54 lines
1.8 KiB
C#
54 lines
1.8 KiB
C#
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using BotSharp.Core.Abstractions;
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using BotSharp.Core.Agents;
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using BotSharp.Core.Models;
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using DotNetToolkit;
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using Microsoft.Extensions.Configuration;
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using Newtonsoft.Json;
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using Newtonsoft.Json.Linq;
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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.Threading.Tasks;
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namespace BotSharp.Core.Engines
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{
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public class BotPreditor
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{
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public async Task<string> Predict(Agent agent, AIRequest request)
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{
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// load model
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var dir = Path.Join(AppDomain.CurrentDomain.GetData("DataPath").ToString(), "ModelFiles", agent.Id);
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Console.WriteLine($"Load model from {dir}");
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var metaJson = File.ReadAllText(Path.Join(dir, "metadata.json"));
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var meta = JsonConvert.DeserializeObject<ModelMetaData>(metaJson);
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// Get NLP Provider
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var config = (IConfiguration)AppDomain.CurrentDomain.GetData("Configuration");
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var assemblies = (string[])AppDomain.CurrentDomain.GetData("Assemblies");
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var providerPipe = meta.Pipeline.First();
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var provider = TypeHelper.GetInstance(providerPipe.Name, assemblies) as INlpPipeline;
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provider.Configuration = config.GetSection(meta.Platform);
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var data = JObject.FromObject(new
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{
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});
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await provider.Train(agent, data, providerPipe);
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meta.Pipeline.RemoveAt(0);
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// pipe process
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meta.Pipeline.ForEach(async pipeMeta =>
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{
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var pipe = TypeHelper.GetInstance(pipeMeta.Name, assemblies) as INlpPipeline;
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pipe.Configuration = provider.Configuration;
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await pipe.Predict(agent, data, pipeMeta);
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});
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return "";
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}
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}
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}
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