More memory fixes

2026-07-29 22:11:09 -04:00
parent 14f6cdd313
commit 8dfcd06752
9 changed files with 426 additions and 376 deletions
--- a/package-lock.json
+++ b/package-lock.json
@@ -1,12 +1,12 @@
 {
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+	"version": "1.2.6",
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 	"packages": {
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 			"name": "@ztimson/ai-utils",
-			"version": "1.0.6",
+			"version": "1.2.6",
 			"license": "MIT",
 			"dependencies": {
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@@ -57,34 +57,38 @@
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 			"license": "MIT",
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+			"dev": true,
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@@ -573,6 +577,16 @@
 				"url": "https://opencollective.com/libvips"
 			}
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+			"resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.11.3.tgz",
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+			"optional": true,
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@@ -681,22 +695,25 @@
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+			"engines": {
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 			"funding": {
 				"type": "github",
 				"url": "https://github.com/sponsors/Brooooooklyn"
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@@ -1007,6 +1024,18 @@
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 			}
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+		"node_modules/@rolldown/binding-wasm32-wasi/node_modules/@emnapi/core": {
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@@ -1018,6 +1047,17 @@
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 			}
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+		"node_modules/@rolldown/binding-wasm32-wasi/node_modules/@emnapi/wasi-threads": {
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+			"resolved": "https://registry.npmjs.org/@emnapi/wasi-threads/-/wasi-threads-1.2.2.tgz",
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+			"license": "MIT",
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@@ -1408,18 +1448,18 @@
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@@ -1504,9 +1544,9 @@
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@@ -2382,9 +2422,9 @@
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-			"version": "1.32.0",
-			"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.32.0.tgz",
-			"integrity": "sha512-bYcLp+Vb0awsiXg/80uCRezCYHNg1/l3mt0gzHnWV9XP1W5sKa5/TCdGWaR/zBM2PeF/HbsQv/j2URNOiVuxWg==",
+			"version": "1.33.0",
+			"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.33.0.tgz",
+			"integrity": "sha512-RYiYbkokw0trfKqqzfF55lginwEPrD3OJDfTuJzFs1MK6iFnDenaz1fqLLtX4ITG3OktJQXOeTaw1awrBAlZPw==",
 			"cpu": [
 				"x64"
 			],
@@ -2613,9 +2653,9 @@
 			}
 		},
 		"node_modules/lightningcss-win32-arm64-msvc": {
-			"version": "1.32.0",
-			"resolved": "https://registry.npmjs.org/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.32.0.tgz",
-			"integrity": "sha512-8SbC8BR40pS6baCM8sbtYDSwEVQd4JlFTOlaD3gWGHfThTcABnNDBda6eTZeqbofalIJhFx0qKzgHJmcPTnGdw==",
+			"version": "1.33.0",
+			"resolved": "https://registry.npmjs.org/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.33.0.tgz",
+			"integrity": "sha512-1K+MPfLSFVpphzpdbfkhlWk6wBrTObBzS2T6db10PNOZgR9GoVsAWzwNyuhUYYbTp23j+4RrncfujZ4uAzXvwA==",
 			"cpu": [
 				"arm64"
 			],
@@ -2634,9 +2674,9 @@
 			}
 		},
 		"node_modules/lightningcss-win32-x64-msvc": {
-			"version": "1.32.0",
-			"resolved": "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.32.0.tgz",
-			"integrity": "sha512-Amq9B/SoZYdDi1kFrojnoqPLxYhQ4Wo5XiL8EVJrVsB8ARoC1PWW6VGtT0WKCemjy8aC+louJnjS7U18x3b06Q==",
+			"version": "1.33.0",
+			"resolved": "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.33.0.tgz",
+			"integrity": "sha512-OlEICDx/Xl0FqSp4bry8zFnCvGpig3Gl4gCquvYwHuqJKEC1+n9NgDniFvqHGmMv1ZkqDJrDqKKSykTDX+ehuA==",
 			"cpu": [
 				"x64"
 			],
@@ -2794,9 +2834,9 @@
 			}
 		},
 		"node_modules/mdurl": {
-			"version": "2.0.0",
-			"resolved": "https://registry.npmjs.org/mdurl/-/mdurl-2.0.0.tgz",
-			"integrity": "sha512-Lf+9+2r+Tdp5wXDXC4PcIBjTDtq4UKjCPMQhKIuzpJNW0b96kVqSwW0bT7FhRSfmAiFYgP+SCRvdrDozfh0U5w==",
+			"version": "2.1.0",
+			"resolved": "https://registry.npmjs.org/mdurl/-/mdurl-2.1.0.tgz",
+			"integrity": "sha512-1+HBaOx0zi/dQWht8rNv9MYf9qqpqL/kxI0hXImU6Y547zM6Sni8BQibt7ifgMcYtQg41ao3Ivd6cnSM86inpg==",
 			"dev": true,
 			"license": "MIT"
 		},
@@ -2971,9 +3011,9 @@
 			"license": "MIT"
 		},
 		"node_modules/nanoid": {
-			"version": "3.3.15",
-			"resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.15.tgz",
-			"integrity": "sha512-y7Wygv/7mEOvxTuEQDB8StXdMRBWf1kR/tlhAzBRUFkB2jfcLOAxO/SHmOO2zgz1pVgK29/kyupn059/bCHdjA==",
+			"version": "3.3.16",
+			"resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.16.tgz",
+			"integrity": "sha512-bzlKTyNJ7+LdGIIwy8ijFpIqEQIvafahV7eYykJ8Cvh42EdJeODoJ6gUJXpQJvej1BddH8OqTXZNE/KfbWAu8Q==",
 			"dev": true,
 			"funding": [
 				{
@@ -3092,9 +3132,9 @@
 			"license": "MIT"
 		},
 		"node_modules/openai": {
-			"version": "6.46.0",
-			"resolved": "https://registry.npmjs.org/openai/-/openai-6.46.0.tgz",
-			"integrity": "sha512-DFg6jEPT2RO+oAyXtddeUJU8zkGy1OQ1AjGzNIJUMQG03TTqvCpy9tBpQ+2VVVnvrl3E56F8GEin2JYtWpITtA==",
+			"version": "6.49.0",
+			"resolved": "https://registry.npmjs.org/openai/-/openai-6.49.0.tgz",
+			"integrity": "sha512-aYCc0C6L864eR6WSYIwQGyXriw/nIyZx0ObvhzOEVuk0zoBDpynjSbrionWI7q65B5H8jJX0DXR9snEzM6bfPg==",
 			"license": "Apache-2.0",
 			"peerDependencies": {
 				"@aws-sdk/credential-provider-node": ">=3.972.0 <4",
@@ -3232,9 +3272,9 @@
 			"license": "MIT"
 		},
 		"node_modules/postcss": {
-			"version": "8.5.17",
-			"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.17.tgz",
-			"integrity": "sha512-J7EF+8X+CzRPaJPOv9Ck2wNWJvGnnl3PcNPAdGg6GTLjyVpyQ0yATMSXRFRV01BviT/9Gwuc3rjEyJbDJG9a4w==",
+			"version": "8.5.25",
+			"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.25.tgz",
+			"integrity": "sha512-DTPx3RWSSnWyzLxQnlH0rJP+EW5ekl16ZU4/psbIhA0e53kJfdgaN5vKM+xP7yJtXVu+nfdVFmlgFDEKAe4Pyw==",
 			"dev": true,
 			"funding": [
 				{
@@ -3252,7 +3292,7 @@
 			],
 			"license": "MIT",
 			"dependencies": {
-				"nanoid": "^3.3.12",
+				"nanoid": "^3.3.16",
 				"picocolors": "^1.1.1",
 				"source-map-js": "^1.2.1"
 			},
@@ -3787,9 +3827,9 @@
 			"license": "MIT"
 		},
 		"node_modules/undici": {
-			"version": "7.28.0",
-			"resolved": "https://registry.npmjs.org/undici/-/undici-7.28.0.tgz",
-			"integrity": "sha512-cRZYrTDwWznlnRiPjggAGxZXanty6M8RV1ff8Wm4LWXBp7/IG8v5DnOm74DtUBp9OONpK75YlPnIjQqX0dBDtA==",
+			"version": "7.29.0",
+			"resolved": "https://registry.npmjs.org/undici/-/undici-7.29.0.tgz",
+			"integrity": "sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==",
 			"license": "MIT",
 			"engines": {
 				"node": ">=20.18.1"
@@ -3981,16 +4021,16 @@
 			}
 		},
 		"node_modules/vite": {
-			"version": "8.1.4",
-			"resolved": "https://registry.npmjs.org/vite/-/vite-8.1.4.tgz",
-			"integrity": "sha512-bTT9PsdWO+MQMNG9ZXIP/qM9wGh37DFxTV/sPq9cFpHr3w4jkgef032PkAL9jAqhk3Nz8NQw3O8n6/xFkqO4QQ==",
+			"version": "8.1.5",
+			"resolved": "https://registry.npmjs.org/vite/-/vite-8.1.5.tgz",
+			"integrity": "sha512-7ULLwsCdYx/nRyrpiEwvqb5TFHrMVZyBt+rg/OAXT7rgj/z+DtTDyKFeLAdDkubDVDKD8jOsndmy7m55XcfUsw==",
 			"dev": true,
 			"license": "MIT",
 			"dependencies": {
 				"lightningcss": "^1.32.0",
 				"picomatch": "^4.0.5",
-				"postcss": "^8.5.16",
-				"rolldown": "~1.1.4",
+				"postcss": "^8.5.17",
+				"rolldown": "~1.1.5",
 				"tinyglobby": "^0.2.17"
 			},
 			"bin": {
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@ztimson/ai-utils",
-	"version": "1.2.6",
+	"version": "1.2.7",
 	"description": "AI Utility library",
 	"author": "Zak Timson",
 	"license": "MIT",
--- a/src/index.ts
+++ b/src/index.ts
@@ -3,6 +3,8 @@ export * from './antrhopic';
 export * from './audio';
 export * from './llm';
 export * from './memory';
+export * from './memory-cache';
+export * from './memory-graph';
 export * from './open-ai';
 export * from './provider';
 export * from './tools';
--- a/src/llm.ts
+++ b/src/llm.ts
@@ -1,12 +1,13 @@
 import {AbortablePromise, Ai} from './ai.ts';
 import {Anthropic} from './antrhopic.ts';
+import {MemoryCache} from './memory-cache.ts';
 import {OpenAi} from './open-ai.ts';
 import {LLMProvider} from './provider.ts';
 import {AiTool, AiToolArg} from './tools.ts';
 import {fileURLToPath} from 'url';
 import {dirname, join} from 'path';
 import {spawn} from 'node:child_process';
-import {Memory, MemoryCache, MemoryManager} from './memory.ts';
+import {Memory, MemoryManager} from './memory.ts';

 export type AnthropicConfig = {proto: 'anthropic', token: string};
 export type OpenAiConfig = {proto: 'openai', host?: string, token: string};
@@ -143,7 +144,7 @@ class LLM {
 		return {
 			prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
 			tools: [{
-				name: 'read_skill',
+				name: 'skill_read',
 				description: 'Read the full content of a skill/knowledge document',
 				args: {
 					name: {type: 'string', description: 'Exact skill name', required: true}
@@ -167,8 +168,14 @@ class LLM {
 		}
 		const m = options.model || this.defaultModel;
 		if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
-		let abort = () => {};
-		return Object.assign(new Promise<string>(async res => {
+		let request: AbortablePromise<string> | null = null;
+		let aborted = false;
+		const abort = () => {
+			aborted = true;
+			request?.abort?.();
+		};
+
+		const promise = (async () => {
 			let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
 			const prompts: string[] = [];
 			let history = options.history || [];
@@ -192,22 +199,27 @@ class LLM {
 			// Memory
 			if (options.memory) {
 				const mems = options.memory instanceof MemoryCache ? options.memory.memories : options.memory;
-				const relevant = await this.memoryManager.recollect(message, options.memory, 5);
-				prompts.unshift(`You have access to the following memory files:
-${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
-${relevant.length ? `
-Relevant memories have been preloaded:
-${relevant.map(r => `
-**${r.name}**
-${r.description}
-${r.content}
-`).join('\n---\n')}
-` : ''}`.trim());
-				tools.push(this.memoryManager.tools.read(options.memory));
+				if(mems.length) {
+					const relevant = await this.memoryManager.recollect(message, options.memory, 5);
+					prompts.unshift(`You have access to the following memory files:
+	${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
+	${relevant.length ? `
+	Relevant memories have been preloaded:
+	${relevant.map(r => `
+	**${r.name}**
+	${r.description}
+	${r.content}
+	`).join('\n---\n')}
+	` : ''}`.trim());
+					tools.push(this.memoryManager.tools.read(options.memory));
+				}
 			}

+			if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
+
 			prompts.unshift(options.system || this.ai.options.llm?.system || '');
-			const resp = await this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
+			request = this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
+			const resp = await request;

 			// Trim memory injections from history
 			if(options.memory) {
@@ -221,8 +233,10 @@ ${r.content}
 				if(options.history) options.history.splice(0, options.history.length, ...compressed);
 			}

-			return res(resp);
-		}), {abort});
+			return resp;
+		})();
+
+		return Object.assign(promise, {abort});
 	}

 	/**
--- a/src/memory-cache.ts
+++ b/src/memory-cache.ts
@@ -0,0 +1,59 @@
+import {KDPoint, KDTree} from './kd-tree.ts';
+import {Memory, MemoryRef} from './memory.ts';
+
+export class MemoryCache {
+	private tree: KDTree<MemoryRef>;
+	public memories: Memory[];
+
+	get length() { return this.memories.length; }
+
+	constructor(memories: Memory[]) {
+		this.memories = memories;
+		this.tree = this.buildTree();
+	}
+
+	private buildTree(): KDTree<MemoryRef> {
+		const embedded = this.memories.filter(m => m.embedding?.length);
+		if (!embedded.length) return new KDTree<MemoryRef>(0);
+
+		const dims = embedded[0].embedding.length;
+		const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
+			vector: m.embedding,
+			payload: {name: m.name, description: m.description},
+		}));
+
+		return new KDTree<MemoryRef>(dims, 'cosine', points);
+	}
+
+	search(query: number[], limit: number): MemoryRef[] {
+		const results = this.tree.knn(query, limit);
+		return results.map(r => r.point.payload);
+	}
+
+	add(memory: Memory): void {
+		this.memories.push(memory);
+		this.rebuild();
+	}
+
+	update(memory: Memory): void {
+		const idx = this.memories.findIndex(m => m.name === memory.name);
+		if (idx !== -1) {
+			this.memories[idx] = memory;
+		} else {
+			this.memories.push(memory);
+		}
+		this.rebuild();
+	}
+
+	remove(name: string): void {
+		const idx = this.memories.findIndex(m => m.name === name);
+		if (idx !== -1) {
+			this.memories.splice(idx, 1);
+			this.rebuild();
+		}
+	}
+
+	rebuild(): void {
+		this.tree = this.buildTree();
+	}
+}
--- a/src/memory-graph.ts
+++ b/src/memory-graph.ts
@@ -0,0 +1,69 @@
+import {MemoryCache} from './memory-cache.ts';
+import {extractMetadata, Memory, MemoryNode} from './memory.ts';
+
+export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
+	const mems = memories instanceof MemoryCache ? memories.memories : memories;
+	const nameSet = new Set(mems.map(m => m.name));
+	const ghosts = new Set<string>();
+
+	const nodes: MemoryNode[] = mems.map(m => {
+		const {links, backlinks} = extractMetadata(m.content);
+		return {
+			name: m.name,
+			missing: false,
+			links,
+			backlinks,
+		};
+	});
+
+	for (const node of nodes) {
+		for (const link of node.links) {
+			if (!nameSet.has(link)) ghosts.add(link);
+		}
+	}
+
+	return [
+		...nodes,
+		...[...ghosts].map(name => ({
+			name,
+			missing: true,
+			links: [],
+			backlinks: nodes
+				.filter(n => n.links.includes(name))
+				.map(n => n.name),
+		}))
+	];
+}
+
+export function renderMemoryGraph(nodes) {
+	if (!nodes.length) return 'No memories yet.';
+
+	const groups = new Map();
+	for (const node of nodes) {
+		const [prefix, ...rest] = node.name.split('/');
+		const group = rest.length ? prefix : 'Root';
+		const label = rest.length ? rest.join('/') : node.name;
+		if (!groups.has(group)) groups.set(group, []);
+		groups.get(group).push({...node, label});
+	}
+
+	const ghostCount = nodes.filter(n => n.missing).length;
+	const lines = [`Memory Graph (${nodes.length} nodes, ${ghostCount} ghost${ghostCount === 1 ? '' : 's'})`, ''];
+
+	for (const group of [...groups.keys()].sort()) {
+		const items = groups.get(group).sort((a, b) => a.label.localeCompare(b.label));
+		lines.push(`${group}/`);
+		items.forEach((n, i) => {
+			const last = i === items.length - 1;
+			const branch = last ? '└─' : '├─';
+			const pad = last ? '  ' : '│ ';
+			const tag = n.missing ? ' (ghost)' : '';
+			lines.push(`  ${branch} ${n.label}${tag}`);
+			if (n.links.length) lines.push(`  ${pad}   → ${n.links.join(', ')}`);
+			if (n.backlinks.length) lines.push(`  ${pad}   ← ${n.backlinks.join(', ')}`);
+		});
+		lines.push('');
+	}
+
+	return lines.join('\n').trimEnd();
+}
--- a/src/memory.ts
+++ b/src/memory.ts
@@ -1,6 +1,6 @@
 import {LLMRequest, LLMMessage} from './llm.ts';
+import {MemoryCache} from './memory-cache.ts';
 import {AiTool} from './tools.ts';
-import {KDTree, KDPoint} from './kd-tree.ts';

 export type Memory = {
 	name: string;
@@ -9,15 +9,14 @@ export type Memory = {
 	embedding: number[];
 }

-type MemoryRef = {
+export type MemoryRef = {
 	name: string;
 	description: string;
 }

-type FactBucket = {
+export type FactBucket = {
 	subject: string;
 	facts: string[];
-	isNew: boolean;
 }

 export type MemoryNode = {
@@ -27,41 +26,8 @@ export type MemoryNode = {
 	backlinks: string[];
 }

-export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
-	const mems = memories instanceof MemoryCache ? memories.memories : memories;
-	const nameSet = new Set(mems.map(m => m.name));
-	const ghosts = new Set<string>();
-
-	const nodes: MemoryNode[] = mems.map(m => {
-		const {links, backlinks} = extractMetadata(m.content);
-		return {
-			name: m.name,
-			missing: false,
-			links,
-			backlinks,
-		};
-	});
-
-	for (const node of nodes) {
-		for (const link of node.links) {
-			if (!nameSet.has(link)) ghosts.add(link);
-		}
-	}
-
-	return [
-		...nodes,
-		...[...ghosts].map(name => ({
-			name,
-			missing: true,
-			links: [],
-			backlinks: nodes
-				.filter(n => n.links.includes(name))
-				.map(n => n.name),
-		}))
-	];
-}
-
 function extractLinks(content: string): string[] {
+	if(!content) return [];
 	const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
 	return [...new Set([...matches].map(m => m[1].trim()))];
 }
@@ -83,6 +49,15 @@ export function extractMetadata(content: string): {links: string[], backlinks: s
 	};
 }

+function dedupeFacts(facts: string[]): string[] {
+	const seen = new Map<string, string>();
+	for (const f of facts) {
+		const clean = f.trim();
+		if (clean) seen.set(clean.toLowerCase(), clean);
+	}
+	return [...seen.values()];
+}
+
 function cosineDistance(a: number[], b: number[]): number {
 	let dot = 0, normA = 0, normB = 0;
 	for (let i = 0; i < a.length; i++) {
@@ -108,103 +83,7 @@ function getWeekSunday(monday: string): string {
 	return d.toISOString().slice(0, 10);
 }

-function tagsFromName(name: string): string[] {
-	const prefix = name.split('/')[0];
-	return prefix ? [prefix.toLowerCase()] : [];
-}

-export function serializeMemory(mem: Memory, week?: {monday: string, sunday: string}): string {
-	return mem.content;
-}
-
-export function deserializeMemory(raw: string, embedding: number[] = []): Memory {
-	const match = raw.match(/^---\n([\s\S]*?)\n---\n\n?([\s\S]*)$/);
-	if (!match) {
-		return {name: '', description: '', content: raw.trim(), embedding};
-	}
-
-	const [, fm] = match;
-	const get = (key: string): string => {
-		const m = fm.match(new RegExp(`^${key}:\\s*(.+)$`, 'm'));
-		return m ? m[1].trim() : '';
-	};
-
-	return {
-		name: get('name'),
-		description: get('description'),
-		content: raw.trim(),
-		embedding,
-	};
-}
-
-export class MemoryCache {
-	private tree: KDTree<MemoryRef>;
-	public memories: Memory[];
-	private locks = new Map<string, Promise<void>>();
-
-	constructor(memories: Memory[]) {
-		this.memories = memories;
-		this.tree = this.buildTree();
-	}
-
-	private buildTree(): KDTree<MemoryRef> {
-		const embedded = this.memories.filter(m => m.embedding?.length);
-		if (!embedded.length) return new KDTree<MemoryRef>(0);
-
-		const dims = embedded[0].embedding.length;
-		const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
-			vector: m.embedding,
-			payload: {name: m.name, description: m.description},
-		}));
-
-		return new KDTree<MemoryRef>(dims, 'cosine', points);
-	}
-
-	search(query: number[], limit: number): MemoryRef[] {
-		const results = this.tree.knn(query, limit);
-		return results.map(r => r.point.payload);
-	}
-
-	add(memory: Memory): void {
-		this.memories.push(memory);
-		this.rebuild();
-	}
-
-	update(memory: Memory): void {
-		const idx = this.memories.findIndex(m => m.name === memory.name);
-		if (idx !== -1) {
-			this.memories[idx] = memory;
-		} else {
-			this.memories.push(memory);
-		}
-		this.rebuild();
-	}
-
-	remove(name: string): void {
-		const idx = this.memories.findIndex(m => m.name === name);
-		if (idx !== -1) {
-			this.memories.splice(idx, 1);
-			this.rebuild();
-		}
-	}
-
-	rebuild(): void {
-		this.tree = this.buildTree();
-	}
-
-	lock<T>(name: string, fn: () => Promise<T>): Promise<T> {
-		const prev = this.locks.get(name) ?? Promise.resolve();
-		let resolveLock!: () => void;
-		const next = new Promise<void>(r => { resolveLock = r; });
-		this.locks.set(name, next);
-
-		const result = prev.then(fn).finally(resolveLock);
-		result.finally(() => {
-			if (this.locks.get(name) === next) this.locks.delete(name);
-		});
-		return result;
-	}
-}

 export class MemoryManager {
 	private pendingMemorizations = new Map<string, {
@@ -213,9 +92,15 @@ export class MemoryManager {
 		timestamp: number,
 	}>();

+	private queues = new Map<string, {
+		pending: string[],
+		request: {abort?: () => void} | null,
+		task: Promise<void>,
+	}>();
+
 	tools = {
 		read: (memories: Memory[] | MemoryCache): AiTool => ({
-			name: 'read_memory',
+			name: 'memory_recall',
 			description: 'Read the full content of a memory document',
 			args: {
 				name: {type: 'string', description: 'Exact memory name', required: true},
@@ -229,11 +114,10 @@ export class MemoryManager {
 		}),

 		forget: (memories: Memory[] | MemoryCache): AiTool => ({
-			name: 'forget_memory',
+			name: 'memory_forget',
 			description: 'Permanently delete a memory document and clean up all references to it',
 			args: {
-				name: {type: 'string', description: 'Exact memory name to forget', required: true},
-				reason: {type: 'string', description: 'Why this memory is being deleted', required: true},
+				name: {type: 'string', description: 'Exact memory name to forget', required: true}
 			},
 			fn: (args: any) => {
 				const result = this.forget(args.name, memories);
@@ -245,12 +129,8 @@ export class MemoryManager {
 	constructor(private llm: any) {}

 	private async createTempMemory(conversation: string): Promise<Memory> {
-		const [e] = await this.llm.embedding(conversation);
 		const timestamp = Date.now();
-		return {
-			name: `_temp_${timestamp}`,
-			description: 'Temporary memory - processing in background',
-			content: `---
+		const content = `---
 name: _temp_${timestamp}
 description: Temporary memory - processing in background
 tags: [_temporary]
@@ -261,7 +141,12 @@ modified: ${new Date().toISOString()}

 # Recent Conversation (Processing)

-${conversation}`,
+${conversation}`;
+		const [e] = await this.llm.embedding(content);
+		return {
+			name: `_temp_${timestamp}`,
+			description: 'Temporary memory - processing in background',
+			content,
 			embedding: e?.embedding || [],
 		};
 	}
@@ -302,17 +187,6 @@ ${conversation}`,
 		return scored.map(s => s.ref);
 	}

-	private createNode(name: string, memories: Memory[]): Memory {
-		const existing = memories.find(m => m.name === name);
-		if (existing) return existing;
-		return {
-			name,
-			description: '',
-			content: '',
-			embedding: [],
-		};
-	}
-
 	private listNodes(memories: Memory[]): MemoryRef[] {
 		return memories.map(m => ({name: m.name, description: m.description}));
 	}
@@ -361,7 +235,6 @@ ${conversation}`,
 			.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
 		if(!conversation) return [];

-		// Create and insert temp memory immediately
 		const trackingId = `${Date.now()}_${Math.random()}`;
 		const tempMemory = await this.createTempMemory(conversation);
 		const mem = memories instanceof MemoryCache ? memories.memories : memories;
@@ -374,65 +247,68 @@ ${conversation}`,
 		});

 		try {
-			await this._memorizeBackground(conversation, memories, options);
-			// Return the final memories (excluding temp ones)
+			await this._memorizeBackground(conversation, memories, options, tempMemory.name);
 			const finalMem = memories instanceof MemoryCache ? memories.memories : memories;
 			return finalMem.filter(m => !m.name.startsWith('_temp_'));
-		} catch (err) {
-			throw err;
 		} finally {
-			// Remove temp memory from the exact same memory array/cache
 			const pending = this.pendingMemorizations.get(trackingId);
 			if (pending) {
 				const cleanMem = pending.memories instanceof MemoryCache
 					? pending.memories.memories
 					: pending.memories;
 				const idx = cleanMem.findIndex(m => m.name === pending.tempMemoryName);
-				if (idx !== -1) {
-					cleanMem.splice(idx, 1);
-				}
-				if (pending.memories instanceof MemoryCache) {
-					pending.memories.rebuild();
-				}
+				if (idx !== -1) cleanMem.splice(idx, 1);
+				if (pending.memories instanceof MemoryCache) pending.memories.rebuild();
 			}
 			this.pendingMemorizations.delete(trackingId);
 		}
 	}

-	private async _memorizeBackground(conversation: string, memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
+	private async _memorizeBackground(conversation: string, memories: Memory[] | MemoryCache, options: LLMRequest, tempName: string): Promise<void> {
 		const mem = memories instanceof MemoryCache ? memories.memories : memories;
 		const monday = getWeekMonday();
 		const sunday = getWeekSunday(monday);
 		const buckets = await this.factAgent(conversation, mem, options, monday);
 		if(!buckets.length) return;
-
-		const runDocAgent = (node: Memory, bucket: FactBucket, embedding?: number[], week?: {monday: string, sunday: string}) => {
-			if (memories instanceof MemoryCache) {
-				return memories.lock(node.name, () => this.docAgent(node, bucket, mem, options, embedding, week));
+		const jobs = [...buckets].map(({subject, facts}) => {
+			let node = mem.find(m => m.name === subject);
+			if(!node) {
+				node = {name: subject, description: '', content: '', embedding: [],};
+				mem.push(node);
 			}
-			return this.docAgent(node, bucket, mem, options, embedding, week);
-		};
+			const week = subject.startsWith('Journal/') ? {monday, sunday} : undefined;
+			return this.enqueue(node, facts, mem, options, tempName, week);
+		});
+		await Promise.all(jobs);
+	}

-		await Promise.all(buckets.map(async bucket => {
-			let node = mem.find(m => m.name === bucket.subject && !m.name.startsWith('_temp_'));
-			let embedding: number[] | undefined;
+	/**
+	 * Coalescing queue: if a doc is already compiling, abort the in-flight run, merge its
+	 * facts with the new ones and restart. Never blocks a pending update, never drops facts.
+	 */
+	private enqueue(node: Memory, facts: string[], memories: Memory[] | MemoryCache, options: LLMRequest, tempName: string, week?: {monday: string, sunday: string}): Promise<void> {
+		const key = node.name;
+		const existing = this.queues.get(key);
+		if (existing) {
+			existing.pending.push(...facts);
+			existing.request?.abort?.();
+			return existing.task;
+		}

-			if (!node || bucket.isNew) {
-				const [e] = await this.llm.embedding(`${bucket.subject}\n${bucket.facts.join('\n')}`);
-				embedding = e?.embedding;
-
-				if (!node) {
-					node = this.createNode(bucket.subject, mem);
-					mem.push(node);
-				}
+		const entry: {pending: string[], request: {abort?: () => void} | null, task: Promise<void>} = {pending: [...facts], request: null, task: Promise.resolve()};
+		this.queues.set(key, entry);
+		const m = memories instanceof MemoryCache ? memories.memories : memories;
+		entry.task = (async () => {
+			while (entry.pending.length) {
+				const batch = dedupeFacts(entry.pending.splice(0, entry.pending.length));
+				const written = await this.docAgent(node, batch, m, options, tempName, week, entry);
+				if (!written) entry.pending.unshift(...batch);
 			}
-
-			const week = bucket.subject.startsWith('Journal/') ? {monday, sunday} : undefined;
-			await runDocAgent(node, bucket, embedding, week);
-		}));
-
-		if(memories instanceof MemoryCache)
-			memories.rebuild();
+		})().finally(() => {
+			this.queues.delete(key);
+			if(!this.queues.size && memories instanceof MemoryCache) memories.rebuild();
+		});
+		return entry.task;
 	}

 	private buildHeader(node: Memory, week?: {monday: string, sunday: string}, links: string[] = [], backlinks: string[] = []): string {
@@ -452,11 +328,7 @@ ${conversation}`,
 	}

 	private applyHeader(content: string, header: string): string {
-		const hasFrontmatter = content.trimStart().startsWith('---');
-		if (hasFrontmatter) {
-			return content.replace(/^---[\s\S]*?---\n?/, `${header}\n`);
-		}
-		return `${header}\n\n${content}`;
+		return `${header}\n\n${this.stripHeader(content)}`;
 	}

 	private updateFrontmatter(content: string, updates: {links?: string[], backlinks?: string[]}): string {
@@ -482,53 +354,53 @@ ${conversation}`,
 	}

 	private stripHeader(content: string): string {
-		return content.replace(/^---[\s\S]*?---\n?/, '').trimStart();
+		return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
 	}

-	private async docAgent(node: Memory, bucket: FactBucket, memories: Memory[], options: LLMRequest, precomputedEmbedding?: number[], week?: {monday: string, sunday: string}): Promise<void> {
+	private async docAgent(node: Memory, facts: string[], memories: Memory[], options: LLMRequest, tempName: string, week: {monday: string, sunday: string} | undefined, entry: {request: {abort?: () => void} | null}): Promise<boolean> {
 		const {links: oldLinks} = extractMetadata(node.content);
-		let finalContent = node.content;
-
-		await this.llm.ask(
-			`New facts to integrate:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`,
-			{
-				model: options.model,
-				temperature: 0.3,
-				system: `You are a knowledge base editor. Integrate the provided facts into the document below.
+		const currentBody = this.stripHeader(node.content);
+		let update;
+		try {
+			for(let i = 0; i < 3 && !update?.content; i++) {
+				const request = this.llm.ask(`New Facts:\n${facts.map(f => `- ${f}`).join('\n')}`, {
+					model: options.model,
+					temperature: 0.3,
+					schema: {
+						description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
+						content: {type: 'string', description: 'Rewritten document in markdown, without the frontmatter block', required: true},
+					},
+					system: `You are a knowledge base editor. Rewrite the current document below so it incorporates the new facts.

 Formatting rules:
- Use Obsidian-style markdown: # headings, **bold** for key terms, bullet lists for facts
+- Use Obsidian-style markdown: # headings, **bold** to add emphasis, __italics__ for titles, terms, etc, bullet & numbered lists for grouped 1D data and tables for 2D data
 - Link related concepts with [[WikiLink]] notation using full paths like [[People/Sarah]] or [[Projects/Website]]
- You may create links to nodes that don't exist yet if the concept is important
+- Create links for specific entities (person, place, project, program) and abstract concepts (quantum mechanics, entropy) but skip generics (car, red, dog)
 - Keep the document concise, factual, and human-readable
- Resolve any contradictions between old content and new facts (new facts win)
- Do not add filler, preamble, or AI commentary — just clean knowledge documents
- The document begins with a YAML frontmatter block (between --- markers) — do not remove or rewrite it, it is maintained automatically
-${week ? '- This is a weekly journal entry. The frontmatter contains the week date range.\n' : ''}
+- Resolve contradictions: the new facts always win — delete the outdated statement entirely, never keep both
+- Later facts in the list override earlier ones
+- Do not add frontmatter blocks, filler, preamble, or AI commentary
+${week ? '- This is a weekly journal entry.\n' : ''}
 All nodes:
 ${this.listNodes(memories).map(n => n.name).join(', ') || 'none'}

 Current document:
 \`\`\`markdown
-${node.content || '(empty — this is a new document)'}
-\`\`\``,
-				tools: [{
-					name: 'update_document',
-					description: 'Write the complete updated document content. Include everything after the frontmatter block — the frontmatter will be recalculated automatically.',
-					args: {
-						description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
-						content: {type: 'string', description: 'Document body in markdown, without the frontmatter block', required: true},
-					},
-					fn: (args: any) => {
-						node.description = args.description;
-						finalContent = args.content;
-						return 'Saved';
-					},
-				}],
+${currentBody}
+\`\`\``}
+				);
+				entry.request = request;
+				update = await request;
 			}
-		);
+		} catch (err: any) {
+			if (err?.name === 'AbortError') return false;
+			throw err;
+		} finally {
+			entry.request = null;
+		}

-		const newLinks = extractLinks(finalContent).filter(l => l !== node.name);
+		if(!update?.content) return false;
+		const newLinks = extractLinks(update.content).filter(l => l !== node.name && l !== tempName);
 		const newLinkSet = new Set(newLinks);
 		const oldLinkSet = new Set(oldLinks);

@@ -558,61 +430,55 @@ ${node.content || '(empty — this is a new document)'}
 		}

 		const {backlinks} = extractMetadata(node.content);
-		const header = this.buildHeader(node, week, newLinks, backlinks);
-		node.content = this.applyHeader(finalContent, header);
-
-		if (precomputedEmbedding) {
-			node.embedding = precomputedEmbedding;
-		} else {
-			const embedInput = `${node.description}\n\n${this.stripHeader(node.content)}`.trim();
-			const [e] = await this.llm.embedding(embedInput);
-			if (e) node.embedding = e.embedding;
-		}
+		node.description = update.description;
+		node.content = this.applyHeader(update.content, this.buildHeader(node, week, newLinks, backlinks));
+		const [e] = await this.llm.embedding(node.content);
+		if(e) node.embedding = e.embedding;
+		return true;
 	}

 	private async factAgent(conversation: string, memories: Memory[], options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
-		const buckets: FactBucket[] = [];
+		const buckets = new Map<string, string[]>();
 		await this.llm.ask(conversation, {
 			model: options.model,
 			temperature: 0.2,
 			system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.

 Rules:
- ONLY extract facts the USER explicitly stated about themselves, their work, or their projects
+- ONLY extract current facts the USER explicitly stated about themselves, their work, or their projects
 - ONLY extract decisions that were MADE during this conversation
 - DO NOT extract anything the AI said, its capabilities, or meta-conversation about the AI
 - DO NOT extract greetings, pleasantries, or generic exchanges
+- DO NOT extract deltas or changes in facts; ONLY the end fact
 - If nothing worth remembering was said, do not call any tools

 When extracting facts, you MUST also decide the exact destination path:
 - Use an existing node name if the facts clearly belong there
- All information primary about the user should go under "Personal/Subject" (e.g., Personal/Info, Personal/Todos)
+- All information primary about the user should go under "Personal/..." (e.g., Personal/Info, Personal/Todos)
 - When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide)
- For journal entries, use "journal" (will auto-route to Journal/${weekKey})
+- For journal entries, use "Journal"

 Available nodes:
-${this.listNodes(memories).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
+- Journal
+${this.listNodes(memories).filter(n => !n.name.includes('_temp_') && !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
 			tools: [{
-				name: 'extract_facts',
+				name: 'facts_extract',
 				description: 'Submit facts with their destination',
 				args: {
 					destination: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide")', required: true},
 					facts: {type: 'string', description: 'Comma-separated facts', required: true},
-					create_new: {type: 'boolean', description: 'True if this is a new node that doesn\'t exist yet', required: true},
 				},
 				fn: (args: any) => {
 					const subject = args.destination.trim().toLowerCase() === 'journal'
 						? `Journal/${weekKey}`
-						: args.destination;
-					buckets.push({
-						subject,
-						facts: args.facts.split(',').map((f: string) => f.trim()).filter(Boolean),
-						isNew: args.create_new,
-					});
+						: args.destination.trim();
+					const facts = buckets.get(subject) ?? [];
+					facts.push(...dedupeFacts(String(args.facts).split(',')));
+					buckets.set(subject, facts);
 					return 'Recorded';
 				},
 			}],
 		});
-		return buckets;
+		return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
 	}
 }
--- a/src/provider.ts
+++ b/src/provider.ts
@@ -1,5 +1,5 @@
 import {AbortablePromise} from './ai.ts';
-import {LLMMessage, LLMRequest} from './llm.ts';
+import {LLMRequest} from './llm.ts';

 export abstract class LLMProvider {
 	abstract ask(message: string, options: LLMRequest): AbortablePromise<string>;
--- a/src/tools.ts
+++ b/src/tools.ts
@@ -133,7 +133,7 @@ export const ExecTool: AiTool = {
 }

 export const FetchTool: AiTool = {
-	name: 'fetch',
+	name: 'net_fetch',
 	description: 'Make HTTP request to URL',
 	args: {
 		url: {type: 'string', description: 'URL to fetch', required: true},
@@ -172,7 +172,7 @@ export const PythonTool: AiTool = {
 }

 export const ReadWebpageTool: AiTool = {
-	name: 'read_webpage',
+	name: 'net_read',
 	description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
 	args: {
 		url: {type: 'string', description: 'URL to read', required: true},
@@ -276,7 +276,7 @@ export const ReadWebpageTool: AiTool = {
 };

 export const WebSearchTool: AiTool = {
-	name: 'web_search',
+	name: 'net_search',
 	description: 'Use duckduckgo (anonymous) to find find relevant online resources. Returns a list of URLs that works great with the `read_webpage` tool',
 	args: {
 		query: {type: 'string', description: 'Search string', required: true},
@@ -302,7 +302,7 @@ export const WebSearchTool: AiTool = {
 }

 export const WikipediaTool: AiTool = {
-	name: 'wikipedia_search',
+	name: 'get_wikipedia',
 	description: 'Search Wikipedia for matching articles',
 	args: {
 		query: {type: 'string', description: 'Search term or article title', required: true},