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feat: parse real workspace files for knowledge graph topology and add organic organic movement

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This commit is contained in:
Jay
2026-04-18 16:32:55 +09:00
parent 4fa224b4c3
commit 279e6715cd
1 changed files with 54 additions and 25 deletions
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src/extension.ts
+54 -25
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@@ -393,7 +393,7 @@ console.log('Connect AI extension activated.');
);
}
function showBrainNetwork(context: vscode.ExtensionContext) {
async function showBrainNetwork(context: vscode.ExtensionContext) {
const panel = vscode.window.createWebviewPanel(
'brainTopology',
'Neural Construct (Brain)',
@@ -401,6 +401,28 @@ function showBrainNetwork(context: vscode.ExtensionContext) {
{ enableScripts: true, retainContextWhenHidden: true }
);
// Scan REAL workspace files
const uris = await vscode.workspace.findFiles('**/*.{md,ts,js,json,html,css,py,tsx,jsx}', '{**/node_modules/**,**/.git/**,**/dist/**,**/out/**,**/.svelte-kit/**}', 400);
const realClusters: Record<string, string[]> = {};
for (const uri of uris) {
const pathParts = uri.path.split('/');
const fileName = pathParts.pop() || 'Unknown';
const folderName = pathParts.pop() || 'Root';
// Prefix folder to group them
const groupName = folderName === 'local-ai-coder' || folderName === 'Root' ? 'Project Core' : folderName;
if (!realClusters[groupName]) realClusters[groupName] = [];
realClusters[groupName].push(fileName);
}
// Fallback if empty
if (Object.keys(realClusters).length === 0) {
realClusters['Empty Node'] = ['No files found in workspace...'];
}
const clustersJsonString = JSON.stringify(realClusters);
panel.webview.html = `<!DOCTYPE html>
<html lang="ko">
<head>
@@ -420,24 +442,15 @@ function showBrainNetwork(context: vscode.ExtensionContext) {
</head>
<body>
<div id="ui-layer">
<h1>\\u2726 <span>Neural Construct</span></h1>
<h1>\\u2726 <span id="titleSpan">Neural Construct</span></h1>
<p id="mem-status">loading...</p>
</div>
<div id="graph"></div>
<script>
const clusters = {
'AI/ML': ['Transformer Architecture','Attention Mechanism','Backpropagation','Gradient Descent','Neural Network Layers','Loss Function','Embedding Space','Tokenization','Fine-tuning','Transfer Learning','LoRA Adapter','RLHF','DPO Training','Prompt Engineering','Chain of Thought','RAG Pipeline','Vector Database'],
'Programming': ['TypeScript','React Components','Node.js Runtime','REST API Design','GraphQL Schema','WebSocket Protocol','Docker Container','Kubernetes','CI/CD Pipeline','Git Version Control','Database Schema','SQL Optimization','Redis Caching','Message Queue','Microservices','Load Balancing'],
'YouTube': ['YouTube Algorithm','CTR Optimization','Thumbnail Design','Title A/B Testing','Audience Retention','Content Calendar','Funnel Strategy','Email Marketing','SEO Fundamentals','Analytics Dashboard','Conversion Rate','Growth Hacking','Brand Positioning','Community Building','Monetization','Ad Revenue Model'],
'Tools': ['VS Code Extension API','Ollama Runtime','Gemma Model','LLaMA Architecture','Google Veo','Nanobanana Pro','NotebookLM','Google Stitch','MCP Protocol','Antigravity CLI','Agent University','Brain Pack Format','OPAL Framework','Gemini API','DeepSeek Model','Whisper STT'],
'Knowledge': ['Second Brain Method','Zettelkasten System','Spaced Repetition','Active Recall','Mind Mapping','Knowledge Graph','Semantic Search','Document Chunking','Metadata Extraction','Tag Taxonomy','Bidirectional Links','Atomic Notes'],
'Korean': ['#AI\\uc218\\uc775\\ud654','#\\ubc14\\uc774\\ube0c\\ucf54\\ub529','#1\\uc778\\uae30\\uc5c5','#AI\\ucc3d\\uc5c5','#\\ucf54\\ub529\\uae30\\ucd08','#\\uc2dc\\ub2c8\\uc5b4\\uc804\\uc131\\uc2dc\\ub300','#\\uc790\\uae30\\uac1c\\ubc1c','#AI\\uc1fc\\ud551\\ubab0','#GPT\\uc0ac\\uc6a9\\ubc95','#\\uc0ac\\uc774\\ud2b8\\ub9cc\\ub4e4\\uae30','#\\uc218\\uc775\\ud654\\ubaa8\\ub378','#\\ub178\\ucf54\\ub4dc','#AI\\uc790\\ub3d9\\uc218\\uc775','#VEO3.1','#\\uc655\\ucd08\\ubcf4\\uac00\\uc774\\ub4dc','#\\ub514\\uc9c0\\ud138\\uac74\\ubb3c\\uc8fc'],
'Math': ['Linear Algebra','Probability Theory','Calculus','Statistics','Information Theory','Game Theory','Optimization','Graph Theory'],
'MrBeast': ['MrBeast Viral Formula','Hook Strategy','Retention Graph','Challenge Format','Giveaway ROI','Production Scaling','Clickbait Psychology','First 30s Rule','Re-watch Value','Comment Engagement','Shorts Repurposing','Thumbnail Contrast','Emotional Arc','Pacing Rhythm','Sound Design']
};
const clusters = ${clustersJsonString};
let nid = 0;
const gData = { nodes: [], links: [] };
gData.nodes.push({ id: nid++, group: -1, name: 'Core Agent', val: 22, connections: 0 });
gData.nodes.push({ id: nid++, group: -1, name: 'Workspace Root', val: 22, connections: 0 });
let gi = 0;
Object.values(clusters).forEach(names => {
names.forEach(name => { gData.nodes.push({ id: nid++, group: gi, name, val: 2, connections: 0 }); });
@@ -446,12 +459,25 @@ function showBrainNetwork(context: vscode.ExtensionContext) {
const byGroup = {};
gData.nodes.forEach(n => { if(n.group>=0){ if(!byGroup[n.group]) byGroup[n.group]=[]; byGroup[n.group].push(n); }});
Object.values(byGroup).forEach(g => {
for(let i=0;i<g.length;i++) for(let j=i+1;j<g.length;j++) if(Math.random()<0.22){
gData.links.push({source:g[i].id,target:g[j].id}); g[i].connections++; g[j].connections++;
// Connect files in the same folder to each other (dense subgraph)
for(let i=0;i<g.length;i++) {
for(let j=i+1;j<g.length;j++) {
// Much higher connection chance inside the same folder so they cluster well
if(Math.random()<0.6){
gData.links.push({source:g[i].id,target:g[j].id}); g[i].connections++; g[j].connections++;
}
}
}
});
gData.nodes.forEach(n => { if(n.group>=0 && Math.random()<0.05){ gData.links.push({source:n.id,target:0}); n.connections++; gData.nodes[0].connections++; }});
for(let i=0;i<35;i++){
// Connect all folder nodes up to the root to unify the graph
gData.nodes.forEach(n => {
if(n.group>=0){
if (Math.random() < 0.15) { // 15% chance to link to root to maintain overall structure
gData.links.push({source:n.id,target:0}); n.connections++; gData.nodes[0].connections++;
}
}
});
for(let i=0;i< (gData.nodes.length * 1.5);i++){
const a=1+Math.floor(Math.random()*(gData.nodes.length-1)), b=1+Math.floor(Math.random()*(gData.nodes.length-1));
if(a!==b && gData.nodes[a].group!==gData.nodes[b].group){ gData.links.push({source:a,target:b}); gData.nodes[a].connections++; gData.nodes[b].connections++; }
}
@@ -477,16 +503,19 @@ function showBrainNetwork(context: vscode.ExtensionContext) {
.nodePointerAreaPaint((node,color,ctx) => {
const r=Math.sqrt(node.val)*1.8+4; ctx.beginPath(); ctx.arc(node.x,node.y,r,0,2*Math.PI); ctx.fillStyle=color; ctx.fill();
})
.linkColor(() => 'rgba(255,255,255,0.04)')
.linkWidth(0.3)
.d3VelocityDecay(0.3)
.warmupTicks(150)
.cooldownTicks(300)
.linkColor(() => 'rgba(200,200,200,0.15)')
.linkWidth(0.6)
.d3VelocityDecay(0.08) // Lower friction so they drift and move organically!
.warmupTicks(50)
.cooldownTicks(500) // Keep them moving longer
.graphData(gData);
Graph.d3Force('charge').strength(-100);
Graph.d3Force('link').distance(35);
Graph.d3Force('charge').strength(-60); // Softer repulsion for gentle drift
Graph.d3Force('link').distance(60);
Graph.onNodeClick(node => { Graph.centerAt(node.x,node.y,800); Graph.zoom(4,1200); });
setTimeout(() => Graph.zoomToFit(1500, 40), 500);
setTimeout(() => {
Graph.zoomToFit(1500, 40);
document.getElementById('titleSpan').innerText = "Live Workspace Topology";
}, 500);
</script>
</body>
</html>`;