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1.2.3 ... 1.3.2

Author SHA1 Message Date
afc6653364 fixed openai system calls in history breaking anthropic calls
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2026-08-02 22:35:17 -04:00
68e72445a2 Keep recent memories in context
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2026-08-01 21:42:05 -04:00
1aa6cdf329 Agent/subagent support
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2026-08-01 18:28:16 -04:00
d022a5ef4d Improved levenshtein fuzzy match
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2026-08-01 12:00:26 -04:00
a1d438a20a Tools can now emit "done" event and end chat early gracefully
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2026-07-31 17:49:06 -04:00
52a9e3aaa4 Fixed history poisoning on empty tool response
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2026-07-30 22:12:49 -04:00
a7aec4ee29 Improved memory prompt slightly
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2026-07-30 16:00:03 -04:00
dda2d4c2a3 Bump 1.2.8
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2026-07-29 22:35:29 -04:00
58e0e488e4 Added Geo, FS and flarescraperr tools
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2026-07-29 22:34:51 -04:00
8dfcd06752 More memory fixes
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2026-07-29 22:11:09 -04:00
14f6cdd313 Personal file memory organization instructions
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2026-07-27 22:47:48 -04:00
73d6ee0f2a Personal file memory organization instructions
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2026-07-27 22:39:06 -04:00
bee4085666 updatememory awaits full result
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2026-07-27 22:34:36 -04:00
3b5c71de7c Improved memory management
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2026-07-27 20:10:09 -04:00
8 changed files with 1399 additions and 628 deletions

234
package-lock.json generated
View File

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"integrity": "sha512-0nnMyoyOLRJXfbMOilaSRcLH3Jw5z9HDNGfT/gwCPgaDjnx0i8w7vBzFLFR1f6CMLKF8gVbebmkUN3fa/kQJpQ==", "integrity": "sha512-j2v/itmy4HlNxlc6voKXYgBqNi0Ng2LShg4z7GufpEgs05P+2suBVyi9I6YHq5uoVFx9ETin3eCEhLVyXGQnKg==",
"cpu": [ "cpu": [
"arm64" "arm64"
], ],
@@ -2541,9 +2581,9 @@
} }
}, },
"node_modules/lightningcss-linux-arm64-musl": { "node_modules/lightningcss-linux-arm64-musl": {
"version": "1.32.0", "version": "1.33.0",
"resolved": "https://registry.npmjs.org/lightningcss-linux-arm64-musl/-/lightningcss-linux-arm64-musl-1.32.0.tgz", "resolved": "https://registry.npmjs.org/lightningcss-linux-arm64-musl/-/lightningcss-linux-arm64-musl-1.33.0.tgz",
"integrity": "sha512-UpQkoenr4UJEzgVIYpI80lDFvRmPVg6oqboNHfoH4CQIfNA+HOrZ7Mo7KZP02dC6LjghPQJeBsvXhJod/wnIBg==", "integrity": "sha512-yiO5ROMuYQgXbC60yjZU5CYSFZGKXL0HFATXt9mHJn1+zW55oCtMI9NfcVhYLMFDL7gV7oBPon/EmMMGg2OvtQ==",
"cpu": [ "cpu": [
"arm64" "arm64"
], ],
@@ -2565,9 +2605,9 @@
} }
}, },
"node_modules/lightningcss-linux-x64-gnu": { "node_modules/lightningcss-linux-x64-gnu": {
"version": "1.32.0", "version": "1.33.0",
"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-gnu/-/lightningcss-linux-x64-gnu-1.32.0.tgz", "resolved": "https://registry.npmjs.org/lightningcss-linux-x64-gnu/-/lightningcss-linux-x64-gnu-1.33.0.tgz",
"integrity": "sha512-V7Qr52IhZmdKPVr+Vtw8o+WLsQJYCTd8loIfpDaMRWGUZfBOYEJeyJIkqGIDMZPwPx24pUMfwSxxI8phr/MbOA==", "integrity": "sha512-ar+Ju7LmcN0Jo4FpL4hpFybwNG9/3A/Br5KW2n2jyODg3MEZXaDYADdemoNS+BDNfMgKvylJLj4S5tyRActuAg==",
"cpu": [ "cpu": [
"x64" "x64"
], ],
@@ -2589,9 +2629,9 @@
} }
}, },
"node_modules/lightningcss-linux-x64-musl": { "node_modules/lightningcss-linux-x64-musl": {
"version": "1.32.0", "version": "1.33.0",
"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.32.0.tgz", "resolved": "https://registry.npmjs.org/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.33.0.tgz",
"integrity": "sha512-bYcLp+Vb0awsiXg/80uCRezCYHNg1/l3mt0gzHnWV9XP1W5sKa5/TCdGWaR/zBM2PeF/HbsQv/j2URNOiVuxWg==", "integrity": "sha512-RYiYbkokw0trfKqqzfF55lginwEPrD3OJDfTuJzFs1MK6iFnDenaz1fqLLtX4ITG3OktJQXOeTaw1awrBAlZPw==",
"cpu": [ "cpu": [
"x64" "x64"
], ],
@@ -2613,9 +2653,9 @@
} }
}, },
"node_modules/lightningcss-win32-arm64-msvc": { "node_modules/lightningcss-win32-arm64-msvc": {
"version": "1.32.0", "version": "1.33.0",
"resolved": "https://registry.npmjs.org/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.32.0.tgz", "resolved": "https://registry.npmjs.org/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.33.0.tgz",
"integrity": "sha512-8SbC8BR40pS6baCM8sbtYDSwEVQd4JlFTOlaD3gWGHfThTcABnNDBda6eTZeqbofalIJhFx0qKzgHJmcPTnGdw==", "integrity": "sha512-1K+MPfLSFVpphzpdbfkhlWk6wBrTObBzS2T6db10PNOZgR9GoVsAWzwNyuhUYYbTp23j+4RrncfujZ4uAzXvwA==",
"cpu": [ "cpu": [
"arm64" "arm64"
], ],
@@ -2634,9 +2674,9 @@
} }
}, },
"node_modules/lightningcss-win32-x64-msvc": { "node_modules/lightningcss-win32-x64-msvc": {
"version": "1.32.0", "version": "1.33.0",
"resolved": "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.32.0.tgz", "resolved": "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.33.0.tgz",
"integrity": "sha512-Amq9B/SoZYdDi1kFrojnoqPLxYhQ4Wo5XiL8EVJrVsB8ARoC1PWW6VGtT0WKCemjy8aC+louJnjS7U18x3b06Q==", "integrity": "sha512-OlEICDx/Xl0FqSp4bry8zFnCvGpig3Gl4gCquvYwHuqJKEC1+n9NgDniFvqHGmMv1ZkqDJrDqKKSykTDX+ehuA==",
"cpu": [ "cpu": [
"x64" "x64"
], ],
@@ -2794,9 +2834,9 @@
} }
}, },
"node_modules/mdurl": { "node_modules/mdurl": {
"version": "2.0.0", "version": "2.1.0",
"resolved": "https://registry.npmjs.org/mdurl/-/mdurl-2.0.0.tgz", "resolved": "https://registry.npmjs.org/mdurl/-/mdurl-2.1.0.tgz",
"integrity": "sha512-Lf+9+2r+Tdp5wXDXC4PcIBjTDtq4UKjCPMQhKIuzpJNW0b96kVqSwW0bT7FhRSfmAiFYgP+SCRvdrDozfh0U5w==", "integrity": "sha512-1+HBaOx0zi/dQWht8rNv9MYf9qqpqL/kxI0hXImU6Y547zM6Sni8BQibt7ifgMcYtQg41ao3Ivd6cnSM86inpg==",
"dev": true, "dev": true,
"license": "MIT" "license": "MIT"
}, },
@@ -2971,9 +3011,9 @@
"license": "MIT" "license": "MIT"
}, },
"node_modules/nanoid": { "node_modules/nanoid": {
"version": "3.3.15", "version": "3.3.16",
"resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.15.tgz", "resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.16.tgz",
"integrity": "sha512-y7Wygv/7mEOvxTuEQDB8StXdMRBWf1kR/tlhAzBRUFkB2jfcLOAxO/SHmOO2zgz1pVgK29/kyupn059/bCHdjA==", "integrity": "sha512-bzlKTyNJ7+LdGIIwy8ijFpIqEQIvafahV7eYykJ8Cvh42EdJeODoJ6gUJXpQJvej1BddH8OqTXZNE/KfbWAu8Q==",
"dev": true, "dev": true,
"funding": [ "funding": [
{ {
@@ -3092,9 +3132,9 @@
"license": "MIT" "license": "MIT"
}, },
"node_modules/openai": { "node_modules/openai": {
"version": "6.46.0", "version": "6.49.0",
"resolved": "https://registry.npmjs.org/openai/-/openai-6.46.0.tgz", "resolved": "https://registry.npmjs.org/openai/-/openai-6.49.0.tgz",
"integrity": "sha512-DFg6jEPT2RO+oAyXtddeUJU8zkGy1OQ1AjGzNIJUMQG03TTqvCpy9tBpQ+2VVVnvrl3E56F8GEin2JYtWpITtA==", "integrity": "sha512-aYCc0C6L864eR6WSYIwQGyXriw/nIyZx0ObvhzOEVuk0zoBDpynjSbrionWI7q65B5H8jJX0DXR9snEzM6bfPg==",
"license": "Apache-2.0", "license": "Apache-2.0",
"peerDependencies": { "peerDependencies": {
"@aws-sdk/credential-provider-node": ">=3.972.0 <4", "@aws-sdk/credential-provider-node": ">=3.972.0 <4",
@@ -3232,9 +3272,9 @@
"license": "MIT" "license": "MIT"
}, },
"node_modules/postcss": { "node_modules/postcss": {
"version": "8.5.17", "version": "8.5.25",
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.17.tgz", "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.25.tgz",
"integrity": "sha512-J7EF+8X+CzRPaJPOv9Ck2wNWJvGnnl3PcNPAdGg6GTLjyVpyQ0yATMSXRFRV01BviT/9Gwuc3rjEyJbDJG9a4w==", "integrity": "sha512-DTPx3RWSSnWyzLxQnlH0rJP+EW5ekl16ZU4/psbIhA0e53kJfdgaN5vKM+xP7yJtXVu+nfdVFmlgFDEKAe4Pyw==",
"dev": true, "dev": true,
"funding": [ "funding": [
{ {
@@ -3252,7 +3292,7 @@
], ],
"license": "MIT", "license": "MIT",
"dependencies": { "dependencies": {
"nanoid": "^3.3.12", "nanoid": "^3.3.16",
"picocolors": "^1.1.1", "picocolors": "^1.1.1",
"source-map-js": "^1.2.1" "source-map-js": "^1.2.1"
}, },
@@ -3787,9 +3827,9 @@
"license": "MIT" "license": "MIT"
}, },
"node_modules/undici": { "node_modules/undici": {
"version": "7.28.0", "version": "7.29.0",
"resolved": "https://registry.npmjs.org/undici/-/undici-7.28.0.tgz", "resolved": "https://registry.npmjs.org/undici/-/undici-7.29.0.tgz",
"integrity": "sha512-cRZYrTDwWznlnRiPjggAGxZXanty6M8RV1ff8Wm4LWXBp7/IG8v5DnOm74DtUBp9OONpK75YlPnIjQqX0dBDtA==", "integrity": "sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==",
"license": "MIT", "license": "MIT",
"engines": { "engines": {
"node": ">=20.18.1" "node": ">=20.18.1"
@@ -3981,16 +4021,16 @@
} }
}, },
"node_modules/vite": { "node_modules/vite": {
"version": "8.1.4", "version": "8.1.5",
"resolved": "https://registry.npmjs.org/vite/-/vite-8.1.4.tgz", "resolved": "https://registry.npmjs.org/vite/-/vite-8.1.5.tgz",
"integrity": "sha512-bTT9PsdWO+MQMNG9ZXIP/qM9wGh37DFxTV/sPq9cFpHr3w4jkgef032PkAL9jAqhk3Nz8NQw3O8n6/xFkqO4QQ==", "integrity": "sha512-7ULLwsCdYx/nRyrpiEwvqb5TFHrMVZyBt+rg/OAXT7rgj/z+DtTDyKFeLAdDkubDVDKD8jOsndmy7m55XcfUsw==",
"dev": true, "dev": true,
"license": "MIT", "license": "MIT",
"dependencies": { "dependencies": {
"lightningcss": "^1.32.0", "lightningcss": "^1.32.0",
"picomatch": "^4.0.5", "picomatch": "^4.0.5",
"postcss": "^8.5.16", "postcss": "^8.5.17",
"rolldown": "~1.1.4", "rolldown": "~1.1.5",
"tinyglobby": "^0.2.17" "tinyglobby": "^0.2.17"
}, },
"bin": { "bin": {

View File

@@ -1,6 +1,6 @@
{ {
"name": "@ztimson/ai-utils", "name": "@ztimson/ai-utils",
"version": "1.2.3", "version": "1.3.2",
"description": "AI Utility library", "description": "AI Utility library",
"author": "Zak Timson", "author": "Zak Timson",
"license": "MIT", "license": "MIT",

View File

@@ -21,10 +21,10 @@ export class Anthropic extends LLMProvider {
messages.push(<any>{timestamp, ...h}); messages.push(<any>{timestamp, ...h});
} else { } else {
const textContent = h.content?.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n'); const textContent = h.content?.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
if(textContent) messages.push({timestamp, role: h.role, content: textContent}); if(textContent) messages.push({role: h.role, content: textContent, timestamp: timestamp});
h.content.forEach((c: any) => { h.content.forEach((c: any) => {
if(c.type == 'tool_use') { if(c.type == 'tool_use') {
messages.push({timestamp, role: 'tool', id: c.id, name: c.name, args: c.input, content: undefined}); messages.push({role: 'tool', id: c.id, name: c.name, args: c.input, timestamp: c.timestamp, content: undefined});
} else if(c.type == 'tool_result') { } else if(c.type == 'tool_result') {
const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id); const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id);
if(m) m[c.is_error ? 'error' : 'content'] = c.content; if(m) m[c.is_error ? 'error' : 'content'] = c.content;
@@ -46,13 +46,16 @@ export class Anthropic extends LLMProvider {
i++; i++;
} }
} }
return history.map(({timestamp, ...h}) => h); return history;
} }
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> { ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
const controller = new AbortController(); const controller = new AbortController();
return Object.assign(new Promise<any>(async (res) => { return Object.assign(new Promise<any>(async (res) => {
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]); let history = this.fromStandard([
...(options.history || []).filter(h => h.role !== 'system'),
{role: 'user', content: message, timestamp: Date.now()}
]);
const tools = options.tools || this.ai.options.llm?.tools || []; const tools = options.tools || this.ai.options.llm?.tools || [];
const requestParams: any = { const requestParams: any = {
model: options.model || this.model, model: options.model || this.model,
@@ -83,8 +86,9 @@ export class Anthropic extends LLMProvider {
}; };
} }
let resp: any, isFirstMessage = true; let resp: any, hasStreamedText = false, terminal = false;
do { do {
requestParams.messages = history.map(({timestamp, ...m}) => m);
resp = await this.client.messages.create(requestParams).catch(err => { resp = await this.client.messages.create(requestParams).catch(err => {
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`; err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
throw err; throw err;
@@ -92,8 +96,7 @@ export class Anthropic extends LLMProvider {
// Streaming mode // Streaming mode
if(options.stream) { if(options.stream) {
if(!isFirstMessage) options.stream({text: '\n\n'}); if(hasStreamedText) options.stream({text: '\n\n'});
else isFirstMessage = false;
resp.content = []; resp.content = [];
for await (const chunk of resp) { for await (const chunk of resp) {
if(controller.signal.aborted) break; if(controller.signal.aborted) break;
@@ -107,13 +110,13 @@ export class Anthropic extends LLMProvider {
if(chunk.delta.type === 'text_delta') { if(chunk.delta.type === 'text_delta') {
const text = chunk.delta.text; const text = chunk.delta.text;
resp.content.at(-1).text += text; resp.content.at(-1).text += text;
options.stream({text}); if(text) { hasStreamedText = true; options.stream({text}); }
} else if(chunk.delta.type === 'input_json_delta') { } else if(chunk.delta.type === 'input_json_delta') {
resp.content.at(-1).input += chunk.delta.partial_json; resp.content.at(-1).input += chunk.delta.partial_json;
} }
} else if(chunk.type === 'content_block_stop') { } else if(chunk.type === 'content_block_stop') {
const last = resp.content.at(-1); const last = resp.content.at(-1);
if(last.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {}; if(last?.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
} else if(chunk.type === 'message_stop') { } else if(chunk.type === 'message_stop') {
break; break;
} }
@@ -123,31 +126,35 @@ export class Anthropic extends LLMProvider {
// Run tools // Run tools
const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use'); const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use');
if(toolCalls.length && !controller.signal.aborted) { if(toolCalls.length && !controller.signal.aborted) {
history.push({role: 'assistant', content: resp.content}); history.push({role: 'assistant', content: resp.content, timestamp: Date.now()});
const results = await Promise.all(toolCalls.map(async (toolCall: any) => { const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
const tool = tools.find(findByProp('name', toolCall.name)); const tool = tools.find(findByProp('name', toolCall.name));
if(options.stream) options.stream({tool: toolCall.name}); if(options.stream) options.stream({tool: toolCall.name});
if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'}; if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'};
try { try {
const result = await tool.fn(toolCall.input, options?.stream, this.ai); // Wrap stream so a tool's `done` ends turn gracefully
const toolStream = options.stream && ((chunk: any) => {
if(chunk.done) { terminal = true; return; }
options.stream!(chunk);
});
const result = await tool.fn(toolCall.input, toolStream, this.ai);
return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result}; return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
} catch (err: any) { } catch (err: any) {
return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'}; return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
} }
})); }));
history.push({role: 'user', content: results}); history.push({role: 'user', content: results, timestamp: Date.now()});
requestParams.messages = history; requestParams.messages = history;
} }
} while (!controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use')); } while (!terminal && !controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
if(!terminal) {
const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n'); const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
history.push({role: 'assistant', content: textContent}); history.push({role: 'assistant', content: textContent, timestamp: Date.now()});
}
history = this.toStandard(history); history = this.toStandard(history);
if(options.stream) options.stream({done: true}); if(options.stream) options.stream({done: true});
if(options.history) options.history.splice(0, options.history.length, ...history); if(options.history) options.history.splice(0, options.history.length, ...history);
// Return parsed JSON if schema provided
const finalContent = history.at(-1)?.content; const finalContent = history.at(-1)?.content;
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent); res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
}), {abort: () => controller.abort()}); }), {abort: () => controller.abort()});

View File

@@ -1,3 +1,4 @@
import {snakeCase} from '@ztimson/utils';
import {AbortablePromise, Ai} from './ai.ts'; import {AbortablePromise, Ai} from './ai.ts';
import {Anthropic} from './antrhopic.ts'; import {Anthropic} from './antrhopic.ts';
import {OpenAi} from './open-ai.ts'; import {OpenAi} from './open-ai.ts';
@@ -6,11 +7,25 @@ import {AiTool, AiToolArg} from './tools.ts';
import {fileURLToPath} from 'url'; import {fileURLToPath} from 'url';
import {dirname, join} from 'path'; import {dirname, join} from 'path';
import {spawn} from 'node:child_process'; import {spawn} from 'node:child_process';
import {Memory, MemoryCache, MemoryManager} from './memory.ts'; import {Memory, MemoryCache, MemoryManager, MemoryOptions} from './memory.ts';
export type AnthropicConfig = {proto: 'anthropic', token: string}; export type AnthropicConfig = {proto: 'anthropic', token: string};
export type OpenAiConfig = {proto: 'openai', host?: string, token: string}; export type OpenAiConfig = {proto: 'openai', host?: string, token: string};
export type Agent = {
name: string;
description?: string;
model?: string | null;
temperature?: number;
system: string;
delegate?: boolean;
skills?: Skill[] | null;
tools?: AiTool[] | null;
mcp?: McpServer[] | null;
/** Explicit whitelist of agents this agent may delegate to. Default: none - must opt-in, self is always excluded */
agents?: string[] | null;
}
export type LLMMessage = { export type LLMMessage = {
/** Message originator */ /** Message originator */
role: 'assistant' | 'system' | 'user'; role: 'assistant' | 'system' | 'user';
@@ -55,13 +70,17 @@ export type LLMRequest = {
/** Compress old messages in the chat to free up context */ /** Compress old messages in the chat to free up context */
compress?: {max: number; min: number}; compress?: {max: number; min: number};
/** User's memory documents - RAG injected automatically each turn */ /** User's memory documents - RAG injected automatically each turn */
memory?: Memory[] | MemoryCache; memory?: Memory[] | MemoryCache | MemoryOptions;
/** Model to use for memory operations */ /** Model to use for memory operations */
memoryModel?: string; memoryModel?: string;
/** Skill documents the AI can browse and read on demand */ /** Skill documents the AI can browse and read on demand */
skills?: Skill[]; skills?: Skill[];
/** MCP servers to connect and expose as tools */ /** MCP servers to connect and expose as tools */
mcp?: McpServer[]; mcp?: McpServer[];
/** Subagents exposed as delegatable/wrapped tools */
agents?: Agent[];
/** @internal recursion guard for nested agent delegation */
_agentDepth?: number;
} }
export type McpServer = { export type McpServer = {
@@ -82,6 +101,7 @@ export type Skill = {
content: string; content: string;
} }
const MAX_AGENT_DEPTH = 5;
class LLM { class LLM {
private memoryManager!: MemoryManager; private memoryManager!: MemoryManager;
@@ -99,6 +119,60 @@ class LLM {
this.memoryManager = new MemoryManager(this); this.memoryManager = new MemoryManager(this);
} }
/**
* Wrap agents as tools. Nested delegation is opt-in only (empty by default, like
* tools/skills/mcp) and an agent can never call itself even if explicitly whitelisted.
* Delegate results are queued in `pending` and spliced into history by `ask()` after
* the provider's own end-of-turn history sync has already run.
*/
private setupAgent(agents: Agent[] = [], allAgents: Agent[], pending: Map<string, {resp: string, subHistory: LLMMessage[]}[]>, aborts: (() => void)[], depth = 0): AiTool[] {
return agents.map(a => {
const toolName = `${a.delegate ? '' : 'sub'}agent_${snakeCase(a.name)}`;
return {
name: toolName,
description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
args: {
context: {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true},
instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
},
fn: async (args: any, stream: any) => {
if(depth >= MAX_AGENT_DEPTH) return 'Max agent delegation depth exceeded';
const subHistory: LLMMessage[] = [];
// Opt-in only, self always excluded regardless of whitelist
const nested = (a.agents || [])
.map(name => allAgents.find(x => x.name === name))
.filter((x): x is Agent => !!x && x.name !== a.name);
const request = this.ask(`${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`, {
system: `You are a specialized subagent. ${a.delegate ? 'Your output streams directly to the user for the remainder of this turn.' : 'You are wrapped in a tool call that will be analysis by an LLM'}
As a subagent, focus on executing your task completely using available tools and returning only the final result - no commentary, questions, or dialogue.
${a.system}`,
model: a.model || undefined,
temperature: a.temperature,
stream: a.delegate ? stream : undefined,
history: subHistory,
mcp: a.mcp || undefined,
skills: a.skills || undefined,
tools: a.tools || undefined,
agents: nested,
_agentDepth: depth + 1,
} as any);
aborts.push(request.abort);
const resp = await request;
if(a.delegate) {
if(!pending.has(toolName)) pending.set(toolName, []);
pending.get(toolName)!.push({resp, subHistory});
return '';
}
return resp;
}
};
});
}
private async setupMcp(servers: McpServer[] = []): Promise<{prompt: string, tools: AiTool[]}> { private async setupMcp(servers: McpServer[] = []): Promise<{prompt: string, tools: AiTool[]}> {
if(!servers?.length) return {prompt: '', tools: []}; if(!servers?.length) return {prompt: '', tools: []};
const allTools: AiTool[] = []; const allTools: AiTool[] = [];
@@ -143,7 +217,7 @@ class LLM {
return { return {
prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`, prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
tools: [{ tools: [{
name: 'read_skill', name: 'skill_read',
description: 'Read the full content of a skill/knowledge document', description: 'Read the full content of a skill/knowledge document',
args: { args: {
name: {type: 'string', description: 'Exact skill name', required: true} name: {type: 'string', description: 'Exact skill name', required: true}
@@ -167,8 +241,16 @@ class LLM {
} }
const m = options.model || this.defaultModel; const m = options.model || this.defaultModel;
if(!this.models[m]) throw new Error(`Model does not exist: ${m}`); if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
let abort = () => {}; let request: AbortablePromise<string> | null = null;
return Object.assign(new Promise<string>(async res => { let aborted = false;
const nestedAborts: (() => void)[] = [];
const abort = () => {
aborted = true;
request?.abort?.();
nestedAborts.forEach(a => a());
};
const promise = (async () => {
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || []; let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
const prompts: string[] = []; const prompts: string[] = [];
let history = options.history || []; let history = options.history || [];
@@ -189,48 +271,96 @@ class LLM {
tools.push(...s.tools); tools.push(...s.tools);
} }
// Agents
const agents = options.agents || this.ai.options?.llm?.agents;
const pendingDelegates = new Map<string, {resp: string, subHistory: LLMMessage[]}[]>();
if(agents?.length) tools.push(...this.setupAgent(agents, agents, pendingDelegates, nestedAborts, options._agentDepth || 0));
// Memory // Memory
if (options.memory) { const mem = MemoryManager.normalize(options.memory);
const mems = options.memory instanceof MemoryCache ? options.memory.memories : options.memory; if(mem) {
const relevant = await this.memoryManager.recollect(message, options.memory, 5); const mems = mem.memory instanceof MemoryCache ? mem.memory.memories : mem.memory;
if(mems.length) {
if(mem.inject) {
const pool = 15; // candidates considered, cheap since only refs are listed
const budget = mem.maxTokens ?? 2000; // actual content injected
const relevant = await this.memoryManager.recollect(message, mem.memory, pool);
let used = 0;
const preloaded: typeof relevant = [];
const listed: typeof relevant = [];
for(const r of relevant) {
const t = this.estimateTokens(r.content);
if(used + t <= budget || preloaded.length === 0) {
preloaded.push(r);
used += t;
} else listed.push(r);
}
prompts.unshift(`You have access to the following memory files: prompts.unshift(`You have access to the following memory files:
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')} ${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
${relevant.length ? ` ${preloaded.length ? `
Relevant memories have been preloaded: Relevant memories have been preloaded:
${relevant.map(r => ` ${preloaded.map(r => `
**${r.name}** **${r.name}**
${r.description} ${r.description}
${r.content} ${r.content}
`).join('\n---\n')} `).join('\n---\n')}
` : ''}${listed.length ? `
Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.name).join(', ')}
` : ''}`.trim()); ` : ''}`.trim());
tools.push(this.memoryManager.tools.read(options.memory));
} }
if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
}
}
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
prompts.unshift(options.system || this.ai.options.llm?.system || ''); 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')});
let resp = await request;
// Spice delegated agents response into history
let lastDelegateResp: string | null = null;
if(pendingDelegates.size) {
for(let i = 0; i < history.length; i++) {
const h = history[i];
if(h.role !== 'tool' || h.content !== '') continue;
const queue = pendingDelegates.get(h.name);
if(!queue?.length) continue;
const {resp: delegateResp, subHistory} = queue.shift()!;
const insert: LLMMessage[] = [...subHistory.filter(sh => sh.role === 'tool'), {role: 'assistant', content: delegateResp, timestamp: Date.now()}];
history.splice(i + 1, 0, ...insert);
lastDelegateResp = delegateResp;
i += insert.length;
}
}
// If the orchestrator added no commentary of its own, its answer IS the delegate's answer
if(typeof resp === 'string' && !resp.trim() && lastDelegateResp !== null) resp = lastDelegateResp;
// Trim memory injections from history // Trim memory injections from history
if(options.memory) { if(mem?.tool) history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'memory_recall'));
history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'recall'));
}
// Auto-memorize before compressing // Auto-memorize before compressing
if(options.compress && this.estimateTokens(history) >= options.compress.max) { if(options.compress && this.estimateTokens(history) >= options.compress.max) {
if(options.memory) await this.memoryManager.memorize(history, options.memory, {model: options.memoryModel || this.defaultModel, ...options}); if(mem?.update) await this.memoryManager.memorize(history, mem.memory, {model: options.memoryModel || this.defaultModel, ...options});
const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options); const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options);
if(options.history) options.history.splice(0, options.history.length, ...compressed); if(options.history) options.history.splice(0, options.history.length, ...compressed);
} }
return res(resp); return resp;
}), {abort}); })();
return Object.assign(promise, {abort});
} }
/** /**
* Digest full conversation history into memory documents. * Digest full conversation history into memory documents.
* Call on session end to persist the conversation. * Call on session end to persist the conversation.
*/ */
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<void> { async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
await this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options}); return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
} }
/** /**
@@ -383,15 +513,33 @@ ${r.content}
* @param {string} searchTerms Multiple search terms to check against target * @param {string} searchTerms Multiple search terms to check against target
* @returns {{avg: number, max: number, similarities: number[]}} Similarity values 0-1: 0 = unique, 1 = identical * @returns {{avg: number, max: number, similarities: number[]}} Similarity values 0-1: 0 = unique, 1 = identical
*/ */
fuzzyMatch(target: string, ...searchTerms: string[]) { fuzzyMatch(target, ...searchTerms) {
if (searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare'); if (searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
const vector = (text: string, dimensions: number = 10): number[] => { const levenshtein = (a, b) => {
return text.toLowerCase().split('').map((char, index) => const m = a.length, n = b.length;
(char.charCodeAt(0) * (index + 1)) % dimensions / dimensions).slice(0, dimensions); if (!m) return n;
if (!n) return m;
const dp = Array.from({length: m + 1}, (_, i) => [i, ...Array(n).fill(0)]);
for (let j = 0; j <= n; j++) dp[0][j] = j;
for (let i = 1; i <= m; i++) {
for (let j = 1; j <= n; j++) {
dp[i][j] = a[i - 1] === b[j - 1]
? dp[i - 1][j - 1]
: 1 + Math.min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]);
} }
const v = vector(target); }
const similarities = searchTerms.map(t => vector(t)).map(refVector => this.cosineSimilarity(v, refVector)); return dp[m][n];
return {avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length, max: Math.max(...similarities), similarities}; };
const similarity = (a, b) => {
a = a.toLowerCase(); b = b.toLowerCase();
return 1 - levenshtein(a, b) / Math.max(a.length, b.length, 1);
};
const similarities = searchTerms.map(t => similarity(target, t));
return {
avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length,
max: Math.max(...similarities),
similarities
};
} }
/** /**

View File

@@ -1,92 +1,80 @@
import {LLMRequest, LLMMessage} from './llm.ts'; import {LLMRequest, LLMMessage} from './llm.ts';
import {AiTool} from './tools.ts'; import {AiTool} from './tools.ts';
import {KDTree, KDPoint} from './kd-tree.ts'; import {KDPoint, KDTree} from './kd-tree.ts';
export type Memory = {
name: string;
description: string;
content: string;
embedding: number[];
links: string[];
backlinks: string[];
}
type MemoryRef = {
name: string;
description: string;
}
type FactBucket = {
subject: string;
facts: string[];
}
export type MemoryNode = {
name: string;
missing: boolean;
links: string[];
backlinks: string[];
}
export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] { export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
const mems = memories instanceof MemoryCache ? memories.memories : memories; const mems = memories instanceof MemoryCache ? memories.memories : memories;
const nameSet = new Set(mems.map(m => m.name)); const nameSet = new Set(mems.map(m => m.name));
const ghosts = new Set<string>(); const ghosts = new Set<string>();
for (const m of mems) { const nodes: MemoryNode[] = mems.map(m => {
for (const link of m.links) { 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); if (!nameSet.has(link)) ghosts.add(link);
} }
} }
return [ return [
...mems.map(m => ({ ...nodes,
name: m.name,
missing: false,
links: m.links,
backlinks: m.backlinks,
})),
...[...ghosts].map(name => ({ ...[...ghosts].map(name => ({
name, name,
missing: true, missing: true,
links: [], links: [],
backlinks: mems backlinks: nodes
.filter(m => m.links.includes(name)) .filter(n => n.links.includes(name))
.map(m => m.name), .map(n => n.name),
})) }))
]; ];
} }
function extractLinks(content: string): string[] { export function renderMemoryGraph(nodes) {
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g); if (!nodes.length) return 'No memories yet.';
return [...new Set([...matches].map(m => m[1].trim()))];
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});
} }
function rebuildBacklinks(memories: Memory[]): void { const ghostCount = nodes.filter(n => n.missing).length;
for (const m of memories) m.backlinks = []; const lines = [`Memory Graph (${nodes.length} nodes, ${ghostCount} ghost${ghostCount === 1 ? '' : 's'})`, ''];
for (const m of memories) {
for (const link of m.links) { for (const group of [...groups.keys()].sort()) {
const target = memories.find(t => t.name === link); const items = groups.get(group).sort((a, b) => a.label.localeCompare(b.label));
if (target) target.backlinks.push(m.name); 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('');
} }
function cosineDistance(a: number[], b: number[]): number { return lines.join('\n').trimEnd();
let dot = 0, normA = 0, normB = 0;
for (let i = 0; i < a.length; i++) {
dot += a[i] * b[i];
normA += a[i] * a[i];
normB += b[i] * b[i];
}
const denom = Math.sqrt(normA) * Math.sqrt(normB);
return denom === 0 ? 1 : 1 - dot / denom;
} }
export class MemoryCache { export class MemoryCache {
private tree: KDTree<MemoryRef>; private tree: KDTree<MemoryRef>;
public memories: Memory[]; public memories: Memory[];
get length() { return this.memories.length; }
constructor(memories: Memory[]) { constructor(memories: Memory[]) {
this.memories = memories; this.memories = memories;
this.tree = this.buildTree(); this.tree = this.buildTree();
@@ -125,20 +113,131 @@ export class MemoryCache {
this.rebuild(); 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 { rebuild(): void {
this.tree = this.buildTree(); this.tree = this.buildTree();
} }
rebuildLinks(): void {
rebuildBacklinks(this.memories);
} }
export type MemoryOptions = {
/** Memory object */
memory: Memory[] | MemoryCache;
/** Inject N memories into the system prompt */
inject?: boolean;
/** expose recall tool to LLM */
tool?: boolean;
/** Update memory on compression */
update?: boolean;
/** Max context size of memories to inject to each call (removed immediately after use) */
maxTokens?: number;
}
export type Memory = {
name: string;
description: string;
content: string;
embedding: number[];
}
export type MemoryRef = {
name: string;
description: string;
}
export type FactBucket = {
subject: string;
facts: string[];
}
export type MemoryNode = {
name: string;
missing: boolean;
links: string[];
backlinks: string[];
}
function extractLinks(content: string): string[] {
if(!content) return [];
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
return [...new Set([...matches].map(m => m[1].trim()))];
}
export function extractMetadata(content: string): {links: string[], backlinks: string[]} {
const match = content.match(/^---\n([\s\S]*?)\n---/);
if (!match) return {links: [], backlinks: []};
const fm = match[1];
const getList = (key: string): string[] => {
const m = fm.match(new RegExp(`^${key}:\\s*\\[(.*)\\]$`, 'm'));
if (!m || !m[1].trim()) return [];
return m[1].split(',').map(s => s.trim().replace(/^"|"$/g, '')).filter(Boolean);
};
return {
links: getList('links'),
backlinks: getList('backlinks'),
};
}
function dedupeFacts(facts: string[]): string[] {
const seen = new Map<string, string>();
for (const f of facts) {
const clean = f.trim();
if (clean) seen.set(clean.toLowerCase(), clean);
}
return [...seen.values()];
}
function cosineDistance(a: number[], b: number[]): number {
let dot = 0, normA = 0, normB = 0;
for (let i = 0; i < a.length; i++) {
dot += a[i] * b[i];
normA += a[i] * a[i];
normB += b[i] * b[i];
}
const denom = Math.sqrt(normA) * Math.sqrt(normB);
return denom === 0 ? 1 : 1 - dot / denom;
}
function getWeekMonday(date: Date = new Date()): string {
const d = new Date(Date.UTC(date.getFullYear(), date.getMonth(), date.getDate()));
const day = d.getUTCDay();
const diff = day === 0 ? -6 : 1 - day;
d.setUTCDate(d.getUTCDate() + diff);
return d.toISOString().slice(0, 10);
}
function getWeekSunday(monday: string): string {
const d = new Date(`${monday}T00:00:00Z`);
d.setUTCDate(d.getUTCDate() + 6);
return d.toISOString().slice(0, 10);
} }
export class MemoryManager { export class MemoryManager {
private recentlyTouched = new Map<string, number>();
private pendingMemorizations = new Map<string, {
memories: Memory[] | MemoryCache,
tempMemoryName: string,
timestamp: number,
}>();
private queues = new Map<string, {
pending: string[],
request: {abort?: () => void} | null,
task: Promise<void>,
}>();
tools = { tools = {
read: (memories: Memory[] | MemoryCache): AiTool => ({ read: (memories: Memory[] | MemoryCache): AiTool => ({
name: 'read_memory', name: 'memory_recall',
description: 'Read the full content of a memory document', description: 'Read the full content of a memory document',
args: { args: {
name: {type: 'string', description: 'Exact memory name', required: true}, name: {type: 'string', description: 'Exact memory name', required: true},
@@ -147,56 +246,212 @@ export class MemoryManager {
const mems = memories instanceof MemoryCache ? memories.memories : memories; const mems = memories instanceof MemoryCache ? memories.memories : memories;
const mem = mems.find(m => m.name === args.name); const mem = mems.find(m => m.name === args.name);
if (!mem) return 'Document not found'; if (!mem) return 'Document not found';
return this.formatMemory(mem); this.touch(mem.name);
} return mem.content;
},
}),
forget: (memories: Memory[] | MemoryCache): AiTool => ({
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}
},
fn: (args: any) => {
const result = this.forget(args.name, memories);
return result ? `Forgotten: ${args.name}` : `Not found: ${args.name}`;
},
}), }),
}; };
constructor(private llm: any) {} constructor(private llm: any) {}
static normalize(m?: Memory[] | MemoryCache | MemoryOptions) {
if(!m) return null;
const raw = m instanceof MemoryCache || Array.isArray(m);
return raw ? {memory: <Memory[] | MemoryCache>m, inject: true, tool: true, update: true} : {inject: true, tool: true, update: true, ...m};
}
private async createTempMemory(conversation: string): Promise<Memory> {
const timestamp = Date.now();
const content = `---
name: _temp_${timestamp}
description: Temporary memory - processing in background
tags: [_temporary]
links: []
backlinks: []
modified: ${new Date().toISOString()}
---
# Recent Conversation (Processing)
${conversation}`;
const [e] = await this.llm.embedding(content);
return {
name: `_temp_${timestamp}`,
description: 'Temporary memory - processing in background',
content,
embedding: e?.embedding || [],
};
}
private applyHeader(content: string, header: string): string {
return `${header}\n\n${this.stripHeader(content)}`;
}
private async backgroundMemorization(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 jobs = [...buckets].map(({subject, facts}) => {
let node = mem.find(m => m.name === subject);
if(!node) {
node = {name: subject, description: '', content: '', embedding: [],};
mem.push(node);
}
const week = subject.startsWith('Journal/') ? {monday, sunday} : undefined;
return this.enqueue(node, facts, mem, options, tempName, week);
});
await Promise.all(jobs);
}
private buildHeader(node: Memory, week?: {monday: string, sunday: string}, links: string[] = [], backlinks: string[] = []): string {
const tags = node.name.split('/')[0]?.toLowerCase();
const lines = [
'---',
`name: ${node.name}`,
`description: ${node.description || ''}`,
tags ? `tags: [${tags}]` : '',
links.length ? `links: [${links.map(l => `"${l}"`).join(', ')}]` : 'links: []',
backlinks.length ? `backlinks: [${backlinks.map(l => `"${l}"`).join(', ')}]` : 'backlinks: []',
week ? `week: ${week.monday} ${week.sunday}` : '',
`modified: ${new Date().toISOString()}`,
'---',
].filter(Boolean);
return lines.join('\n');
}
private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] { private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
const scored = memories const scored = memories
.filter(m => m.embedding?.length) .filter(m => m.embedding?.length)
.map(m => ({ .map(m => ({
ref: {name: m.name, description: m.description}, ref: {name: m.name, description: m.description},
distance: cosineDistance(query, m.embedding) distance: cosineDistance(query, m.embedding),
})) }))
.sort((a, b) => a.distance - b.distance) .sort((a, b) => a.distance - b.distance)
.slice(0, limit); .slice(0, limit);
return scored.map(s => s.ref); return scored.map(s => s.ref);
} }
private createNode(name: string, memories: Memory[]): Memory { /**
const existing = memories.find(m => m.name === name); * Coalescing queue: if a doc is already compiling, abort the in-flight run, merge its
if(existing) return existing; * facts with the new ones and restart. Never blocks a pending update, never drops facts.
return { */
name, private enqueue(node: Memory, facts: string[], memories: Memory[] | MemoryCache, options: LLMRequest, tempName: string, week?: {monday: string, sunday: string}): Promise<void> {
description: '', const key = node.name;
content: '', const existing = this.queues.get(key);
embedding: [], if (existing) {
links: [], existing.pending.push(...facts);
backlinks: [], existing.request?.abort?.();
}; return existing.task;
} }
private formatMemory(mem: Memory): string { const entry: {pending: string[], request: {abort?: () => void} | null, task: Promise<void>} = {pending: [...facts], request: null, task: Promise.resolve()};
return [ this.queues.set(key, entry);
`# ${mem.name}`, const m = memories instanceof MemoryCache ? memories.memories : memories;
mem.description ? `> ${mem.description}` : '', entry.task = (async () => {
mem.links.length ? `**Links:** ${mem.links.map(l => `[[${l}]]`).join(', ')}` : '', while (entry.pending.length) {
mem.backlinks.length ? `**Referenced by:** ${mem.backlinks.map(l => `[[${l}]]`).join(', ')}` : '', const batch = dedupeFacts(entry.pending.splice(0, entry.pending.length));
'', const written = await this.docAgent(node, batch, m, options, tempName, week, entry);
mem.content, if (!written) entry.pending.unshift(...batch);
].filter(l => l !== undefined).join('\n'); }
})().finally(() => {
this.queues.delete(key);
if(!this.queues.size && memories instanceof MemoryCache) memories.rebuild();
});
return entry.task;
} }
private listNodes(memories: Memory[]): MemoryRef[] { private listNodes(memories: Memory[]): MemoryRef[] {
return memories.map(m => ({name: m.name, description: m.description})); return memories.map(m => ({name: m.name, description: m.description}));
} }
decay() {
for(const [name, ttl] of this.recentlyTouched) {
if(ttl <= 1) this.recentlyTouched.delete(name);
else this.recentlyTouched.set(name, ttl - 1);
}
}
forget(name: string, memories: Memory[] | MemoryCache): boolean {
const mem = memories instanceof MemoryCache ? memories.memories : memories;
const idx = mem.findIndex(m => m.name === name);
if (idx === -1) return false;
for (const node of mem) {
const {links, backlinks} = extractMetadata(node.content);
const newBacklinks = backlinks.filter(b => b !== name);
const newLinks = links.filter(l => l !== name);
if (newBacklinks.length !== backlinks.length || newLinks.length !== links.length) {
node.content = this.updateFrontmatter(node.content, {
links: newLinks,
backlinks: newBacklinks,
});
}
}
mem.splice(idx, 1);
if (memories instanceof MemoryCache) memories.rebuild();
return true;
}
getTouched(): string[] {
return [...this.recentlyTouched.keys()];
}
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory[]> {
const conversation = history
.filter(h => h.role === 'user' || h.role === 'assistant')
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
if(!conversation) return [];
const trackingId = `${Date.now()}_${Math.random()}`;
const tempMemory = await this.createTempMemory(conversation);
const mem = memories instanceof MemoryCache ? memories.memories : memories;
mem.push(tempMemory);
if (memories instanceof MemoryCache) memories.rebuild();
this.pendingMemorizations.set(trackingId, {
memories,
tempMemoryName: tempMemory.name,
timestamp: Date.now(),
});
try {
await this.backgroundMemorization(conversation, memories, options, tempMemory.name);
const finalMem = memories instanceof MemoryCache ? memories.memories : memories;
return finalMem.filter(m => !m.name.startsWith('_temp_'));
} finally {
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();
}
this.pendingMemorizations.delete(trackingId);
}
}
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> { async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
const mem: Memory[] = memories instanceof MemoryCache ? memories.memories : memories; const mem: Memory[] = memories instanceof MemoryCache ? memories.memories : memories;
if (!mem.length) return []; if (!mem.length) return [];
const [e] = await this.llm.embedding(query); const [e] = await this.llm.embedding(query);
if (!e) return []; if (!e) return [];
@@ -212,7 +467,8 @@ export class MemoryManager {
for (const name of frontier) { for (const name of frontier) {
const node = mem.find(m => m.name === name); const node = mem.find(m => m.name === name);
if (!node) continue; if (!node) continue;
for(const link of node.links) { const {links} = extractMetadata(node.content);
for (const link of links) {
if (!found.has(link) && mem.find(m => m.name === link)) { if (!found.has(link) && mem.find(m => m.name === link)) {
found.add(link); found.add(link);
next.push(link); next.push(link);
@@ -230,272 +486,157 @@ export class MemoryManager {
return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean); return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean);
} }
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> { touch(name: string, ttl = 2) {
const mem = memories instanceof MemoryCache ? memories.memories : memories; this.recentlyTouched.set(name, ttl);
const conversation = history
.filter(h => h.role === 'user' || h.role === 'assistant')
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
if(conversation) {
const buckets = await this.factAgent(conversation, mem, options);
if(buckets.length) {
await Promise.all(buckets.map(async bucket => {
const node = await this.organizingAgent(bucket, mem, options);
if(!mem.find(m => m.name === node.name)) mem.push(node);
await this.docAgent(node, bucket, mem, options);
}));
}
} }
// Auto-compress old journals private updateFrontmatter(content: string, updates: {links?: string[], backlinks?: string[]}): string {
const weekAgo = Date.now() - (7 * 24 * 60 * 60 * 1000); const match = content.match(/^---\n([\s\S]*?)\n---\n\n?([\s\S]*)$/);
const oldDailies = mem.filter(m => { if (!match) return content;
const journal = /^Journal\/(\d{4}-\d{2}-\d{2}$)/.exec(m.name);
return journal && new Date(journal[1]).getTime() < weekAgo;
});
if(oldDailies.length) { const [, fm, body] = match;
const byMonth = new Map<string, Memory[]>(); let newFm = fm;
for(const daily of oldDailies) {
const match = daily.name.match(/^Journal\/(\d{4}-\d{2})-\d{2}$/); if (updates.links !== undefined) {
if(!match) continue; const linksList = updates.links.length ? `[${updates.links.map(l => `"${l}"`).join(', ')}]` : '[]';
const monthKey = match[1]; newFm = newFm.replace(/^links:.*$/m, `links: ${linksList}`);
if(!byMonth.has(monthKey)) byMonth.set(monthKey, []);
byMonth.get(monthKey)!.push(daily);
} }
for(const [monthKey, entries] of byMonth) { if (updates.backlinks !== undefined) {
const monthlyPath = `Journal/${monthKey}`; const backlinksList = updates.backlinks.length ? `[${updates.backlinks.map(l => `"${l}"`).join(', ')}]` : '[]';
let monthly = mem.find(m => m.name === monthlyPath); newFm = newFm.replace(/^backlinks:.*$/m, `backlinks: ${backlinksList}`);
if(!monthly) {
monthly = this.createNode(monthlyPath, mem);
mem.push(monthly);
} }
const bucket: FactBucket = { newFm = newFm.replace(/^modified:.*$/m, `modified: ${new Date().toISOString()}`);
subject: monthlyPath,
facts: entries.flatMap(e => e.content.split('\n').filter(line => line.trim())),
};
await this.docAgent(monthly, bucket, mem, options); return `---\n${newFm}\n---\n\n${body}`;
for(const daily of entries) {
const idx = mem.indexOf(daily);
if(idx !== -1) mem.splice(idx, 1);
}
}
} }
if (memories instanceof MemoryCache) { private stripHeader(content: string): string {
memories.rebuildLinks(); return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
memories.rebuild();
} else {
rebuildBacklinks(mem);
}
} }
private async docAgent(node: Memory, bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<void> { private async docAgent(node: Memory, facts: string[], memories: Memory[], options: LLMRequest, tempName: string, week: {monday: string, sunday: string} | undefined, entry: {request: {abort?: () => void} | null}): Promise<boolean> {
let finalContent = node.content; const {links: oldLinks} = extractMetadata(node.content);
const isJournalCompression = node.name.match(/^Journal\/\d{4}-\d{2}$/); const currentBody = this.stripHeader(node.content);
const systemPrompt = isJournalCompression let update;
? `You are a journal compressor. Condense the daily entries below into a monthly summary. try {
for(let i = 0; i < 3 && !update?.content; i++) {
Format: const request = this.llm.ask(`New Facts:\n${facts.map(f => `- ${f}`).join('\n')}`, {
# ${node.name} model: options.model,
temperature: 0.3,
## Themes schema: {
(Recurring topics, moods, patterns) 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},
## Key Events },
(Important moments, decisions, milestones) system: `You are a knowledge base editor. Rewrite the current document below so it incorporates the new facts.
## Notable Conversations
(Significant discussions or revelations)
Rules:
- Use [[WikiLinks]] to reference permanent notes using full paths like [[People/Sarah]] or [[Projects/Website]]
- Keep it concise but preserve emotional/temporal context
- Discard filler but keep things the user vented about or cared about
- If a fact belongs in a permanent note, link to it instead of duplicating
Current monthly summary:
\`\`\`markdown
${node.content || '(empty — first compression for this month)'}
\`\`\``
: `You are a knowledge base editor. Integrate the provided facts into the document below.
Formatting rules: 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]] - 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 - Keep the document concise, factual, and human-readable
- Resolve any contradictions between old content and new facts (new facts win) - Resolve contradictions: the new facts always win — delete the outdated statement entirely, never keep both
- Do not add filler, preamble, or AI commentary — just clean knowledge documents - 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: All nodes:
${this.listNodes(memories).map(n => n.name).join(', ') || 'none'} ${this.listNodes(memories).map(n => n.name).join(', ') || 'none'}
Current document: Current document:
\`\`\`markdown \`\`\`markdown
${node.content || '(empty — this is a new document)'} ${currentBody}
\`\`\``; \`\`\``}
await this.llm.ask(
`New facts to integrate:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`,
{
model: options.model,
temperature: 0.3,
system: systemPrompt,
tools: [{
name: 'update_document',
description: 'Write the complete updated document content',
args: {
description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
content: {type: 'string', description: 'Fully updated document in markdown', required: true},
},
fn:(args: any) => {
node.description = args.description;
finalContent = args.content;
return 'Saved';
}
}]
}
); );
entry.request = request;
update = await request;
}
} catch (err: any) {
if (err?.name === 'AbortError') return false;
throw err;
} finally {
entry.request = null;
}
node.content = finalContent; if(!update?.content) return false;
node.links = extractLinks(finalContent); const newLinks = extractLinks(update.content).filter(l => l !== node.name && l !== tempName);
const needsEmbed = !node.embedding?.length || node.description !== memories.find(m => m.name === node.name)?.description; const newLinkSet = new Set(newLinks);
if (needsEmbed) { const oldLinkSet = new Set(oldLinks);
const [e] = await this.llm.embedding(node.description);
for (const added of newLinkSet) {
if (!oldLinkSet.has(added)) {
const target = memories.find(m => m.name === added);
if (target) {
const {backlinks} = extractMetadata(target.content);
if (!backlinks.includes(node.name)) {
target.content = this.updateFrontmatter(target.content, {
backlinks: [...backlinks, node.name],
});
}
}
}
}
for (const removed of oldLinkSet) {
if (!newLinkSet.has(removed)) {
const target = memories.find(m => m.name === removed);
if (target) {
const {backlinks} = extractMetadata(target.content);
target.content = this.updateFrontmatter(target.content, {
backlinks: backlinks.filter(b => b !== node.name),
});
}
}
}
const {backlinks} = extractMetadata(node.content);
node.description = node.name !== 'Person/User' ? update.description : 'All information about the current user';
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; if(e) node.embedding = e.embedding;
} return true;
} }
private async factAgent(conversation: string, memories: Memory[], options: LLMRequest): Promise<FactBucket[]> { private async factAgent(conversation: string, memories: Memory[], options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
const buckets: FactBucket[] = []; const buckets = new Map<string, string[]>();
const today = new Date().toISOString().split('T')[0];
await this.llm.ask(conversation, { await this.llm.ask(conversation, {
model: options.model, model: options.model,
temperature: 0.2, temperature: 0.2,
system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term. system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.
Rules: 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 - 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 anything the AI said, its capabilities, or meta-conversation about the AI
- DO NOT extract greetings, pleasantries, or generic exchanges - 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 - If nothing worth remembering was said, do not call any tools
**Organizational patterns:** When extracting facts, you MUST also decide the exact destination path:
- Journal entries use paths like: Journal/${today} - Use an existing node name if the facts clearly belong there
- People use paths like: People/Name - All information primary about the user should go under "People/User"
- Projects use paths like: Projects/Name - When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide)
- Personal info uses paths like: Personal/Goals, Personal/Tasks, etc. - For journal entries, use "Journal"
- General knowledge uses paths like: Biology/Topic, History/Topic, etc.
Learn from existing nodes and follow the same pattern when extracting.
Group facts by subject. For each group call \`extract_facts\` once with the FULL PATH.
Known nodes (name: description):
${this.listNodes(memories).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
tools: [{
name: 'extract_facts',
description: 'Submit a group of related facts for a specific subject',
args: {
subject: {type: 'string', description: 'Full path for the subject (e.g., "Journal/2025-01-27", "People/Sarah", "Projects/Website")', required: true},
facts: {type: 'string', description: 'Comma-separated list of extracted facts', required: true},
},
fn: (args: any) => {
buckets.push({
subject: args.subject,
facts: args.facts.split(',').map((f: string) => f.trim()).filter(Boolean),
});
return 'Recorded';
}
}]
});
return buckets;
}
private async organizingAgent(bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<Memory> {
let candidates = this.listNodes(memories);
let attempts = 0;
const maxAttempts = 3;
while (attempts++ < maxAttempts) {
let home = '', mode: string | null = null;
const resp = await this.llm.ask(`Subject: ${bucket.subject}\n\nFacts:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`, {
model: options.model,
temperature: 0.1,
system: `You are a knowledge organizer. Your job is to find the correct home for the supplied facts.
1. Review the facts and the node list below. Pick the most likely match or decide if a new node is needed.
2. If you picked an existing node, use \`read\` to verify it's the right place.
- After reading, call either \`confirm\` (correct node) or \`mismatched\` (wrong node).
3. If none of the nodes match, call \`create\` to make a new node.
**Organizational patterns:**
- Journal entries: Journal/YYYY-MM-DD
- People: People/Name
- Projects: Projects/Name
- Personal: Personal/Goals, Personal/Tasks, etc.
- Knowledge: Biology/Topic, History/Topic, etc.
Available nodes: Available nodes:
${candidates.map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None — create a new node.'}`, - Journal
${this.listNodes(memories).filter(n => !n.name.includes('_temp_') && !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
tools: [{ tools: [{
name: 'read', name: 'facts_extract',
description: 'Read a node file to verify it is the right home for these facts', description: 'Submit facts with their destination',
args: {name: {type: 'string', description: 'Exact node name (full path)', required: true}},
fn: ({name}) => {
const mem = memories.find(m => m.name === name);
if (!mem) return 'Node not found';
home = name;
return this.formatMemory(mem);
}
}, {
name: 'confirm',
description: 'Confirm this is the correct node for the facts',
args: {},
fn: () => {
mode = 'success';
resp.abort();
}
}, {
name: 'mismatched',
description: 'This is not the node you are looking for',
args: {},
fn: () => {
mode = 'failed';
resp.abort();
}
}, {
name: 'create',
description: 'No existing node fits — create a new one',
args: { args: {
name: {type: 'string', description: 'Full path for the new node (e.g., "People/Sarah", "Journal/2025-01-27")', required: true} destination: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide")', required: true},
facts: {type: 'string', description: 'Comma-separated facts', required: true},
}, },
fn: ({name}) => { fn: (args: any) => {
home = name; const subject = args.destination.trim().toLowerCase() === 'journal'
mode = 'create'; ? `Journal/${weekKey}` : args.destination.trim();
resp.abort(); const facts = buckets.get(subject) ?? [];
} facts.push(...dedupeFacts(String(args.facts).split(',')));
}] buckets.set(subject, facts);
return 'Recorded';
},
}],
}); });
return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
if(mode === 'create') {
return this.createNode(home, memories);
} else if (mode === 'failed') {
candidates = candidates.filter(c => c.name !== home);
if(!candidates.length) return this.createNode(bucket.subject, memories);
} else if (mode === 'success') {
const existing = memories.find(m => m.name === home);
return existing || this.createNode(home, memories);
}
}
return this.createNode(bucket.subject, memories);
} }
} }

View File

@@ -29,11 +29,11 @@ export class OpenAi extends LLMProvider {
})); }));
history.splice(i, 1, ...tools); history.splice(i, 1, ...tools);
i += tools.length - 1; i += tools.length - 1;
} else if(h.role === 'tool' && h.content) { } else if(h.role === 'tool') {
const record = history.find(h2 => h.tool_call_id == h2.id); const record = history.find(h2 => h.tool_call_id == h2.id);
if(record) { if(record) {
if(h.content.includes('"error":')) record.error = h.content; if(h.content?.includes('"error":')) record.error = h.content;
else record.content = h.content; else record.content = h.content || '';
} }
history.splice(i, 1); history.splice(i, 1);
i--; i--;
@@ -51,15 +51,16 @@ export class OpenAi extends LLMProvider {
content: null, content: null,
tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }], tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }],
refusal: null, refusal: null,
annotations: [] annotations: [],
timestamp: h.timestamp,
}, { }, {
role: 'tool', role: 'tool',
tool_call_id: h.id, tool_call_id: h.id,
content: h.error || h.content content: h.error || h.content,
timestamp: h.timestamp,
}); });
} else { } else {
const {timestamp, ...rest} = h; result.push(h);
result.push(rest);
} }
return result; return result;
}, [] as any[]); }, [] as any[]);
@@ -68,11 +69,12 @@ export class OpenAi extends LLMProvider {
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> { ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
const controller = new AbortController(); const controller = new AbortController();
return Object.assign(new Promise<any>(async (res, rej) => { return Object.assign(new Promise<any>(async (res, rej) => {
if(options.system) { const base = (options.history || []).filter(h => h.role !== 'system');
if(options.history?.[0]?.role != 'system') options.history?.splice(0, 0, {role: 'system', content: options.system, timestamp: Date.now()}); let history = this.fromStandard([
else options.history[0].content = options.system; ...(options.system ? [{role: <any>'system', content: options.system, timestamp: Date.now()}] : []),
} ...base,
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]); {role: 'user', content: message, timestamp: Date.now()}
]);
const tools = options.tools || this.ai.options.llm?.tools || []; const tools = options.tools || this.ai.options.llm?.tools || [];
const requestParams: any = { const requestParams: any = {
model: options.model || this.model, model: options.model || this.model,
@@ -106,24 +108,24 @@ export class OpenAi extends LLMProvider {
}; };
} }
let resp: any, isFirstMessage = true; let resp: any, hasStreamedText = false, terminal = false;
do { do {
requestParams.messages = history.map(({timestamp, ...m}) => m);
resp = await this.client.chat.completions.create(requestParams).catch(err => { resp = await this.client.chat.completions.create(requestParams).catch(err => {
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`; err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
throw err; throw err;
}); });
if(options.stream) { if(options.stream) {
if(!isFirstMessage) options.stream({text: '\n\n'}); if(hasStreamedText) options.stream({text: '\n\n'});
else isFirstMessage = false; resp.choices = [{message: {role: 'assistant', content: '', tool_calls: [], timestamp: Date.now()}}];
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: []}}];
for await (const chunk of resp) { for await (const chunk of resp) {
if(controller.signal.aborted) break; if(controller.signal.aborted) break;
if(chunk.choices[0].delta.content) { if(chunk.choices[0].delta.content) {
resp.choices[0].message.content += chunk.choices[0].delta.content; const text = chunk.choices[0].delta.content;
options.stream({text: chunk.choices[0].delta.content}); resp.choices[0].message.content += text;
if(text) { hasStreamedText = true; options.stream({text}); }
} }
if(chunk.choices[0].delta.tool_calls) { if(chunk.choices[0].delta.tool_calls) {
for(const deltaTC of chunk.choices[0].delta.tool_calls) { for(const deltaTC of chunk.choices[0].delta.tool_calls) {
const existing = resp.choices[0].message.tool_calls.find(tc => tc.index === deltaTC.index); const existing = resp.choices[0].message.tool_calls.find(tc => tc.index === deltaTC.index);
@@ -158,28 +160,32 @@ export class OpenAi extends LLMProvider {
const results = await Promise.all(toolCalls.map(async (toolCall: any) => { const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
const tool = tools?.find(findByProp('name', toolCall.function.name)); const tool = tools?.find(findByProp('name', toolCall.function.name));
if(options.stream) options.stream({tool: toolCall.function.name}); if(options.stream) options.stream({tool: toolCall.function.name});
if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}'}; if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}', timestamp: Date.now()};
try { try {
const args = JSONAttemptParse(toolCall.function.arguments, {}); const args = JSONAttemptParse(toolCall.function.arguments, {});
const result = await tool.fn(args, options.stream, this.ai); // Wrap stream so a tool's `done` ends turn gracefully
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result}; const toolStream = options.stream && ((chunk: any) => {
if(chunk.done) { terminal = true; return; }
options.stream!(chunk);
});
const result = await tool.fn(args, toolStream, this.ai);
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result, timestamp: Date.now()};
} catch (err: any) { } catch (err: any) {
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'})}; return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'}), timestamp: Date.now()};
} }
})); }));
history.push(...results); history.push(...results);
requestParams.messages = history; requestParams.messages = history;
} }
} while (!controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length); } while (!terminal && !controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
if(!terminal) {
const textContent = resp.choices[0].message.content?.trim() || ''; const textContent = resp.choices[0].message.content?.trim() || '';
history.push({role: 'assistant', content: textContent}); history.push({role: 'assistant', content: textContent, timestamp: Date.now()});
}
history = this.toStandard(history); history = this.toStandard(history);
if(options.history) options.history.splice(0, options.history.length, ...history.filter(h => h.role !== 'system'));
if(options.stream) options.stream({done: true}); if(options.stream) options.stream({done: true});
if(options.history) options.history.splice(0, options.history.length, ...history);
// Return parsed JSON if schema provided
const finalContent = history.at(-1)?.content; const finalContent = history.at(-1)?.content;
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent); res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
}), {abort: () => controller.abort()}); }), {abort: () => controller.abort()});

View File

@@ -1,5 +1,5 @@
import {AbortablePromise} from './ai.ts'; import {AbortablePromise} from './ai.ts';
import {LLMMessage, LLMRequest} from './llm.ts'; import {LLMRequest} from './llm.ts';
export abstract class LLMProvider { export abstract class LLMProvider {
abstract ask(message: string, options: LLMRequest): AbortablePromise<string>; abstract ask(message: string, options: LLMRequest): AbortablePromise<string>;

View File

@@ -91,20 +91,33 @@ export function convertSchema(schema: any): any {
}; };
} }
export const CliTool: AiTool = { export const ExecCliTool: AiTool = {
name: 'cli', name: 'cli',
description: 'Use the command line interface, returns any output', description: 'Use the command line interface, returns any output',
args: {command: {type: 'string', description: 'Command to run', required: true}}, args: {command: {type: 'string', description: 'Command to run', required: true}},
fn: (args: {command: string}) => $Sync`${args.command}` fn: (args: {command: string}) => $Sync`${args.command}`
} }
export const DateTimeTool: AiTool = { export const ExecJSTool: AiTool = {
name: 'get_datetime', name: 'exec_javascript',
description: 'Get local/UTC date/time', description: 'Execute commonjs javascript',
args: { args: {
timezone: {type: 'string', description: 'Which timezone to return, defaults to local', enum: ['local', 'utc'], default: 'local'} code: {type: 'string', description: 'CommonJS javascript', required: true}
}, },
fn: ({timezone}) => new Date()[timezone === 'local' ? 'toString' : 'toUTCString']() fn: async (args: {code: string}) => {
const c = consoleInterceptor(null);
const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err));
return {...c.output, return: resp, stdout: undefined, stderr: undefined};
}
}
export const ExecPythonTool: AiTool = {
name: 'exec_python',
description: 'Execute commonjs javascript',
args: {
code: {type: 'string', description: 'CommonJS javascript', required: true}
},
fn: async (args: {code: string}) => ({result: $Sync`python -c "${args.code}"`})
} }
export const ExecTool: AiTool = { export const ExecTool: AiTool = {
@@ -118,11 +131,11 @@ export const ExecTool: AiTool = {
try { try {
switch(args.language) { switch(args.language) {
case 'cli': case 'cli':
return await CliTool.fn({command: args.code}, stream, ai); return await ExecCliTool.fn({command: args.code}, stream, ai);
case 'node': case 'node':
return await JSTool.fn({code: args.code}, stream, ai); return await ExecJSTool.fn({code: args.code}, stream, ai);
case 'python': case 'python':
return await PythonTool.fn({code: args.code}, stream, ai); return await ExecPythonTool.fn({code: args.code}, stream, ai);
default: default:
throw new Error(`Unsupported language: ${args.language}`); throw new Error(`Unsupported language: ${args.language}`);
} }
@@ -132,8 +145,483 @@ export const ExecTool: AiTool = {
} }
} }
export const FetchTool: AiTool = { export const FsDeleteTool = (whitelist: null | string[] = null): AiTool => {
name: 'fetch', return {
name: 'fs_delete',
description: 'Delete a file or directory',
args: {
path: {type: 'string', description: 'Path to file or directory', required: true},
recursive: {type: 'boolean', description: 'Delete all children', required: false}
},
fn: async ({path, recursive = false}) => {
const {existsSync, rmSync} = await import('fs');
const normalizePath = p => p.replace(/\\/g, '/');
path = normalizePath(path);
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
if(!existsSync(path)) return {error: 'Path does not exist'};
rmSync(path, {recursive, force: true});
return {success: true, path};
}
}
}
export const FsMoveTool = (whitelist: null | string[] = null): AiTool => {
return {
name: 'fs_move',
description: 'Move or rename a file or directory',
args: {
source: {type: 'string', description: 'Path to source file or directory', required: true},
destination: {type: 'string', description: 'Path to destination file or directory', required: true}
},
fn: async ({source, destination}) => {
const {existsSync, renameSync} = await import('fs');
const normalizePath = p => p.replace(/\\/g, '/');
source = normalizePath(source);
destination = normalizePath(destination);
if(whitelist && !whitelist.some(p => source.startsWith(p) && destination.startsWith(p))) return {error: 'Permission denied'};
if(!existsSync(source)) return {error: 'Source path does not exist'};
if(existsSync(destination)) return {error: 'Destination path already exists'};
renameSync(source, destination);
return {success: true, source, destination};
}
}
}
export const FsReadTool = (whitelist: null | string[] = null): AiTool => {
return {
name: 'fs_read',
description: 'Read the contents of a provided path. Works with files and directories',
args: {path: {type: 'string', description: 'Path to file or directory', required: true}},
fn: async ({path}) => {
const {existsSync, lstatSync, readdirSync, readFileSync} = await import('fs');
const {join} = await import('path');
const normalizePath = p => p.replace(/\\/g, '/');
path = normalizePath(path);
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
if(!existsSync(path)) return {error: 'Path does not exist'};
const stats = lstatSync(path);
if(stats.isDirectory()) {
const children = readdirSync(path).map(name => {
const childPath = normalizePath(join(path, name));
const childStats = lstatSync(childPath);
return {name, type: childStats.isDirectory() ? 'directory' : 'file', size: childStats.size};
});
return {type: 'directory', children};
}
const content = readFileSync(path, 'utf-8');
return {type: 'file', content};
}
}
}
export const FsSearchTool = (whitelist: null | string[] = null): AiTool => {
return {
name: 'fs_search',
description: 'Scan a directory for matching glob patterns (e.g. "**/*.js", "src/**/*.test.ts")',
args: {
pattern: {type: 'string', description: 'Glob pattern to match against paths', required: true},
root: {type: 'string', description: 'Directory to search from', required: false, default: '.'}
},
fn: async ({pattern, root = '.'}) => {
const {existsSync, lstatSync, readdirSync} = await import('fs');
const {join, relative} = await import('path');
const normalizePath = p => p.replace(/\\/g, '/');
root = normalizePath(root);
if(!existsSync(root)) return {error: 'Root path does not exist'};
if(!lstatSync(root).isDirectory()) return {error: 'Root path is not a directory'};
if(whitelist && !whitelist.some(p => root.startsWith(p))) return {error: 'Permission denied'};
const globToRegex = (glob) => {
let re = '';
for(let i = 0; i < glob.length; i++) {
const c = glob[i];
if(c === '*') {
if(glob[i + 1] === '*') {
const isSlash = glob[i + 2] === '/';
re += '.*';
i += isSlash ? 2 : 1;
} else {
re += '[^/]*';
}
} else if(c === '?') {
re += '[^/]';
} else if('.+^$(){}|[]\\'.includes(c)) {
re += '\\' + c;
} else {
re += c;
}
}
return new RegExp('^' + re + '$');
};
const regex = globToRegex(pattern);
const results: any = [];
const walk = (dir) => {
for(const name of readdirSync(dir)) {
const fullPath = normalizePath(join(dir, name));
const stats = lstatSync(fullPath);
const relPath = normalizePath(relative(root, fullPath));
if(regex.test(relPath)) {
results.push({path: relPath, type: stats.isDirectory() ? 'directory' : 'file', size: stats.size});
}
if(stats.isDirectory()) walk(fullPath);
}
};
walk(root);
return results;
}
}
}
export const FsWriteTool = (whitelist: null | string[] = null): AiTool => {
return {
name: 'fs_write',
description: 'Create a directory, write content to a file or preform a find & replace',
args: {
path: {type: 'string', description: 'Path to file or directory', required: true},
content: {type: 'string', description: 'Content to write or replace (Omit to create a directory)'},
find: {type: 'string', description: 'Text or regex pattern to match (regex must match pattern: "/pattern/g")'}
},
fn: async ({path, content, find}) => {
const {existsSync, mkdirSync, readFileSync, writeFileSync} = await import('fs');
const {dirname} = await import('path');
const normalizePath = p => p.replace(/\\/g, '/');
path = normalizePath(path);
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
if(content === undefined) {
mkdirSync(path, {recursive: true});
return {success: true, type: 'directory', path};
}
const dir = normalizePath(dirname(path));
if(!existsSync(dir)) mkdirSync(dir, {recursive: true});
if(find && existsSync(path)) {
const existing = readFileSync(path, 'utf-8');
const regexMatch = find.match(/^\/(.+)\/([gimuy]*)$/);
const pattern = regexMatch ? new RegExp(regexMatch[1], regexMatch[2]) : find;
if(!existing.match(pattern)) return {error: 'Find pattern not found in file'};
const updated = existing.replace(pattern, content);
writeFileSync(path, updated, 'utf-8');
return {success: true, type: 'file', path, replaced: true, content: updated};
}
writeFileSync(path, content, 'utf-8');
return {success: true, type: 'file', path, content};
}
}
}
export const GetPathsTool: AiTool = {
name: 'get_paths',
description: 'Get the current working directory, and paths to the users home directory',
fn: async () => {
return {
home: os.homedir(),
cwd: process.cwd()
};
}
}
export const GetDatetimeTool: AiTool = {
name: 'get_datetime',
description: 'Get local/UTC timestamp',
args: {
timezone: {type: 'string', description: 'Which timezone to return, defaults to local', enum: ['local', 'utc'], default: 'local'}
},
fn: ({timezone}) => new Date()[timezone === 'local' ? 'toString' : 'toUTCString']()
}
export const GetDevice: AiTool = {
name: 'get_device',
description: 'Get comprehensive system information including hostname, specs, load, storage, and network status',
args: {},
fn: async () => {
const platform = os.platform();
const hostname = os.hostname();
// CPU Info
const cpus = os.cpus();
const cpuModel = cpus[0].model;
const cpuCores = cpus.length;
// Memory Info
const totalMem: any = (os.totalmem() / 1024 / 1024 / 1024).toFixed(2);
const freeMem: any = (os.freemem() / 1024 / 1024 / 1024).toFixed(2);
const usedMem: any = (totalMem - freeMem).toFixed(2);
const memUsage: any = ((usedMem / totalMem) * 100).toFixed(1);
// Load Average (not available on Windows)
const loadAvg = platform === 'win32' ? ['N/A', 'N/A', 'N/A'] : os.loadavg().map(l => l.toFixed(2));
// Storage Usage
let storage = {};
if(platform === 'win32') {
const ps = $Sync`powershell "Get-PSDrive C | Select-Object Used,Free | ConvertTo-Json"`.trim();
const drive = JSON.parse(ps);
const used: any = (drive.Used / 1024 / 1024 / 1024).toFixed(2);
const free: any = (drive.Free / 1024 / 1024 / 1024).toFixed(2);
const total: any = (parseFloat(used) + parseFloat(free)).toFixed(2);
const usage: any = ((used / total) * 100).toFixed(1);
storage = {
filesystem: 'C:',
size: `${total} GB`,
used: `${used} GB`,
available: `${free} GB`,
usage: `${usage}%`
};
} else {
const df = $Sync`df -h / | tail -1`.trim();
const s = df.split(/\s+/);
storage = {
filesystem: s[0],
size: s[1],
used: s[2],
available: s[3],
usage: s[4]
};
}
// Network Status
const interfaces = os.networkInterfaces();
const activeIfaces = Object.entries(interfaces)
.filter(([name]) => name !== 'lo' && !name.includes('Loopback'))
.map(([name, addrs]) => {
const ipv4 = addrs?.find(a => a.family === 'IPv4');
return ipv4 ? {name, ip: ipv4.address} : null;
})
.filter(Boolean);
// Internet connectivity check
let internet = false;
try {
if(platform === 'win32') {
$Sync`powershell "Test-Connection -ComputerName 8.8.8.8 -Count 1 -Quiet"`;
} else {
$Sync`ping -c 1 -W 2 8.8.8.8 > /dev/null 2>&1`;
}
internet = true;
} catch {}
// Uptime
const uptime = os.uptime();
const days = Math.floor(uptime / 86400);
const hours = Math.floor((uptime % 86400) / 3600);
const minutes = Math.floor((uptime % 3600) / 60);
return {
hostname,
cpu: {
model: cpuModel,
cores: cpuCores
},
memory: {
total: `${totalMem} GB`,
used: `${usedMem} GB`,
free: `${freeMem} GB`,
usage: `${memUsage}%`
},
load: {
'1min': loadAvg[0],
'5min': loadAvg[1],
'15min': loadAvg[2]
},
storage,
network: {
interfaces: activeIfaces,
internet: internet ? 'connected' : 'disconnected'
},
uptime: `${days}d ${hours}h ${minutes}m`,
platform: `${os.type()} ${os.release()}`
};
}
}
export const GetWikipediaTool: AiTool = {
name: 'get_wikipedia',
description: 'Search Wikipedia for matching articles',
args: {
query: {type: 'string', description: 'Search term or article title', required: true},
mode: {type: 'string', description: 'search - look for articles, summary - intro of first found article (default), full - complete first found article', enum: ['search', 'summary', 'full'], default: 'summary'},
ua: {type: 'string', description: 'User Agent'},
},
fn: async ({query, mode, ua}) => {
class WikipediaClient {
useragent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
constructor(useragent: string) {
this.useragent = useragent;
}
async get(url) {
const resp = await fetch(url, {headers: {'User-Agent': this.useragent}});
return resp.json();
}
api(params) {
const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
}
clean(text) {
const cutoffs = ['== See also ==', '== References ==', '== Bibliography ==', '== External links =='];
for (const marker of cutoffs) {
const idx = text.indexOf(marker);
if (idx !== -1) text = text.slice(0, idx);
}
return text
.replace(/^={4}\s*(.+?)\s*={4}$/gm, '#### $1')
.replace(/^={3}\s*(.+?)\s*={3}$/gm, '### $1')
.replace(/^={2}\s*(.+?)\s*={2}$/gm, '## $1')
.replace(/\n{3,}/g, '\n\n')
.replace(/ {2,}/g, ' ')
.replace(/\[\d+]/g, '')
.trim();
}
async searchTitles(query: string, limit = 6) {
const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
return data.query?.search || [];
}
async fetchExtract(title: string, introOnly = false) {
const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
if(introOnly) params.exintro = 1;
const data = await this.api(params);
const page: any = Object.values(data.query?.pages || {})[0];
return this.clean(page?.extract || '');
}
pageUrl(title: string) {
return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
}
stripHtml(text: string) {
return text.replace(/<[^>]+>/g, '');
}
async lookup(query: string, detail = 'summary') {
const results = await this.searchTitles(query, 6);
if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
const title = results[0].title;
const url = this.pageUrl(title);
const introOnly = detail !== 'full';
const content = await this.fetchExtract(title, introOnly);
return `## ${title}\n🔗 ${url}\n\n${content}`;
}
async search(query: string) {
const results = await this.searchTitles(query, 8);
if(!results.length) return `❌ No results for "${query}"`;
const lines = [`### Search results for "${query}"\n`];
for(let i = 0; i < results.length; i++) {
const r = results[i];
const snippet = this.stripHtml(r.snippet || '').trim();
lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
}
return lines.join('\n\n');
}
}
const wiki = new WikipediaClient(ua);
if(mode === 'search') return wiki.search(query);
return wiki.lookup(query, mode || 'summary');
}
};
export const GeoCodeTool: AiTool = {
name: 'geo_code',
description: 'Converts coordinates to address OR vice versa',
args: {
query: {type: 'string', description: 'Search query - coordinates (lat,lon) or address string', required: true},
},
fn: async ({query}) => {
const coordinates = /(-?\d+(?:\.\d+)?).*?,.*?(-?\d+(?:\.\d+)?)/.exec(query);
if(coordinates) { // Geolocate
const url = `https://nominatim.openstreetmap.org/reverse?format=json&lat=${encodeURIComponent(coordinates[1])}&lon=${encodeURIComponent(coordinates[2])}`;
const response = await fetch(url, {headers: {'User-Agent': 'OpenSight/1.0', 'Accept-Language': 'en'}});
const data = await response.json();
if(data.display_name) return {address: data.display_name, mode: 'geolocate'};
} else { // Geocode
const url = `https://nominatim.openstreetmap.org/search?format=json&q=${encodeURIComponent(query)}`;
const response = await fetch(url, {headers: {'User-Agent': 'OpenSight/1.0'}});
const data = await response.json();
if(data[0]) return {latitude: parseFloat(data[0].lat), longitude: parseFloat(data[0].lon), mode: 'geocode'};
}
return {error: 'Not found'};
},
}
export const GeoWeatherTool: AiTool = {
name: 'geo_weather',
description: 'Gets weather and air quality info for a location and time',
args: {
query: {type: 'string', description: 'Location - address or place name', required: true},
day: {type: 'string', description: 'Date to retrieve (YYYY-MM-DD), defaults to today'},
},
fn: async ({query, day}) => {
day = day || new Date().toISOString().slice(0, 10);
const geoUrl = `https://nominatim.openstreetmap.org/search?format=json&q=${encodeURIComponent(query)}`;
const geoResponse = await fetch(geoUrl, {headers: {'User-Agent': 'OpenSight/1.0'}});
const geoData = await geoResponse.json();
if(!geoData[0]) return {error: 'Location not found'};
const lat = parseFloat(geoData[0].lat);
const lon = parseFloat(geoData[0].lon);
const weatherUrl = `https://api.open-meteo.com/v1/forecast?latitude=${lat}&longitude=${lon}&start_date=${day}&end_date=${day}&daily=weathercode,temperature_2m_max,temperature_2m_min,apparent_temperature_max,apparent_temperature_min,precipitation_sum,precipitation_probability_max,windspeed_10m_max,winddirection_10m_dominant,uv_index_max,sunrise,sunset&timezone=auto`;
const airUrl = `https://air-quality-api.open-meteo.com/v1/air-quality?latitude=${lat}&longitude=${lon}&start_date=${day}&end_date=${day}&hourly=us_aqi,european_aqi,pm10,pm2_5&timezone=auto`;
const [weatherResponse, airResponse] = await Promise.all([fetch(weatherUrl), fetch(airUrl)]);
const weatherData = await weatherResponse.json();
const airData = await airResponse.json();
const avg = arr => (arr && arr.length) ? arr.reduce((a, b) => a + b, 0) / arr.length : null;
return {
location: geoData[0].display_name,
latitude: lat,
longitude: lon,
elevation: weatherData.elevation,
date: day,
weatherCode: weatherData.daily?.weathercode?.[0],
tempMax: weatherData.daily?.temperature_2m_max?.[0],
tempMin: weatherData.daily?.temperature_2m_min?.[0],
feelsLikeMax: weatherData.daily?.apparent_temperature_max?.[0],
feelsLikeMin: weatherData.daily?.apparent_temperature_min?.[0],
precipitation: weatherData.daily?.precipitation_sum?.[0],
precipitationChance: weatherData.daily?.precipitation_probability_max?.[0],
windSpeedMax: weatherData.daily?.windspeed_10m_max?.[0],
windDirection: weatherData.daily?.winddirection_10m_dominant?.[0],
uvIndexMax: weatherData.daily?.uv_index_max?.[0],
sunrise: weatherData.daily?.sunrise?.[0],
sunset: weatherData.daily?.sunset?.[0],
usAqi: avg(airData.hourly?.us_aqi),
europeanAqi: avg(airData.hourly?.european_aqi),
pm10: avg(airData.hourly?.pm10),
pm2_5: avg(airData.hourly?.pm2_5),
};
},
}
export const WebFetchTool: AiTool = {
name: 'web_fetch',
description: 'Make HTTP request to URL', description: 'Make HTTP request to URL',
args: { args: {
url: {type: 'string', description: 'URL to fetch', required: true}, url: {type: 'string', description: 'URL to fetch', required: true},
@@ -149,30 +637,59 @@ export const FetchTool: AiTool = {
}) => new Http({url: args.url, headers: args.headers}).request({method: args.method || 'GET', body: args.body}) }) => new Http({url: args.url, headers: args.headers}).request({method: args.method || 'GET', body: args.body})
} }
export const JSTool: AiTool = { export const WebFlareSolverTool = (host: string) => {
name: 'exec_javascript', return {
description: 'Execute commonjs javascript', name: 'web_flaresolverr',
description: 'Use a flaresolverr proxy to bypass cloudflare bot detection',
args: { args: {
code: {type: 'string', description: 'CommonJS javascript', required: true} url: {type: 'string', description: 'URL to fetch', required: true},
cmd: {type: 'string', description: 'Flaresolverr cmd', enum: ['request.get', 'request.post'], default: 'request.get'},
maxTimeout: {type: 'number', description: 'Fetch time limit', default: 60_000},
postData: {type: 'object', description: 'Data to send during request.post requests'},
}, },
fn: async (args: {code: string}) => { fn: async ({url, cmd, maxTimeout, postData}) => {
const c = consoleInterceptor(null); function toFormUrlEncoded(obj, prefix = '') {
const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err)); const pairs: any = [];
return {...c.output, return: resp, stdout: undefined, stderr: undefined}; for (const key in obj) {
if (!obj.hasOwnProperty(key)) continue;
const value = obj[key];
const encodedKey = prefix
? `${prefix}[${encodeURIComponent(key)}]`
: encodeURIComponent(key);
if (value === null || value === undefined) {
pairs.push(`${encodedKey}=`);
} else if (typeof value === 'object' && !Array.isArray(value)) {
pairs.push(toFormUrlEncoded(value, encodedKey));
} else if (Array.isArray(value)) {
value.forEach(item => {
pairs.push(`${encodedKey}[]=${encodeURIComponent(item)}`);
});
} else {
pairs.push(`${encodedKey}=${encodeURIComponent(value)}`);
} }
} }
export const PythonTool: AiTool = { return pairs.join('&');
name: 'exec_python',
description: 'Execute commonjs javascript',
args: {
code: {type: 'string', description: 'CommonJS javascript', required: true}
},
fn: async (args: {code: string}) => ({result: $Sync`python -c "${args.code}"`})
} }
export const ReadWebpageTool: AiTool = { const res = await fetch(host + '/v1', {
name: 'read_webpage', method: 'POST',
headers: {'Content-Type': 'application/json'},
body: JSON.stringify({cmd, url, maxTimeout, postData: postData ? toFormUrlEncoded(postData) : undefined}),
});
if(!res.ok) throw new Error(`FlareSolverr HTTP error: ${res.status} ${res.statusText}`);
const data = await res.json();
if(data.status !== 'ok') throw new Error(`FlareSolverr error: ${data.message ?? data.status}`);
return data.solution.response;
}
}
}
export const WebReadTool: AiTool = {
name: 'web_read',
description: 'Extract clean content from webpages, or convert media/documents to accessible formats', description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
args: { args: {
url: {type: 'string', description: 'URL to read', required: true}, url: {type: 'string', description: 'URL to read', required: true},
@@ -300,91 +817,3 @@ export const WebSearchTool: AiTool = {
return results; return results;
} }
} }
export const WikipediaTool: AiTool = {
name: 'wikipedia_search',
description: 'Search Wikipedia for matching articles',
args: {
query: {type: 'string', description: 'Search term or article title', required: true},
mode: {type: 'string', description: 'search - look for articles, summary - intro of first found article (default), full - complete first found article', enum: ['search', 'summary', 'full'], default: 'summary'}
},
fn: async (args: {query: string, mode: 'search' | 'summary' | 'full'}) => {
const UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
class WikipediaClient {
async get(url: string) {
const resp = await fetch(url, {headers: {'User-Agent': UA}});
return resp.json();
}
api(params: any) {
const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
}
clean(text: string) {
const cutoffs = ['== See also ==', '== References ==', '== Bibliography ==', '== External links =='];
for (const marker of cutoffs) {
const idx = text.indexOf(marker);
if (idx !== -1) text = text.slice(0, idx);
}
return text
.replace(/^={4}\s*(.+?)\s*={4}$/gm, '#### $1')
.replace(/^={3}\s*(.+?)\s*={3}$/gm, '### $1')
.replace(/^={2}\s*(.+?)\s*={2}$/gm, '## $1')
.replace(/\n{3,}/g, '\n\n')
.replace(/ {2,}/g, ' ')
.replace(/\[\d+\]/g, '')
.trim();
}
async searchTitles(query: string, limit = 6) {
const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
return data.query?.search || [];
}
async fetchExtract(title: string, introOnly = false) {
const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
if(introOnly) params.exintro = 1;
const data = await this.api(params);
const page: any = Object.values(data.query?.pages || {})[0];
return this.clean(page?.extract || '');
}
pageUrl(title: string) {
return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
}
stripHtml(text: string) {
return text.replace(/<[^>]+>/g, '');
}
async lookup(query: string, detail = 'summary') {
const results = await this.searchTitles(query, 6);
if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
const title = results[0].title;
const url = this.pageUrl(title);
const introOnly = detail !== 'full';
const content = await this.fetchExtract(title, introOnly);
return `## ${title}\n🔗 ${url}\n\n${content}`;
}
async search(query: string) {
const results = await this.searchTitles(query, 8);
if(!results.length) return `❌ No results for "${query}"`;
const lines = [`### Search results for "${query}"\n`];
for(let i = 0; i < results.length; i++) {
const r = results[i];
const snippet = this.stripHtml(r.snippet || '').trim();
lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
}
return lines.join('\n\n');
}
}
const wiki = new WikipediaClient();
if(args.mode == 'search') return wiki.search(args.query);
return wiki.lookup(args.query, args.mode || 'summary');
}
};