text: let fs = require("fs")
  let path = require("path")
  let modelfox = require("@modelfoxdotdev/modelfox")
  let url = require("url")
  
  // Get the path to the .modelfox file.
  let modelPath = path.join(__dirname, "heart_disease.modelfox")
  // Load the model from the path.
  let modelData = fs.readFileSync(modelPath)
  let model = new modelfox.Model(modelData.buffer)
  
  // Create an example input matching the schema of the CSV file the model was trained on. Here the data is just hard-coded, but in your application you will probably get this from a database or user input.
  let input = {
  	age: 63,
  	chest_pain: "typical angina",
  	cholesterol: 233,
  	exercise_induced_angina: "no",
  	exercise_max_heart_rate: 150,
  	exercise_st_depression: 2.3,
  	exercise_st_slope: "downsloping",
  	fasting_blood_sugar_greater_than_120: "true",
  	fluoroscopy_vessels_colored: "0",
  	gender: "male",
  	resting_blood_pressure: 145,
  	resting_ecg_result: "probable or definite left ventricular hypertrophy",
  	thallium_stress_test: "fixed defect",
  }
  
  // Make the prediction!
  let output = model.predict(input)
  
  // Print the output.
  console.log("Output:", output)
  