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README.md
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README.md
@@ -8,11 +8,15 @@ In kongruity, the artifacts become "sticky notes." A board full of them looks ch
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With a click, they are semantically evaluated, grouped into thematic clusters with descriptive headers, rankable and exportable to project planning and execution tools.
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## Voyage AI voyage-3.5
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## Clustering and evaluation: methodology
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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.
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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.
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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.
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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.
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@@ -30,14 +34,18 @@ Average silhouette width is a widely-used measure of clustering quality. Higher
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2. How well-separated each cluster is from its nearest neighboring cluster.
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Although the coefficient is mathematically bounded by [−1, 1], cosine distance between high-dimensional text embeddings is compressed: unrelated notes sit close to orthogonal, so both the within-cluster and nearest-cluster distances land near 0.8. Because silhouette divides the gap between them by the larger of the two, the practical range on embedding data is roughly [−0.05, 0.10] rather than the full interval.
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The bands below are therefore calibrated against that observed range. On the seed board, the five ideal thematic clusters score 0.09; swapping a few notes between clusters drops it to 0.06; a scrambled assignment falls below zero.
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The score appears above the results with a plain-language band:
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- **0.70 and above** — Strong
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- **0.40 to 0.69** — Moderate
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- **0.10 to 0.39** — Weak
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- **Below 0.10** — Poor
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- **0.07 and above** — Strong
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- **0.04 to 0.06** — Moderate
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- **0.01 to 0.03** — Weak
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- **Below 0.01** — Poor
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Silhouette values are archetypically bounded below 1.0 for real-world data, so the number is best read as a relative measure. See Hugo Sträng, Tai Dinh. An upper bound on the silhouette evaluation metric for clustering. Pattern Recognition, Volume 178, 2026, 113402, ISSN 0031-3203.
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A score near 0.00 means the grouping is no better than chance. Bands are specific to `voyage-3` cosine distance and would need recalibration behind a different embedding model. See Hugo Sträng, Tai Dinh. An upper bound on the silhouette evaluation metric for clustering. Pattern Recognition, Volume 178, 2026, 113402, ISSN 0031-3203.
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## Organizing clusters, exporting to workflow software
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BIN
Voyage.jpg
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Voyage.jpg
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After Width: | Height: | Size: 114 KiB |
42
agents.md
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agents.md
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@@ -0,0 +1,42 @@
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# AI Agent Instructions: Fullstack Vite 7 (React) + Express + TypeScript + npm
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You are an expert AI fullstack software engineer specialized in Vite 7, React, Express, TypeScript, and modern web architectures. Follow these rules strictly when modifying this codebase.
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## 1. Project Structure & Context
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* **Frontend:** React SPA powered by Vite 7.x (Entry: `src/main.tsx` or client folder).
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* **Backend:** Express Node.js application (Server entry: `server.ts` or server folder).
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* **Package Manager:** npm (`package-lock.json` is the strict source of truth).
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* **TypeScript Setup:** Strict Mode enabled independently across both environments.
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## 2. Express Backend TypeScript Rules
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* **Typed Request/Response:** Explicitly type Express route handlers using native Express types:
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```typescript
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import { Request, Response, NextFunction } from 'express';
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// Example for typed request bodies/params:
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interface CreateUserBody { username: string; }
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app.post('/user', (req: Request<{}, {}, CreateUserBody>, res: Response) => { ... });
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```
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* **Async Error Catching:** Always wrap async middleware/route handlers in `try/catch` and pass errors to `next(err)`. Do not let unhandled promise rejections crash the Node process.
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* **Shared Types:** If frontend and backend share types (e.g., API payloads, User models), place them in a shared directory or export them cleanly from the backend to prevent duplicating code.
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## 3. Frontend React + Vite Rules
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* **Component Typings:** Use standard type inference or explicit return types (`function Component(): React.JSX.Element`). Avoid the legacy `React.FC`.
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* **Strict Prop Types:** Every component must have an explicitly typed `interface` or `type` for its props. No implicit `any`.
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* **Event Handlers:** Use exact React synthetic event types (e.g., `React.ChangeEvent<HTMLInputElement>`) instead of generic native events.
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* **File Extensions:** Use `.tsx` exclusively for files containing JSX. Use `.ts` strictly for pure logic, hooks, or type definitions.
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## 4. Strict Code Quality & Native Guards
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* **No `any`:** Never use `any`. Use `unknown` for unpredictable runtime data (like Express `req.body` or frontend `fetch` payloads).
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* **No Validation Libraries:** Do not install Zod, TypeBox, or Yup. Write explicit, manual type predicate functions (`function isUser(obj: any): obj is User`) to safely validate runtime data incoming to both the server and client.
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* **No Enums:** Avoid TypeScript `enum`. Use string-literal unions (`type Status = 'active' | 'pending'`) or `const StatusEnum = { ... } as const`.
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## 5. Verification & Workflow Commands
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Before declaring a task complete, you must verify both environments compile flawlessly via npm:
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* **Install Dependencies:** `npm install`
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* **Type-Check Project:** Run the designated workspace or folder type-checking scripts (e.g., `npm run type-check` or `npx tsc --noEmit` across both roots).
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* **Build Verification:** Run production build scripts (e.g., `npm run build`) to ensure both Express asset compilation and Vite bundling pass without error.
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## 6. How to Respond
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* **Verify Types First:** Run type-checking commands automatically after modifying files to capture compilation breaks before presenting the solution.
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* **Targeted Diffs:** Provide concise, targeted updates. Do not rewrite whole files if only a few lines change.
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* **Self-Correct:** If a build command fails, read the compiler/Vite/Node logs, fix the root cause, and re-test before asking the user for help.
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@@ -27,7 +27,7 @@ export const embedNotes = async (notes) => {
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for await (const chunk of batches) {
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const response = await client.embed({
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input: chunk.map((n) => n.text),
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model: "voyage-3",
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model: "voyage-3.5",
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});
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response.data.forEach((item, i) => {
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@@ -1,5 +1,5 @@
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{
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"name": "congruity-frontend",
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"name": "kongruity-frontend",
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"private": true,
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"version": "0.1.0",
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"type": "module",
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@@ -36,5 +36,4 @@
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"vite": "^7.3.1",
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"vitest": "^4.0.18"
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}
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}
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}
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@@ -6,10 +6,14 @@ import Sticky from './sticky';
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import Button from './button';
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import '../styles/stickies.css';
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// In practice, silhouette on cosine distance between text embeddings occupies roughly
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// [-0.05, 0.10], not strict theoretical [-1, 1]: near-orthogonal vectors put both the within- and
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// nearest-cluster distances close to 0.8, and the coefficient divides their gap
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// by the larger. These bands are calibrated to that range for voyage-3. see README, Reading the cohesion score
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const scoreLabel = (score: number): string => {
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if (score >= 0.7) return 'Strong';
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if (score >= 0.4) return 'Moderate';
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if (score >= 0.1) return 'Weak';
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if (score >= 0.07) return 'Strong';
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if (score >= 0.04) return 'Moderate';
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if (score >= 0.01) return 'Weak';
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return 'Poor';
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};
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@@ -83,7 +87,7 @@ const Stickies = () => {
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dragIndex.current = null;
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setDragOverIndex(null);
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};
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console.log(score?.toFixed(2))
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return (
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<div className="stickies-container">
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<Button onClick={handleCluster} isLoading={isPending} label="Group Stickies By Topic" />
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@@ -91,7 +95,7 @@ const Stickies = () => {
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<div className="clusters-container">
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{score != null && (
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<div className="cohesion-score">
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Cluster cohesion: <strong>{score.toFixed(2)}</strong> — {scoreLabel(score)}
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Cluster cohesion: <strong>{scoreLabel(score)}</strong>
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</div>
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)}
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{rankedClusters.map((group, index) => (
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@@ -40,10 +40,12 @@
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}
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.cluster-header {
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position: relative;
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display: flex;
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align-items: center;
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gap: 12px;
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margin-bottom: 16px;
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min-height: 32px;
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}
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.cluster-rank {
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@@ -69,13 +71,18 @@
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}
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.cluster-label {
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position: absolute;
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left: 50%;
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transform: translateX(-50%);
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max-width: 50%;
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margin: 0;
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font-size: 1.2em;
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font-weight: 600;
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flex: 1;
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pointer-events: none;
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}
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.cluster-drag-handle {
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margin-left: auto;
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font-size: 1.4em;
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color: #6dd6f4;
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opacity: 0.4;
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@@ -14,7 +14,7 @@ const MOCK_CLUSTER_RESPONSE = {
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{ label: 'Auth Issues', noteIds: ['note_001'] },
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{ label: 'Export Issues', noteIds: ['note_002'] },
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],
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score: 0.74,
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score: 0.09,
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};
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let fetchMock: ReturnType<typeof vi.fn>;
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Reference in New Issue
Block a user