gfsd

src/inc/routeinc/f0cklib.mjs

@@ -2328,7 +2328,9 @@ const f0cklib = {
     mime, 
     exclude_ids,
     session_tags = '',
-    session_creators = ''
+    session_creators = '',
+    continuation = false,
+    prefer_personalized = null
   } = {}) => {
     const ratingsArr = (Array.isArray(ratings) && ratings.length > 0) ? ratings : null;
     const modequery = computeBaseMode(mode, ratingsArr, session);
@@ -2420,13 +2422,30 @@ const f0cklib = {
       });
     }
 
-    // 2. Personalization vs Serendipity Split (60% personalized, 40% random exploration)
+    // 2. Personalization vs Serendipity Split
+    // In the sidebar suggestions:
+    // - 1 of the first 3 recommendations is a personalized recommendation and the other 2 are not.
+    // - After that, recommendations appear sporadically (~20% rate, non-consecutive with 3-5 random items between them).
+    const isFirstBatch = !continuation && excludeItemIds.length === 0;
     let personalizedTarget;
+
     if (maxLimit === 1) {
-      // For single-card replacement: 65% chance personalized, 35% chance discovery
-      personalizedTarget = Math.random() < 0.65 ? 1 : 0;
+      if (prefer_personalized === true) {
+        personalizedTarget = 1;
+      } else if (prefer_personalized === false) {
+        personalizedTarget = 0;
+      } else {
+        personalizedTarget = Math.random() < 0.20 ? 1 : 0;
+      }
+    } else if (isFirstBatch) {
+      // 1 in top 3, plus sporadic recommendations in the remaining slots
+      const topRec = maxLimit >= 1 ? 1 : 0;
+      const remainingSlots = Math.max(0, maxLimit - 3);
+      const sporadicRecs = Math.round(remainingSlots * 0.20);
+      personalizedTarget = topRec + sporadicRecs;
     } else {
-      personalizedTarget = Math.round(maxLimit * 0.60);
+      // Continuation batch: sporadic recommendations throughout
+      personalizedTarget = Math.max(1, Math.round(maxLimit * 0.20));
     }
 
     const targetTagIds = targetTagEntries.map(([tid]) => tid);
@@ -2537,8 +2556,9 @@ const f0cklib = {
     let randomItems = [];
     if (neededRandom > 0) {
       const allExclude = [...excludeItemIds, ...personalizedItems.map(p => p.id)];
+      // Fetch extra buffer of random items to ensure ample spacing
       randomItems = await f0cklib.getRandomRecommendations({
-        limit: neededRandom,
+        limit: Math.max(neededRandom + 3, maxLimit),
         mode,
         ratings,
         session,
@@ -2550,14 +2570,74 @@ const f0cklib = {
       });
     }
 
-    // 4. Combine & Interweave with Fisher-Yates Shuffle
-    const combined = [...personalizedItems, ...randomItems];
-    for (let i = combined.length - 1; i > 0; i--) {
-      const j = Math.floor(Math.random() * (i + 1));
-      [combined[i], combined[j]] = [combined[j], combined[i]];
+    // 4. Combine & Interweave
+    if (maxLimit === 1) {
+      return personalizedItems.length > 0 ? personalizedItems.slice(0, 1) : randomItems.slice(0, 1);
     }
 
-    return combined.slice(0, maxLimit);
+    if (personalizedItems.length === 0) {
+      return randomItems.slice(0, maxLimit);
+    }
+
+    if (randomItems.length === 0) {
+      return personalizedItems.slice(0, maxLimit);
+    }
+
+    const result = [];
+    if (isFirstBatch) {
+      // First 3 items: exactly 1 is a recommendation, and the other 2 are not
+      const topCount = Math.min(3, maxLimit);
+      const topSlots = new Array(topCount);
+      const recSlot = Math.floor(Math.random() * topCount);
+      topSlots[recSlot] = personalizedItems.shift();
+
+      for (let s = 0; s < topCount; s++) {
+        if (s !== recSlot) {
+          topSlots[s] = randomItems.length > 0 ? randomItems.shift() : personalizedItems.shift();
+        }
+      }
+      for (let s = 0; s < topCount; s++) {
+        if (topSlots[s]) result.push(topSlots[s]);
+      }
+
+      // Remaining slots: recommendations come sporadically (separated by 3 to 5 non-recommendations)
+      let gapSinceRec = topCount - 1 - recSlot;
+      let targetGap = Math.floor(Math.random() * 3) + 3; // 3, 4, or 5 random items
+
+      while (result.length < maxLimit && (personalizedItems.length > 0 || randomItems.length > 0)) {
+        if (personalizedItems.length > 0 && gapSinceRec >= targetGap && randomItems.length > 0) {
+          result.push(personalizedItems.shift());
+          gapSinceRec = 0;
+          targetGap = Math.floor(Math.random() * 3) + 3;
+        } else if (randomItems.length > 0) {
+          result.push(randomItems.shift());
+          gapSinceRec++;
+        } else if (personalizedItems.length > 0) {
+          result.push(personalizedItems.shift());
+          gapSinceRec = 0;
+        }
+      }
+    } else {
+      // Continuation batch: recommendations come sporadically throughout
+      let gapSinceRec = Math.floor(Math.random() * 2) + 1;
+      let targetGap = Math.floor(Math.random() * 3) + 3;
+
+      while (result.length < maxLimit && (personalizedItems.length > 0 || randomItems.length > 0)) {
+        if (personalizedItems.length > 0 && gapSinceRec >= targetGap && randomItems.length > 0) {
+          result.push(personalizedItems.shift());
+          gapSinceRec = 0;
+          targetGap = Math.floor(Math.random() * 3) + 3;
+        } else if (randomItems.length > 0) {
+          result.push(randomItems.shift());
+          gapSinceRec++;
+        } else if (personalizedItems.length > 0) {
+          result.push(personalizedItems.shift());
+          gapSinceRec = 0;
+        }
+      }
+    }
+
+    return result.slice(0, maxLimit);
   },
 
   getTagFeedItems: async ({