ai-media-hub/backend/services/ranker.go

package services

import (
	"sort"
	"strings"
	"sync"
)

type GeminiBatchStats struct {
	CandidateCap     int      `json:"candidateCap"`
	Requested        int      `json:"requested"`
	Batches          int      `json:"batches"`
	Succeeded        int      `json:"succeeded"`
	Failed           int      `json:"failed"`
	RecommendedCount int      `json:"recommendedCount"`
	Errors           []string `json:"errors,omitempty"`
}

func RankSearchResults(query string, results []SearchResult) []SearchResult {
	queryTerms := strings.Fields(strings.ToLower(query))
	positiveTerms := []string{
		"b-roll", "b roll", "stock", "stock footage", "footage", "cinematic", "editorial",
		"establishing", "4k", "hd", "drone", "ambient", "scene", "urban", "cityscape",
	}
	negativeTerms := []string{
		"shocking", "amazing", "crazy", "must watch", "reaction", "gossip", "celebrity",
		"thumbnail", "meme", "prank", "drama", "breaking", "viral", "tutorial",
		"how to", "review", "walkthrough", "course", "lesson", "podcast", "interview",
		"premiere pro", "after effects", "explained", "breakdown", "vlog",
	}
	type scoredResult struct {
		item  SearchResult
		score int
	}

	scored := make([]scoredResult, 0, len(results))
	for _, result := range results {
		score := 0
		text := strings.ToLower(result.Title + " " + result.Snippet + " " + result.Source)
		for _, term := range queryTerms {
			if strings.Contains(text, term) {
				score += 3
			}
		}
		for _, term := range positiveTerms {
			if strings.Contains(text, term) {
				score += 2
			}
		}
		for _, term := range negativeTerms {
			if strings.Contains(text, term) {
				score -= 4
			}
		}
		if result.ThumbnailURL != "" {
			score += 2
		}
		if result.PreviewVideoURL != "" {
			score += 3
		}
		switch result.Source {
		case "Google Video":
			score -= 1
		case "Envato":
			score += 7
		case "Artgrid":
			score += 7
		}
		scored = append(scored, scoredResult{item: result, score: score})
	}

	sort.SliceStable(scored, func(i, j int) bool {
		return scored[i].score > scored[j].score
	})

	ranked := make([]SearchResult, 0, len(scored))
	for _, item := range scored {
		ranked = append(ranked, item.item)
	}
	return ranked
}

func GeminiCandidateLimit(total int) int {
	return total
}

func EvaluateAllCandidatesWithGemini(service *GeminiService, query string, ranked []SearchResult) ([]AIRecommendation, GeminiBatchStats) {
	const chunkSize = 8
	const maxConcurrentBatches = 2
	limit := GeminiCandidateLimit(len(ranked))
	stats := GeminiBatchStats{
		CandidateCap: limit,
		Requested:    min(limit, len(ranked)),
	}
	type batchResult struct {
		index           int
		recommendations []AIRecommendation
		err             error
	}
	batches := make([][]SearchResult, 0, (limit+chunkSize-1)/chunkSize)
	for start := 0; start < limit; start += chunkSize {
		end := start + chunkSize
		if end > limit {
			end = limit
		}
		batches = append(batches, ranked[start:end])
	}
	stats.Batches = len(batches)

	results := make([]batchResult, len(batches))
	var wg sync.WaitGroup
	sem := make(chan struct{}, maxConcurrentBatches)
	for idx, batch := range batches {
		wg.Add(1)
		go func(batchIndex int, candidates []SearchResult) {
			defer wg.Done()
			sem <- struct{}{}
			defer func() { <-sem }()
			recommended, err := service.Recommend(query, candidates)
			results[batchIndex] = batchResult{
				index:           batchIndex,
				recommendations: recommended,
				err:             err,
			}
		}(idx, batch)
	}
	wg.Wait()

	merged := make([]AIRecommendation, 0, len(ranked))
	seen := map[string]bool{}
	for _, batch := range results {
		if batch.err != nil {
			stats.Failed++
			if len(stats.Errors) < 5 {
				stats.Errors = append(stats.Errors, batch.err.Error())
			}
			continue
		}
		stats.Succeeded++
		for _, item := range batch.recommendations {
			if item.Link == "" || seen[item.Link] {
				continue
			}
			seen[item.Link] = true
			merged = append(merged, item)
		}
	}
	stats.RecommendedCount = len(merged)
	return merged, stats
}

func MergeRecommendations(recommended []AIRecommendation, ranked []SearchResult, limit int) []AIRecommendation {
	merged := make([]AIRecommendation, 0, min(limit, len(ranked)))
	seen := map[string]bool{}

	for _, item := range recommended {
		if !item.Recommended {
			continue
		}
		if item.Link == "" || seen[item.Link] {
			continue
		}
		seen[item.Link] = true
		merged = append(merged, item)
	}

	for _, item := range recommended {
		if item.Recommended || item.Link == "" || seen[item.Link] || len(merged) >= limit {
			continue
		}
		seen[item.Link] = true
		merged = append(merged, item)
	}

	for _, item := range ranked {
		if len(merged) >= limit || item.Link == "" || seen[item.Link] {
			continue
		}
		seen[item.Link] = true
		merged = append(merged, AIRecommendation{
			Title:           item.Title,
			Link:            item.Link,
			Snippet:         item.Snippet,
			ThumbnailURL:    item.ThumbnailURL,
			PreviewVideoURL: item.PreviewVideoURL,
			Source:          item.Source,
			Reason:          "Gemini Vision 응답이 부족해 키워드 기준으로 보강된 결과입니다.",
			Recommended:     false,
		})
	}
	return merged
}