Include viewer in feed

db/queries/core/recommend.sql

@@ -78,13 +78,9 @@ with refreshed as (
 select sqlc.embed(feed_entity_scores), sqlc.embed(posts)
 from feed_entity_scores
 join posts on feed_entity_scores.id = posts.id
-where feed_entity_scores.created_at > @window_end::timestamptz
-  and (@include_viewer::bool or feed_entity_scores.actor_id != @viewer_id)
-  and not posts.deleted
+where feed_entity_scores.created_at > @window_end::timestamptz and not posts.deleted
 union
 select sqlc.embed(feed_entity_scores), sqlc.embed(posts)
 from feed_entity_score_view feed_entity_scores
 join posts on feed_entity_scores.id = posts.id
-where feed_entity_scores.created_at > (select last_updated from refreshed limit 1)
-  and (@include_viewer::bool or feed_entity_scores.actor_id != @viewer_id)
-  and not posts.deleted;
+where feed_entity_scores.created_at > (select last_updated from refreshed limit 1) and not posts.deleted;

publicapi/feed.go

@@ -427,16 +427,8 @@ func (api FeedAPI) GlobalFeed(ctx context.Context, before *string, after *string
 	return paginator.paginate(before, after, first, last)
 }
 
-func fetchFeedEntityScores(ctx context.Context, queries *db.Queries, excludeUserID persist.DBID) (map[persist.DBID]db.GetFeedEntityScoresRow, error) {
-	params := db.GetFeedEntityScoresParams{
-		IncludeViewer: true,
-		WindowEnd:     time.Now().Add(-feedLookback),
-	}
-	if excludeUserID != "" {
-		params.IncludeViewer = false
-		params.ViewerID = excludeUserID
-	}
-	scores, err := queries.GetFeedEntityScores(ctx, params)
+func fetchFeedEntityScores(ctx context.Context, queries *db.Queries) (map[persist.DBID]db.GetFeedEntityScoresRow, error) {
+	scores, err := queries.GetFeedEntityScores(ctx, time.Now().Add(-feedLookback))
 	if err != nil {
 		return nil, err
 	}
@@ -506,7 +498,7 @@ func (api FeedAPI) TrendingFeed(ctx context.Context, before *string, after *stri
 		var posts []db.Post
 
 		cacheCalcFunc := func(ctx context.Context) ([]persist.FeedEntityType, []persist.DBID, error) {
-			postScores, err := fetchFeedEntityScores(ctx, api.queries, "")
+			postScores, err := fetchFeedEntityScores(ctx, api.queries)
 			if err != nil {
 				return nil, nil, err
 			}
@@ -565,7 +557,7 @@ func (api FeedAPI) TrendingFeed(ctx context.Context, before *string, after *stri
 	return paginator.paginate(before, after, first, last)
 }
 
-func (api FeedAPI) CuratedFeed(ctx context.Context, before, after *string, first, last *int) ([]any, PageInfo, error) {
+func (api FeedAPI) ForYouFeed(ctx context.Context, before, after *string, first, last *int) ([]any, PageInfo, error) {
 	// Validate
 	userID, _ := getAuthenticatedUserID(ctx)
 
@@ -592,7 +584,7 @@ func (api FeedAPI) CuratedFeed(ctx context.Context, before, after *string, first
 			return nil, PageInfo{}, err
 		}
 	} else {
-		postScores, err := fetchFeedEntityScores(ctx, api.queries, userID)
+		postScores, err := fetchFeedEntityScores(ctx, api.queries)
 		if err != nil {
 			return nil, PageInfo{}, err
 		}
@@ -603,22 +595,19 @@ func (api FeedAPI) CuratedFeed(ctx context.Context, before, after *string, first
 		personalizationScores := make(map[persist.DBID]float64)
 
 		for _, e := range postScores {
-			// Boost new events
-			boost := 1.0
-			if now.Sub(e.Post.CreatedAt) < 6*time.Hour {
-				boost *= 2.0
-			}
+			boost := newPostFactor(e.Post.CreatedAt, now)
 			timeF := timeFactor(e.Post.CreatedAt, now)
 			engagementScores[e.Post.ID] = boost * timeF * (1 + engagementFactor(int(e.FeedEntityScore.Interactions)))
 			personalizationScores[e.Post.ID] = boost * timeF * userpref.For(ctx).RelevanceTo(userID, e.FeedEntityScore)
 		}
 
 		// Rank by engagement first, then by personalization
-		topNByEngagement := api.scoreFeedEntities(ctx, 128, scores, func(e db.FeedEntityScore) float64 { return engagementScores[e.ID] })
-		topNByEngagement = api.scoreFeedEntities(ctx, 128, topNByEngagement, func(e db.FeedEntityScore) float64 { return personalizationScores[e.ID] })
+		topNByPersonalization := api.scoreFeedEntities(ctx, 128, scores, func(e db.FeedEntityScore) float64 { return engagementScores[e.ID] })
+		topNByPersonalization = api.scoreFeedEntities(ctx, 128, topNByPersonalization, func(e db.FeedEntityScore) float64 { return personalizationScores[e.ID] })
+
 		// Rank by personalization, then by engagement
-		topNByPersonalization := api.scoreFeedEntities(ctx, 128, scores, func(e db.FeedEntityScore) float64 { return personalizationScores[e.ID] })
-		topNByPersonalization = api.scoreFeedEntities(ctx, 128, topNByPersonalization, func(e db.FeedEntityScore) float64 { return engagementScores[e.ID] })
+		topNByEngagement := api.scoreFeedEntities(ctx, 128, scores, func(e db.FeedEntityScore) float64 { return personalizationScores[e.ID] })
+		topNByEngagement = api.scoreFeedEntities(ctx, 128, topNByEngagement, func(e db.FeedEntityScore) float64 { return engagementScores[e.ID] })
 
 		// Get ranking of both
 		seen := make(map[persist.DBID]bool)
@@ -644,10 +633,13 @@ func (api FeedAPI) CuratedFeed(ctx context.Context, before, after *string, first
 
 		// Score based on the average of the two rankings
 		interleaved := api.scoreFeedEntities(ctx, 128, combined, func(e db.FeedEntityScore) float64 {
+			if e.ActorID == userID {
+				return float64(engagementRank[e.ID])
+			}
 			return float64(engagementRank[e.ID]+personalizationRank[e.ID]) / 2.0
 		})
 
-		recommend.Shuffle(interleaved, 8)
+		recommend.Shuffle(interleaved, 4)
 
 		posts := make([]db.Post, len(interleaved))
 		postIDs := make([]persist.DBID, len(interleaved))
@@ -878,6 +870,14 @@ func timeFactor(t0, t1 time.Time) float64 {
 	return math.Pow(2, -(age / tHalf))
 }
 
+// newPostFactor returns a scaling factor for a post based on how recently it was made.
+func newPostFactor(t1, t2 time.Time) float64 {
+	if t2.Sub(t1) < 6*time.Hour {
+		return 2.0
+	}
+	return 1.0
+}
+
 func engagementFactor(interactions int) float64 {
 	return math.Log1p(float64(interactions))
 }

service/recommend/userpref/personalize.go

@@ -196,6 +196,11 @@ func (p *Personalization) RelevanceTo(userID persist.DBID, e db.FeedEntityScore)
 		return 0
 	}
 
+	// If scoring themselves, return 1 which is the max score
+	if userID == e.ActorID {
+		return 1.0
+	}
+
 	var relevanceScore float64
 
 	for _, contractID := range e.ContractIds {
@@ -208,7 +213,7 @@ func (p *Personalization) RelevanceTo(userID persist.DBID, e db.FeedEntityScore)
 	}
 
 	edgeScore, _ := p.scoreEdge(userID, e.ActorID)
-	return relevanceScore + edgeScore
+	return (relevanceScore + edgeScore) / 2.0
 }
 
 func (p *Personalization) scoreEdge(viewerID, queryID persist.DBID) (float64, error) {
@@ -219,7 +224,7 @@ func (p *Personalization) scoreEdge(viewerID, queryID persist.DBID) (float64, er
 	}
 	socialScore := calcSocialScore(p.pM.userM, vIdx, qIdx)
 	similarityScore := calcSimilarityScore(p.pM.simM, vIdx, qIdx)
-	return socialScore + similarityScore, nil
+	return (socialScore + similarityScore) / 2.0, nil
 }
 
 func (p *Personalization) scoreRelevance(viewerID, contractID persist.DBID) (float64, error) {
@@ -288,6 +293,9 @@ func (p *Personalization) readCache(ctx context.Context) {
 
 // calcSocialScore determines if vIdx is in the same friend circle as qIdx by running a bfs on userM
 func calcSocialScore(userM *sparse.CSR, vIdx, qIdx int) float64 {
+	if vIdx == qIdx {
+		return 1
+	}
 	return bfs(userM, vIdx, qIdx)
 }
 
@@ -314,7 +322,7 @@ func calcSimilarityScore(simM *sparse.CSR, vIdx, qIdx int) float64 {
 }
 
 // idLookup uses a slice to lookup a value by its index
-// Its purpose is to avoid using a map because indexing a slice is suprisingly much quicker than a map lookup.
+// Its purpose is to avoid using a map because indexing a slice is surprisingly much quicker than a map lookup.
 // It should be pretty space efficient: with one million users, it should take: 1 million users * 1 byte = 1MB of memory.
 type idLookup struct {
 	l []uint8