dashboard Anda
download_from_hf("mpg_highway_model.rds")
download_from_hf("train_statistics.rds")
download_from_hf("train_data.rds")
# Jika Anda punya file metadata, buka tanda pagar di bawah ini:
# download_from_hf("model_metadata.rds")
 
source("02_api_plumber.R")

# Deteksi Port Dinamis (Kritis untuk Hugging Face Spaces!)
# Jika variabel PORT kosong (saat dijalankan di laptop lokal), otomatis pakai 8000.
port <- as.numeric(Sys.getenv("PORT", 8000))

# Run server
cat("🚀 Starting API server...\n")
cat(paste0("📊 API documentation available at /__docs__/\n"))
cat("💚 Prediction endpoint: /predict_custom\n")
cat("💚 Health check: /ping\n")
cat("🔍 Metadata info: /metadata\n")

api %>% 
  pr_run(
    host = "0.0.0.0", 
    port = port, 
    docs = TRUE
  )