122 lines
4.2 KiB
C#
122 lines
4.2 KiB
C#
using BotSharp.Core.Agents;
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using BotSharp.Core.Engines;
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using BotSharp.Core.Engines.Rasa;
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using Microsoft.AspNetCore.Mvc;
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using Newtonsoft.Json;
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using Newtonsoft.Json.Linq;
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using Newtonsoft.Json.Serialization;
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using System;
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using System.Collections.Generic;
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using System.IO;
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using System.Linq;
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using System.Text;
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using System.Text.RegularExpressions;
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using System.Threading.Tasks;
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namespace BotSharp.RestApi.Rasa
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{
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#if RASA
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/// <summary>
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/// You can post your training data to this endpoint to train a new model for a project.
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/// This request will wait for the server answer: either the model was trained successfully or the training exited with an error.
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/// </summary>
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[Route("[controller]")]
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public class TrainController : ControllerBase
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{
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private readonly IBotPlatform _platform;
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/// <summary>
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/// Initialize dialog controller and get a platform instance
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/// </summary>
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/// <param name="platform"></param>
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public TrainController(IBotPlatform platform)
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{
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_platform = platform;
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}
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/// <summary>
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/// Using the HTTP server, you must specify the project you want to train a new model for to be able to use it during parse requests later on : /train?project=my_project.
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/// </summary>
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/// <param name="model">Model name</param>
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/// <param name="project"></param>
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/// <returns></returns>
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[HttpPost]
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public async Task<ActionResult<String>> Train([FromQuery] string model, [FromQuery] string project)
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{
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string body = "";
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using (var reader = new StreamReader(Request.Body))
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{
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body = reader.ReadToEnd();
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}
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string lang = Regex.Match(body, @"language:.+")?.Value;
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if (!String.IsNullOrEmpty(lang))
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{
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lang = lang.Substring(11, 2);
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}
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string data = Regex.Match(body, @"data:([\s\S]*)")?.Value;
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if (String.IsNullOrEmpty(data))
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{
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data = body;
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}
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else
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{
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data = data.Substring(6);
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}
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var rasa_nlu_data = JsonConvert.DeserializeObject<RasaTrainRequestModel>(data);
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rasa_nlu_data.Model = model;
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rasa_nlu_data.Project = project;
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var trainResult = await Train(rasa_nlu_data, project);
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return trainResult;
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}
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private async Task<ActionResult<String>> Train([FromBody] RasaTrainRequestModel request, [FromQuery] string project)
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{
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var trainer = new BotTrainer();
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if (String.IsNullOrEmpty(request.Project))
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{
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request.Project = project;
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}
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// save corpus to agent dir
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var projectPath = Path.Combine(AppDomain.CurrentDomain.GetData("DataPath").ToString(), "Projects", project);
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var modelPath = Path.Combine(projectPath, request.Model);
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if (!Directory.Exists(modelPath))
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{
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Directory.CreateDirectory(modelPath);
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}
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// Save raw data to file, then parse it to Agent instance.
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var metaFileName = Path.Combine(modelPath, "meta.json");
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System.IO.File.WriteAllText(metaFileName, JsonConvert.SerializeObject(new AgentImportHeader
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{
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Name = project,
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Platform = PlatformType.Rasa
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}));
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// in order to unify the process.
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var fileName = Path.Combine(modelPath, "corpus.json");
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System.IO.File.WriteAllText(fileName, JsonConvert.SerializeObject(request.Corpus, new JsonSerializerSettings
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{
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Formatting = Formatting.Indented,
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NullValueHandling = NullValueHandling.Ignore,
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ContractResolver = new CamelCasePropertyNamesContractResolver()
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}));
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var agent = _platform.LoadAgentFromFile(modelPath);
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var info = await trainer.Train(agent, new BotTrainOptions
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{
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AgentDir = projectPath,
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Model = request.Model
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});
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return Ok(new { info = info.Model });
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}
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}
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#endif
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}
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