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//* *
//* This is an auto-generated file by Microsoft ML.NET CLI (Command-Line Interface) tool. *
//* *
using System;
using System.IO;
using System.Linq;
using Microsoft.ML;
using SentimentModel.Model.DataModels;
namespace SentimentModel.ConsoleApp
class Program
//Machine Learning model to load and use for predictions
private const string MODEL_FILEPATH = @"../../../../SentimentModel.Model/";
static void Main(string[] args)
MLContext mlContext = new MLContext();
// Training code used by ML.NET CLI and AutoML to generate the model
ITransformer mlModel = mlContext.Model.Load(GetAbsolutePath(MODEL_FILEPATH), out DataViewSchema inputSchema);
var predEngine = mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(mlModel);
// Create sample data to do a single prediction with it
string inputSampleText = "ML.NET is awesome!";
ModelInput sampleData = CreateSingleDataSample(inputSampleText);
// Try a single prediction
ModelOutput predictionResult = predEngine.Predict(sampleData);
Console.WriteLine($"Single Prediction --> Prediction for '{inputSampleText}' was PositiveSentiment = {predictionResult.Prediction}");
Console.WriteLine("=============== End of process, hit any key to finish ===============");
// Here I create your my sample hard-coded data (Could be coming from an end-user app)
private static ModelInput CreateSingleDataSample(string inputTextStatement)
// Here (ModelInput object) you could provide new test data, hardcoded or from the end-user application, instead of the row from the file.
ModelInput sampleForPrediction = new ModelInput { Text = inputTextStatement };
return sampleForPrediction;
public static string GetAbsolutePath(string relativePath)
FileInfo _dataRoot = new FileInfo(typeof(Program).Assembly.Location);
string assemblyFolderPath = _dataRoot.Directory.FullName;
string fullPath = Path.Combine(assemblyFolderPath, relativePath);
return fullPath;
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