优化调试工作流1的AI分析流程(知识点权重,来源,AI复查复检...)

2026-01-19 18:17:58 +08:00 · 2026-01-19 18:17:58 +08:00 · a2d14487cb
parent b4b02cfbd3
commit a2d14487cb
10 changed files with 168 additions and 86 deletions
--- a/VideoAnalysisCore/AICore/GPT/DeepSeek/DeepSeekGPTClient.cs
+++ b/VideoAnalysisCore/AICore/GPT/DeepSeek/DeepSeekGPTClient.cs
@ -42,7 +42,7 @@ namespace VideoAnalysisCore.AICore.GPT.ChatGPT
        /// <param name="max_tokens">最大token <para>不设置默认最大值 16000/8000</para></param>
        /// <returns></returns>
        /// <exception cref="Exception"></exception>
-        public override async Task<T> ChatAsync<T>(string task, string postMessages, string title, string model =null, int max_tokens = 16000)
+        public override async Task<T> ChatAsync<T>(string task, string postMessages, string title, string model =null, int max_tokens = 32000)
        {
            Message[] messageArr = [
               new Message(postMessages,"user"),
@ -53,7 +53,7 @@ namespace VideoAnalysisCore.AICore.GPT.ChatGPT
                taskId = task,
                title = title,
                model = model ?? ChatGPTType.Deepseek_Reasoner,
-                max_tokens = model == ChatGPTType.Deepseek_Reasoner ? 16000 : max_tokens,
+                max_tokens = model == ChatGPTType.Deepseek_Reasoner ? 32000 : max_tokens,
                stream = true,
                temperature = 0.2f,
                messages = messageArr
--- a/VideoAnalysisCore/AICore/GPT/Dto/QuestionRes.cs
+++ b/VideoAnalysisCore/AICore/GPT/Dto/QuestionRes.cs
@ -34,9 +34,10 @@ namespace VideoAnalysisCore.AICore.GPT.Dto
    }
    public class VideoKnowPointDto
    {
+        public float KnowPointWeight { get; set; }
        public string KnowPoint { get; set; }
        public string KnowPointId { get; set; }
-        public float KnowSourceTime { get; set; }
+        public string KnowSource { get; set; }
    }
    public class VideoKnowRes
    {
@ -64,6 +65,10 @@ namespace VideoAnalysisCore.AICore.GPT.Dto
        /// </summary>
        public virtual string? KnowPoint { get; set; }
        /// <summary>
+        /// 知识点权重
+        /// </summary>
+        public virtual float? KnowPointWeight { get; set; }
+        /// <summary>
        /// 知识点ID
        /// </summary>
        public virtual string? KnowPointId { get; set; }
--- a/VideoAnalysisCore/AICore/GPT/GPTClient.cs
+++ b/VideoAnalysisCore/AICore/GPT/GPTClient.cs
@ -13,6 +13,8 @@ using System.IO;
 using VideoAnalysisCore.AICore.GPT.ChatGPT;
 using System.Threading.Tasks;
 using System.Text.Json;
+using FFmpeg.NET.Services;
+using NetTaste;

 namespace VideoAnalysisCore.AICore.GPT
 {
@ -156,7 +158,7 @@ namespace VideoAnalysisCore.AICore.GPT
        /// <param name="max_tokens">最大token <para>不设置默认最大值 16000/8000</para></param>
        /// <returns></returns>
        /// <exception cref="Exception"></exception>
-        public async Task<T> ChatAsync<T>(ChatRequest chatRep)
+        public async Task<T> ChatAsync<T>(ChatRequest chatRep) where T:class,new()
        {
            var tryCount = 10;
            while (tryCount-- > 0)
@ -186,8 +188,14 @@ namespace VideoAnalysisCore.AICore.GPT

                    if (string.IsNullOrEmpty(chatResContent))
                        throw new Exception($"GPT返回结果无有效JSON =>{chatResp?.res}");
-                    var startsStr = typeof(T).IsArray ? "[" : "{";
-                    var endStr = typeof(T).IsArray ? "]" : "}";
+                    var startsStr = "{";
+                    var endStr = "}";
+                    var resT = new T();
+                    if (resT is Array || resT is System.Collections.IList || resT is System.Collections.IList)
+                    {
+                        startsStr = "[";
+                        endStr = "]";
+                    }
                    if (!chatResContent.StartsWith(startsStr))
                        chatResContent = startsStr + chatResContent;
                    if (!chatResContent.EndsWith(endStr))
@ -271,7 +279,7 @@ namespace VideoAnalysisCore.AICore.GPT
        /// <returns></returns>
        /// <exception cref="Exception"></exception>
        public virtual Task<T> ChatAsync<T>(string task, string postMessages, string title,
-            string model = null, int max_tokens = 16000) 
+            string model = null, int max_tokens = 16000) where T : class, new()
        {
            throw new Exception("需要实现");
        }
--- a/VideoAnalysisCore/AICore/GPT/GTP_Analysis_1.cs
+++ b/VideoAnalysisCore/AICore/GPT/GTP_Analysis_1.cs
@ -22,6 +22,7 @@ using System.Collections.Generic;
 using UserCenter.Model.Enum;
 using Dm.filter;
 using System.Text.RegularExpressions;
+using System.Diagnostics;

 namespace VideoAnalysisCore.AICore.GPT.DeepSeek
 {
@ -81,28 +82,37 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
            questionRes = questionRes.Where(s => s != null)
                .OrderBy(s => s.StartTime).ToList();
            var thems = questionRes.Adapt<VideoKnowQueryDto[]>().ToJson();
-            var checkResFormat1 = """[{"StartTime":开始秒(number),"TextbookSource":教材来源(string),"KnowPoints":[{"KnowSourceTime":"知识点来源的开始秒(number)","KnowPoint":知识点名称(string),"KnowPointId":知识点Id(string)}]}]""";
+            var checkResFormat1 = """[{"StartTime":12.3,"TextbookSource":"课本","KnowPoints":[{"KnowPointWeight":0.5,"KnowSource":"开始时间(秒),匹配的原因","KnowPoint":"知识点名称","KnowPointId":"123"}]}]""";
            var knowMessages =
-              $"我针对{taskInfo.Subject}课堂授课视频分析出了视频的授课阶段片段。\n" +
-              $"现在需要你通过每个片段的内容总结来分配正确的知识点(单个片段允许多个知识点)。\n" +
-              $"KnowSourceTime字段 需要提供出知识点被匹配的字幕内容最开始的时间来源。\n" +
-              $"TextbookSource字段  需要你分析出单个片段内讲述内容所属的教材范围 例如 (范围限定在 课本/试卷/挹青苑/其他)。\n" +
-              $"这是我的分段 {thems}。\n" +
-              $"课堂内容与{sections}章节相关\n" +
-              $"最后请确保分配的知识点是用户提供的,并且一定正确合理!\n" +
-              $"返回的片段数量与传入片段数量一致!(硬性条件)\n" +
-              $"输出内容只返回json格式({checkResFormat1})\n" +
-              $" 格式 (方法点Id|方法点名称) \n" +
-              $"提供的`知识点名称({knows})。\n";
+                $"""
+                角色：你是一位{taskInfo.Subject}学科教研老师。
+                任务：为每个【视频分段】分配对应的知识点（可多个），并补充来源信息。
+                字段说明：
+                    - TextbookSource：该分段讲授内容所属教材来源，仅允许取值：课本/试卷/挹青苑/其他
+                    - KnowPoints：数组。每个元素代表一个知识点匹配结果
+                    - KnowPoint：知识点名称（必须来自我提供的列表）
+                    - KnowPointId：知识点ID（必须与 KnowPoint 对应）
+                    - KnowPointWeight：知识点在本分段的占比权重(最高为1,单个分段内的知识点权重之和必须等于1)
+                    - KnowSource：该知识点在字幕中被首次提及的“开始秒,为什么匹配的原因(最多50字)”
+                强制约束（硬性条件）：
+                    1) 输出数组长度必须与输入分段长度一致，且顺序一致；不得新增/删除/合并分段。
+                    2) 每个对象的 StartTime 必须与输入分段的 StartTime 完全一致（不得改动）。
+                    3) KnowPoints 允许为空数组（表示未能匹配任何知识点），但不要输出空字符串或用逗号拼接。
+                    4) 只输出 JSON（禁止 Markdown/解释/额外文本）。
+                输入分段：{thems}
+                章节：{sections}
+                知识点列表（Id|Name）：{knows}
+                输出格式示例：{checkResFormat1}
+                """;
            await redisManager.AddTaskLog(taskInfo.Id, "==>2.开始分析视频内容知识点");
-            VideoKnowRes[] konwRes;
+            List<VideoKnowRes> konwRes;
            var knowOK = false;
            var chatClentArr = new GPTClient[] { chatGPTClient, geminiClient, deepSeekClient };
            for (int i = 0; i < 3; i++)
            {
-                konwRes = await chatClentArr[i].ChatAsync<VideoKnowRes[]>(taskInfo.Id.ToString(), knowMessages, "知识点");
+                konwRes = await chatClentArr[i].ChatAsync<List<VideoKnowRes>>(taskInfo.Id.ToString(), knowMessages, "知识点");
                // 分析结果的片段数量与预期不匹配
-                if (questionRes.Count() != konwRes.Length) continue;
+                if (questionRes.Count() != konwRes.Count()) continue;
                for (int xi = 0; xi < konwRes.Count(); xi++)
                {
                    questionRes[xi].KnowPoints = konwRes[xi].KnowPoints;
@ -132,7 +142,9 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                        EndTime = s.EndTime,
                        StageId = StageId,
                        KnowPoint = x.KnowPoint,
-                        KnowSourceTime = x.KnowSourceTime,
+                        KnowPointWeight=x.KnowPointWeight,
+                        TextbookSource = s.TextbookSource,
+                        KnowSource = x.KnowSource,
                        KnowPointId = knowDic[x.KnowPoint].ToString(),
                        TagId = taskInfo.TagId,
                        VideoTaskId = taskInfo.Id,
@ -197,7 +209,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
            var pptFormat = taskInfo.VideoType == AttachmentsInfoType.复习
                ? "这堂课是习题课,所讲解内容几乎都是试题。"
                : string.Empty;
-            var checkResFormat = """{"Score":85.5,"MinusScore":"简洁的扣分原因","Suggestion":"改进建议"}""";
+            var checkResFormat = """{"Score":65.5,"MinusScore":"简洁的扣分原因","Suggestion":"简洁的改进建议"}""";
            var checkMessage =
                $"""
                请你担任一位专业的视频内容分析教研老师，擅长评估视频内容的结构和逻辑流暢度。
@ -209,8 +221,9 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                    知识点分配：检查分段内的知识点是否与分段Conten有关联，知识点分配给这个分段是否合理(硬性指标)。
                    逻辑过渡：评估分段之间的过渡是否自然流畅，后一段是否是前一段内容的合理延伸或转折。
                综合评分：
-                    请基于以上分析，提供一个0-100的综合得分（70分及格）。
-                    详细说明打分理由，并逐条对应到上述评估维度。
+                    请基于以上分析，提供一个0-100的综合得分（70分及格,打分一定要严谨,总分一定要准确）。
+                   MinusScore: 详细说明打分理由，并逐条对应到上述评估维度。
+                   Suggestion: 基于扣分原因提出针对分段方案的改进意见(请忽略掉分段没有结束时间的问题我会自己处理)。
                输入数据格式说明：
                    分段方案： {thems}
                    字幕文本： 格式为说话人:开始秒:结束秒:内容|下一段字幕。完整内容为：{captions.Captions}
@ -257,8 +270,8 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                输出格式（仅 JSON）：{resFormat}
                """;

-            var improved = await geminiClient.ChatAsync<VideoKnowRes[]>(taskInfo.Id.ToString(), message, "分段优化");
-            if (improved is null || improved.Length != questionRes.Count())
+            var improved = await geminiClient.ChatAsync<List<VideoKnowRes>>(taskInfo.Id.ToString(), message, "分段优化");
+            if (improved is null || improved.Count() != questionRes.Count())
                return null;

            return improved.OrderBy(s => s.StartTime ?? 0).ToList();
@ -271,7 +284,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
        private async Task<SenseVoiceRes[]> OptimizeSubtitles(VideoTask taskInfo,
            SenseVoiceRes[] captionsArr, string sections)
        {
-            if (!string.IsNullOrEmpty(taskInfo.CaptionsAI))
+            if (!string.IsNullOrEmpty(taskInfo.CaptionsAI) && taskInfo.CaptionsAI!="[]")
                return JsonSerializer.Deserialize<SenseVoiceRes[]>(taskInfo.CaptionsAI);
            var subject = taskInfo.Subject.ToString();
            var newCaptionsList = new List<SenseVoiceRes>(captionsArr.Length);
@ -306,10 +319,10 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                      $"待优化字幕内容：\n" +
                      $"{nowCaptionStr}\n" +
                      $"最终核对：请确保输出 JSON 中包含的字幕条数与输入的字幕条数完全对应。";
-                string[]? resData = null;
+                List<string>? resData = null;
                for (int i = 0; i < 3; i++)
                {
-                    resData = await chatClentArr[i].ChatAsync<string[]>(taskInfo.Id.ToString(), postMessages, "优化字幕", ChatGPTType.Deepseek_Chat, 8000);
+                    resData = await chatClentArr[i].ChatAsync<List<string>>(taskInfo.Id.ToString(), postMessages, "优化字幕", ChatGPTType.Deepseek_Chat, 8000);
                    if (resData.Count() == cArr.Count())
                        break;
                    else
@ -318,7 +331,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek

                if (resData.Count() != cArr.Count())
                {
-                    resData = cStrArr.ToArray();
+                    resData = cStrArr.ToList();
                    await redisManager.AddTaskLog(taskInfo.Id, $"==>字幕优化 分段{s} AI结果数量不匹配 采用原始值");
                }
                newCaptionsList.AddRange(resData.Select((text, i) => new SenseVoiceRes()
@ -366,13 +379,12 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                             $"完整的课堂标准流程包含以下5个阶段：课程引入/新知讲解/例题精讲/课堂练习/知识总结。\n" +
                             reviewStr +
                             $"讲解知识内容的阶段的细分程度到某个知识点的讲解/认识/例题/总结\n" +
+                             $"不分析课堂作业相关的内容我已经预处理了\n" +
                             $"初步划分阶段：{keyFrameStr}\n" +
-                             $"\n" +
-                             $"内容分析：对每个时间段，提取主要讲解内容：识别关键词（如“例题”“证明”“练习”“总结”）和内容结构。\n" +
-                             $"判断阶段类型：如果内容以解题为主，归类为“例题精讲”；如果涉及新知识讲解，归类为“新知讲解”；以此类推。\n" +
-                             $"内容总结：简述该阶段的核心讲解内容40~150字, 必须完全基于字幕文本可推断的信息，禁止捏造不存在的内容（硬性条件）。\n" +
-                             $"阶段主题：基于内容总结，提炼一个恰当的主题（例如，“柯西不等式的基本应用”）。\n" +
-                             $"输出要求：确保阶段划分合理、无重叠\n" +
+                             $"Stage：判断阶段类型如果内容以解题为主，归类为“例题精讲”；如果涉及新知识讲解，归类为“新知讲解”；以此类推。\n" +
+                             $"Content：简述单个阶段的核心讲解内容40~150字（如“例题”“证明”“练习”“总结”...）, 必须完全基于字幕文本可推断的信息，禁止捏造不存在的内容（硬性条件）。\n" +
+                             $"Theme：理解Content，提炼一个精确的主题（例如，“柯西不等式的基本应用”）。\n" +
+                             $"输出要求：确保阶段划分合理、无重叠、\n" +
                             $"作业布置阶段一般出现在末尾如果有" +
                             $"输出格式要求：内容只返回json格式({resFormat})\n" +
                             $"字幕格式(开始秒:内容|下一段字幕).以下是包含时间的视频字幕文本。\n" +
@ -424,7 +436,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                输出格式（仅 JSON）：{resFormat}
                """;

-            var res = await deepSeekClient.ChatAsync<VideoKnowRes>(taskInfo.Id.ToString(), message, "作业布置识别");
+            var res = await deepSeekClient.ChatAsync<VideoKnowRes>(taskInfo.Id.ToString(), message, "作业布置识别", ChatGPTType.Deepseek_Chat, 8000);
            if (res is null)
                return null;
            if (!string.Equals(res.Stage, "作业布置", StringComparison.OrdinalIgnoreCase))
@ -575,7 +587,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                           $"输出内容只返回json格式为({resFormat})" +
                           $"以下是试题内容" +
                           $"`{sRes.Result.res.value}`";
-                        var resData = await deepSeekClient.ChatAsync<VideoQuestionOSSDto[]>(taskInfo.Id.ToString(), postMessages, "提取试题");
+                        var resData = await deepSeekClient.ChatAsync<List<VideoQuestionOSSDto>>(taskInfo.Id.ToString(), postMessages, "提取试题");
                        //var resData = await chatClient.ChatAsync<VideoQuestionOSSDto[]>(taskInfo.Id.ToString(), postMessages, "提取试题");
                        if (resData is null || resData.Count() == 0)
                            break;
@ -704,8 +716,7 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                if (questionRes is null) continue;
                //处理分段 知识点
                List<VideoKonwPoint> insertData = await GetVideoKnow(questionRes, taskInfo, sections, knowledgeInfos);
-                if (homework != null)
-                    questionRes.Add(homework);
+                
                //校验结果质量
                var checkRes = await VerifySpanQuality(questionRes, taskInfo, captions, sections, Course_Id);

@ -715,16 +726,19 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                // 质量复检
                if (checkRes != null)
                {
-                    var improved = await ImproveSpanBySuggestion(questionRes, taskInfo, captions, sections, checkRes.Suggestion);
+                    var improved = await ImproveSpanBySuggestion(questionRes, taskInfo, captions, sections, "扣分原因 {checkRes.MinusScore}  \n 改进意见 {checkRes.Suggestion}");
                    if (improved != null)
                    {
                        var improvedCheck = await VerifySpanQuality(improved, taskInfo, captions, sections, Course_Id);
                        await redisManager.AddTaskLog(taskInfo.Id, $"==>优化后复检得分=>{improvedCheck.Score}");
                        await redisManager.AddTaskLog(taskInfo.Id, $"==>优化后扣分原因 {improvedCheck.MinusScore}");

-                        if (improvedCheck != null && improvedCheck.Score >= 90)
+                        if (improvedCheck != null && improvedCheck.Score >= 90 && improvedCheck.Score > checkRes.Score)
                        {
                            questionRes = improved;
+                            if (homework != null && (!questionRes.Any(s => s.Stage == StageEnum.作业布置.ToString())))
+                                questionRes.Add(homework);
+
                            insertData = await GetVideoKnow(questionRes, taskInfo, sections, knowledgeInfos);
                            await videoKonwPointDB.DeleteAsync(s => s.VideoTaskId == taskInfo.Id);
                            await videoTaskStageDB.DeleteAsync(s => s.VideoTaskId == taskInfo.Id);
@ -733,9 +747,10 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                                Id = s.Key,
                                TagId = s.First().TagId,
                                CloudSchoolId = s.First().CloudSchoolId,
-                                StartTime = s.Last().StartTime,
-                                EndTime =s.Last().EndTime,
-                                KnowSourceTime=s.Last().KnowSourceTime,
+                                StartTime = s.First().StartTime,
+                                EndTime = s.First().EndTime,
+                                Content = s.First().Content,
+                                TextbookSource = s.First().TextbookSource,
                                Stage = s.First().Stage,
                                Theme = s.First().Theme,
                                VideoTaskId = taskInfo.Id,
@ -744,6 +759,11 @@ namespace VideoAnalysisCore.AICore.GPT.DeepSeek
                            await videoKonwPointDB.InsertRangeAsync(insertData);
                            break;
                        }
+                        else
+                        {
+                            await redisManager.AddTaskLog(taskInfo.Id, $"==>优化之后的得分降低/得分过低");
+                            continue;
+                        }
                    }
                }

--- a/VideoAnalysisCore/AICore/GPT/Gemini/GeminiGPTClient.cs
+++ b/VideoAnalysisCore/AICore/GPT/Gemini/GeminiGPTClient.cs
@ -58,7 +58,7 @@ namespace VideoAnalysisCore.AICore.GPT.ChatGPT
                stream = true,
                temperature = 0.2f,
                messages = messageArr,
-                max_completion_tokens=16000,
+                max_completion_tokens= 12288,
            };

            chatReq.modalities = null;
--- a/VideoAnalysisCore/AICore/SherpaOnnx/SenseVoice.cs
+++ b/VideoAnalysisCore/AICore/SherpaOnnx/SenseVoice.cs
@ -143,7 +143,7 @@ namespace VideoAnalysisCore.AICore.SherpaOnnx
                throw new Exception("task 音频路径未找到");
            if (OR is null) Init();
            serviceProvider.GetRequiredService<SherpaVad>()
-               .TaskHandle(new WaveReader(filePath), null, SoundHandle, SherpaVadVersion.silero_vad_v5);
+               .TaskHandle(new WaveReader(filePath), task, SoundHandle, SherpaVadVersion.silero_vad_v5);

            return Task.CompletedTask;
        }
--- a/VideoAnalysisCore/Controllers/LJZK_Controller.cs
+++ b/VideoAnalysisCore/Controllers/LJZK_Controller.cs
@ -35,6 +35,7 @@ namespace VideoAnalysisCore.Controllers
        private readonly Repository<VideoTask> videoTaskDB;
        private readonly Repository<CourseInfo> courseInfoDB;
        private readonly Repository<VideoKonwPoint> videoKonwPointDB;
+        private readonly Repository<VideoTaskStage> videoTaskStageDB;
        private readonly Repository<NodePackageInfo> nodePackageInfoDB;
        private readonly Repository<VideoQuestion> videoQuestionDB;
        private readonly Repository<VideoQuestionKonw> videoQuestionKonwDB;
@ -42,7 +43,7 @@ namespace VideoAnalysisCore.Controllers

        public LJZK_Controller(IMapper mp, Repository<NodeSubscription> nodesubscriptionDB,
            Repository<VideoTask> videoTaskDB = null, Repository<VideoKonwPoint> videoKonwPointDB = null
-            , Repository<NodePackageInfo> nodePackageInfoDB = null, Repository<VideoQuestion> videoQuestionDB = null, Repository<VideoQuestionKonw> videoQuestionKonwDB = null, Repository<CourseInfo> courseInfoDB = null, RedisManager redisManager = null)
+            , Repository<NodePackageInfo> nodePackageInfoDB = null, Repository<VideoQuestion> videoQuestionDB = null, Repository<VideoQuestionKonw> videoQuestionKonwDB = null, Repository<CourseInfo> courseInfoDB = null, RedisManager redisManager = null, Repository<VideoTaskStage> videoTaskStageDB = null)
        {
            this.mp = mp;
            this.nodesubscriptionDB = nodesubscriptionDB;
@ -53,6 +54,7 @@ namespace VideoAnalysisCore.Controllers
            this.videoQuestionKonwDB = videoQuestionKonwDB;
            this.courseInfoDB = courseInfoDB;
            this.redisManager = redisManager;
+            this.videoTaskStageDB = videoTaskStageDB;
        }


@ -201,27 +203,49 @@ namespace VideoAnalysisCore.Controllers
                .ToArrayAsync();
            if (konwArr is null || konwArr.Length == 0)
                return BadRequest("ÎÞÓÐÐ§ÈÎÎñ·Ö¶Î");
+
+
+            var stageArr = await videoTaskStageDB.AsQueryable()
+             .Where(s => s.VideoTaskId == task.Id)
+             .ToArrayAsync();
+            var videoKnowDic = konwArr
+                .GroupBy(s => s.StageId)
+                .ToDictionary(s => s.Key);
+            var videoKnows = stageArr
+                .Select(s => new VideoKnowRes()
+                {
+                    Content = s.Content,
+                    StartTime = s.StartTime,
+                    EndTime = s.EndTime,
+                    Theme = s.Theme,
+                    StageId = s.Id,
+                    KnowPoint = videoKnowDic.ContainsKey(s.Id)
+                    ? string.Join(',', videoKnowDic[s.Id].Select(x => x.KnowPoint))
+                    : string.Empty
+                }).ToArray();
+
            var res = new TaskKnowRes()
            {
                TagId = task.TagId,
                Status = task.LastEnum,
                VideoTaskId = task.Id,
-                KnowBlockArr = konwArr
-                .GroupBy(s => s.StartTime)
+                KnowBlockArr = stageArr
                .Select(s => new TaskKnowBlock()
                {
-                    Id = s.First().Id,
-                    Content = s.First().Content,
-                    StartTime = s.First().StartTime,
-                    StageId = s.First().StageId,
-                    EndTime = s.First().EndTime,
-                    Theme = s.First().Theme,
-                    Know = s.Select(x => new TaskKnowInfo()
+                    Id = s.Id,
+                    Content = s.Content,
+                    StartTime = s.StartTime,
+                    StageId = s.Id,
+                    EndTime = s.EndTime,
+                    Theme = s.Theme,
+                    Know = videoKnowDic.ContainsKey(s.Id)
+                    ? videoKnowDic[s.Id]?.Select(x => new TaskKnowInfo()
                        {
                            Id = x.Id,
                            KnowPoint = x.KnowPoint,
-                        KnowPointId = x.KnowPointId
-                    }).ToArray()
+                            KnowPointId = x.KnowPointId,
+                        })?.ToArray()
+                    : null
                }).ToArray()
            };
            if (task.VideoType == AttachmentsInfoType.¸´Ï°)
--- a/VideoAnalysisCore/Controllers/VideoTaskController.cs
+++ b/VideoAnalysisCore/Controllers/VideoTaskController.cs
@ -33,9 +33,11 @@ namespace VideoAnalysisCore.Controllers
        readonly Repository<VideoTask> baseService;
        readonly Repository<VideoQuestion> videoQuestionDB;
        readonly Repository<VideoKonwPoint> videoKonwPointDB;
+        readonly Repository<VideoTaskStage> videoTaskStageDB;
        readonly Repository<VideoQuestionKonw> videoQuestionKonwDB;
        readonly Repository<TaskLog> taskLogDB;

+
        readonly RedisManager redisManager;
        public readonly SenseVoice senseVoice;
        public readonly FunASRNano funASRNano;
@ -43,7 +45,7 @@ namespace VideoAnalysisCore.Controllers
        private readonly IMapper mp;
        public VideoTaskController(Repository<VideoTask> baseService, RedisManager redisManager,
            Repository<VideoQuestion> videoQuestionDB,
-            Repository<VideoQuestionKonw> videoQuestionKonwDB, Repository<VideoKonwPoint> videoKonwPointDB, SenseVoice senseVoice, IMapper mp, Repository<TaskLog> taskLogDB, FunASRNano funASRNano) : base(baseService)
+            Repository<VideoQuestionKonw> videoQuestionKonwDB, Repository<VideoKonwPoint> videoKonwPointDB, SenseVoice senseVoice, IMapper mp, Repository<TaskLog> taskLogDB, FunASRNano funASRNano, Repository<VideoTaskStage> videoTaskStageDB) : base(baseService)
        {
            this.baseService = baseService;
            this.redisManager = redisManager;
@ -54,6 +56,7 @@ namespace VideoAnalysisCore.Controllers
            this.mp = mp;
            this.taskLogDB = taskLogDB;
            this.funASRNano = funASRNano;
+            this.videoTaskStageDB = videoTaskStageDB;
        }


@ -370,17 +373,23 @@ namespace VideoAnalysisCore.Controllers
            var konwArr = await videoKonwPointDB.AsQueryable()
               .Where(s => s.VideoTaskId == nowTask.Id)
               .ToArrayAsync();
-
-            var videoKnows = konwArr
-                .GroupBy(s => s.StartTime)
+            var stageArr = await videoTaskStageDB.AsQueryable()
+              .Where(s => s.VideoTaskId == nowTask.Id)
+              .ToArrayAsync();
+            var videoKnowDic = konwArr
+                .GroupBy(s => s.StageId)
+                .ToDictionary(s => s.Key);
+            var videoKnows = stageArr
                .Select(s => new VideoKnowRes()
                {
-                    Content = s.First().Content,
-                    StartTime = s.First().StartTime,
-                    EndTime = s.First().EndTime,
-                    Theme = s.First().Theme,
-                    StageId = s.First().StageId,
-                    KnowPoint = string.Join(',', s.Select(x => x.KnowPoint))
+                    Content = s.Content,
+                    StartTime = s.StartTime,
+                    EndTime = s.EndTime,
+                    Theme = s.Theme,
+                    StageId = s.Id,
+                    KnowPoint = videoKnowDic.ContainsKey(s.Id)
+                    ? string.Join(',', videoKnowDic[s.Id].Select(x => x.KnowPoint))
+                    : string.Empty
                }).ToArray();
            if (nowTask.VideoType == AttachmentsInfoType.复习)
            {
--- a/VideoAnalysisCore/Model/VideoKonwPoint.cs
+++ b/VideoAnalysisCore/Model/VideoKonwPoint.cs
@ -65,9 +65,13 @@ namespace VideoAnalysisCore.Model
        /// </summary>
        public string? KnowPointId { get; set; }
        /// <summary>
-        /// 知识点来源 视频秒
+        /// 知识点占比权重
        /// </summary>
-        public float KnowSourceTime { get; set; }
+        public float? KnowPointWeight { get; set; }
+        /// <summary>
+        /// 知识点来源
+        /// </summary>
+        public string KnowSource { get; set; }
        /// <summary>
        /// 内容总结[不写入数据库]
        /// </summary>
@ -84,5 +88,11 @@ namespace VideoAnalysisCore.Model
        /// </summary>
        [SugarColumn(IsNullable = true)]
        public long? CloudSchoolId { get; set; }
+        /// <summary>
+        /// 教材来源
+        /// <para> 课本/试卷/挹青苑 ...</para>
+        /// </summary>
+        [SugarColumn(IsIgnore = true)]
+        public virtual string? TextbookSource { get; set; }
    }
 }
--- a/VideoAnalysisCore/Model/VideoTaskStage.cs
+++ b/VideoAnalysisCore/Model/VideoTaskStage.cs
@ -54,9 +54,9 @@ namespace VideoAnalysisCore.Model
        /// </summary>
        public string? Theme { get; set; }
        /// <summary>
-        /// 知识点来源 视频秒
+        /// 知识点来源 视频秒,来源原因
        /// </summary>
-        public float KnowSourceTime { get; set; }
+        public string Content { get; set; }
        /// <summary>
        /// 课程阶段
        /// </summary>
@ -68,5 +68,11 @@ namespace VideoAnalysisCore.Model
        /// </summary>
        [SugarColumn(IsNullable = true)]
        public long? CloudSchoolId { get; set; }
+        /// <summary>
+        /// 教材来源
+        /// <para> 课本/试卷/挹青苑 ...</para>
+        /// </summary>
+        [SugarColumn(IsNullable = true)]
+        public virtual string? TextbookSource { get; set; }
    }
 }