From 2e1570651ac36794fc4739d4c547590802736123 Mon Sep 17 00:00:00 2001 From: laoboli <1293528695@qq.com> Date: Thu, 30 Apr 2026 08:37:19 +0800 Subject: [PATCH] feat: mock data. --- controllers/statistics.go | 65 ++++++++++++++++++---- mockdata/main.go | 110 ++++++++++++++++++++++++++++++++++++++ 2 files changed, 164 insertions(+), 11 deletions(-) create mode 100644 mockdata/main.go diff --git a/controllers/statistics.go b/controllers/statistics.go index e6e9273..8289563 100644 --- a/controllers/statistics.go +++ b/controllers/statistics.go @@ -7,6 +7,7 @@ import ( "net/http" "strconv" "strings" + "time" "github.com/gin-gonic/gin" "gorm.io/gorm" @@ -110,16 +111,19 @@ func (sc *StatisticsController) DeleteAIAnalysisRecord(c *gin.Context) { // --- 统计接口 --- type regionStatisticsItem struct { - RegionID uint32 `json:"regionId"` - Count int64 `json:"count"` - TotalInputTokens int64 `json:"totalInputTokens"` - TotalOutputTokens int64 `json:"totalOutputTokens"` - TotalInputSizeBytes int64 `json:"totalInputSizeBytes"` - TotalOutputSizeBytes int64 `json:"totalOutputSizeBytes"` - TotalDurationMs int64 `json:"totalDurationMs"` - AvgDurationMs float64 `json:"avgDurationMs"` - TotalOriginalFileSize int64 `json:"totalOriginalFileSize"` - TotalCompressedSize int64 `json:"totalCompressedSize"` + RegionID uint32 `json:"regionId"` + KindergartenName string `json:"kindergartenName"` + Count int64 `json:"count"` + TotalInputTokens int64 `json:"totalInputTokens"` + TotalOutputTokens int64 `json:"totalOutputTokens"` + TotalInputSizeBytes int64 `json:"totalInputSizeBytes"` + TotalOutputSizeBytes int64 `json:"totalOutputSizeBytes"` + TotalDurationMs int64 `json:"totalDurationMs"` + AvgDurationMs float64 `json:"avgDurationMs"` + TotalOriginalFileSize int64 `json:"totalOriginalFileSize"` + TotalCompressedSize int64 `json:"totalCompressedSize"` + FirstUsedAt *time.Time `json:"firstUsedAt"` + LastUsedAt *time.Time `json:"lastUsedAt"` } func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { @@ -154,6 +158,8 @@ func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { TotalDurationMs int64 TotalOriginalFileSize int64 TotalCompressedSize int64 + FirstUsedAt *time.Time + LastUsedAt *time.Time } var rawResults []rawStats @@ -166,7 +172,9 @@ func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { COALESCE(SUM(output_size_bytes), 0) as total_output_size_bytes, COALESCE(SUM(duration_ms), 0) as total_duration_ms, COALESCE(SUM(original_file_size), 0) as total_original_file_size, - COALESCE(SUM(compressed_content_size), 0) as total_compressed_size + COALESCE(SUM(compressed_content_size), 0) as total_compressed_size, + MIN(created_at) as first_used_at, + MAX(created_at) as last_used_at `).Group("region_id").Scan(&rawResults).Error if err != nil { @@ -174,6 +182,23 @@ func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { return } + // 收集所有 regionId 查询幼儿园名称 + regionIDs := make([]uint32, 0, len(rawResults)) + for _, r := range rawResults { + if r.RegionID != nil && *r.RegionID > 0 { + regionIDs = append(regionIDs, *r.RegionID) + } + } + kindergartenMap := make(map[uint32]string) + if len(regionIDs) > 0 { + var kindergartens []models.Kindergarten + if err := sc.DB.Where("region_id IN ?", regionIDs).Find(&kindergartens).Error; err == nil { + for _, k := range kindergartens { + kindergartenMap[k.RegionID] = k.Name + } + } + } + overall := regionStatisticsItem{} regions := make(map[string]regionStatisticsItem, len(rawResults)) @@ -186,8 +211,13 @@ func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { if r.Count > 0 { avgDuration = float64(r.TotalDurationMs) / float64(r.Count) } + kgName := "" + if regionID > 0 { + kgName = kindergartenMap[regionID] + } item := regionStatisticsItem{ RegionID: regionID, + KindergartenName: kgName, Count: r.Count, TotalInputTokens: r.TotalInputTokens, TotalOutputTokens: r.TotalOutputTokens, @@ -197,6 +227,8 @@ func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { AvgDurationMs: avgDuration, TotalOriginalFileSize: r.TotalOriginalFileSize, TotalCompressedSize: r.TotalCompressedSize, + FirstUsedAt: r.FirstUsedAt, + LastUsedAt: r.LastUsedAt, } regions[strconv.FormatUint(uint64(regionID), 10)] = item @@ -209,6 +241,17 @@ func (sc *StatisticsController) StatisticsByRegion(c *gin.Context) { overall.TotalDurationMs += r.TotalDurationMs overall.TotalOriginalFileSize += r.TotalOriginalFileSize overall.TotalCompressedSize += r.TotalCompressedSize + + if r.FirstUsedAt != nil { + if overall.FirstUsedAt == nil || r.FirstUsedAt.Before(*overall.FirstUsedAt) { + overall.FirstUsedAt = r.FirstUsedAt + } + } + if r.LastUsedAt != nil { + if overall.LastUsedAt == nil || r.LastUsedAt.After(*overall.LastUsedAt) { + overall.LastUsedAt = r.LastUsedAt + } + } } if overall.Count > 0 { diff --git a/mockdata/main.go b/mockdata/main.go new file mode 100644 index 0000000..6733a41 --- /dev/null +++ b/mockdata/main.go @@ -0,0 +1,110 @@ +package main + +import ( + "fmt" + "math/rand" + "time" + + "hr_receiver/config" + "hr_receiver/models" +) + +func main() { + config.InitConfig() + config.ConnectDB() + + // 生成100条测试数据 + count := 100 + records := make([]models.AIAnalysisRecord, 0, count) + + for i := 0; i < count; i++ { + records = append(records, generateRecord()) + } + + if err := config.DB.CreateInBatches(records, 50).Error; err != nil { + panic("failed to insert mock data: " + err.Error()) + } + + fmt.Printf("成功插入 %d 条 AI 分析记录\n", count) +} + +func generateRecord() models.AIAnalysisRecord { + // regionID 为 1 或 3 + regionID := uint32(1) + if rand.Intn(2) == 1 { + regionID = 3 + } + + // sourceType: upload 或 cloud + sourceType := "upload" + if rand.Intn(2) == 1 { + sourceType = "cloud" + } + + // docx 教案原始文件大小: 50KB ~ 500KB + docxSize := int64(rand.Intn(451*1024) + 50*1024) + + // 心率 csv 原始文件大小: 约 80KB (70KB ~ 90KB) + csvSize := int64(rand.Intn(20*1024) + 70*1024) + + // 步数 csv 原始文件大小: 约 20KB ~ 40KB (heart_rate_with_steps 时才有) + var stepCsvSize int64 + analysisType := analysisType() + if analysisType == "heart_rate_with_steps" { + stepCsvSize = int64(rand.Intn(20*1024) + 20*1024) + } + + originalFileSize := docxSize + csvSize + stepCsvSize + + // 压缩后内容大小: csv 每4行保留1行，大约压缩为 25% + 表头；docx 提取文本后大约 30%~60% + compressedDocx := int64(float64(docxSize) * (0.3 + rand.Float64()*0.3)) + compressedCsv := int64(float64(csvSize) * (0.22 + rand.Float64()*0.08)) // ~22%-30% + var compressedStepCsv int64 + if stepCsvSize > 0 { + compressedStepCsv = int64(float64(stepCsvSize) * (0.22 + rand.Float64()*0.08)) + } + compressedContentSize := compressedDocx + compressedCsv + compressedStepCsv + + // prompt 大小 = 压缩后内容 + 提示词模板 (~1.5KB) + promptTemplateSize := 1500 + rand.Intn(500) + inputSizeBytes := int(compressedContentSize) + promptTemplateSize + + // AI 输出大小: 3KB ~ 25KB (分析报告) + outputSizeBytes := rand.Intn(22*1024) + 3*1024 + + // token 估算: 中文混合场景，平均约 3.5 字节/token + inputTokens := inputSizeBytes / (3 + rand.Intn(2)) + outputTokens := outputSizeBytes / (3 + rand.Intn(2)) + + // 分析时长: 主要和输出 token 数量相关，1分钟以内 + // 基础延迟 500ms + 每token约 15~40ms + tokenLatency := int64(15 + rand.Intn(26)) + durationMs := 500 + int64(outputTokens)*tokenLatency + if durationMs > 60000 { + durationMs = 60000 - int64(rand.Intn(5000)) + } + + // 上传时间: 最近 90 天内随机 + uploadTime := time.Now().Add(-time.Duration(rand.Intn(90*24)) * time.Hour).Add(-time.Duration(rand.Intn(60)) * time.Minute).UnixMilli() + + return models.AIAnalysisRecord{ + RegionID: ®ionID, + SourceType: sourceType, + InputTokens: inputTokens, + OutputTokens: outputTokens, + InputSizeBytes: inputSizeBytes, + OutputSizeBytes: outputSizeBytes, + DurationMs: durationMs, + OriginalFileSize: originalFileSize, + CompressedContentSize: compressedContentSize, + UploadTime: uploadTime, + } +} + +func analysisType() string { + // 约 30% 的带步数分析 + if rand.Intn(100) < 30 { + return "heart_rate_with_steps" + } + return "heart_rate_only" +}