Upgraded embedding model to voyage-3.5, updated README.md

Reviewed-on: #3

README.md

@@ -1,4 +1,4 @@
-# kongruity
+# kongruity: Signal from noise
 
 “...All those moments will be lost in time, like tears in rain.”
 
@@ -8,15 +8,19 @@ In kongruity, the artifacts become "sticky notes." A board full of them looks ch
 
 With a click, they are semantically evaluated, grouped into thematic clusters with descriptive headers, rankable and exportable to project planning and execution tools.
 
+## Voyage AI voyage-3.5
+
+![Embedding model benchmarking.](Voyage.jpg)
+
 ## Clustering and evaluation: methodology
 
 Two models run in parallel, and neither sees the other's work. Anthropic's `claude-sonnet-5` (`backend/services/clustering.service.js`) reads the raw text of every note and groups them into labeled thematic clusters. 
 
-At the same time, Voyage AI's voyage-3 model (`backend/services/embedding.service.js`) converts each note's text into a numeric representation of its semantic meaning aka vector. 
+At the same time, Voyage AI's voyage-3.5 model (`backend/services/embedding.service.js`) converts each note's text into a numeric representation of its semantic meaning aka vector. 
 
 Once the LLM returns, kongruity scores that grouping (`backend/services/validation.service.js`) using an established silhouette coefficient, with cosine distance rather than Euclidean as the proximity metric. 
 
-For each note, it weighs the average distance to the other notes in its own cluster against the average distance to the notes in the nearest neighboring cluster. Averaged across every note, this yields a single cohesion score in the range [−1, 1], displayed at the top of the results.
+For each note, it weighs the average distance to the other notes in its own cluster against the average distance to the notes in the nearest neighboring cluster. Averaged across every note, this yields a single numeric cohesion score, displayed at the top of the results, along with plaintext: Strong, Moderate, Weak, Poor.
 
 This yields an empirical groundedness evaluation. One model proposes the grouping; an independent model evaluates grouping accuracy.
 

backend/services/embedding.service.js

@@ -27,7 +27,7 @@ export const embedNotes = async (notes) => {
             for await (const chunk of batches) {
                 const response = await client.embed({
                     input: chunk.map((n) => n.text),
-                    model: "voyage-3",
+                    model: "voyage-3.5",
                 });
 
                 response.data.forEach((item, i) => {

frontend/src/components/stickies.tsx

@@ -87,7 +87,7 @@ const Stickies = () => {
         dragIndex.current = null;
         setDragOverIndex(null);
     };
-
+    console.log(score?.toFixed(2))
     return (
         <div className="stickies-container">
             <Button onClick={handleCluster} isLoading={isPending} label="Group Stickies By Topic" />
@@ -95,7 +95,7 @@ const Stickies = () => {
                 <div className="clusters-container">
                     {score != null && (
                         <div className="cohesion-score">
-                            Cluster cohesion: <strong>{score.toFixed(2)}</strong> — {scoreLabel(score)}
+                            Cluster cohesion: <strong>{scoreLabel(score)}</strong>
                         </div>
                     )}
                     {rankedClusters.map((group, index) => (

frontend/src/styles/stickies.css

@@ -1,100 +1,107 @@
 .stickies-grid {
-  display: flex;
+    display: flex;
-  flex-wrap: wrap;
+    flex-wrap: wrap;
-  gap: 16px;
+    gap: 16px;
-  justify-content: center;
+    justify-content: center;
-  margin-top: 18px;
+    margin-top: 18px;
-  padding: 24px;
+    padding: 24px;
 }
 
 .stickies-container {
-  margin: 36px 0px 36px 0px;
+    margin: 36px 0px 36px 0px;
 }
 
 .clusters-container {
-  display: flex;
+    display: flex;
-  flex-direction: column;
+    flex-direction: column;
-  gap: 32px;
+    gap: 32px;
-  padding: 24px 0;
+    padding: 24px 0;
 }
 
 .cluster-group {
-  border: 1px solid #6dd6f4;
+    border: 1px solid #6dd6f4;
-  border-radius: 8px;
+    border-radius: 8px;
-  padding: 16px;
+    padding: 16px;
 }
 
 .cluster-draggable {
-  cursor: grab;
+    cursor: grab;
-  transition: box-shadow 0.2s ease, border-color 0.2s ease, transform 0.15s ease;
+    transition: box-shadow 0.2s ease, border-color 0.2s ease, transform 0.15s ease;
 }
 
 .cluster-draggable:active {
-  cursor: grabbing;
+    cursor: grabbing;
 }
 
 .cluster-drag-over {
-  border-color: #ffb7ce;
+    border-color: #ffb7ce;
-  box-shadow: 0 0 12px rgba(255, 183, 206, 0.4);
+    box-shadow: 0 0 12px rgba(255, 183, 206, 0.4);
-  transform: scale(1.01);
+    transform: scale(1.01);
 }
 
 .cluster-header {
-  display: flex;
+    position: relative;
-  align-items: center;
+    display: flex;
-  gap: 12px;
+    align-items: center;
-  margin-bottom: 16px;
+    gap: 12px;
+    margin-bottom: 16px;
+    min-height: 32px;
 }
 
 .cluster-rank {
-  display: flex;
+    display: flex;
-  align-items: center;
+    align-items: center;
-  justify-content: center;
+    justify-content: center;
-  width: 32px;
+    width: 32px;
-  height: 32px;
+    height: 32px;
-  border-radius: 50%;
+    border-radius: 50%;
-  background: #6dd6f4;
+    background: #6dd6f4;
-  color: #1a1a2e;
+    color: #1a1a2e;
-  font-weight: 700;
+    font-weight: 700;
-  font-size: 0.95em;
+    font-size: 0.95em;
-  flex-shrink: 0;
+    flex-shrink: 0;
 }
 
 .cluster-reorder-hint {
-  font-size: 0.8em;
+    font-size: 0.8em;
-  color: #9ca3af;
+    color: #9ca3af;
-  font-style: italic;
+    font-style: italic;
-  white-space: nowrap;
+    white-space: nowrap;
-  flex-shrink: 0;
+    flex-shrink: 0;
 }
 
 .cluster-label {
-  margin: 0;
+    position: absolute;
-  font-size: 1.2em;
+    left: 50%;
-  font-weight: 600;
+    transform: translateX(-50%);
-  flex: 1;
+    max-width: 50%;
+    margin: 0;
+    font-size: 1.2em;
+    font-weight: 600;
+    pointer-events: none;
 }
 
 .cluster-drag-handle {
-  font-size: 1.4em;
+    margin-left: auto;
-  color: #6dd6f4;
+    font-size: 1.4em;
-  opacity: 0.4;
+    color: #6dd6f4;
-  user-select: none;
+    opacity: 0.4;
-  transition: opacity 0.2s ease;
+    user-select: none;
-  flex-shrink: 0;
+    transition: opacity 0.2s ease;
+    flex-shrink: 0;
 }
 
 .cluster-draggable:hover .cluster-drag-handle {
-  opacity: 0.8;
+    opacity: 0.8;
 }
 
 .cohesion-score {
-  text-align: center;
+    text-align: center;
-  font-size: 0.95em;
+    font-size: 0.95em;
-  color: #e0e0e0;
+    color: #e0e0e0;
-  padding: 8px 16px;
+    padding: 8px 16px;
-  background: rgba(109, 214, 244, 0.1);
+    background: rgba(109, 214, 244, 0.1);
-  border-radius: 6px;
+    border-radius: 6px;
-  width: fit-content;
+    width: fit-content;
-  margin: 0 auto;
+    margin: 0 auto;
-}
+}