2.0 KiB
2.0 KiB
Stateless executor
using LLama.Common;
using LLama.Examples.Extensions;
namespace LLama.Examples.Examples
{
// Basic usage of the stateless executor.
public class StatelessModeExecute
{
public static async Task Run()
{
string modelPath = UserSettings.GetModelPath();
var parameters = new ModelParams(modelPath)
{
ContextSize = 1024,
Seed = 1337,
GpuLayerCount = 5
};
using var model = LLamaWeights.LoadFromFile(parameters);
var ex = new StatelessExecutor(model, parameters);
Console.ForegroundColor = ConsoleColor.Yellow;
Console.WriteLine("The executor has been enabled. In this example, the inference is an one-time job. That says, the previous input and response has " +
"no impact on the current response. Now you can ask it questions. Note that in this example, no prompt was set for LLM and the maximum response tokens is 50. " +
"It may not perform well because of lack of prompt. This is also an example that could indicate the importance of prompt in LLM. To improve it, you can add " +
"a prompt for it yourself!");
Console.ForegroundColor = ConsoleColor.White;
var inferenceParams = new InferenceParams() { Temperature = 0.6f, AntiPrompts = new List<string> { "Question:", "#", "Question: ", ".\n" }, MaxTokens = 50 };
while (true)
{
Console.Write("\nQuestion: ");
Console.ForegroundColor = ConsoleColor.Green;
var prompt = Console.ReadLine();
Console.ForegroundColor = ConsoleColor.White;
Console.Write("Answer: ");
prompt = $"Question: {prompt?.Trim()} Answer: ";
await foreach (var text in ex.InferAsync(prompt, inferenceParams).Spinner())
{
Console.Write(text);
}
}
}
}
}