111 lines
3.2 KiB
Go
111 lines
3.2 KiB
Go
package main
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import (
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"fmt"
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"math/rand"
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"time"
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"hr_receiver/config"
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"hr_receiver/models"
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)
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func main() {
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config.InitConfig()
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config.ConnectDB()
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// 生成100条测试数据
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count := 100
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records := make([]models.AIAnalysisRecord, 0, count)
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for i := 0; i < count; i++ {
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records = append(records, generateRecord())
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}
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if err := config.DB.CreateInBatches(records, 50).Error; err != nil {
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panic("failed to insert mock data: " + err.Error())
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}
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fmt.Printf("成功插入 %d 条 AI 分析记录\n", count)
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}
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func generateRecord() models.AIAnalysisRecord {
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// regionID 为 1 或 3
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regionID := uint32(1)
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if rand.Intn(2) == 1 {
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regionID = 3
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}
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// sourceType: upload 或 cloud
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sourceType := "upload"
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if rand.Intn(2) == 1 {
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sourceType = "cloud"
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}
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// docx 教案原始文件大小: 50KB ~ 500KB
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docxSize := int64(rand.Intn(451*1024) + 50*1024)
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// 心率 csv 原始文件大小: 约 80KB (70KB ~ 90KB)
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csvSize := int64(rand.Intn(20*1024) + 70*1024)
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// 步数 csv 原始文件大小: 约 20KB ~ 40KB (heart_rate_with_steps 时才有)
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var stepCsvSize int64
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analysisType := analysisType()
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if analysisType == "heart_rate_with_steps" {
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stepCsvSize = int64(rand.Intn(20*1024) + 20*1024)
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}
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originalFileSize := docxSize + csvSize + stepCsvSize
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// 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%
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compressedDocx := int64(float64(docxSize) * (0.3 + rand.Float64()*0.3))
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compressedCsv := int64(float64(csvSize) * (0.22 + rand.Float64()*0.08)) // ~22%-30%
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var compressedStepCsv int64
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if stepCsvSize > 0 {
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compressedStepCsv = int64(float64(stepCsvSize) * (0.22 + rand.Float64()*0.08))
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}
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compressedContentSize := compressedDocx + compressedCsv + compressedStepCsv
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// prompt 大小 = 压缩后内容 + 提示词模板 (~1.5KB)
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promptTemplateSize := 1500 + rand.Intn(500)
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inputSizeBytes := int(compressedContentSize) + promptTemplateSize
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// AI 输出大小: 3KB ~ 25KB (分析报告)
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outputSizeBytes := rand.Intn(22*1024) + 3*1024
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// token 估算: 中文混合场景，平均约 3.5 字节/token
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inputTokens := inputSizeBytes / (3 + rand.Intn(2))
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outputTokens := outputSizeBytes / (3 + rand.Intn(2))
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// 分析时长: 主要和输出 token 数量相关，1分钟以内
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// 基础延迟 500ms + 每token约 15~40ms
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tokenLatency := int64(15 + rand.Intn(26))
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durationMs := 500 + int64(outputTokens)*tokenLatency
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if durationMs > 60000 {
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durationMs = 60000 - int64(rand.Intn(5000))
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}
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// 上传时间: 最近 90 天内随机
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uploadTime := time.Now().Add(-time.Duration(rand.Intn(90*24)) * time.Hour).Add(-time.Duration(rand.Intn(60)) * time.Minute).UnixMilli()
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return models.AIAnalysisRecord{
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RegionID: ®ionID,
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SourceType: sourceType,
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InputTokens: inputTokens,
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OutputTokens: outputTokens,
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InputSizeBytes: inputSizeBytes,
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OutputSizeBytes: outputSizeBytes,
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DurationMs: durationMs,
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OriginalFileSize: originalFileSize,
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CompressedContentSize: compressedContentSize,
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UploadTime: uploadTime,
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}
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}
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func analysisType() string {
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// 约 30% 的带步数分析
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if rand.Intn(100) < 30 {
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return "heart_rate_with_steps"
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}
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return "heart_rate_only"
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}
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