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优化 gpt返回结果实体解析方式

This commit is contained in:
小肥羊 2024-11-27 11:48:06 +08:00
parent d3cf043e09
commit 8f4f48fd66
5 changed files with 36 additions and 25 deletions
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5
VideoAnalysis/Program.cs
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@ -1,16 +1,11 @@
using VideoAnalysisCore.Common;
using VideoAnalysisRazor;
using Learn.VideoAnalysis.Components;
using Microsoft.OpenApi.Models;
using AntDesign.ProLayout;
using VideoAnalysisCore.AICore.ChatGPT;
using VideoAnalysisCore.AICore.ChatGPT.KIMI;
using VideoAnalysisCore.AICore.SherpaOnnx;
using SqlSugar;
using Mapster;
using VideoAnalysisCore.AICore.ChatGPT.Dto;
using System.Text.Json;
using Newtonsoft.Json;

20
VideoAnalysisCore/AICore/ChatGPT/Dto/QuestionRes.cs
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@ -4,6 +4,7 @@ using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Text.Json;
using System.Text.Json.Nodes;
using System.Threading.Tasks;
@ -18,7 +19,24 @@ namespace VideoAnalysisCore.AICore.ChatGPT.Dto
/// <summary>
/// 结果
/// </summary>
public JToken 结果 { get; set; }
public JsonDocument 结果 { get; set; }
/// <summary>
/// 转换结果为对象
/// </summary>
/// <typeparam name="T"></typeparam>
/// <returns></returns>
public T? ToObject<T>()
{
try
{
return System.Text.Json.JsonSerializer.Deserialize<T>(结果.RootElement.GetRawText());
}
catch
{
return default;
}
}
/// <summary>
/// 问题解释
/// </summary>

24
VideoAnalysisCore/AICore/ChatGPT/KIMI/KIMI_GPT.cs
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@ -14,7 +14,6 @@ using VideoAnalysisCore.Enum;
using System.Reflection;
using FreeRedis;
using VideoAnalysisCore.Model.Dto;
using Newtonsoft.Json;
using AntDesign;
using SqlSugar.IOC;
@ -86,7 +85,7 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
var modelId = reqTokenCount > 32 * 1000 ? "moonshot-v1-128k" : "moonshot-v1-32k";
var chatRep = new ChatReq
{
max_tokens = 32*1024 - (reqTokenCount + 20),
max_tokens = 32*1024 - (reqTokenCount + 30),
temperature = 0.3f,
frequency_penalty = 0,
presence_penalty = 0,
@ -100,14 +99,13 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
RedisExpand.SetTaskGPTCached(task, chatResp);
if (chatResp is null || chatResp.error != null)
throw new Exception($"KIMI模型返回异常 Chat 返回参数: " +
$" {System.Text.Json.JsonSerializer.Serialize(chatResp)}");
$" {JsonSerializer.Serialize(chatResp)}");
var chatResContent = chatResp?.choices.FirstOrDefault()?.message.content;
if (chatResContent is null)
throw new Exception("KIMIGPT返回message无效结果");
var questionRes = JsonConvert.DeserializeObject<QuestionRes[]>(chatResContent);
var questionRes = JsonSerializer.Deserialize<QuestionRes[]>(chatResContent);
var gptRes = new TaskRes(captions);
if (questionRes is null)
throw new Exception("KIMIGPT返回无效结果");
@ -119,20 +117,20 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
var criteriaDic = criteriaArr.ToDictionary(s => s.Id);
gptRes.Assessment = new AssessmentDto()
{
Bad = arr1.Where(s => s.结果.ToObject<int>() < 6)
Bad = arr1.Where(s => s.ToObject<int>() < 6)
.Select(s => new CourseCriteria()
{
Id = criteriaDic[s.问题编号].Id,
ImprovedMethods = criteriaDic[s.问题编号].ImprovedMethods,
Analyze = s.问题解释 ?? string.Empty,
Score = s.结果.ToObject<int>(),
Score = s.ToObject<int>(),
Prompt = criteriaDic[s.问题编号].Flaw,
}).ToArray(),
Merit = arr1.Where(s => s.结果.ToObject<int>() >= 6)
Merit = arr1.Where(s => s.ToObject<int>() >= 6)
.Select(s => new CourseCriteria()
{
Id = criteriaDic[s.问题编号].Id,
Score = s.结果.ToObject<int>(),
Score = s.ToObject<int>(),
//ImprovedMethods = criteriaDic[s.问题编号].ImprovedMethods,
Analyze = s.问题解释 ?? string.Empty,
Prompt = criteriaDic[s.问题编号].Advantage,
@ -140,18 +138,18 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
};
//高频词汇
gptRes.Hotwords = arr2[(int)QuestionTypeEnum.高频词].结果.ToObject<string[]>() ?? ["暂无数据"];
gptRes.Hotwords = arr2[(int)QuestionTypeEnum.高频词].ToObject<string[]>() ?? ["暂无数据"];
//时间段概览
gptRes.TimeOverview = arr2[(int)QuestionTypeEnum.时间段概览]
.结果.ToObject<TimeBase[]>();
.ToObject<TimeBase[]>();
//提问类型
gptRes.QuestionType = arr2[(int)QuestionTypeEnum.提问类型]
.结果.ToObject<Dictionary<TeacherAnswerTypeEnum, int>>();
.ToObject<Dictionary<TeacherAnswerTypeEnum, int>>();
//分析上课时间段情况 分析 独立学习 小组合作 随堂练习等情况
var extraTimeBase = arr2[(int)QuestionTypeEnum.额外课堂情况]
.结果.ToObject<TimeBase[]>();
.ToObject<TimeBase[]>();
if (extraTimeBase is not null)
foreach (var item in extraTimeBase)
{

10
VideoAnalysisCore/AICore/ChatGPT/KIMI/MoonshotClient.cs
View File

@ -56,7 +56,7 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
/// <returns>Return HttpResponseMessage for SSE</returns>
public async Task<ChatRes?> Chat(ChatReq chatReq)
{
var requestBody = Newtonsoft.Json.JsonConvert.SerializeObject(chatReq);
var requestBody = System.Text.Json.JsonSerializer.Serialize(chatReq);
var chatResp = await PostJsonStreamAsync("/v1/chat/completions", requestBody);
return await chatResp.Content.ReadFromJsonAsync<ChatRes>();
}
@ -84,7 +84,7 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
var responseObj = JToken.Parse(responseText);
return responseObj?["data"]?["total_tokens"]?.ToObject<int>();
}
var error = Newtonsoft.Json.JsonConvert.DeserializeObject<ErrorResponse>(responseText);
var error = JsonConvert.DeserializeObject<ErrorResponse>(responseText);
_logger.LogError($"{error?.error?.type}: {error?.error?.message}");
throw new Exception($"{error?.error.type}: {error?.error.message}");
}
@ -97,7 +97,7 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
/// <returns></returns>
public async Task<int?> GetAsTiMateTokenCount(ChatReq chatReq)
{
var chatReqText = Newtonsoft.Json.JsonConvert.SerializeObject(chatReq);
var chatReqText = JsonConvert.SerializeObject(chatReq);
return await GetAsTiMateTokenCount(chatReqText);
}
@ -226,9 +226,9 @@ namespace VideoAnalysisCore.AICore.ChatGPT.KIMI
var responseText = await response.Content.ReadAsStringAsync();
if (response.IsSuccessStatusCode)
{
return Newtonsoft.Json.JsonConvert.DeserializeObject<T>(responseText) ?? default;
return JsonConvert.DeserializeObject<T>(responseText) ?? default;
}
var error = Newtonsoft.Json.JsonConvert.DeserializeObject<ErrorResponse>(responseText);
var error = JsonConvert.DeserializeObject<ErrorResponse>(responseText);
_logger.LogError($"{error?.error.type}: {error?.error.message}");
throw new Exception($"{error?.error.type}: {error?.error.message}");
}

2
VideoAnalysisCore/Enum/QuestionTypeEnum.cs
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@ -7,7 +7,7 @@ using System.Threading.Tasks;
namespace VideoAnalysisCore.Enum
{
enum QuestionTypeEnum
public enum QuestionTypeEnum
{
[Display(Prompt = "分析授课中使用的高频词" +