342 lines
11 KiB
Go
342 lines
11 KiB
Go
package usecase
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import (
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"crypto/sha256"
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"encoding/hex"
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"net/url"
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"strconv"
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"strings"
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"unicode/utf8"
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"apps/backend/internal/module/scout/domain"
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)
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type classifiedPost struct {
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classification string
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score int
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reason string
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}
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// planScanTerms builds independent search queries (one query per term).
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// Callers fan out: each ScanTerms[i] is searched separately then merged.
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// Avoids dumping all keywords into one diluted Exa query.
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func planScanTerms(brief *domain.RunBrief) []string {
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if brief == nil {
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return nil
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}
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if brief.Mode == domain.ModeActivity {
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return capTerms(dedupeTerms([]string{brief.Intent}, tokenizeIntent(brief.Intent)), 6)
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}
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if brief.Mode == domain.ModeProvider {
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return planProviderTerms(brief.Pains, brief.Tags)
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}
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if brief.Mode == domain.ModeDemand {
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return planDemandTerms(brief.Pains)
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}
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pains := filterSeekablePains(brief.Pains)
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tags := filterSeekablePains(brief.Tags)
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var queries []string
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intent := strings.TrimSpace(brief.Intent)
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if intent != "" {
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if utf8.RuneCountInString(intent) > 48 {
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intent = truncateRunes(intent, 48)
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}
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queries = append(queries, intent)
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}
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for _, p := range pains {
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if !strings.EqualFold(p, intent) {
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queries = append(queries, p)
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}
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}
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for _, tag := range tags {
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if !strings.EqualFold(tag, intent) {
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queries = append(queries, tag)
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}
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}
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// 對前幾個短痛點加求助語感 variant（整句當一 query，不是單獨搜「求推薦」）
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for _, p := range capTerms(pains, 3) {
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if utf8.RuneCountInString(p) <= 18 {
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queries = append(queries, p+" 求推薦")
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}
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}
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return capTerms(dedupeTerms(queries), 8)
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}
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func planDemandTerms(pains []string) []string {
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pains = compactProviderTerms(pains)
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var queries []string
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for _, pain := range pains {
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queries = append(queries, pain+" 怎麼辦", pain+" 推薦", pain+" 有人也這樣嗎")
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}
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return capTerms(dedupeTerms(queries), 6)
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}
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func planProviderTerms(pains, capabilities []string) []string {
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pains = compactProviderTerms(pains)
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capabilities = compactProviderTerms(capabilities)
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var queries []string
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for _, pain := range pains {
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for _, capability := range capabilities {
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if strings.EqualFold(pain, capability) {
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queries = append(queries, capability+" 推薦", capability+" 專業")
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continue
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}
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if utf8.RuneCountInString(pain)+utf8.RuneCountInString(capability)+1 <= 24 {
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queries = append(queries, pain+" "+capability)
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}
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}
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queries = append(queries, pain+" 推薦")
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}
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for _, capability := range capabilities {
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queries = append(queries, capability+" 推薦", capability+" 專業")
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}
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return capTerms(dedupeTerms(queries), 8)
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}
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func compactProviderTerms(terms []string) []string {
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var out []string
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for _, term := range terms {
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term = strings.Join(strings.Fields(strings.TrimSpace(term)), " ")
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for _, filler := range []string{"不知道怎麼辦", "怎麼辦", "有沒有推薦", "求推薦", "請問", "想問", "我想找", "需要"} {
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term = strings.ReplaceAll(term, filler, "")
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}
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term = strings.Trim(term, " ,，、。！？!?：:")
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if utf8.RuneCountInString(term) > 18 {
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term = truncateRunes(term, 18)
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}
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if term != "" {
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out = append(out, term)
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}
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}
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return filterSeekablePains(out)
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}
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// filterSeekablePains drops marketing slogans / long product blurbs that pull competitor posts.
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func filterSeekablePains(in []string) []string {
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var out []string
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for _, raw := range in {
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term := strings.Join(strings.Fields(strings.TrimSpace(raw)), " ")
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if term == "" {
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continue
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}
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if isMarketingPhrase(term) {
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continue
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}
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out = append(out, term)
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}
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return out
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}
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func isMarketingPhrase(term string) bool {
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if utf8.RuneCountInString(term) > 28 {
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return true
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}
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lower := strings.ToLower(term)
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bad := []string{
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"✔", "✓", "x1", "×1", "任選", "內含", "官網", "現折", "折扣碼",
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"完整保養流程", "快速帶走", "滋潤修護", "天然植萃配方", "溫和不刺激",
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"服務洽詢", "限時優惠", "立即購買", "旗艦店",
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}
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for _, b := range bad {
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if strings.Contains(lower, strings.ToLower(b)) {
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return true
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}
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}
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return false
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}
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func capTerms(terms []string, max int) []string {
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if max <= 0 || len(terms) <= max {
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return terms
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}
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return terms[:max]
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}
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func dedupeTerms(groups ...[]string) []string {
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seen := make(map[string]struct{})
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var out []string
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for _, group := range groups {
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for _, term := range group {
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term = strings.Join(strings.Fields(strings.TrimSpace(term)), " ")
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key := strings.ToLower(term)
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if term == "" {
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continue
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}
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if _, ok := seen[key]; ok {
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continue
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}
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seen[key] = struct{}{}
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out = append(out, term)
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}
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}
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return out
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}
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func tokenizeIntent(intent string) []string {
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// 簡單空白／標點切詞，活躍模式備援
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fields := strings.FieldsFunc(intent, func(r rune) bool {
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switch r {
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case ' ', '\t', '\n', ',', '，', '、', '/', '|', '·', '。', '！', '？', '!', '?':
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return true
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default:
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return false
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}
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})
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return fields
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}
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func truncateRunes(s string, max int) string {
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if max <= 0 || utf8.RuneCountInString(s) <= max {
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return s
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}
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runes := []rune(s)
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return string(runes[:max])
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}
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func classifyPost(mode, text string, terms []string) classifiedPost {
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lower := strings.ToLower(text)
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signals := matchedSignals(lower, terms)
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if hasAny(lower, "giveaway", "抽獎", "follow for follow", "互追", "crypto", "賺錢") {
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return classifiedPost{domain.ClassificationNoise, 0, "noise signal"}
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}
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if mode == domain.ModeActivity {
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return classifyActivity(lower, signals)
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}
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if hasAny(lower, "dm me", "私訊我", "服務洽詢", "立即購買", "限時優惠", "團購", "業配") {
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return scored(domain.ClassificationProviderOffer, 35, signals, "provider-offer signal")
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}
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if hasAny(lower, "推薦", "求推", "有沒有推薦", "any recommendation", "what do you recommend") {
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return scored(domain.ClassificationSeekingRecommendation, 60, signals, "recommendation signal")
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}
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if strings.Contains(lower, "?") || strings.Contains(lower, "？") || hasAny(lower, "怎麼", "如何", "請問", "求助", "help") {
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return scored(domain.ClassificationSeekingHelp, 55, signals, "help-seeking signal")
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}
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return scored(domain.ClassificationDiscussion, 40, signals, "discussion signal")
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}
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func classifyProvider(text string, pains, capabilities, excludes []string) classifiedPost {
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lower := strings.ToLower(text)
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if hasMatchingTerm(lower, excludes) {
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return classifiedPost{domain.ClassificationNoise, 0, "same-category exclusion"}
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}
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if hasAny(lower, "dm me", "私訊我", "服務洽詢", "立即購買", "限時優惠", "團購", "業配") {
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return classifiedPost{domain.ClassificationNoise, 0, "sales signal"}
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}
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matchedPains := matchedSignals(lower, pains)
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matchedCapabilities := matchedSignals(lower, capabilities)
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if len(matchedPains) == 0 || len(matchedCapabilities) == 0 {
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return classifiedPost{domain.ClassificationNoise, 0, "missing pain or capability evidence"}
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}
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base := 65
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classification := domain.ClassificationProviderDirect
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reason := "pain and capability evidence"
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if hasAny(lower, "推薦", "介紹", "找", "口碑") {
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base = 75
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classification = domain.ClassificationProviderRecommended
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reason = "recommended provider evidence"
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} else if !hasAny(lower, "案例", "專業", "預約", "諮詢", "服務", "協助", "聯絡", "工作室", "診所", "顧問") {
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return classifiedPost{domain.ClassificationNoise, 0, "missing provider proof"}
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}
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signals := append(matchedPains, matchedCapabilities...)
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return scored(classification, base, signals, reason)
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}
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func classifyDemand(text string, pains, excludes []string) classifiedPost {
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lower := strings.ToLower(text)
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if hasMatchingTerm(lower, excludes) || hasAny(lower, "dm me", "私訊我", "服務洽詢", "立即購買", "限時優惠", "團購", "業配") {
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return classifiedPost{domain.ClassificationNoise, 0, "excluded sales or category signal"}
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}
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signals := matchedSignals(lower, pains)
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if len(signals) == 0 {
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return classifiedPost{domain.ClassificationNoise, 0, "missing pain evidence"}
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}
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if hasAny(lower, "推薦", "求推", "有沒有推薦", "有人也", "哪裡", "找不到") {
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return scored(domain.ClassificationSeekingRecommendation, 75, signals, "pain and recommendation signal")
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}
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if strings.Contains(lower, "?") || strings.Contains(lower, "？") || hasAny(lower, "怎麼", "如何", "請問", "求助", "help", "沒用", "無效", "失敗", "困擾") {
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return scored(domain.ClassificationSeekingHelp, 70, signals, "pain and help signal")
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}
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return classifiedPost{domain.ClassificationNoise, 0, "pain mentioned without demand signal"}
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}
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func hasMatchingTerm(text string, terms []string) bool {
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return len(matchedSignals(text, terms)) > 0
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}
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func classifyActivity(text string, signals []string) classifiedPost {
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if hasAny(text, "dm me", "私訊我", "服務洽詢", "立即購買", "限時優惠", "團購", "業配") {
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return scored(domain.ClassificationProviderOffer, 35, signals, "provider-offer signal; recency unavailable (neutral)")
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}
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if strings.Contains(text, "?") || strings.Contains(text, "？") || hasAny(text, "請問", "怎麼", "如何", "有人知道", "求") {
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return scored(domain.ClassificationAsking, 60, signals, "asking signal; recency unavailable (neutral)")
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}
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if hasAny(text, "活動", "event", "開幕", "launch", "發布", "報名", "登記", "公告") {
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return scored(domain.ClassificationAnnouncement, 50, signals, "announcement signal; recency unavailable (neutral)")
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}
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return scored(domain.ClassificationDiscussion, 40, signals, "discussion signal; recency unavailable (neutral)")
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}
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func scored(classification string, base int, signals []string, label string) classifiedPost {
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score := base + len(signals)*15
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if score > 100 {
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score = 100
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}
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reason := label
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if len(signals) > 0 {
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reason += "; matched: " + strings.Join(signals, ", ")
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}
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return classifiedPost{classification, score, reason}
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}
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func matchedSignals(text string, terms []string) []string {
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var signals []string
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text = normalizeSignal(text)
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for _, term := range dedupeTerms(terms) {
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if normalized := normalizeSignal(term); normalized != "" && strings.Contains(text, normalized) {
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signals = append(signals, term)
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}
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}
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return signals
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}
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func normalizeSignal(text string) string {
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text = strings.ToLower(text)
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for _, filler := range []string{"一直", "真的", "有點", "又", "很", "都"} {
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text = strings.ReplaceAll(text, filler, "")
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}
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return strings.Join(strings.Fields(text), "")
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}
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func hasAny(text string, signals ...string) bool {
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for _, signal := range signals {
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if strings.Contains(text, signal) {
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return true
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}
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}
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return false
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}
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func canonicalPermalink(raw string) string {
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u, err := url.Parse(strings.TrimSpace(raw))
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if err != nil || u.Host == "" {
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return ""
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}
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u.Scheme = "https"
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u.Host = strings.ToLower(u.Host)
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u.RawQuery = ""
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u.Fragment = ""
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u.Path = strings.TrimRight(u.Path, "/")
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return u.String()
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}
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func permalinkID(ownerUID int64, permalink string) string {
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sum := sha256.Sum256([]byte(strings.TrimSpace(permalink) + "|" + formatOwnerUID(ownerUID)))
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return "sp_" + hex.EncodeToString(sum[:])[:20]
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}
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func formatOwnerUID(ownerUID int64) string {
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return strconv.FormatInt(ownerUID, 10)
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}
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