Compare commits
28 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| d42f58d710 | |||
| 878a8794ee | |||
| 3f1289d993 | |||
| 077f75cdd9 | |||
| 566d84fd7a | |||
| 4230b534fc | |||
| 119f8472f2 | |||
| 9c04e58c63 | |||
| 7fbb42c26a | |||
| be08db8e2c | |||
| 497f051c62 | |||
| 62fbe73b22 | |||
| d53b1c6328 | |||
| 89619e211e | |||
| afc6653364 | |||
| 68e72445a2 | |||
| 1aa6cdf329 | |||
| d022a5ef4d | |||
| a1d438a20a | |||
| 52a9e3aaa4 | |||
| a7aec4ee29 | |||
| dda2d4c2a3 | |||
| 58e0e488e4 | |||
| 8dfcd06752 | |||
| 14f6cdd313 | |||
| 73d6ee0f2a | |||
| bee4085666 | |||
| 3b5c71de7c |
@@ -186,7 +186,7 @@ console.log(chunks);
|
||||
|
||||
// Manually compile history into memories at end of conversation
|
||||
// Happens automatically when coverstaions are compressed
|
||||
await ai.language.updateMemory(history, memory);
|
||||
await ai.language.memorize(history, memory);
|
||||
|
||||
// Summarize text
|
||||
const summary = await ai.language.summarize(longText, 200);
|
||||
|
||||
234
package-lock.json
generated
234
package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
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"name": "@ztimson/ai-utils",
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"lockfileVersion": 3,
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"requires": true,
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"packages": {
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"": {
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"name": "@ztimson/ai-utils",
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"version": "1.0.6",
|
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"version": "1.2.6",
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"license": "MIT",
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"dependencies": {
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"@anthropic-ai/sdk": "^0.102.0",
|
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@@ -57,34 +57,38 @@
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}
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"@emnapi/wasi-threads": "2.0.1",
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"tslib": "^2.4.0"
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}
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"node_modules/@emnapi/wasi-threads": {
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"version": "1.2.2",
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"version": "2.0.1",
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}
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@@ -573,6 +577,16 @@
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"url": "https://opencollective.com/libvips"
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}
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},
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"node_modules/@img/sharp-wasm32/node_modules/@emnapi/runtime": {
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"version": "1.11.3",
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"resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.11.3.tgz",
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"license": "MIT",
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"dependencies": {
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"tslib": "^2.4.0"
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}
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"resolved": "https://registry.npmjs.org/@img/sharp-win32-arm64/-/sharp-win32-arm64-0.34.5.tgz",
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@@ -681,22 +695,25 @@
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},
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"node_modules/@napi-rs/wasm-runtime": {
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"version": "1.1.6",
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"dev": true,
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"license": "MIT",
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"optional": true,
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"dependencies": {
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"@tybys/wasm-util": "^0.10.3"
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},
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"engines": {
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"node": "^20.19.0 || ^22.13.0 || >=23.5.0"
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},
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"funding": {
|
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"type": "github",
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"url": "https://github.com/sponsors/Brooooooklyn"
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},
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"peerDependencies": {
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"@emnapi/core": "^1.7.1",
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"@emnapi/runtime": "^1.7.1"
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"@emnapi/core": "^2.0.0-alpha.3",
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"@emnapi/runtime": "^2.0.0-alpha.3"
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}
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},
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"node_modules/@oxc-project/types": {
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@@ -1007,6 +1024,18 @@
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"node": "^20.19.0 || >=22.12.0"
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}
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},
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"node_modules/@rolldown/binding-wasm32-wasi/node_modules/@emnapi/core": {
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"version": "1.11.1",
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"dev": true,
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"license": "MIT",
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"optional": true,
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"tslib": "^2.4.0"
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@@ -1018,6 +1047,17 @@
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"tslib": "^2.4.0"
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}
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},
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"node_modules/@rolldown/binding-wasm32-wasi/node_modules/@emnapi/wasi-threads": {
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"dev": true,
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"license": "MIT",
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"optional": true,
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"dependencies": {
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"tslib": "^2.4.0"
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}
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"node_modules/@rolldown/binding-win32-arm64-msvc": {
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"version": "1.1.5",
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"resolved": "https://registry.npmjs.org/@rolldown/binding-win32-arm64-msvc/-/binding-win32-arm64-msvc-1.1.5.tgz",
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@@ -1408,18 +1448,18 @@
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"license": "MIT"
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"license": "MIT",
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"dependencies": {
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"var-persist": "^1.0.1"
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}
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},
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"node_modules/acorn": {
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"dev": true,
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"bin": {
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@@ -1504,9 +1544,9 @@
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"license": "MIT"
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"dev": true,
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"dependencies": {
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@@ -2009,9 +2049,9 @@
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"dev": true,
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@@ -2382,9 +2422,9 @@
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@@ -2398,23 +2438,23 @@
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@@ -2433,9 +2473,9 @@
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@@ -2454,9 +2494,9 @@
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@@ -2475,9 +2515,9 @@
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@@ -2496,9 +2536,9 @@
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@@ -2517,9 +2557,9 @@
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@@ -2541,9 +2581,9 @@
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@@ -2565,9 +2605,9 @@
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"node_modules/lightningcss-linux-x64-gnu": {
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"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-gnu/-/lightningcss-linux-x64-gnu-1.32.0.tgz",
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"cpu": [
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"x64"
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],
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@@ -2589,9 +2629,9 @@
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"node_modules/lightningcss-linux-x64-musl": {
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"cpu": [
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"x64"
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@@ -2613,9 +2653,9 @@
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"cpu": [
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@@ -2634,9 +2674,9 @@
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"node_modules/lightningcss-win32-x64-msvc": {
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"cpu": [
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@@ -2794,9 +2834,9 @@
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"dev": true,
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"license": "MIT"
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@@ -2971,9 +3011,9 @@
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"license": "MIT"
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"dev": true,
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"funding": [
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{
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@@ -3092,9 +3132,9 @@
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"license": "MIT"
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},
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"node_modules/openai": {
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"resolved": "https://registry.npmjs.org/openai/-/openai-6.46.0.tgz",
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"license": "Apache-2.0",
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"peerDependencies": {
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"@aws-sdk/credential-provider-node": ">=3.972.0 <4",
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@@ -3232,9 +3272,9 @@
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"license": "MIT"
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"node_modules/postcss": {
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"dev": true,
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"funding": [
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{
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@@ -3252,7 +3292,7 @@
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],
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"license": "MIT",
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"dependencies": {
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"nanoid": "^3.3.12",
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"nanoid": "^3.3.16",
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"picocolors": "^1.1.1",
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"source-map-js": "^1.2.1"
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@@ -3787,9 +3827,9 @@
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"license": "MIT"
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"license": "MIT",
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"engines": {
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"node": ">=20.18.1"
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@@ -3981,16 +4021,16 @@
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}
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"node_modules/vite": {
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"integrity": "sha512-7ULLwsCdYx/nRyrpiEwvqb5TFHrMVZyBt+rg/OAXT7rgj/z+DtTDyKFeLAdDkubDVDKD8jOsndmy7m55XcfUsw==",
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"dev": true,
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"license": "MIT",
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"dependencies": {
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"lightningcss": "^1.32.0",
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"picomatch": "^4.0.5",
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"postcss": "^8.5.16",
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"rolldown": "~1.1.4",
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"postcss": "^8.5.17",
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"rolldown": "~1.1.5",
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"tinyglobby": "^0.2.17"
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},
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||||
"bin": {
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||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "1.2.3",
|
||||
"version": "1.4.5",
|
||||
"description": "AI Utility library",
|
||||
"author": "Zak Timson",
|
||||
"license": "MIT",
|
||||
|
||||
167
src/antrhopic.ts
167
src/antrhopic.ts
@@ -1,58 +1,52 @@
|
||||
import {Anthropic as anthropic} from '@anthropic-ai/sdk';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse} from '@ztimson/utils';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, makeArray} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||
import {LLMProvider} from './provider.ts';
|
||||
import {TokenPool} from './token-pool.ts';
|
||||
import {convertSchema} from './tools.ts';
|
||||
|
||||
export class Anthropic extends LLMProvider {
|
||||
client!: anthropic;
|
||||
private clients = new Map<string, anthropic>();
|
||||
tokenPool!: TokenPool;
|
||||
|
||||
constructor(public readonly ai: Ai, public readonly apiToken: string, public model: string) {
|
||||
constructor(public readonly ai: Ai, public readonly apiToken: string | string[], public model: string) {
|
||||
super();
|
||||
this.client = new anthropic({apiKey: apiToken});
|
||||
this.tokenPool = new TokenPool(...makeArray(apiToken).filter(Boolean));
|
||||
}
|
||||
|
||||
private toStandard(history: any[]): LLMMessage[] {
|
||||
const timestamp = Date.now();
|
||||
const messages: LLMMessage[] = [];
|
||||
for(let h of history) {
|
||||
if(typeof h.content == 'string') {
|
||||
messages.push(<any>{timestamp, ...h});
|
||||
} else {
|
||||
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});
|
||||
h.content.forEach((c: any) => {
|
||||
if(c.type == 'tool_use') {
|
||||
messages.push({timestamp, role: 'tool', id: c.id, name: c.name, args: c.input, content: undefined});
|
||||
} else if(c.type == 'tool_result') {
|
||||
const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id);
|
||||
if(m) m[c.is_error ? 'error' : 'content'] = c.content;
|
||||
private getClient(token: string): anthropic {
|
||||
let client = this.clients.get(token);
|
||||
if(!client) {
|
||||
client = new anthropic({apiKey: token});
|
||||
this.clients.set(token, client);
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
return messages;
|
||||
return client;
|
||||
}
|
||||
|
||||
private fromStandard(history: LLMMessage[]): any[] {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
if(history[i].role == 'tool') {
|
||||
const h: any = history[i];
|
||||
history.splice(i, 1,
|
||||
/** Convert standard history -> Anthropic wire format */
|
||||
private toWire(history: LLMMessage[]): any[] {
|
||||
const wire: any[] = [];
|
||||
for(const h of history) {
|
||||
if(h.role === 'tool') {
|
||||
wire.push(
|
||||
{role: 'assistant', content: [{type: 'tool_use', id: h.id, name: h.name, input: h.args}]},
|
||||
{role: 'user', content: [{type: 'tool_result', tool_use_id: h.id, is_error: !!h.error, content: h.error || h.content}]}
|
||||
)
|
||||
i++;
|
||||
{role: 'user', content: [{type: 'tool_result', tool_use_id: h.id, is_error: !!h.error, content: h.error || h.content || ''}]}
|
||||
);
|
||||
} else {
|
||||
wire.push({role: h.role, content: h.content});
|
||||
}
|
||||
}
|
||||
return history.map(({timestamp, ...h}) => h);
|
||||
return wire;
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||
const controller = new AbortController();
|
||||
return Object.assign(new Promise<any>(async (res) => {
|
||||
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]);
|
||||
return Object.assign(new Promise<any>(async (res, rej) => {
|
||||
if(!options.history) options.history = [];
|
||||
const history = options.history;
|
||||
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
|
||||
|
||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||
const requestParams: any = {
|
||||
model: options.model || this.model,
|
||||
@@ -66,90 +60,97 @@ export class Anthropic extends LLMProvider {
|
||||
type: 'object',
|
||||
properties: t.args ? objectMap(t.args, (key, value) => ({...value, required: undefined})) : {},
|
||||
required: t.args ? Object.entries(t.args).filter(t => t[1].required).map(t => t[0]) : []
|
||||
},
|
||||
fn: undefined
|
||||
}
|
||||
})),
|
||||
messages: history,
|
||||
stream: !!options.stream,
|
||||
};
|
||||
|
||||
// Add structured output support
|
||||
if(options.schema) {
|
||||
requestParams.output_config = {
|
||||
format: {
|
||||
type: 'json_schema',
|
||||
schema: convertSchema(options.schema)
|
||||
}
|
||||
};
|
||||
requestParams.output_config = {format: {type: 'json_schema', schema: convertSchema(options.schema)}};
|
||||
}
|
||||
|
||||
let resp: any, isFirstMessage = true;
|
||||
try {
|
||||
let terminal = false;
|
||||
do {
|
||||
resp = await this.client.messages.create(requestParams).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||
requestParams.messages = this.toWire(history.filter(h => h.role !== 'system'));
|
||||
|
||||
const callStart = Date.now();
|
||||
const resp: any = await this.tokenPool.run(token => this.getClient(token).messages.create(requestParams)).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(requestParams.messages, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
|
||||
// Streaming mode
|
||||
let usage: any, content: any[] = [];
|
||||
if(options.stream) {
|
||||
if(!isFirstMessage) options.stream({text: '\n\n'});
|
||||
else isFirstMessage = false;
|
||||
resp.content = [];
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.type === 'content_block_start') {
|
||||
if(chunk.content_block.type === 'text') {
|
||||
resp.content.push({type: 'text', text: ''});
|
||||
} else if(chunk.content_block.type === 'tool_use') {
|
||||
resp.content.push({type: 'tool_use', id: chunk.content_block.id, name: chunk.content_block.name, input: <any>''});
|
||||
}
|
||||
if(chunk.content_block.type === 'text') content.push({type: 'text', text: ''});
|
||||
else if(chunk.content_block.type === 'tool_use') content.push({type: 'tool_use', id: chunk.content_block.id, name: chunk.content_block.name, input: ''});
|
||||
} else if(chunk.type === 'content_block_delta') {
|
||||
if(chunk.delta.type === 'text_delta') {
|
||||
const text = chunk.delta.text;
|
||||
resp.content.at(-1).text += text;
|
||||
options.stream({text});
|
||||
content.at(-1).text += chunk.delta.text;
|
||||
options.stream({text: chunk.delta.text});
|
||||
} else if(chunk.delta.type === 'input_json_delta') {
|
||||
resp.content.at(-1).input += chunk.delta.partial_json;
|
||||
content.at(-1).input += chunk.delta.partial_json;
|
||||
}
|
||||
} else if(chunk.type === 'content_block_stop') {
|
||||
const last = resp.content.at(-1);
|
||||
if(last.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||
const last = content.at(-1);
|
||||
if(last?.type === 'tool_use') last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||
} else if(chunk.type === 'message_delta') {
|
||||
if(chunk.usage) usage = chunk.usage;
|
||||
} else if(chunk.type === 'message_stop') {
|
||||
break;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
usage = resp.usage;
|
||||
content = resp.content;
|
||||
}
|
||||
const duration = Date.now() - callStart;
|
||||
const tps = usage?.output_tokens && duration > 0 ? usage.output_tokens / (duration / 1000) : 0;
|
||||
|
||||
// Run tools
|
||||
const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use');
|
||||
const toolCalls = content.filter((c: any) => c.type === 'tool_use');
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
history.push({role: 'assistant', content: resp.content});
|
||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||
const tool = tools.find(findByProp('name', 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'};
|
||||
const text = content.filter((c: any) => c.type === 'text').map((c: any) => c.text).join('\n\n').trim();
|
||||
if(text) history.push({role: 'assistant', content: text, timestamp: Date.now(), duration, tps});
|
||||
|
||||
const entries = toolCalls.map((tc: any) => {
|
||||
const entry: any = {role: 'tool', id: tc.id, name: tc.name, args: tc.input, content: undefined, timestamp: Date.now()};
|
||||
history.push(entry);
|
||||
return {tc, entry};
|
||||
});
|
||||
|
||||
await Promise.all(entries.map(async ({tc, entry}: any) => {
|
||||
const tool = tools.find(findByProp('name', tc.name));
|
||||
if(options.stream) options.stream({tool: tc.name});
|
||||
if(!tool) { entry.error = 'Tool not found'; return; }
|
||||
try {
|
||||
const result = await tool.fn(toolCall.input, options?.stream, this.ai);
|
||||
return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
||||
} catch (err: any) {
|
||||
return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(entry.args, toolStream, this.ai, tc.id);
|
||||
entry.content = typeof result === 'object' ? JSONSanitize(result) : result;
|
||||
} catch(err: any) {
|
||||
entry.error = err?.message || err?.toString() || 'Unknown';
|
||||
}
|
||||
}));
|
||||
history.push({role: 'user', content: results});
|
||||
requestParams.messages = history;
|
||||
} else {
|
||||
terminal = true;
|
||||
const text = content.filter((c: any) => c.type === 'text').map((c: any) => c.text).join('\n\n').trim();
|
||||
if(text) history.push({role: 'assistant', content: text, timestamp: Date.now(), duration, tps});
|
||||
}
|
||||
} while (!controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
|
||||
|
||||
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 = this.toStandard(history);
|
||||
} while(!terminal && !controller.signal.aborted);
|
||||
|
||||
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 turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => h.role === 'assistant' ? str + (h.content || '') : str, '').trim();
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
} catch(err) {
|
||||
rej(err);
|
||||
}
|
||||
}), {abort: () => controller.abort()});
|
||||
}
|
||||
}
|
||||
|
||||
85
src/helpers.ts
Normal file
85
src/helpers.ts
Normal file
@@ -0,0 +1,85 @@
|
||||
import {Memory, MemoryCache} from './memory.ts';
|
||||
|
||||
export type MemoryNode = {
|
||||
name: string;
|
||||
missing: boolean;
|
||||
links: string[];
|
||||
backlinks: string[];
|
||||
}
|
||||
|
||||
export function extractLinks(content: string): string[] {
|
||||
if (!content) return [];
|
||||
const matches = content.matchAll(/\[\[([^\]|]+)(?:\|[^\]]*)?\]\]/g);
|
||||
return [...new Set([...matches].map(m => m[1].trim()))];
|
||||
}
|
||||
|
||||
export function rebuildGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
|
||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const nameSet = new Set(mems.map(m => m.name));
|
||||
|
||||
for (const m of mems) m.links = extractLinks(m.content).filter(l => l !== m.name);
|
||||
for (const m of mems) m.backlinks = [];
|
||||
for (const m of mems) {
|
||||
for (const link of m.links) {
|
||||
const target = mems.find(t => t.name === link);
|
||||
if (target) target.backlinks.push(m.name);
|
||||
}
|
||||
}
|
||||
|
||||
const nodes: MemoryNode[] = mems.map(m => ({
|
||||
name: m.name,
|
||||
missing: false,
|
||||
links: m.links,
|
||||
backlinks: m.backlinks,
|
||||
}));
|
||||
|
||||
const ghosts = new Set<string>();
|
||||
for (const node of nodes) {
|
||||
for (const link of node.links) {
|
||||
if (!nameSet.has(link)) ghosts.add(link);
|
||||
}
|
||||
}
|
||||
|
||||
return [
|
||||
...nodes,
|
||||
...[...ghosts].map(name => ({
|
||||
name,
|
||||
missing: true,
|
||||
links: [],
|
||||
backlinks: nodes.filter(n => n.links.includes(name)).map(n => n.name),
|
||||
})),
|
||||
];
|
||||
}
|
||||
|
||||
export function renderMemoryGraph(nodes: MemoryNode[]): string {
|
||||
if (!nodes.length) return 'No memories yet.';
|
||||
|
||||
const groups = new Map<string, (MemoryNode & {label: string})[]>();
|
||||
for (const node of nodes) {
|
||||
const [prefix, ...rest] = node.name.split('/');
|
||||
const group = rest.length ? prefix : 'Root';
|
||||
const label = rest.length ? rest.join('/') : node.name;
|
||||
if (!groups.has(group)) groups.set(group, []);
|
||||
groups.get(group)!.push({...node, label});
|
||||
}
|
||||
|
||||
const ghostCount = nodes.filter(n => n.missing).length;
|
||||
const lines = [`Memory Graph (${nodes.length} nodes, ${ghostCount} ghost${ghostCount === 1 ? '' : 's'})`, ''];
|
||||
|
||||
for (const group of [...groups.keys()].sort()) {
|
||||
const items = groups.get(group)!.sort((a, b) => a.label.localeCompare(b.label));
|
||||
lines.push(`${group}/`);
|
||||
items.forEach((n, i) => {
|
||||
const last = i === items.length - 1;
|
||||
const branch = last ? '└─' : '├─';
|
||||
const pad = last ? ' ' : '│ ';
|
||||
const tag = n.missing ? ' (ghost)' : '';
|
||||
lines.push(` ${branch} ${n.label}${tag}`);
|
||||
if (n.links.length) lines.push(` ${pad} → ${n.links.join(', ')}`);
|
||||
if (n.backlinks.length) lines.push(` ${pad} ← ${n.backlinks.join(', ')}`);
|
||||
});
|
||||
lines.push('');
|
||||
}
|
||||
|
||||
return lines.join('\n').trimEnd();
|
||||
}
|
||||
@@ -1,9 +1,11 @@
|
||||
export * from './ai';
|
||||
export * from './antrhopic';
|
||||
export * from './audio';
|
||||
export * from './helpers';
|
||||
export * from './llm';
|
||||
export * from './memory';
|
||||
export * from './open-ai';
|
||||
export * from './provider';
|
||||
export * from './token-pool'
|
||||
export * from './tools';
|
||||
export * from './vision';
|
||||
|
||||
@@ -103,9 +103,10 @@ class BoundedMaxHeap<T> {
|
||||
export class KDTree<T = unknown> {
|
||||
private root: KDNode<T> | null = null;
|
||||
private _size = 0;
|
||||
private readonly dims: number;
|
||||
private readonly distanceFn: (a: number[], b: number[]) => number;
|
||||
|
||||
readonly dims: number;
|
||||
|
||||
/**
|
||||
* @param dims Dimensionality of all vectors (must be consistent).
|
||||
* @param metric Distance metric to use. Default: "euclidean".
|
||||
|
||||
268
src/llm.ts
268
src/llm.ts
@@ -1,3 +1,4 @@
|
||||
import {clean, snakeCase} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {Anthropic} from './antrhopic.ts';
|
||||
import {OpenAi} from './open-ai.ts';
|
||||
@@ -6,10 +7,25 @@ import {AiTool, AiToolArg} from './tools.ts';
|
||||
import {fileURLToPath} from 'url';
|
||||
import {dirname, join} from 'path';
|
||||
import {spawn} from 'node:child_process';
|
||||
import {Memory, MemoryCache, MemoryManager} from './memory.ts';
|
||||
import {Memory, MemoryCache, MemoryManager, MemoryOptions} from './memory.ts';
|
||||
|
||||
export type AnthropicConfig = {proto: 'anthropic', token: string};
|
||||
export type OpenAiConfig = {proto: 'openai', host?: string, token: string};
|
||||
const MAX_AGENT_DEPTH = 5;
|
||||
|
||||
export type AnthropicConfig = {proto: 'anthropic', token: string | string[]};
|
||||
export type OpenAiConfig = {proto: 'openai', host?: string, token: string | 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;
|
||||
agents?: string[] | null;
|
||||
}
|
||||
|
||||
export type LLMMessage = {
|
||||
/** Message originator */
|
||||
@@ -18,6 +34,10 @@ export type LLMMessage = {
|
||||
content: string | any;
|
||||
/** Timestamp */
|
||||
timestamp?: number;
|
||||
/** Response duration in ms */
|
||||
duration?: number;
|
||||
/** Tokens per second */
|
||||
tps?: number;
|
||||
} | {
|
||||
/** Tool call */
|
||||
role: 'tool';
|
||||
@@ -33,6 +53,10 @@ export type LLMMessage = {
|
||||
error?: undefined | string;
|
||||
/** Timestamp */
|
||||
timestamp?: number;
|
||||
/** Response duration in ms */
|
||||
duration?: number;
|
||||
/** Tokens per second */
|
||||
tps?: number;
|
||||
}
|
||||
|
||||
export type LLMRequest = {
|
||||
@@ -55,13 +79,17 @@ export type LLMRequest = {
|
||||
/** Compress old messages in the chat to free up context */
|
||||
compress?: {max: number; min: number};
|
||||
/** User's memory documents - RAG injected automatically each turn */
|
||||
memory?: Memory[] | MemoryCache;
|
||||
memory?: Memory[] | MemoryCache | MemoryOptions;
|
||||
/** Model to use for memory operations */
|
||||
memoryModel?: string;
|
||||
/** Skill documents the AI can browse and read on demand */
|
||||
skills?: Skill[];
|
||||
/** MCP servers to connect and expose as tools */
|
||||
mcp?: McpServer[];
|
||||
/** Subagents exposed as delegatable/wrapped tools */
|
||||
agents?: Agent[];
|
||||
/** @internal recursion guard for nested agent delegation */
|
||||
_agentDepth?: number;
|
||||
}
|
||||
|
||||
export type McpServer = {
|
||||
@@ -82,7 +110,6 @@ export type Skill = {
|
||||
content: string;
|
||||
}
|
||||
|
||||
|
||||
class LLM {
|
||||
private memoryManager!: MemoryManager;
|
||||
|
||||
@@ -99,6 +126,54 @@ class LLM {
|
||||
this.memoryManager = new MemoryManager(this);
|
||||
}
|
||||
|
||||
private setupAgent(agents: Agent[] = [], allAgents: Agent[], history: LLMMessage[], aborts: (() => void)[], depth = 0, delegateState: {resp: string | null}): AiTool[] {
|
||||
return agents.map(a => {
|
||||
const toolName = `${a.delegate ? '' : 'sub'}agent_${snakeCase(a.name)}`;
|
||||
return {
|
||||
name: toolName,
|
||||
description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
|
||||
args: clean<any>({
|
||||
context: !a.delegate ? {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true} : undefined,
|
||||
instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
|
||||
}),
|
||||
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||
if(depth >= MAX_AGENT_DEPTH) return 'Max agent delegation depth exceeded';
|
||||
|
||||
const nested = (a.agents || [])
|
||||
.map(name => allAgents.find(x => x.name === name))
|
||||
.filter((x): x is Agent => !!x && x.name !== a.name);
|
||||
|
||||
const q = a.delegate ? '' : `${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`;
|
||||
|
||||
const request = this.ask(q, {
|
||||
system: `You are a specialized subagent being called from an orchestrator
|
||||
${a.delegate ? 'Your output streams directly to the user for the remainder of this turn. You are mid conversation' : 'You are wrapped in a tool call that will be analysis by an LLM'}
|
||||
Dispense with greetings and focus on your instructions using available tools and returning only the final result unless specifically instructed to converse
|
||||
|
||||
${a.system}`,
|
||||
model: a.model || undefined,
|
||||
temperature: a.temperature,
|
||||
stream: a.delegate ? stream : undefined,
|
||||
history: a.delegate ? history : [],
|
||||
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) {
|
||||
delegateState.resp = resp;
|
||||
return '';
|
||||
}
|
||||
return resp;
|
||||
}
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
private async setupMcp(servers: McpServer[] = []): Promise<{prompt: string, tools: AiTool[]}> {
|
||||
if(!servers?.length) return {prompt: '', tools: []};
|
||||
const allTools: AiTool[] = [];
|
||||
@@ -141,9 +216,9 @@ class LLM {
|
||||
if(!skills?.length) return {prompt: '', tools: []};
|
||||
const list = skills.map(s => `- ${s.name}: ${s.description}`).join('\n');
|
||||
return {
|
||||
prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
|
||||
prompt: `You have access to the following skill documents, whenever there is overlap between a question and a skill file, use \`skill_read\` to get instructions and background knowledge:\n${list}`,
|
||||
tools: [{
|
||||
name: 'read_skill',
|
||||
name: 'skill_read',
|
||||
description: 'Read the full content of a skill/knowledge document',
|
||||
args: {
|
||||
name: {type: 'string', description: 'Exact skill name', required: true}
|
||||
@@ -157,6 +232,20 @@ class LLM {
|
||||
}
|
||||
}
|
||||
|
||||
private wrapToolTiming(tools: AiTool[], timings: Map<string, {duration: number, tps: number}>): AiTool[] {
|
||||
return tools.map(t => ({
|
||||
...t,
|
||||
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||
const start = Date.now();
|
||||
const result = await t.fn(args, stream, ai, id);
|
||||
const duration = Date.now() - start;
|
||||
const tps = duration > 0 ? this.estimateTokens(result) / (duration / 1000) : 0;
|
||||
if(id) timings.set(id, {duration, tps});
|
||||
return result;
|
||||
}
|
||||
}));
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string> {
|
||||
options = <any>{
|
||||
system: '',
|
||||
@@ -167,11 +256,23 @@ class LLM {
|
||||
}
|
||||
const m = options.model || this.defaultModel;
|
||||
if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
|
||||
let abort = () => {};
|
||||
return Object.assign(new Promise<string>(async res => {
|
||||
let request: AbortablePromise<string> | null = null;
|
||||
let aborted = false;
|
||||
const nestedAborts: (() => void)[] = [];
|
||||
const abort = () => {
|
||||
aborted = true;
|
||||
request?.abort?.();
|
||||
nestedAborts.forEach(a => a());
|
||||
};
|
||||
|
||||
let promise: any;
|
||||
const requestStart = Date.now();
|
||||
|
||||
promise = (async () => {
|
||||
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
|
||||
const prompts: string[] = [];
|
||||
let history = options.history || [];
|
||||
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
|
||||
|
||||
// MCP
|
||||
const mcp = options.mcp || this.ai.options?.llm?.mcp;
|
||||
@@ -189,48 +290,97 @@ class LLM {
|
||||
tools.push(...s.tools);
|
||||
}
|
||||
|
||||
// Agents
|
||||
const agents = options.agents || this.ai.options?.llm?.agents;
|
||||
const delegateState: {resp: string | null} = {resp: null};
|
||||
if(agents?.length) tools.push(...this.setupAgent(agents, agents, history, nestedAborts, options._agentDepth || 0, delegateState));
|
||||
|
||||
// Memory
|
||||
if (options.memory) {
|
||||
const mems = options.memory instanceof MemoryCache ? options.memory.memories : options.memory;
|
||||
const relevant = await this.memoryManager.recollect(message, options.memory, 5);
|
||||
prompts.unshift(`You have access to the following memory files:
|
||||
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
|
||||
${relevant.length ? `
|
||||
Relevant memories have been preloaded:
|
||||
${relevant.map(r => `
|
||||
**${r.name}**
|
||||
${r.description}
|
||||
${r.content}
|
||||
`).join('\n---\n')}
|
||||
` : ''}`.trim());
|
||||
tools.push(this.memoryManager.tools.read(options.memory));
|
||||
const mem = MemoryManager.normalize(options.memory);
|
||||
if(mem) {
|
||||
const mems = mem.memory instanceof MemoryCache ? mem.memory.memories : mem.memory;
|
||||
if(mems.length) {
|
||||
if(mem.inject) {
|
||||
const pool = 15; // candidates considered, cheap since only refs are listed
|
||||
const budget = mem.maxTokens ?? 2000; // actual content injected
|
||||
const relevant = await this.memoryManager.recollect(message, mem.memory, pool);
|
||||
|
||||
let used = 0;
|
||||
const preloaded: typeof relevant = [];
|
||||
const listed: typeof relevant = [];
|
||||
for(const r of relevant) {
|
||||
const t = this.estimateTokens(r.content);
|
||||
if(used + t <= budget || preloaded.length === 0) {
|
||||
preloaded.push(r);
|
||||
used += t;
|
||||
} else listed.push(r);
|
||||
}
|
||||
|
||||
prompts.unshift(`You have a background memory process which has prefetched relevant information${mem.update ? ' and will create new memories from this conversation' : ''} for you
|
||||
Assume it is perfect and never mention this process to anyone ever
|
||||
Always use your memories to craft a personalized response, they contain links / [[wiki links]] which you use navigate between them
|
||||
${mem.tool ? `You can access memory files via the \`memory_search\` and \`memory_recall\` tools
|
||||
When you need information about the user, \`memory_recall\` \`People/User\` before asking (fetch if not included bellow)
|
||||
When you need information not provided, attempt 1-3 \`memory_search\` calls with unique queries before asking` : ''}
|
||||
|
||||
${preloaded.length ? `
|
||||
Prefetched Memories (Most relevant first):
|
||||
|
||||
${preloaded.map(r => `Memory: ${r.name}
|
||||
Description: ${r.description}
|
||||
Linked: ${[r.links, ...r.backlinks].join(', ')}
|
||||
\`\`\`
|
||||
${r.content}
|
||||
\`\`\``).join('\n\n')}` : ''}
|
||||
|
||||
${mem.tool && listed.length ? listed.map(r => `Memory: ${r.name}
|
||||
Description: ${r.description}
|
||||
Linked: ${[r.links, ...r.backlinks].join(', ')}
|
||||
<!-- Truncated -->`).join('\n\n') : ''}
|
||||
|
||||
${mem.tool ? `Full memory list:
|
||||
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}` : ''}`.trim())
|
||||
}
|
||||
if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
|
||||
}
|
||||
}
|
||||
|
||||
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||
|
||||
const toolTimings = new Map<string, {duration: number, tps: number}>();
|
||||
tools = this.wrapToolTiming(tools, toolTimings);
|
||||
|
||||
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||
|
||||
prompts.unshift(options.system || this.ai.options.llm?.system || '');
|
||||
const resp = await this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||
request = this.models[m].ask('', {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||
let resp = await request;
|
||||
|
||||
// Trim memory injections from history
|
||||
if(options.memory) {
|
||||
history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'recall'));
|
||||
// Capture meta (duration / tps)
|
||||
for(const h of history) {
|
||||
if(h.role === 'tool' && toolTimings.has(h.id)) Object.assign(h, toolTimings.get(h.id));
|
||||
}
|
||||
|
||||
// Auto-memorize before compressing
|
||||
if(typeof resp === 'string' && !resp.trim() && delegateState.resp !== null) resp = delegateState.resp;
|
||||
|
||||
if(mem?.tool) history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'memory_recall'));
|
||||
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);
|
||||
if(options.history) options.history.splice(0, options.history.length, ...compressed);
|
||||
}
|
||||
|
||||
return res(resp);
|
||||
}), {abort});
|
||||
}
|
||||
const requestDuration = Date.now() - requestStart;
|
||||
const totalTokens = history
|
||||
.filter((h: any) => h.role === 'assistant' && h.duration && h.tps)
|
||||
.reduce((sum: number, h: any) => sum + h.tps * (h.duration / 1000), 0);
|
||||
const requestTps = requestDuration > 0 ? totalTokens / (requestDuration / 1000) : 0;
|
||||
Object.assign(promise, {duration: requestDuration, tps: requestTps});
|
||||
|
||||
/**
|
||||
* Digest full conversation history into memory documents.
|
||||
* Call on session end to persist the conversation.
|
||||
*/
|
||||
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<void> {
|
||||
await this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||
return resp;
|
||||
})();
|
||||
|
||||
return Object.assign(promise, {abort});
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -383,15 +533,41 @@ ${r.content}
|
||||
* @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
|
||||
*/
|
||||
fuzzyMatch(target: string, ...searchTerms: string[]) {
|
||||
if(searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
|
||||
const vector = (text: string, dimensions: number = 10): number[] => {
|
||||
return text.toLowerCase().split('').map((char, index) =>
|
||||
(char.charCodeAt(0) * (index + 1)) % dimensions / dimensions).slice(0, dimensions);
|
||||
fuzzyMatch(target, ...searchTerms) {
|
||||
if (searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
|
||||
const levenshtein = (a, b) => {
|
||||
const m = a.length, n = b.length;
|
||||
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 {avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length, max: Math.max(...similarities), similarities};
|
||||
}
|
||||
return dp[m][n];
|
||||
};
|
||||
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
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Digest full conversation history into memory documents.
|
||||
* Call on session end to persist the conversation.
|
||||
*/
|
||||
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
|
||||
return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
784
src/memory.ts
784
src/memory.ts
@@ -1,6 +1,17 @@
|
||||
import {MemoryNode, rebuildGraph} from './helpers.ts';
|
||||
import {LLMRequest, LLMMessage} from './llm.ts';
|
||||
import {AiTool} from './tools.ts';
|
||||
import {KDTree, KDPoint} from './kd-tree.ts';
|
||||
import {KDPoint, KDTree} from './kd-tree.ts';
|
||||
|
||||
const FACTS_HEADING = '## Facts';
|
||||
|
||||
const GENERIC_TEMPLATE = `# {{Title}}
|
||||
|
||||
## Summary
|
||||
|
||||
## Details
|
||||
|
||||
## Related`;
|
||||
|
||||
export type Memory = {
|
||||
name: string;
|
||||
@@ -21,55 +32,13 @@ type FactBucket = {
|
||||
facts: string[];
|
||||
}
|
||||
|
||||
export type MemoryNode = {
|
||||
name: string;
|
||||
missing: boolean;
|
||||
links: string[];
|
||||
backlinks: string[];
|
||||
}
|
||||
|
||||
export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
|
||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const nameSet = new Set(mems.map(m => m.name));
|
||||
const ghosts = new Set<string>();
|
||||
|
||||
for (const m of mems) {
|
||||
for (const link of m.links) {
|
||||
if (!nameSet.has(link)) ghosts.add(link);
|
||||
}
|
||||
}
|
||||
|
||||
return [
|
||||
...mems.map(m => ({
|
||||
name: m.name,
|
||||
missing: false,
|
||||
links: m.links,
|
||||
backlinks: m.backlinks,
|
||||
})),
|
||||
...[...ghosts].map(name => ({
|
||||
name,
|
||||
missing: true,
|
||||
links: [],
|
||||
backlinks: mems
|
||||
.filter(m => m.links.includes(name))
|
||||
.map(m => m.name),
|
||||
}))
|
||||
];
|
||||
}
|
||||
|
||||
function extractLinks(content: string): string[] {
|
||||
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
|
||||
return [...new Set([...matches].map(m => m[1].trim()))];
|
||||
}
|
||||
|
||||
function rebuildBacklinks(memories: Memory[]): void {
|
||||
for (const m of memories) m.backlinks = [];
|
||||
for (const m of memories) {
|
||||
for (const link of m.links) {
|
||||
const target = memories.find(t => t.name === link);
|
||||
if (target) target.backlinks.push(m.name);
|
||||
}
|
||||
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 {
|
||||
@@ -83,18 +52,30 @@ function cosineDistance(a: number[], b: number[]): number {
|
||||
return denom === 0 ? 1 : 1 - dot / denom;
|
||||
}
|
||||
|
||||
function cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
|
||||
return memories
|
||||
.filter(m => m.embedding?.length)
|
||||
.map(m => ({ref: {name: m.name, description: m.description}, distance: cosineDistance(query, m.embedding)}))
|
||||
.sort((a, b) => a.distance - b.distance)
|
||||
.slice(0, limit)
|
||||
.map(s => s.ref);
|
||||
}
|
||||
|
||||
export class MemoryCache {
|
||||
private tree: KDTree<MemoryRef>;
|
||||
private tree!: KDTree<MemoryRef>;
|
||||
public memories: Memory[];
|
||||
public nodes: MemoryNode[] = [];
|
||||
|
||||
get length() { return this.memories.length; }
|
||||
|
||||
constructor(memories: Memory[]) {
|
||||
this.memories = memories;
|
||||
this.tree = this.buildTree();
|
||||
this.rebuild();
|
||||
}
|
||||
|
||||
private buildTree(): KDTree<MemoryRef> {
|
||||
const embedded = this.memories.filter(m => m.embedding?.length);
|
||||
if(!embedded.length) return new KDTree<MemoryRef>(0);
|
||||
if (!embedded.length) return new KDTree<MemoryRef>(0);
|
||||
|
||||
const dims = embedded[0].embedding.length;
|
||||
const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
|
||||
@@ -106,8 +87,8 @@ export class MemoryCache {
|
||||
}
|
||||
|
||||
search(query: number[], limit: number): MemoryRef[] {
|
||||
const results = this.tree.knn(query, limit);
|
||||
return results.map(r => r.point.payload);
|
||||
if (!this.tree || this.tree.dims === 0) return [];
|
||||
return this.tree.knn(query, limit).map(r => r.point.payload);
|
||||
}
|
||||
|
||||
add(memory: Memory): void {
|
||||
@@ -117,385 +98,438 @@ export class MemoryCache {
|
||||
|
||||
update(memory: Memory): void {
|
||||
const idx = this.memories.findIndex(m => m.name === memory.name);
|
||||
if (idx !== -1) {
|
||||
this.memories[idx] = memory;
|
||||
} else {
|
||||
this.memories.push(memory);
|
||||
}
|
||||
if (idx !== -1) this.memories[idx] = memory;
|
||||
else this.memories.push(memory);
|
||||
this.rebuild();
|
||||
}
|
||||
|
||||
rebuild(): void {
|
||||
this.tree = this.buildTree();
|
||||
remove(name: string): void {
|
||||
const idx = this.memories.findIndex(m => m.name === name);
|
||||
if (idx !== -1) {
|
||||
this.memories.splice(idx, 1);
|
||||
this.rebuild();
|
||||
}
|
||||
}
|
||||
|
||||
rebuildLinks(): void {
|
||||
rebuildBacklinks(this.memories);
|
||||
rebuild(): void {
|
||||
this.nodes = rebuildGraph(this.memories);
|
||||
this.tree = this.buildTree();
|
||||
}
|
||||
}
|
||||
|
||||
class MemoryAccessor {
|
||||
readonly list: Memory[];
|
||||
private readonly cache: MemoryCache | null;
|
||||
|
||||
constructor(memories: Memory[] | MemoryCache) {
|
||||
this.cache = memories instanceof MemoryCache ? memories : null;
|
||||
this.list = this.cache ? this.cache.memories : <Memory[]>memories;
|
||||
}
|
||||
|
||||
find(name: string): Memory | undefined {
|
||||
return this.list.find(m => m.name === name);
|
||||
}
|
||||
|
||||
commit(): MemoryNode[] {
|
||||
if (this.cache) {
|
||||
this.cache.rebuild();
|
||||
return this.cache.nodes;
|
||||
}
|
||||
return rebuildGraph(this.list);
|
||||
}
|
||||
|
||||
ghosts(): string[] {
|
||||
const nodes = this.cache ? this.cache.nodes : rebuildGraph(this.list);
|
||||
return nodes.filter(n => n.missing).map(n => n.name);
|
||||
}
|
||||
|
||||
search(vector: number[], limit: number): MemoryRef[] {
|
||||
return this.cache ? this.cache.search(vector, limit) : cosineSearch(vector, this.list, limit);
|
||||
}
|
||||
|
||||
forget(name: string): boolean {
|
||||
const idx = this.list.findIndex(m => m.name === name);
|
||||
if (idx === -1) return false;
|
||||
this.list.splice(idx, 1);
|
||||
this.commit();
|
||||
return true;
|
||||
}
|
||||
|
||||
async backfillEmbeddings(llm: any): Promise<number> {
|
||||
const missing = this.list.filter(m => !m.embedding?.length);
|
||||
if (!missing.length) return 0;
|
||||
await Promise.all(missing.map(async node => {
|
||||
const [e] = await llm.embedding(node.content);
|
||||
if (e) node.embedding = e.embedding;
|
||||
}));
|
||||
this.commit();
|
||||
return missing.length;
|
||||
}
|
||||
}
|
||||
|
||||
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 class MemoryManager {
|
||||
private recentlyTouched = new Map<string, number>();
|
||||
|
||||
private queues = new Map<string, {
|
||||
dirty: boolean,
|
||||
request: {abort?: () => void} | null,
|
||||
task: Promise<void>,
|
||||
}>();
|
||||
|
||||
tools = {
|
||||
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}`;
|
||||
},
|
||||
}),
|
||||
|
||||
read: (memories: Memory[] | MemoryCache): AiTool => ({
|
||||
name: 'read_memory',
|
||||
name: 'memory_recall',
|
||||
description: 'Read the full content of a memory document',
|
||||
args: {
|
||||
name: {type: 'string', description: 'Exact memory name', required: true},
|
||||
},
|
||||
fn:(args: any) => {
|
||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const mem = mems.find(m => m.name === args.name);
|
||||
if(!mem) return 'Document not found';
|
||||
return this.formatMemory(mem);
|
||||
}
|
||||
fn: (args: any) => {
|
||||
const mem = this.access(memories).find(args.name);
|
||||
if (!mem) return 'Document not found';
|
||||
this.touch(mem.name);
|
||||
return mem.content;
|
||||
},
|
||||
}),
|
||||
|
||||
search: (memories: Memory[] | MemoryCache): AiTool => ({
|
||||
name: 'memory_search',
|
||||
description: 'Use embeddings to find the MOST relevant memories, even if NOT relevant',
|
||||
args: {
|
||||
query: {type: 'string', description: 'What to look for in the memories', required: true},
|
||||
limit: {type: 'number', description: 'Number of memories to return', default: 1},
|
||||
},
|
||||
fn: async ({query, limit}) => {
|
||||
const mem = await this.recollect(query, memories, limit)
|
||||
return mem.map(m => `Memory: ${m.name}
|
||||
Description: ${m.description}
|
||||
Links: ${[...m.links, ...m.backlinks].join(', ')}
|
||||
\`\`\`
|
||||
${m.content}
|
||||
\`\`\``).join('\n\n');
|
||||
},
|
||||
}),
|
||||
};
|
||||
|
||||
constructor(private llm: any) {}
|
||||
|
||||
private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
|
||||
const scored = memories
|
||||
.filter(m => m.embedding?.length)
|
||||
.map(m => ({
|
||||
ref: {name: m.name, description: m.description},
|
||||
distance: cosineDistance(query, m.embedding)
|
||||
}))
|
||||
.sort((a, b) => a.distance - b.distance)
|
||||
.slice(0, limit);
|
||||
return scored.map(s => s.ref);
|
||||
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 createNode(name: string, memories: Memory[]): Memory {
|
||||
const existing = memories.find(m => m.name === name);
|
||||
if(existing) return existing;
|
||||
return {
|
||||
name,
|
||||
description: '',
|
||||
content: '',
|
||||
embedding: [],
|
||||
links: [],
|
||||
backlinks: [],
|
||||
};
|
||||
private access(memories: Memory[] | MemoryCache): MemoryAccessor {
|
||||
return new MemoryAccessor(memories);
|
||||
}
|
||||
|
||||
private formatMemory(mem: Memory): string {
|
||||
return [
|
||||
`# ${mem.name}`,
|
||||
mem.description ? `> ${mem.description}` : '',
|
||||
mem.links.length ? `**Links:** ${mem.links.map(l => `[[${l}]]`).join(', ')}` : '',
|
||||
mem.backlinks.length ? `**Referenced by:** ${mem.backlinks.map(l => `[[${l}]]`).join(', ')}` : '',
|
||||
'',
|
||||
mem.content,
|
||||
].filter(l => l !== undefined).join('\n');
|
||||
private appendFacts(node: Memory, facts: string[]): void {
|
||||
this.ensureDoc(node);
|
||||
const body = this.stripHeader(node.content);
|
||||
const bullets = facts.map(f => `- ${f}`).join('\n');
|
||||
const idx = body.indexOf(FACTS_HEADING);
|
||||
const newBody = idx === -1
|
||||
? `${body.trimEnd()}\n\n${FACTS_HEADING}\n${bullets}\n`
|
||||
: `${body.slice(0, idx + FACTS_HEADING.length)}\n${bullets}${body.slice(idx + FACTS_HEADING.length)}`;
|
||||
node.content = this.touchHeader(node, newBody);
|
||||
}
|
||||
|
||||
private ensureDoc(node: Memory): void {
|
||||
if (node.content) return;
|
||||
const title = node.name.split('/').pop() ?? node.name;
|
||||
node.content = this.touchHeader(node, `# ${title}\n`);
|
||||
}
|
||||
|
||||
private async factAgent(conversation: string, store: MemoryAccessor, options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
|
||||
const ghosts = store.ghosts();
|
||||
|
||||
const response = await this.llm.ask(conversation, {
|
||||
model: options.model,
|
||||
temperature: 0.2,
|
||||
system: `You are a fact extractor to build obsidian knowledge vaults.
|
||||
Analyze this conversation and extract facts worth remembering long-term.
|
||||
|
||||
Rules:
|
||||
- Always extract facts that the user explicitly told you to remember
|
||||
- ONLY extract current facts the USER explicitly stated about themselves, their work, projects or decisions that were MADE during this conversation
|
||||
- DO NOT extract greetings, pleasantries, or generic exchanges
|
||||
- DO NOT extract deltas or changes in facts; ONLY the end fact
|
||||
- DO NOT extract anything the AI/assistant itself said
|
||||
- If nothing worth remembering was said, return an empty buckets array
|
||||
|
||||
When extracting facts, you MUST also decide the exact destination path:
|
||||
- Reuse node names (including ghost) as much as possible IF the facts belongs there
|
||||
- All information primarily about the user should go under "People/User"
|
||||
- When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide) — you are not limited to any fixed list of collections, use whatever fits
|
||||
- For journal entries, use "Journal"
|
||||
|
||||
Available nodes:
|
||||
- Journal
|
||||
${this.listNodes(store.list).filter(n => !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}
|
||||
${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
|
||||
schema: {
|
||||
buckets: {type: 'array', description: 'Groups of facts to remember, each assigned to a different node. Return an empty array if there is nothing worth storing in an obsidian vault', items: {
|
||||
type: 'object', items: {
|
||||
subject: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide"), or "Journal"', required: true},
|
||||
facts: {
|
||||
type: 'array',
|
||||
description: 'Facts to store at this destination',
|
||||
items: {type: 'string', description: 'A single fact'},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const buckets = new Map<string, string[]>();
|
||||
for(const bucket of response.buckets ?? []) {
|
||||
const subject = bucket.subject.trim().toLowerCase() === 'journal'
|
||||
? `Journal/${weekKey}` : bucket.subject.trim();
|
||||
const facts = buckets.get(subject) ?? [];
|
||||
facts.push(...dedupeFacts(bucket.facts));
|
||||
buckets.set(subject, facts);
|
||||
}
|
||||
|
||||
return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
|
||||
}
|
||||
|
||||
private 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);
|
||||
}
|
||||
|
||||
private listNodes(memories: Memory[]): MemoryRef[] {
|
||||
return memories.map(m => ({name: m.name, description: m.description}));
|
||||
}
|
||||
|
||||
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
|
||||
const mem: Memory[] = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
if(!mem.length) return [];
|
||||
const [e] = await this.llm.embedding(query);
|
||||
if(!e) return [];
|
||||
private reconcile(node: Memory, memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
|
||||
const key = node.name;
|
||||
const existing = this.queues.get(key);
|
||||
if (existing) {
|
||||
existing.dirty = true;
|
||||
existing.request?.abort?.();
|
||||
return existing.task;
|
||||
}
|
||||
|
||||
let vectorResults: MemoryRef[];
|
||||
if(memories instanceof MemoryCache) vectorResults = memories.search(e.embedding, limit);
|
||||
else vectorResults = this.cosineSearch(e.embedding, mem, limit);
|
||||
const entry = {dirty: false, request: null, task: Promise.resolve()};
|
||||
this.queues.set(key, entry);
|
||||
const store = this.access(memories);
|
||||
entry.task = (async () => {
|
||||
do {
|
||||
entry.dirty = false;
|
||||
await this.docAgent(node, store.list, options, entry);
|
||||
} while (entry.dirty);
|
||||
})().finally(() => {
|
||||
this.queues.delete(key);
|
||||
store.commit();
|
||||
});
|
||||
return entry.task;
|
||||
}
|
||||
|
||||
private async docAgent(node: Memory, memories: Memory[], options: LLMRequest, entry: {request: {abort?: () => void} | null}): Promise<void> {
|
||||
const currentBody = this.stripHeader(node.content);
|
||||
let update;
|
||||
try {
|
||||
for (let i = 0; i < 2 && !update?.content; i++) {
|
||||
const request = this.llm.ask(currentBody, {
|
||||
model: options.model,
|
||||
temperature: 0.3,
|
||||
schema: {
|
||||
description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
|
||||
content: {type: 'string', description: 'Rewritten document body in markdown, without the frontmatter block', required: true},
|
||||
},
|
||||
system: `You are a knowledge base editor maintaining one document in an Obsidian-style vault.
|
||||
|
||||
If the document has a "${FACTS_HEADING}" section, integrate every bullet under it into the appropriate part of the document, then remove the "${FACTS_HEADING}" section entirely. If there is no such section, just tidy the document per the rules below.
|
||||
|
||||
Structure: follow this generic shape loosely, adapting section names/order to what the content actually needs (e.g. journal-style docs may want a timeline instead of "Details"):
|
||||
\`\`\`markdown
|
||||
${GENERIC_TEMPLATE}
|
||||
\`\`\`
|
||||
|
||||
Formatting rules:
|
||||
- Use Obsidian-style markdown: # headings, **bold** for emphasis, bullet & numbered lists for grouped 1D data, tables for 2D data
|
||||
- Link related concepts with [[WikiLink]] notation using full paths like [[People/Sarah]] or [[Projects/Website]]
|
||||
- Create links for specific entities (person, place, project, program) and abstract concepts, but skip generics (car, red, dog)
|
||||
- Keep the document concise, factual, and human-readable
|
||||
- Resolve contradictions: newer facts always win — delete the outdated statement entirely, never keep both
|
||||
- Do not add frontmatter blocks, filler, preamble, or AI commentary
|
||||
|
||||
Other nodes in the vault (link to these instead of duplicating their content):
|
||||
${this.listNodes(memories).filter(n => n.name !== node.name).map(n => n.name).join(', ') || 'none'}
|
||||
|
||||
Current document:
|
||||
\`\`\`markdown
|
||||
${currentBody}
|
||||
\`\`\``,
|
||||
});
|
||||
entry.request = request;
|
||||
update = await request;
|
||||
}
|
||||
} catch (err: any) {
|
||||
if (err?.name === 'AbortError') return;
|
||||
throw err;
|
||||
} finally {
|
||||
entry.request = null;
|
||||
}
|
||||
|
||||
if (!update?.content) return;
|
||||
node.description = node.name !== 'People/User' ? update.description : 'All information about the current user';
|
||||
node.content = this.touchHeader(node, update.content);
|
||||
const [e] = await this.llm.embedding(node.content);
|
||||
if (e) node.embedding = e.embedding;
|
||||
}
|
||||
|
||||
private parseFrontmatter(content: string): {fm: Map<string, string>, body: string} {
|
||||
const match = content.match(/^---\n([\s\S]*?)\n---\n?([\s\S]*)$/);
|
||||
if (!match) return {fm: new Map(), body: content};
|
||||
const fm = new Map<string, string>();
|
||||
for (const line of match[1].split('\n')) {
|
||||
const i = line.indexOf(':');
|
||||
if (i === -1) continue;
|
||||
fm.set(line.slice(0, i).trim(), line.slice(i + 1).trim());
|
||||
}
|
||||
return {fm, body: match[2]};
|
||||
}
|
||||
|
||||
private stripHeader(content: string): string {
|
||||
return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
|
||||
}
|
||||
|
||||
private touchHeader(node: Memory, body: string): string {
|
||||
const {fm} = this.parseFrontmatter(node.content);
|
||||
fm.set('name', node.name);
|
||||
fm.set('description', node.description || '');
|
||||
fm.set('modified', new Date().toISOString());
|
||||
return this.writeFrontmatter(fm, body);
|
||||
}
|
||||
|
||||
private writeFrontmatter(fm: Map<string, string>, body: string): string {
|
||||
const lines = [...fm.entries()].map(([k, v]) => `${k}: ${v}`);
|
||||
return `---\n${lines.join('\n')}\n---\n\n${body.trimStart()}`;
|
||||
}
|
||||
|
||||
decay() {
|
||||
for (const [name, ttl] of this.recentlyTouched) {
|
||||
if (ttl <= 1) this.recentlyTouched.delete(name);
|
||||
else this.recentlyTouched.set(name, ttl - 1);
|
||||
}
|
||||
}
|
||||
|
||||
touch(name: string, ttl = 2) {
|
||||
this.recentlyTouched.set(name, ttl);
|
||||
}
|
||||
|
||||
forget(name: string, memories: Memory[] | MemoryCache): boolean {
|
||||
return this.access(memories).forget(name);
|
||||
}
|
||||
|
||||
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
|
||||
const store = this.access(memories);
|
||||
if (!store.list.length) return [];
|
||||
|
||||
await store.backfillEmbeddings(this.llm);
|
||||
|
||||
const [e] = await this.llm.embedding(query);
|
||||
if (!e) return [];
|
||||
|
||||
const vectorResults = store.search(e.embedding, limit);
|
||||
const found = new Set<string>(vectorResults.map(r => r.name));
|
||||
|
||||
if(graphDepth > 0) {
|
||||
const frontier = [...found];
|
||||
for(let depth = 0; depth < graphDepth; depth++) {
|
||||
if (graphDepth > 0) {
|
||||
let frontier = [...found];
|
||||
for (let depth = 0; depth < graphDepth && frontier.length; depth++) {
|
||||
const next: string[] = [];
|
||||
for(const name of frontier) {
|
||||
const node = mem.find(m => m.name === name);
|
||||
if(!node) continue;
|
||||
for(const link of node.links) {
|
||||
if(!found.has(link) && mem.find(m => m.name === link)) {
|
||||
for (const name of frontier) {
|
||||
const node = store.find(name);
|
||||
if (!node) continue;
|
||||
for (const link of node.links) {
|
||||
if (!found.has(link) && store.find(link)) {
|
||||
found.add(link);
|
||||
next.push(link);
|
||||
}
|
||||
}
|
||||
}
|
||||
frontier.splice(0, frontier.length, ...next);
|
||||
if(!frontier.length) break;
|
||||
frontier = next;
|
||||
}
|
||||
}
|
||||
|
||||
const vectorOrder = vectorResults.map(r => r.name);
|
||||
const graphExpansions = [...found].filter(n => !vectorOrder.includes(n));
|
||||
const ordered = [...vectorOrder, ...graphExpansions];
|
||||
return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean);
|
||||
return [...vectorOrder, ...graphExpansions].map(n => store.find(n)!).filter(Boolean);
|
||||
}
|
||||
|
||||
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
|
||||
const mem = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
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}]: ${h.content}`).join('\n\n').trim();
|
||||
if (!conversation) return [];
|
||||
|
||||
if(conversation) {
|
||||
const buckets = await this.factAgent(conversation, mem, options);
|
||||
if(buckets.length) {
|
||||
await Promise.all(buckets.map(async bucket => {
|
||||
const node = await this.organizingAgent(bucket, mem, options);
|
||||
if(!mem.find(m => m.name === node.name)) mem.push(node);
|
||||
await this.docAgent(node, bucket, mem, options);
|
||||
}));
|
||||
const uid = `${Date.now()}_${Math.random().toString(36).slice(2)}`;
|
||||
const pending = {role: 'tool', name: 'memory_process', id: uid, content: conversation} as unknown as LLMMessage;
|
||||
history.push(pending);
|
||||
|
||||
const store = this.access(memories);
|
||||
const buckets = await this.factAgent(conversation, store, options, this.getWeekMonday());
|
||||
const touched: Memory[] = [];
|
||||
|
||||
for (const {subject, facts} of buckets) {
|
||||
let node = store.find(subject);
|
||||
if (!node) {
|
||||
node = {name: subject, description: '', content: '', embedding: [], links: [], backlinks: []};
|
||||
store.list.push(node);
|
||||
}
|
||||
}
|
||||
|
||||
// Auto-compress old journals
|
||||
const weekAgo = Date.now() - (7 * 24 * 60 * 60 * 1000);
|
||||
const oldDailies = mem.filter(m => {
|
||||
const journal = /^Journal\/(\d{4}-\d{2}-\d{2}$)/.exec(m.name);
|
||||
return journal && new Date(journal[1]).getTime() < weekAgo;
|
||||
});
|
||||
|
||||
if(oldDailies.length) {
|
||||
const byMonth = new Map<string, Memory[]>();
|
||||
for(const daily of oldDailies) {
|
||||
const match = daily.name.match(/^Journal\/(\d{4}-\d{2})-\d{2}$/);
|
||||
if(!match) continue;
|
||||
const monthKey = match[1];
|
||||
if(!byMonth.has(monthKey)) byMonth.set(monthKey, []);
|
||||
byMonth.get(monthKey)!.push(daily);
|
||||
}
|
||||
|
||||
for(const [monthKey, entries] of byMonth) {
|
||||
const monthlyPath = `Journal/${monthKey}`;
|
||||
let monthly = mem.find(m => m.name === monthlyPath);
|
||||
if(!monthly) {
|
||||
monthly = this.createNode(monthlyPath, mem);
|
||||
mem.push(monthly);
|
||||
}
|
||||
|
||||
const bucket: FactBucket = {
|
||||
subject: monthlyPath,
|
||||
facts: entries.flatMap(e => e.content.split('\n').filter(line => line.trim())),
|
||||
};
|
||||
|
||||
await this.docAgent(monthly, bucket, mem, options);
|
||||
for(const daily of entries) {
|
||||
const idx = mem.indexOf(daily);
|
||||
if(idx !== -1) mem.splice(idx, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (memories instanceof MemoryCache) {
|
||||
memories.rebuildLinks();
|
||||
memories.rebuild();
|
||||
} else {
|
||||
rebuildBacklinks(mem);
|
||||
}
|
||||
}
|
||||
|
||||
private async docAgent(node: Memory, bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<void> {
|
||||
let finalContent = node.content;
|
||||
const isJournalCompression = node.name.match(/^Journal\/\d{4}-\d{2}$/);
|
||||
const systemPrompt = isJournalCompression
|
||||
? `You are a journal compressor. Condense the daily entries below into a monthly summary.
|
||||
|
||||
Format:
|
||||
# ${node.name}
|
||||
|
||||
## Themes
|
||||
(Recurring topics, moods, patterns)
|
||||
|
||||
## Key Events
|
||||
(Important moments, decisions, milestones)
|
||||
|
||||
## 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:
|
||||
- Use Obsidian-style markdown: # headings, **bold** for key terms, bullet lists for facts
|
||||
- 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
|
||||
- Keep the document concise, factual, and human-readable
|
||||
- Resolve any contradictions between old content and new facts (new facts win)
|
||||
- Do not add filler, preamble, or AI commentary — just clean knowledge documents
|
||||
|
||||
All nodes:
|
||||
${this.listNodes(memories).map(n => n.name).join(', ') || 'none'}
|
||||
|
||||
Current document:
|
||||
\`\`\`markdown
|
||||
${node.content || '(empty — this is a new document)'}
|
||||
\`\`\``;
|
||||
|
||||
await this.llm.ask(
|
||||
`New facts to integrate:\n${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';
|
||||
}
|
||||
}]
|
||||
}
|
||||
);
|
||||
|
||||
node.content = finalContent;
|
||||
node.links = extractLinks(finalContent);
|
||||
const needsEmbed = !node.embedding?.length || node.description !== memories.find(m => m.name === node.name)?.description;
|
||||
if (needsEmbed) {
|
||||
const [e] = await this.llm.embedding(node.description);
|
||||
this.appendFacts(node, facts);
|
||||
const [e] = await this.llm.embedding(node.content);
|
||||
if (e) node.embedding = e.embedding;
|
||||
}
|
||||
this.touch(node.name);
|
||||
touched.push(node);
|
||||
}
|
||||
|
||||
private async factAgent(conversation: string, memories: Memory[], options: LLMRequest): Promise<FactBucket[]> {
|
||||
const buckets: FactBucket[] = [];
|
||||
const today = new Date().toISOString().split('T')[0];
|
||||
|
||||
await this.llm.ask(conversation, {
|
||||
model: options.model,
|
||||
temperature: 0.2,
|
||||
system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.
|
||||
|
||||
Rules:
|
||||
- ONLY extract facts the USER explicitly stated about themselves, their work, or their projects
|
||||
- ONLY extract decisions that were MADE during this conversation
|
||||
- DO NOT extract anything the AI said, its capabilities, or meta-conversation about the AI
|
||||
- DO NOT extract greetings, pleasantries, or generic exchanges
|
||||
- If nothing worth remembering was said, do not call any tools
|
||||
|
||||
**Organizational patterns:**
|
||||
- Journal entries use paths like: Journal/${today}
|
||||
- People use paths like: People/Name
|
||||
- Projects use paths like: Projects/Name
|
||||
- Personal info uses paths like: Personal/Goals, Personal/Tasks, etc.
|
||||
- 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;
|
||||
if (touched.length) {
|
||||
store.commit();
|
||||
(pending as any).content = `Saved to ${touched.map(n => `[[${n.name}]]`).join(', ')}`;
|
||||
await Promise.all(touched.map(node => this.reconcile(node, memories, options).catch(() => {})));
|
||||
} else {
|
||||
(pending as any).content = 'Nothing worth remembering.';
|
||||
}
|
||||
|
||||
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:
|
||||
${candidates.map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None — create a new node.'}`,
|
||||
tools: [{
|
||||
name: 'read',
|
||||
description: 'Read a node file to verify it is the right home for these facts',
|
||||
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);
|
||||
(touched as any).uid = uid;
|
||||
return touched;
|
||||
}
|
||||
}, {
|
||||
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: {
|
||||
name: {type: 'string', description: 'Full path for the new node (e.g., "People/Sarah", "Journal/2025-01-27")', required: true}
|
||||
},
|
||||
fn: ({name}) => {
|
||||
home = name;
|
||||
mode = 'create';
|
||||
resp.abort();
|
||||
}
|
||||
}]
|
||||
});
|
||||
|
||||
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);
|
||||
async reconcileVault(memories: Memory[] | MemoryCache, options: LLMRequest, scope: 'touched' | 'all' = 'touched'): Promise<void> {
|
||||
const store = this.access(memories);
|
||||
const targets = scope === 'all' ? store.list : store.list.filter(m => m.content.includes(FACTS_HEADING));
|
||||
await Promise.all(targets.map(node => this.reconcile(node, memories, options)));
|
||||
store.commit();
|
||||
}
|
||||
}
|
||||
|
||||
184
src/open-ai.ts
184
src/open-ai.ts
@@ -1,82 +1,62 @@
|
||||
import {OpenAI as openAI} from 'openai';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, clean} from '@ztimson/utils';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, clean, makeArray} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||
import {LLMProvider} from './provider.ts';
|
||||
import {TokenPool} from './token-pool.ts';
|
||||
import {convertSchema} from './tools.ts';
|
||||
|
||||
export class OpenAi extends LLMProvider {
|
||||
client!: openAI;
|
||||
tokenPool!: TokenPool;
|
||||
private clients = new Map<string, openAI>();
|
||||
|
||||
constructor(public readonly ai: Ai, public readonly host: string | null, public readonly token: string, public model: string) {
|
||||
constructor(public readonly ai: Ai, public readonly host: string | null, public readonly token: string | string[], public model: string) {
|
||||
super();
|
||||
this.client = new openAI(clean({
|
||||
baseURL: host,
|
||||
apiKey: token || (host ? 'ignored' : undefined)
|
||||
}));
|
||||
const tokens = makeArray(token).filter(Boolean);
|
||||
this.tokenPool = new TokenPool(...(tokens.length ? tokens : [host ? 'ignored' : '']));
|
||||
}
|
||||
|
||||
private toStandard(history: any[]): LLMMessage[] {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
const h = history[i];
|
||||
if(h.role === 'assistant' && h.tool_calls) {
|
||||
const tools = h.tool_calls.map((tc: any) => ({
|
||||
role: 'tool',
|
||||
id: tc.id,
|
||||
name: tc.function.name,
|
||||
args: JSONAttemptParse(tc.function.arguments, {}),
|
||||
timestamp: h.timestamp
|
||||
}));
|
||||
history.splice(i, 1, ...tools);
|
||||
i += tools.length - 1;
|
||||
} else if(h.role === 'tool' && h.content) {
|
||||
const record = history.find(h2 => h.tool_call_id == h2.id);
|
||||
if(record) {
|
||||
if(h.content.includes('"error":')) record.error = h.content;
|
||||
else record.content = h.content;
|
||||
private getClient(token: string): openAI {
|
||||
let client = this.clients.get(token);
|
||||
if(!client) {
|
||||
client = new openAI(clean({baseURL: this.host, apiKey: token || undefined}));
|
||||
this.clients.set(token, client);
|
||||
}
|
||||
history.splice(i, 1);
|
||||
i--;
|
||||
}
|
||||
if(!history[i]?.timestamp) history[i].timestamp = Date.now();
|
||||
}
|
||||
return history;
|
||||
return client;
|
||||
}
|
||||
|
||||
private fromStandard(history: LLMMessage[]): any[] {
|
||||
return history.reduce((result, h) => {
|
||||
/** Convert standard history -> OpenAI wire format */
|
||||
private toWire(history: LLMMessage[], system?: string): any[] {
|
||||
const wire: any[] = [];
|
||||
if(system) wire.push({role: 'system', content: system});
|
||||
for(const h of history) {
|
||||
if(h.role === 'tool') {
|
||||
result.push({
|
||||
wire.push({
|
||||
role: 'assistant',
|
||||
content: null,
|
||||
tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }],
|
||||
refusal: null,
|
||||
annotations: []
|
||||
tool_calls: [{id: h.id, type: 'function', function: {name: h.name, arguments: JSON.stringify(h.args)}}],
|
||||
}, {
|
||||
role: 'tool',
|
||||
tool_call_id: h.id,
|
||||
content: h.error || h.content
|
||||
content: h.error || h.content || '',
|
||||
});
|
||||
} else {
|
||||
const {timestamp, ...rest} = h;
|
||||
result.push(rest);
|
||||
wire.push({role: h.role, content: h.content});
|
||||
}
|
||||
return result;
|
||||
}, [] as any[]);
|
||||
}
|
||||
return wire;
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||
const controller = new AbortController();
|
||||
return Object.assign(new Promise<any>(async (res, rej) => {
|
||||
if(options.system) {
|
||||
if(options.history?.[0]?.role != 'system') options.history?.splice(0, 0, {role: 'system', content: options.system, timestamp: Date.now()});
|
||||
else options.history[0].content = options.system;
|
||||
}
|
||||
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]);
|
||||
if(!options.history) options.history = [];
|
||||
const history = options.history;
|
||||
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
|
||||
|
||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||
const requestParams: any = {
|
||||
model: options.model || this.model,
|
||||
messages: history,
|
||||
stream: !!options.stream,
|
||||
max_completion_tokens: options.max_tokens || this.ai.options.llm?.max_tokens || undefined,
|
||||
temperature: options.temperature || this.ai.options.llm?.temperature || undefined,
|
||||
@@ -96,92 +76,94 @@ export class OpenAi extends LLMProvider {
|
||||
|
||||
if(options.schema) {
|
||||
const schema = convertSchema(options.schema);
|
||||
requestParams.response_format = {
|
||||
type: 'json_schema',
|
||||
json_schema: {
|
||||
name: 'response',
|
||||
strict: true,
|
||||
schema
|
||||
}
|
||||
};
|
||||
requestParams.response_format = {type: 'json_schema', json_schema: {name: 'response', strict: true, schema}};
|
||||
}
|
||||
if(options.stream) requestParams.stream_options = {include_usage: true};
|
||||
|
||||
let resp: any, isFirstMessage = true;
|
||||
try {
|
||||
let terminal = false;
|
||||
do {
|
||||
resp = await this.client.chat.completions.create(requestParams).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||
requestParams.messages = this.toWire(history.filter(h => h.role !== 'system'), options.system);
|
||||
|
||||
const callStart = Date.now();
|
||||
const resp: any = await this.tokenPool.run(token => this.getClient(token).chat.completions.create(requestParams)).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(requestParams.messages, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
|
||||
let usage: any, msg: any = {content: '', tool_calls: []};
|
||||
if(options.stream) {
|
||||
if(!isFirstMessage) options.stream({text: '\n\n'});
|
||||
else isFirstMessage = false;
|
||||
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: []}}];
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.choices[0].delta.content) {
|
||||
resp.choices[0].message.content += chunk.choices[0].delta.content;
|
||||
if(chunk.usage) usage = chunk.usage;
|
||||
if(chunk.choices[0]?.delta?.content) {
|
||||
msg.content += chunk.choices[0].delta.content;
|
||||
options.stream({text: chunk.choices[0].delta.content});
|
||||
}
|
||||
|
||||
if(chunk.choices[0].delta.tool_calls) {
|
||||
if(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 = msg.tool_calls.find((tc: any) => tc.index === deltaTC.index);
|
||||
if(existing) {
|
||||
if(deltaTC.id) existing.id = deltaTC.id;
|
||||
if(deltaTC.type) existing.type = deltaTC.type;
|
||||
if(deltaTC.function) {
|
||||
if(!existing.function) existing.function = {};
|
||||
if(deltaTC.function.name) existing.function.name = deltaTC.function.name;
|
||||
if(deltaTC.function.arguments) existing.function.arguments = (existing.function.arguments || '') + deltaTC.function.arguments;
|
||||
}
|
||||
if(deltaTC.function?.name) existing.function.name = deltaTC.function.name;
|
||||
if(deltaTC.function?.arguments) existing.function.arguments += deltaTC.function.arguments;
|
||||
} else {
|
||||
resp.choices[0].message.tool_calls.push({
|
||||
msg.tool_calls.push({
|
||||
index: deltaTC.index,
|
||||
id: deltaTC.id || '',
|
||||
type: deltaTC.type || 'function',
|
||||
function: {
|
||||
name: deltaTC.function?.name || '',
|
||||
arguments: deltaTC.function?.arguments || ''
|
||||
}
|
||||
function: {name: deltaTC.function?.name || '', arguments: deltaTC.function?.arguments || ''}
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
usage = resp.usage;
|
||||
msg = resp.choices[0].message;
|
||||
}
|
||||
const duration = Date.now() - callStart;
|
||||
const tps = usage?.completion_tokens && duration > 0 ? usage.completion_tokens / (duration / 1000) : 0;
|
||||
|
||||
if(resp.error) throw new Error(resp.error);
|
||||
const toolCalls = resp.choices[0].message.tool_calls || [];
|
||||
const toolCalls = msg.tool_calls || [];
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
history.push(resp.choices[0].message);
|
||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||
const tool = tools?.find(findByProp('name', 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(msg.content?.trim()) history.push({role: 'assistant', content: msg.content.trim(), timestamp: Date.now(), duration, tps});
|
||||
|
||||
const entries = toolCalls.map((tc: any) => {
|
||||
const entry: any = {role: 'tool', id: tc.id, name: tc.function.name, args: JSONAttemptParse(tc.function.arguments, {}), content: undefined, timestamp: Date.now()};
|
||||
history.push(entry);
|
||||
return {tc, entry};
|
||||
});
|
||||
|
||||
await Promise.all(entries.map(async ({tc, entry}: any) => {
|
||||
const tool = tools.find(findByProp('name', tc.function.name));
|
||||
if(options.stream) options.stream({tool: tc.function.name});
|
||||
if(!tool) { entry.error = 'Tool not found'; return; }
|
||||
try {
|
||||
const args = JSONAttemptParse(toolCall.function.arguments, {});
|
||||
const result = await tool.fn(args, options.stream, this.ai);
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
||||
} catch (err: any) {
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'})};
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(entry.args, toolStream, this.ai, tc.id);
|
||||
entry.content = typeof result === 'object' ? JSONSanitize(result) : result;
|
||||
} catch(err: any) {
|
||||
entry.error = err?.message || err?.toString() || 'Unknown';
|
||||
}
|
||||
}));
|
||||
history.push(...results);
|
||||
requestParams.messages = history;
|
||||
} else {
|
||||
terminal = true;
|
||||
const text = (msg.content || '').trim();
|
||||
if(text) history.push({role: 'assistant', content: text, timestamp: Date.now(), duration, tps});
|
||||
}
|
||||
} while (!controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
|
||||
|
||||
const textContent = resp.choices[0].message.content?.trim() || '';
|
||||
history.push({role: 'assistant', content: textContent});
|
||||
history = this.toStandard(history);
|
||||
} while(!terminal && !controller.signal.aborted);
|
||||
|
||||
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 turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => h.role === 'assistant' ? str + (h.content || '') : str, '').trim();
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
} catch(err) {
|
||||
rej(err);
|
||||
}
|
||||
}), {abort: () => controller.abort()});
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import {AbortablePromise} from './ai.ts';
|
||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||
import {LLMRequest} from './llm.ts';
|
||||
|
||||
export abstract class LLMProvider {
|
||||
abstract ask(message: string, options: LLMRequest): AbortablePromise<string>;
|
||||
|
||||
65
src/token-pool.ts
Normal file
65
src/token-pool.ts
Normal file
@@ -0,0 +1,65 @@
|
||||
const DEFAULT_COOLDOWN = 15 * 60 * 1000;
|
||||
|
||||
type TokenState = {
|
||||
token: string;
|
||||
cooldownUntil: number; // 0 = available now
|
||||
lastError?: {code: number, message: string};
|
||||
};
|
||||
|
||||
export class TokenPoolExhaustedError extends Error {
|
||||
constructor(public tokens: Record<string, {code: number, message: string}>) {
|
||||
super(`All tokens exhausted:\n${Object.entries(tokens).map(([t, e]) => `${t}: [${e.code}] ${e.message}`).join('\n')}`);
|
||||
this.name = 'TokenPoolExhaustedError';
|
||||
}
|
||||
}
|
||||
|
||||
export class TokenPool {
|
||||
private states: TokenState[];
|
||||
|
||||
constructor(...tokens: string[]) {
|
||||
this.states = tokens.map(token => ({token, cooldownUntil: 0}));
|
||||
}
|
||||
|
||||
private preview(token: string): string {
|
||||
return token.length <= 8 ? '****' : `${token.slice(0, 4)}...${token.slice(-4)}`;
|
||||
}
|
||||
|
||||
/** Anthropic & OpenAI SDKs both attach `status` to thrown errors */
|
||||
private statusCode(err: any): number {
|
||||
return err?.status ?? err?.response?.status ?? err?.statusCode;
|
||||
}
|
||||
|
||||
private retryAfter(err: any): number {
|
||||
const headers = err?.headers || err?.response?.headers;
|
||||
const raw = headers?.get?.('retry-after') ?? headers?.['retry-after'];
|
||||
if(raw) {
|
||||
const seconds = Number(raw);
|
||||
if(!isNaN(seconds)) return Date.now() + seconds * 1000;
|
||||
const date = new Date(raw).getTime();
|
||||
if(!isNaN(date)) return date;
|
||||
}
|
||||
return Date.now() + DEFAULT_COOLDOWN;
|
||||
}
|
||||
|
||||
async run<T>(fn: (token: string) => Promise<T>): Promise<T> {
|
||||
const now = Date.now();
|
||||
for(const state of this.states) {
|
||||
if(state.cooldownUntil > now) continue;
|
||||
try {
|
||||
const result = await fn(state.token);
|
||||
state.cooldownUntil = 0;
|
||||
state.lastError = undefined;
|
||||
return result;
|
||||
} catch(err: any) {
|
||||
const code = this.statusCode(err);
|
||||
if(![401, 403, 429].includes(code)) throw err;
|
||||
state.cooldownUntil = code === 429 ? this.retryAfter(err) : Date.now() + DEFAULT_COOLDOWN;
|
||||
state.lastError = {code, message: err?.message || 'Unknown error'};
|
||||
}
|
||||
}
|
||||
|
||||
const failures: Record<string, {code: number, message: string}> = {};
|
||||
this.states.forEach(s => { if(s.lastError) failures[this.preview(s.token)] = s.lastError; });
|
||||
throw new TokenPoolExhaustedError(failures);
|
||||
}
|
||||
}
|
||||
667
src/tools.ts
667
src/tools.ts
@@ -41,7 +41,7 @@ export type AiTool = {
|
||||
/** Tool arguments */
|
||||
args?: AiToolArg,
|
||||
/** Callback function */
|
||||
fn: (args: any, stream: LLMRequest['stream'], ai: Ai) => any | Promise<any>,
|
||||
fn: (args: any, stream: LLMRequest['stream'], ai: Ai, toolId?: string) => any | Promise<any>,
|
||||
};
|
||||
|
||||
export function convertSchema(schema: any): any {
|
||||
@@ -91,20 +91,33 @@ export function convertSchema(schema: any): any {
|
||||
};
|
||||
}
|
||||
|
||||
export const CliTool: AiTool = {
|
||||
export const ExecCliTool: AiTool = {
|
||||
name: 'cli',
|
||||
description: 'Use the command line interface, returns any output',
|
||||
args: {command: {type: 'string', description: 'Command to run', required: true}},
|
||||
fn: (args: {command: string}) => $Sync`${args.command}`
|
||||
}
|
||||
|
||||
export const DateTimeTool: AiTool = {
|
||||
name: 'get_datetime',
|
||||
description: 'Get local/UTC date/time',
|
||||
export const ExecJSTool: AiTool = {
|
||||
name: 'exec_javascript',
|
||||
description: 'Execute commonjs javascript',
|
||||
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 = {
|
||||
@@ -118,11 +131,11 @@ export const ExecTool: AiTool = {
|
||||
try {
|
||||
switch(args.language) {
|
||||
case 'cli':
|
||||
return await CliTool.fn({command: args.code}, stream, ai);
|
||||
return await ExecCliTool.fn({command: args.code}, stream, ai);
|
||||
case 'node':
|
||||
return await JSTool.fn({code: args.code}, stream, ai);
|
||||
return await ExecJSTool.fn({code: args.code}, stream, ai);
|
||||
case 'python':
|
||||
return await PythonTool.fn({code: args.code}, stream, ai);
|
||||
return await ExecPythonTool.fn({code: args.code}, stream, ai);
|
||||
default:
|
||||
throw new Error(`Unsupported language: ${args.language}`);
|
||||
}
|
||||
@@ -132,8 +145,483 @@ export const ExecTool: AiTool = {
|
||||
}
|
||||
}
|
||||
|
||||
export const FetchTool: AiTool = {
|
||||
name: 'fetch',
|
||||
export const FsDeleteTool = (whitelist: null | string[] = null): AiTool => {
|
||||
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',
|
||||
args: {
|
||||
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})
|
||||
}
|
||||
|
||||
export const JSTool: AiTool = {
|
||||
name: 'exec_javascript',
|
||||
description: 'Execute commonjs javascript',
|
||||
export const WebFlareSolverTool = (host: string) => {
|
||||
return {
|
||||
name: 'web_flaresolverr',
|
||||
description: 'Use a flaresolverr proxy to bypass cloudflare bot detection',
|
||||
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}) => {
|
||||
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};
|
||||
fn: async ({url, cmd, maxTimeout, postData}) => {
|
||||
function toFormUrlEncoded(obj, prefix = '') {
|
||||
const pairs: any = [];
|
||||
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)}`);
|
||||
}
|
||||
}
|
||||
|
||||
return pairs.join('&');
|
||||
}
|
||||
|
||||
const res = await fetch(host + '/v1', {
|
||||
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 PythonTool: 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 ReadWebpageTool: AiTool = {
|
||||
name: 'read_webpage',
|
||||
export const WebReadTool: AiTool = {
|
||||
name: 'web_read',
|
||||
description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
|
||||
args: {
|
||||
url: {type: 'string', description: 'URL to read', required: true},
|
||||
@@ -300,91 +817,3 @@ export const WebSearchTool: AiTool = {
|
||||
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');
|
||||
}
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user