57 lines
1.7 KiB
C#
57 lines
1.7 KiB
C#
using BotSharp.Core.Abstractions;
|
|
using BotSharp.Core.Agents;
|
|
using BotSharp.Core.Models;
|
|
using BotSharp.MachineLearning.NLP;
|
|
using EntityFrameworkCore.BootKit;
|
|
using Microsoft.Extensions.Configuration;
|
|
using Newtonsoft.Json.Linq;
|
|
using RestSharp;
|
|
using System;
|
|
using System.Collections.Generic;
|
|
using System.Linq;
|
|
using System.Text;
|
|
using System.Threading.Tasks;
|
|
|
|
namespace BotSharp.Core.Engines.SpaCy
|
|
{
|
|
public class SpaCyTokenizer : INlpPipeline
|
|
{
|
|
public IConfiguration Configuration { get; set; }
|
|
|
|
public async Task<bool> Train(Agent agent, JObject data, PipeModel meta)
|
|
{
|
|
var client = new RestClient(Configuration.GetSection("SpaCyProvider:Url").Value);
|
|
var request = new RestRequest("tokenizer", Method.GET);
|
|
List<List<NlpToken>> tokens = new List<List<NlpToken>>();
|
|
Boolean res = true;
|
|
var dc = new DefaultDataContextLoader().GetDefaultDc();
|
|
var corpus = agent.Corpus;
|
|
|
|
corpus.UserSays.ForEach(usersay => {
|
|
Console.WriteLine(usersay.Text);
|
|
request.AddParameter("text", usersay.Text);
|
|
var response = client.Execute<Result>(request);
|
|
|
|
tokens.Add(response.Data.Tokens);
|
|
|
|
res = res && response.IsSuccessful;
|
|
|
|
});
|
|
|
|
data.Add("Tokens", JToken.FromObject(tokens));
|
|
|
|
return res;
|
|
}
|
|
|
|
public async Task<bool> Predict(Agent agent, JObject data, PipeModel meta)
|
|
{
|
|
return true;
|
|
}
|
|
|
|
private class Result
|
|
{
|
|
public List<NlpToken> Tokens { get; set; }
|
|
}
|
|
}
|
|
}
|