优化 gpt返回结果实体解析方式

VideoAnalysis/Program.cs

@@ -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;
 
 
 

VideoAnalysisCore/AICore/ChatGPT/Dto/QuestionRes.cs

@@ -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>

VideoAnalysisCore/AICore/ChatGPT/KIMI/KIMI_GPT.cs

@@ -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 = JsonSerializer.Deserialize<QuestionRes[]>(chatResContent);
-            var questionRes = JsonConvert.DeserializeObject<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)
                 {

VideoAnalysisCore/AICore/ChatGPT/KIMI/MoonshotClient.cs

@@ -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}");
         }

VideoAnalysisCore/Enum/QuestionTypeEnum.cs

@@ -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" +