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00_db_helper.R

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+# 00_db_helper.R
+library(DBI)
+library(RPostgres)
+
+# Cek apakah file .env ada di folder (biasanya saat di laptop lokal)
+# Jika tidak ada (seperti di Hugging Face), lewati saja agar tidak error
+if (file.exists(".env")) {
+  library(dotenv)
+  load_dot_env(".env")
+}
+
+
+# Fungsi sentral untuk koneksi ke Supabase
+connect_supabase <- function() {
+  dbConnect(
+    RPostgres::Postgres(),
+    host     = Sys.getenv("DB_HOST1"), 
+    dbname   = Sys.getenv("DB_NAME1"),
+    user     = Sys.getenv("DB_USER1"),
+    password = Sys.getenv("DB_PSWD1"),
+    port     = as.integer(Sys.getenv("DB_PORT1")),
+    bigint   = "integer", 
+    options  = "-c search_path=mlops"
+  ) 
+}

Dockerfile

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+# ============================================================================
+# Dockerfile untuk Deployment
+# ============================================================================
+
+FROM rocker/r-ver:4.5.0
+
+# Install system dependencies
+# Pasang dependensi sistem Linux yang dibutuhkan
+RUN apt-get update && apt-get install -y \
+    libcurl4-openssl-dev \
+    libssl-dev \
+    libxml2-dev \
+    libfontconfig1-dev \
+    libharfbuzz-dev \
+    libfribidi-dev \
+    libfreetype6-dev \
+    libpng-dev \
+    libtiff5-dev \
+    libjpeg-dev \
+    cmake \
+    libpq-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+
+# Install R packages
+# RUN R -e "install.packages(c( \
+#     'tidymodels', \
+#     'vetiver', \
+#     'pins', \
+#     'plumber', \
+#     'ranger', \
+#     'httr', \
+#     'jsonlite', \
+#     'dplyr', \
+#     'ggplot2' \
+#     ), repos='https://cloud.r-project.org/')"
+
+# 5. Salin semua file dari proyek lokal Anda ke dalam kontainer
+COPY . .
+
+# COPY renv.lock ./
+# RUN R -e "install.packages('renv'); renv::restore()"
+
+# Pasang paket R versi biner (Cepat dan Anti-Gagal Kompilasi)
+# Kita menggunakan repositori 'noble' karena rocker:4.5.0 berbasis Ubuntu 24.04
+RUN R -e "options(repos = c(CRAN = 'https://packagemanager.posit.co/cran/__linux__/noble/latest')); install.packages(c('plumber', 'vetiver', 'pins', 'DBI', 'RPostgres', 'jsonlite', 'dotenv', 'purrr', 'dplyr', 'ranger', 'tidymodels'))"
+
+# 6. Atur hak akses agar kontainer bisa menulis file (misal saat mengunduh model)
+RUN chmod -R 777 /app
+
+# 7. Berikan instruksi port dinamis (Hugging Face default adalah 7860)
+ENV PORT=7860
+EXPOSE 7860
+
+# 8. Jalankan eksekusi API Server menggunakan skrip yang sudah kita buat
+CMD ["R", "-e", "source('run_backend.R')"]

plumber.R

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+library(plumber)
+library(dplyr)
+library(DBI)
+library(RPostgres)
+library(httr2)
+library(jsonlite)
+
+source("00_db_helper.R")
+# source("backend/00_db_helper.R")
+
+# Baca statistik training sekali saja saat API start
+train_stats <- NULL
+if (file.exists("models/train_statistics.rds")) {
+  train_stats <- readRDS("models/train_statistics.rds")
+  # print(train_stats)
+} else {
+  con <- connect_supabase()
+  train_stats <- dbGetQuery(con, "SELECT * FROM mlops.train_statistics ORDER BY create_date DESC LIMIT 1")
+  DBI::dbDisconnect(con)
+}
+
+#* @filter cors
+function(req, res) {
+  res$setHeader("Access-Control-Allow-Origin", "*")
+  res$setHeader("Access-Control-Allow-Methods", "GET, POST, OPTIONS")
+  res$setHeader("Access-Control-Allow-Headers", "Content-Type, Authorization")
+
+  if (req$REQUEST_METHOD == "OPTIONS") {
+    res$status <- 200
+    return(list())
+  }
+  plumber::forward()
+}
+
+#* Mengambil ringkasan performa model
+#* @param window:int Ukuran window data
+#* @get /performance
+function(window = 100) {
+  con <- connect_supabase()
+  db_res <- dbGetQuery(con,  
+    "SELECT predicted_value FROM mlops.predictions ORDER BY timestamp DESC LIMIT $1", 
+    list(as.integer(window))
+  )
+  
+  total_db_res <- dbGetQuery(con, "SELECT count(predicted_value) as total FROM mlops.predictions")
+  dbDisconnect(con)
+  
+  if(nrow(db_res) == 0) {
+    return(list(total = 0, mean_pred = NA, sd_pred = NA))
+  }
+  
+  list(
+    total = total_db_res$total,
+    window = window, 
+    mean_pred = mean(db_res$predicted_value, na.rm = TRUE),
+    sd_pred = sd(db_res$predicted_value, na.rm = TRUE),
+    min_pred = min(db_res$predicted_value, na.rm = TRUE),
+    max_pred = max(db_res$predicted_value, na.rm = TRUE)
+  )
+}
+
+#* Mengambil data logs dan drift yang sudah diproses
+#* @param window:int Ukuran window data
+#* @param drift_feature:str Fitur yang ingin dihitung Z-Score nya
+#* @get /logs-drift
+function(window = 100) {
+  con <- connect_supabase()
+  query_sql <- "
+  WITH exploded_data AS (
+    SELECT 
+      request_id,
+      timestamp,
+      variant, version, row_id, 
+      predicted_value,
+      (input_features->>'displ')::numeric AS displ,
+      (input_features->>'year')::numeric AS year,
+      (input_features->>'cyl')::numeric AS cyl,
+      (input_features->>'class')::text as class, 
+      status, 
+      COALESCE(error_message::text, '') AS error_message
+    FROM mlops.predictions
+    WHERE status = 'SUCCESS'
+    ORDER BY timestamp DESC
+    LIMIT %d
+  )
+  SELECT 
+    *,
+    ABS(displ - %f) / %f AS z_displ,
+    ABS(year - %f) / %f AS z_year,
+    ABS(cyl - %f) / %f AS z_cyl
+  FROM exploded_data;
+  "
+  # print(train_stats)
+  query_filled <- sprintf(
+    query_sql,
+    as.integer(window),
+    train_stats$displ_mean, train_stats$displ_sd,
+    train_stats$year_mean, train_stats$year_sd,
+    train_stats$cyl_mean, train_stats$cyl_sd
+  )
+  # print(query_filled)
+
+  final_data <- dbGetQuery(con, query_filled)
+  # print("final_data:")
+  # print(head(final_data))
+  # print(str(final_data))
+  
+  # Jika query kosong, langsung kembalikan data frame kosong
+  if(nrow(final_data) == 0) {
+    dbDisconnect(con)
+    return(list(data = data.frame()))
+  }
+
+  actuals_db <- tryCatch({
+    dbGetQuery(con, "SELECT request_id, row_id, actual_value FROM mlops.actuals;")
+  }, error = function(e) { 
+    data.frame(request_id = character(), row_id = character(), actual_value = numeric()) 
+  })
+  dbDisconnect(con)
+  
+  
+  # Gabung Actual
+  # print(nrow(actuals_db) > 0) 
+  # print("row_id" %in% names(final_data))
+  if (nrow(actuals_db) > 0 && "row_id" %in% names(final_data)) {
+    actuals_db$request_id <- as.character(actuals_db$request_id)
+    actuals_db$row_id <- as.character(actuals_db$row_id)
+    final_data <- final_data %>% 
+      left_join(actuals_db, by = c("request_id", "row_id"))
+    # print(final_data)
+  } else {
+    final_data$actual_value <- NA_real_
+  }
+  # print("final_data:")
+  # print(nrow(final_data))
+  # print(str(final_data))
+    
+  return(final_data)
+}

run_backend.R

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+plumber::plumb("backend/plumber.R")$run(port=7860)