143 lines
3.9 KiB
Go
143 lines
3.9 KiB
Go
package worker
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import (
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"context"
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"fmt"
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"log"
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"strings"
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"time"
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"github.com/zs/InsightReply/internal/model"
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"github.com/zs/InsightReply/internal/repository"
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"github.com/zs/InsightReply/internal/scraper"
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"github.com/zs/InsightReply/internal/service"
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)
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type PerformanceWorker struct {
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repo *repository.ReplyRepository
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client *scraper.ScraperClient
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aiSvc *service.AIService
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baseUrl string
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}
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func NewPerformanceWorker(repo *repository.ReplyRepository, aiSvc *service.AIService) *PerformanceWorker {
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return &PerformanceWorker{
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repo: repo,
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client: scraper.NewScraperClient(),
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aiSvc: aiSvc,
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baseUrl: "https://x.beenglish.eu.org",
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}
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}
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// Start begins the 24h retroactive performance checking loop
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func (w *PerformanceWorker) Start(ctx context.Context, interval time.Duration) {
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log.Printf("[PerformanceWorker] Starting retroactive engagement tracking every %v", interval)
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ticker := time.NewTicker(interval)
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defer ticker.Stop()
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for {
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select {
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case <-ctx.Done():
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log.Println("[PerformanceWorker] Stopping background performance loop")
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return
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case <-ticker.C:
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w.runCycle(ctx)
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}
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}
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}
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func (w *PerformanceWorker) runCycle(ctx context.Context) {
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pending, err := w.repo.GetPendingPerformanceChecks()
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if err != nil {
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log.Printf("[PerformanceWorker] Error fetching pending checks: %v", err)
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return
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}
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for _, reply := range pending {
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// Stop processing if context cancelled
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select {
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case <-ctx.Done():
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return
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default:
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}
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xTweetID, err := w.repo.GetTweetXTweetID(reply.TweetID)
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if err != nil {
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continue
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}
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// Scrape the specific thread
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// Nitter handles /i/status/12345 generic routes
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url := fmt.Sprintf("%s/i/status/%s", w.baseUrl, xTweetID)
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log.Printf("[PerformanceWorker] Checking thread %s for user's AI reply performance", url)
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htmlData, err := w.client.Fetch(url)
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if err != nil {
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w.client.JitterDelay(2000, 5000)
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continue
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}
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threadReplies, err := scraper.ParseTimeline(htmlData)
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if err != nil {
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continue
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}
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// Search for the user's generated text within the thread replies
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found := false
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for _, threadReply := range threadReplies {
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// Basic similarity check: if 50% of the AI sentence is present
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// Real implementation might use Levenshtein distance, but strings.Contains on chunks works for MVP
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snippet := reply.Content
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if len(snippet) > 20 {
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snippet = snippet[:20]
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}
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if strings.Contains(threadReply.Content, snippet) {
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found = true
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// WE FOUND OUR REPLY! Record its metrics
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perf := &model.ReplyPerformance{
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ReplyID: reply.ID,
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UserID: reply.UserID,
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LikeCountIncrease: threadReply.Likes,
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ReplyCountIncrease: threadReply.Replies,
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CheckTime: time.Now(),
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}
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w.repo.SaveReplyPerformance(perf)
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log.Printf("[PerformanceWorker] 🎯 Verified AI reply in wild! Likes: %d, Replies: %d", perf.LikeCountIncrease, perf.ReplyCountIncrease)
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// Epic 13 AI Tone Engine: Autonomous Style Cloning for proven viral comments
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if perf.LikeCountIncrease >= 10 {
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log.Printf("[PerformanceWorker] Reply went viral! Asking AI to reverse-engineer linguistic styling.")
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styleProfile, err := w.aiSvc.ExtractStyle(ctx, reply.Content)
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if err == nil && styleProfile != "" {
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err = w.repo.SaveStyleExtraction(reply.UserID, styleProfile)
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if err != nil {
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log.Printf("[PerformanceWorker] Error saving style database mapping: %v", err)
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} else {
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log.Printf("[PerformanceWorker] Successfully built user style clone: %s", styleProfile)
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}
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}
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}
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break
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}
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}
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// Even if not found (maybe they edited heavily or didn't actually post it), we mark it as checked to prevent infinite re-checking
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if !found {
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perf := &model.ReplyPerformance{
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ReplyID: reply.ID,
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UserID: reply.UserID,
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CheckTime: time.Now(),
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}
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w.repo.SaveReplyPerformance(perf)
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}
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w.client.JitterDelay(3000, 8000)
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}
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}
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