using Microsoft.ML.OnnxRuntime;
using System.Numerics.Tensors;

 public static async Task<IActionResult> Run(
            [HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)] HttpRequest req,
            ILogger log, ExecutionContext context)
        {
            log.LogInformation("C# HTTP trigger function processed a request.");

            string review = req.Query["review"];

            string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
            dynamic data = JsonConvert.DeserializeObject(requestBody);
            review = review ?? data?.review;

            // Get path to model to create inference session.
            var modelPath = "./model.onnx";

            // create input tensor (nlp example)
            var inputTensor = new DenseTensor<string>(new string[] { review }, new int[] { 1, 1 });

            // Create input data for session.
            var input = new List<NamedOnnxValue> { NamedOnnxValue.CreateFromTensor<string>("input", inputTensor) };

            // Create an InferenceSession from the Model Path.
            var session = new InferenceSession(modelPath);

            // Run session and send input data in to get inference output. Call ToList then get the Last item. Then use the AsEnumerable extension method to return the Value result as an Enumerable of NamedOnnxValue.
            var output = session.Run(input).ToList().Last().AsEnumerable<NamedOnnxValue>();

            // From the Enumerable output create the inferenceResult by getting the First value and using the AsDictionary extension method of the NamedOnnxValue.
            var inferenceResult = output.First().AsDictionary<string, float>();

            // Return the inference result as json.
            return new JsonResult(inferenceResult);
        }