feat: implement RAG indexing worker with vector database schema and document embedding support
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+18
-5
@@ -19,13 +19,26 @@ import (
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func runStatistics(ctx context.Context, repo repositories.StatisticRepository) {
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log.Info().Msg("Running daily statistics...")
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today := time.Now().Truncate(24 * time.Hour)
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_, err := repo.Upsert(ctx, today)
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loc, err := time.LoadLocation("Asia/Ho_Chi_Minh")
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if err != nil {
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log.Error().Err(err).Msg("Failed to upsert system statistics")
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} else {
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log.Info().Msg("Successfully updated daily statistics and cleared cache")
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log.Warn().Err(err).Msg("Failed to load Asia/Ho_Chi_Minh timezone, falling back to fixed UTC+7")
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loc = time.FixedZone("ICT", 7*3600)
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}
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now := time.Now().In(loc)
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today := time.Date(now.Year(), now.Month(), now.Day(), 0, 0, 0, 0, time.UTC)
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// Upsert stats for today, yesterday, and the day before to prevent timezone gaps/delays
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for i := 0; i < 3; i++ {
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date := today.AddDate(0, 0, -i)
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log.Info().Str("date", date.Format("2006-01-02")).Msg("Upserting system statistics")
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_, err = repo.Upsert(ctx, date)
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if err != nil {
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log.Error().Err(err).Str("date", date.Format("2006-01-02")).Msg("Failed to upsert system statistics")
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}
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}
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log.Info().Msg("Successfully updated daily statistics and cleared cache")
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}
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func runBackup(ctx context.Context, s3 storage.Storage, dbURI string) {
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