mirror of
https://github.com/nomic-ai/gpt4all
synced 2024-11-02 09:40:42 +00:00
8e89ceb54b
* added optional support for .NET logging * bump version and add missing alpha suffix * avoid creating additional namespace for extensions * prefer NullLogger/NullLoggerFactory over null-conditional ILogger to avoid errors --------- Signed-off-by: mvenditto <venditto.matteo@gmail.com>
133 lines
4.0 KiB
C#
133 lines
4.0 KiB
C#
using System.Diagnostics;
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using Gpt4All.Bindings;
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using Microsoft.Extensions.Logging;
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using Microsoft.Extensions.Logging.Abstractions;
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namespace Gpt4All;
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public class Gpt4All : IGpt4AllModel
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{
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private readonly ILLModel _model;
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private readonly ILogger _logger;
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private const string ResponseErrorMessage =
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"The model reported an error during token generation error={ResponseError}";
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/// <inheritdoc/>
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public IPromptFormatter? PromptFormatter { get; set; }
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internal Gpt4All(ILLModel model, ILogger? logger = null)
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{
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_model = model;
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_logger = logger ?? NullLogger.Instance;
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PromptFormatter = new DefaultPromptFormatter();
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}
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private string FormatPrompt(string prompt)
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{
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if (PromptFormatter == null) return prompt;
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return PromptFormatter.FormatPrompt(prompt);
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}
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public Task<ITextPredictionResult> GetPredictionAsync(string text, PredictRequestOptions opts, CancellationToken cancellationToken = default)
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{
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ArgumentNullException.ThrowIfNull(text);
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return Task.Run(() =>
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{
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_logger.LogInformation("Start prediction task");
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var sw = Stopwatch.StartNew();
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var result = new TextPredictionResult();
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var context = opts.ToPromptContext();
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var prompt = FormatPrompt(text);
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try
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{
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_model.Prompt(prompt, context, responseCallback: e =>
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{
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if (e.IsError)
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{
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_logger.LogWarning(ResponseErrorMessage, e.Response);
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result.Success = false;
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result.ErrorMessage = e.Response;
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return false;
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}
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result.Append(e.Response);
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return true;
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}, cancellationToken: cancellationToken);
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}
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catch (Exception e)
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{
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_logger.LogError(e, "Prompt error");
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result.Success = false;
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}
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sw.Stop();
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_logger.LogInformation("Prediction task completed elapsed={Elapsed}s", sw.Elapsed.TotalSeconds);
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return (ITextPredictionResult)result;
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}, CancellationToken.None);
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}
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public Task<ITextPredictionStreamingResult> GetStreamingPredictionAsync(string text, PredictRequestOptions opts, CancellationToken cancellationToken = default)
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{
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ArgumentNullException.ThrowIfNull(text);
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var result = new TextPredictionStreamingResult();
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_ = Task.Run(() =>
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{
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_logger.LogInformation("Start streaming prediction task");
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var sw = Stopwatch.StartNew();
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try
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{
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var context = opts.ToPromptContext();
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var prompt = FormatPrompt(text);
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_model.Prompt(prompt, context, responseCallback: e =>
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{
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if (e.IsError)
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{
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_logger.LogWarning(ResponseErrorMessage, e.Response);
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result.Success = false;
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result.ErrorMessage = e.Response;
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return false;
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}
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result.Append(e.Response);
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return true;
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}, cancellationToken: cancellationToken);
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}
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catch (Exception e)
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{
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_logger.LogError(e, "Prompt error");
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result.Success = false;
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}
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finally
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{
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result.Complete();
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sw.Stop();
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_logger.LogInformation("Prediction task completed elapsed={Elapsed}s", sw.Elapsed.TotalSeconds);
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}
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}, CancellationToken.None);
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return Task.FromResult((ITextPredictionStreamingResult)result);
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}
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protected virtual void Dispose(bool disposing)
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{
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if (disposing)
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{
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_model.Dispose();
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}
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}
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public void Dispose()
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{
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Dispose(true);
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GC.SuppressFinalize(this);
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}
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}
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