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ztimson:0.8.9 ztimson:0.8.8 ztimson:0.8.7 ztimson:0.8.6 ztimson:0.8.5 ztimson:0.8.4 ztimson:0.8.3 ztimson:0.8.2 ztimson:0.8.1 ztimson:0.8.0 ztimson:0.7.11 ztimson:0.7.10 ztimson:0.7.9 ztimson:0.7.8 ztimson:0.7.7 ztimson:0.7.6 ztimson:0.7.5 ztimson:0.7.4 ztimson:0.7.3 ztimson:0.7.2 ztimson:0.7.1 ztimson:0.7.0 ztimson:0.6.10 ztimson:0.6.9 ztimson:0.6.8 ztimson:0.6.7-rc.1 ztimson:0.6.7 ztimson:0.6.6 ztimson:0.6.5 ztimson:0.6.4 ztimson:0.6.3 ztimson:0.6.2 ztimson:0.6.1 ztimson:0.6.0 ztimson:0.5.6 ztimson:0.5.5 ztimson:0.5.4 ztimson:0.5.3 ztimson:0.5.2 ztimson:0.5.1 ztimson:0.4.1 ztimson:0.4.0 ztimson:0.3.0 ztimson:0.2.7 ztimson:0.2.6 ztimson:0.2.5 ztimson:0.2.4 ztimson:0.2.3 ztimson:0.2.2 ztimson:0.2.1 ztimson:0.2.0 ztimson:0.1.22 ztimson:0.1.21 ztimson:0.1.20 ztimson:0.1.19 ztimson:0.1.18 ztimson:0.1.16 ztimson:0.1.15 ztimson:0.1.14 ztimson:0.1.13 ztimson:0.1.12 ztimson:0.1.11 ztimson:0.1.10 ztimson:0.1.9 ztimson:0.1.8 ztimson:0.1.7 ztimson:0.1.6 ztimson:0.1.5 ztimson:0.1.4
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ztimson:0.8.9 ztimson:0.8.8 ztimson:0.8.7 ztimson:0.8.6 ztimson:0.8.5 ztimson:0.8.4 ztimson:0.8.3 ztimson:0.8.2 ztimson:0.8.1 ztimson:0.8.0 ztimson:0.7.11 ztimson:0.7.10 ztimson:0.7.9 ztimson:0.7.8 ztimson:0.7.7 ztimson:0.7.6 ztimson:0.7.5 ztimson:0.7.4 ztimson:0.7.3 ztimson:0.7.2 ztimson:0.7.1 ztimson:0.7.0 ztimson:0.6.10 ztimson:0.6.9 ztimson:0.6.8 ztimson:0.6.7-rc.1 ztimson:0.6.7 ztimson:0.6.6 ztimson:0.6.5 ztimson:0.6.4 ztimson:0.6.3 ztimson:0.6.2 ztimson:0.6.1 ztimson:0.6.0 ztimson:0.5.6 ztimson:0.5.5 ztimson:0.5.4 ztimson:0.5.3 ztimson:0.5.2 ztimson:0.5.1 ztimson:0.4.1 ztimson:0.4.0 ztimson:0.3.0 ztimson:0.2.7 ztimson:0.2.6 ztimson:0.2.5 ztimson:0.2.4 ztimson:0.2.3 ztimson:0.2.2 ztimson:0.2.1 ztimson:0.2.0 ztimson:0.1.22 ztimson:0.1.21 ztimson:0.1.20 ztimson:0.1.19 ztimson:0.1.18 ztimson:0.1.16 ztimson:0.1.15 ztimson:0.1.14 ztimson:0.1.13 ztimson:0.1.12 ztimson:0.1.11 ztimson:0.1.10 ztimson:0.1.9 ztimson:0.1.8 ztimson:0.1.7 ztimson:0.1.6 ztimson:0.1.5 ztimson:0.1.4

7 Commits
0.5.6 ... 0.6.6

Author SHA1 Message Date
ztimson
ad1ee48763 Use one-off workers to process requests without blocking
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2026-02-12 19:45:17 -05:00
ztimson
3ed206923f Fix ASR
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2026-02-12 18:32:19 -05:00
ztimson
22d5427e86 Fix ASR
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2026-02-12 17:49:33 -05:00
ztimson
43b53164c0 Bump 0.6.3
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2026-02-12 17:24:15 -05:00
ztimson
575fbac099 Fixed ASR
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2026-02-12 13:31:30 -05:00
ztimson
46ae0f7913 expose diarization support checking function
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2026-02-12 11:55:29 -05:00
ztimson
54730a2b9a Speaker diarization
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2026-02-12 11:26:11 -05:00
10 changed files with 359 additions and 240 deletions
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6
README.md
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@@ -75,6 +75,7 @@ A TypeScript library that provides a unified interface for working with multiple
#### Instructions #### Instructions
1. Install the package: `npm i @ztimson/ai-utils` 1. Install the package: `npm i @ztimson/ai-utils`
2. For speaker diarization: `pip install pyannote.audio`
</details> </details>
@@ -90,8 +91,9 @@ A TypeScript library that provides a unified interface for working with multiple
#### Instructions #### Instructions
1. Install the dependencies: `npm i` 1. Install the dependencies: `npm i`
2. Build library: `npm build` 2. For speaker diarization: `pip install pyannote.audio`
3. Run unit tests: `npm test` 3. Build library: `npm build`
4. Run unit tests: `npm test`
</details> </details>

337
package-lock.json generated
View File

@@ -1,12 +1,12 @@
{ {
"name": "@ztimson/ai-utils", "name": "@ztimson/ai-utils",
"version": "0.4.0", "version": "0.6.4",
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"requires": true, "requires": true,
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"version": "0.4.0", "version": "0.6.4",
"license": "MIT", "license": "MIT",
"dependencies": { "dependencies": {
"@anthropic-ai/sdk": "^0.67.0", "@anthropic-ai/sdk": "^0.67.0",
@@ -16,7 +16,8 @@
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"cheerio": "^1.2.0", "cheerio": "^1.2.0",
"openai": "^6.6.0", "openai": "^6.6.0",
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"wavefile": "^11.0.0"
}, },
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@@ -106,9 +107,9 @@
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@@ -242,9 +243,9 @@
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"integrity": "sha512-a54IwgWPaeBCAAsv13YgmALOF1elABB08FxO9i+r4VFk5Vl4pKokRPeX8u5TCgSsPi6ec1otfLjdOpVcgbpshg==", "integrity": "sha512-BuU2qnTti9YKgK5N+IeMubp14ZUKUUw7yeJbkjtosvHiP0AZ5c8IAgEMk79D0eC8F23r4Ac/q8cAIFdm2FtyoA==",
"dev": true, "dev": true,
"license": "MIT", "license": "MIT",
"dependencies": { "dependencies": {
@@ -3509,9 +3510,9 @@
} }
}, },
"node_modules/openai": { "node_modules/openai": {
"version": "6.17.0", "version": "6.21.0",
"resolved": "https://registry.npmjs.org/openai/-/openai-6.17.0.tgz", "resolved": "https://registry.npmjs.org/openai/-/openai-6.21.0.tgz",
"integrity": "sha512-NHRpPEUPzAvFOAFs9+9pC6+HCw/iWsYsKCMPXH5Kw7BpMxqd8g/A07/1o7Gx2TWtCnzevVRyKMRFqyiHyAlqcA==", "integrity": "sha512-26dQFi76dB8IiN/WKGQOV+yKKTTlRCxQjoi2WLt0kMcH8pvxVyvfdBDkld5GTl7W1qvBpwVOtFcsqktj3fBRpA==",
"license": "Apache-2.0", "license": "Apache-2.0",
"bin": { "bin": {
"openai": "bin/cli" "openai": "bin/cli"
@@ -3994,9 +3995,9 @@
"license": "MIT" "license": "MIT"
}, },
"node_modules/semver": { "node_modules/semver": {
"version": "7.7.3", "version": "7.7.4",
"resolved": "https://registry.npmjs.org/semver/-/semver-7.7.3.tgz", "resolved": "https://registry.npmjs.org/semver/-/semver-7.7.4.tgz",
"integrity": "sha512-SdsKMrI9TdgjdweUSR9MweHA4EJ8YxHn8DFaDisvhVlUOe4BF1tLD7GAj0lIqWVl+dPb/rExr0Btby5loQm20Q==", "integrity": "sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA==",
"license": "ISC", "license": "ISC",
"bin": { "bin": {
"semver": "bin/semver.js" "semver": "bin/semver.js"
@@ -4403,9 +4404,9 @@
"license": "MIT" "license": "MIT"
}, },
"node_modules/undici": { "node_modules/undici": {
"version": "7.19.2", "version": "7.21.0",
"resolved": "https://registry.npmjs.org/undici/-/undici-7.19.2.tgz", "resolved": "https://registry.npmjs.org/undici/-/undici-7.21.0.tgz",
"integrity": "sha512-4VQSpGEGsWzk0VYxyB/wVX/Q7qf9t5znLRgs0dzszr9w9Fej/8RVNQ+S20vdXSAyra/bJ7ZQfGv6ZMj7UEbzSg==", "integrity": "sha512-Hn2tCQpoDt1wv23a68Ctc8Cr/BHpUSfaPYrkajTXOS9IKpxVRx/X5m1K2YkbK2ipgZgxXSgsUinl3x+2YdSSfg==",
"license": "MIT", "license": "MIT",
"engines": { "engines": {
"node": ">=20.18.1" "node": ">=20.18.1"
@@ -4667,6 +4668,18 @@
"integrity": "sha512-zksaLKM2fVlnB5jQQDqKXXwYHLQUVH9es+5TOOHwGOVJOCeRBCiPjwSg+3tN2AdTCzjgli4jijCH290kXb/zWQ==", "integrity": "sha512-zksaLKM2fVlnB5jQQDqKXXwYHLQUVH9es+5TOOHwGOVJOCeRBCiPjwSg+3tN2AdTCzjgli4jijCH290kXb/zWQ==",
"license": "Apache-2.0" "license": "Apache-2.0"
}, },
"node_modules/wavefile": {
"version": "11.0.0",
"resolved": "https://registry.npmjs.org/wavefile/-/wavefile-11.0.0.tgz",
"integrity": "sha512-/OBiAALgWU24IG7sC84cDO/KfFuvajWc5Uec0oV2zrpOOZZDgGdOwHwgEzOrwh8jkubBk7PtZfQBIcI1OaE5Ng==",
"license": "MIT",
"bin": {
"wavefile": "bin/wavefile.js"
},
"engines": {
"node": ">=8"
}
},
"node_modules/webidl-conversions": { "node_modules/webidl-conversions": {
"version": "3.0.1", "version": "3.0.1",
"resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz", "resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",

5
package.json
View File

@@ -1,6 +1,6 @@
{ {
"name": "@ztimson/ai-utils", "name": "@ztimson/ai-utils",
"version": "0.5.6", "version": "0.6.6",
"description": "AI Utility library", "description": "AI Utility library",
"author": "Zak Timson", "author": "Zak Timson",
"license": "MIT", "license": "MIT",
@@ -32,7 +32,8 @@
"@ztimson/utils": "^0.27.9", "@ztimson/utils": "^0.27.9",
"cheerio": "^1.2.0", "cheerio": "^1.2.0",
"openai": "^6.6.0", "openai": "^6.6.0",
"tesseract.js": "^6.0.1" "tesseract.js": "^6.0.1",
"wavefile": "^11.0.0"
}, },
"devDependencies": { "devDependencies": {
"@types/node": "^24.8.1", "@types/node": "^24.8.1",

20
src/ai.ts
View File

@@ -10,24 +10,16 @@ export type AbortablePromise<T> = Promise<T> & {
export type AiOptions = { export type AiOptions = {
/** Path to models */ /** Path to models */
path?: string; path?: string;
/** Embedding model */ /** ASR model: whisper-tiny, whisper-base */
embedder?: string; // all-MiniLM-L6-v2, bge-small-en-v1.5, bge-large-en-v1.5 asr?: string;
/** Embedding model: all-MiniLM-L6-v2, bge-small-en-v1.5, bge-large-en-v1.5 */
embedder?: string;
/** Large language models, first is default */ /** Large language models, first is default */
llm?: Omit<LLMRequest, 'model'> & { llm?: Omit<LLMRequest, 'model'> & {
models: {[model: string]: AnthropicConfig | OllamaConfig | OpenAiConfig}; models: {[model: string]: AnthropicConfig | OllamaConfig | OpenAiConfig};
} }
/** Tesseract OCR configuration */ /** OCR model: eng, eng_best, eng_fast */
tesseract?: { ocr?: string;
/** Model: eng, eng_best, eng_fast */
model?: string;
}
/** Whisper ASR configuration */
whisper?: {
/** Whisper binary location */
binary: string;
/** Model: `ggml-base.en.bin` */
model: string;
}
} }
export class Ai { export class Ai {

124
src/asr.ts Normal file
View File

@@ -0,0 +1,124 @@
import { pipeline } from '@xenova/transformers';
import { parentPort } from 'worker_threads';
import * as fs from 'node:fs';
import wavefile from 'wavefile';
import { spawn } from 'node:child_process';
let whisperPipeline: any;
export async function canDiarization(): Promise<boolean> {
return new Promise((resolve) => {
const proc = spawn('python3', ['-c', 'import pyannote.audio']);
proc.on('close', (code: number) => resolve(code === 0));
proc.on('error', () => resolve(false));
});
}
async function runDiarization(audioPath: string, torchHome: string): Promise<any[]> {
const script = `
import sys
import json
import os
from pyannote.audio import Pipeline
os.environ['TORCH_HOME'] = "${torchHome}"
pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
diarization = pipeline(sys.argv[1])
segments = []
for turn, _, speaker in diarization.itertracks(yield_label=True):
segments.append({
"start": turn.start,
"end": turn.end,
"speaker": speaker
})
print(json.dumps(segments))
`;
return new Promise((resolve, reject) => {
let output = '';
const proc = spawn('python3', ['-c', script, audioPath]);
proc.stdout.on('data', (data: Buffer) => output += data.toString());
proc.stderr.on('data', (data: Buffer) => console.error(data.toString()));
proc.on('close', (code: number) => {
if(code === 0) {
try {
resolve(JSON.parse(output));
} catch (err) {
reject(new Error('Failed to parse diarization output'));
}
} else {
reject(new Error(`Python process exited with code ${code}`));
}
});
proc.on('error', reject);
});
}
function combineSpeakerTranscript(chunks: any[], speakers: any[]): string {
const speakerMap = new Map();
let speakerCount = 0;
speakers.forEach((seg: any) => {
if(!speakerMap.has(seg.speaker)) speakerMap.set(seg.speaker, ++speakerCount);
});
const lines: string[] = [];
let currentSpeaker = -1;
let currentText = '';
chunks.forEach((chunk: any) => {
const time = chunk.timestamp[0];
const speaker = speakers.find((s: any) => time >= s.start && time <= s.end);
const speakerNum = speaker ? speakerMap.get(speaker.speaker) : 1;
if (speakerNum !== currentSpeaker) {
if(currentText) lines.push(`[speaker ${currentSpeaker}]: ${currentText.trim()}`);
currentSpeaker = speakerNum;
currentText = chunk.text;
} else {
currentText += chunk.text;
}
});
if(currentText) lines.push(`[speaker ${currentSpeaker}]: ${currentText.trim()}`);
return lines.join('\n');
}
parentPort?.on('message', async ({ path, model, speaker, torchHome }) => {
try {
if(!whisperPipeline) whisperPipeline = await pipeline('automatic-speech-recognition', `Xenova/${model}`, {cache_dir: torchHome, quantized: true});
// Prepare audio file (convert to mono channel wave)
const wav = new wavefile.WaveFile(fs.readFileSync(path));
wav.toBitDepth('32f');
wav.toSampleRate(16000);
const samples = wav.getSamples();
let buffer;
if(Array.isArray(samples)) { // stereo to mono - average the channels
const left = samples[0];
const right = samples[1];
buffer = new Float32Array(left.length);
for (let i = 0; i < left.length; i++) buffer[i] = (left[i] + right[i]) / 2;
} else {
buffer = samples;
}
// Transcribe
const transcriptResult = await whisperPipeline(buffer, {return_timestamps: speaker ? 'word' : false});
if(!speaker) {
parentPort?.postMessage({ text: transcriptResult.text?.trim() || null });
return;
}
// Speaker Diarization
const hasDiarization = await canDiarization();
if(!hasDiarization) {
parentPort?.postMessage({ text: transcriptResult.text?.trim() || null, warning: 'Speaker diarization unavailable' });
return;
}
const speakers = await runDiarization(path, torchHome);
const combined = combineSpeakerTranscript(transcriptResult.chunks || [], speakers);
parentPort?.postMessage({ text: combined });
} catch (err) {
parentPort?.postMessage({ error: (err as Error).message });
}
});

68
src/audio.ts
View File

@@ -1,50 +1,40 @@
import {spawn} from 'node:child_process'; import {Worker} from 'worker_threads';
import fs from 'node:fs/promises'; import path from 'node:path';
import Path from 'node:path';
import {AbortablePromise, Ai} from './ai.ts'; import {AbortablePromise, Ai} from './ai.ts';
import {canDiarization} from './asr.ts';
export class Audio { export class Audio {
private downloads: {[key: string]: Promise<string>} = {}; constructor(private ai: Ai) {}
private whisperModel!: string;
constructor(private ai: Ai) { asr(filepath: string, options: { model?: string; speaker?: boolean } = {}): AbortablePromise<string | null> {
if(ai.options.whisper?.binary) { const { model = this.ai.options.asr || 'whisper-base', speaker = false } = options;
this.whisperModel = ai.options.whisper?.model.endsWith('.bin') ? ai.options.whisper?.model : ai.options.whisper?.model + '.bin'; let aborted = false;
this.downloadAsrModel(); const abort = () => { aborted = true; };
}
}
asr(path: string, model: string = this.whisperModel): AbortablePromise<string | null> { const p = new Promise<string | null>((resolve, reject) => {
if(!this.ai.options.whisper?.binary) throw new Error('Whisper not configured'); const worker = new Worker(path.join(import.meta.dirname, 'asr.js'));
let abort: any = () => {}; const handleMessage = ({ text, warning, error }: any) => {
const p = new Promise<string | null>(async (resolve, reject) => { worker.terminate();
const m = await this.downloadAsrModel(model); if(aborted) return;
let output = ''; if(error) reject(new Error(error));
const proc = spawn(<string>this.ai.options.whisper?.binary, ['-nt', '-np', '-m', m, '-f', path], {stdio: ['ignore', 'pipe', 'ignore']}); else {
abort = () => proc.kill('SIGTERM'); if(warning) console.warn(warning);
proc.on('error', (err: Error) => reject(err)); resolve(text);
proc.stdout.on('data', (data: Buffer) => output += data.toString()); }
proc.on('close', (code: number) => { };
if(code === 0) resolve(output.trim() || null); const handleError = (err: Error) => {
else reject(new Error(`Exit code ${code}`)); worker.terminate();
if(!aborted) reject(err);
};
worker.on('message', handleMessage);
worker.on('error', handleError);
worker.on('exit', (code) => {
if(code !== 0 && !aborted) reject(new Error(`Worker exited with code ${code}`));
}); });
worker.postMessage({path: filepath, model, speaker, torchHome: this.ai.options.path,});
}); });
return Object.assign(p, { abort }); return Object.assign(p, { abort });
} }
async downloadAsrModel(model: string = this.whisperModel): Promise<string> { canDiarization = canDiarization;
if(!this.ai.options.whisper?.binary) throw new Error('Whisper not configured');
if(!model.endsWith('.bin')) model += '.bin';
const p = Path.join(<string>this.ai.options.path, model);
if(await fs.stat(p).then(() => true).catch(() => false)) return p;
if(!!this.downloads[model]) return this.downloads[model];
this.downloads[model] = fetch(`https://huggingface.co/ggerganov/whisper.cpp/resolve/main/${model}`)
.then(resp => resp.arrayBuffer())
.then(arr => Buffer.from(arr)).then(async buffer => {
await fs.writeFile(p, buffer);
delete this.downloads[model];
return p;
});
return this.downloads[model];
}
} }

1
src/index.ts
View File

@@ -1,5 +1,6 @@
export * from './ai'; export * from './ai';
export * from './antrhopic'; export * from './antrhopic';
export * from './asr';
export * from './audio'; export * from './audio';
export * from './embedder' export * from './embedder'
export * from './llm'; export * from './llm';

33
src/llm.ts
View File

@@ -75,22 +75,10 @@ export type LLMRequest = {
} }
class LLM { class LLM {
private embedWorker: Worker | null = null;
private embedQueue = new Map<number, { resolve: (value: number[]) => void; reject: (error: any) => void }>();
private embedId = 0;
private models: {[model: string]: LLMProvider} = {}; private models: {[model: string]: LLMProvider} = {};
private defaultModel!: string; private defaultModel!: string;
constructor(public readonly ai: Ai) { constructor(public readonly ai: Ai) {
this.embedWorker = new Worker(join(dirname(fileURLToPath(import.meta.url)), 'embedder.js'));
this.embedWorker.on('message', ({ id, embedding }) => {
const pending = this.embedQueue.get(id);
if (pending) {
pending.resolve(embedding);
this.embedQueue.delete(id);
}
});
if(!ai.options.llm?.models) return; if(!ai.options.llm?.models) return;
Object.entries(ai.options.llm.models).forEach(([model, config]) => { Object.entries(ai.options.llm.models).forEach(([model, config]) => {
if(!this.defaultModel) this.defaultModel = model; if(!this.defaultModel) this.defaultModel = model;
@@ -269,14 +257,21 @@ class LLM {
embedding(target: object | string, maxTokens = 500, overlapTokens = 50) { embedding(target: object | string, maxTokens = 500, overlapTokens = 50) {
const embed = (text: string): Promise<number[]> => { const embed = (text: string): Promise<number[]> => {
return new Promise((resolve, reject) => { return new Promise((resolve, reject) => {
const id = this.embedId++; const worker = new Worker(join(dirname(fileURLToPath(import.meta.url)), 'embedder.js'));
this.embedQueue.set(id, { resolve, reject }); const handleMessage = ({ embedding }: any) => {
this.embedWorker?.postMessage({ worker.terminate();
id, resolve(embedding);
text, };
model: this.ai.options?.embedder || 'bge-small-en-v1.5', const handleError = (err: Error) => {
path: this.ai.options.path worker.terminate();
reject(err);
};
worker.on('message', handleMessage);
worker.on('error', handleError);
worker.on('exit', (code) => {
if(code !== 0) reject(new Error(`Worker exited with code ${code}`));
}); });
worker.postMessage({text, model: this.ai.options?.embedder || 'bge-small-en-v1.5', path: this.ai.options.path});
}); });
}; };
const chunks = this.chunk(target, maxTokens, overlapTokens); const chunks = this.chunk(target, maxTokens, overlapTokens);

2
src/vision.ts
View File

@@ -13,7 +13,7 @@ export class Vision {
ocr(path: string): AbortablePromise<string | null> { ocr(path: string): AbortablePromise<string | null> {
let worker: any; let worker: any;
const p = new Promise<string | null>(async res => { const p = new Promise<string | null>(async res => {
worker = await createWorker(this.ai.options.tesseract?.model || 'eng', 2, {cachePath: this.ai.options.path}); worker = await createWorker(this.ai.options.ocr || 'eng', 2, {cachePath: this.ai.options.path});
const {data} = await worker.recognize(path); const {data} = await worker.recognize(path);
await worker.terminate(); await worker.terminate();
res(data.text.trim() || null); res(data.text.trim() || null);

1
vite.config.ts
View File

@@ -6,6 +6,7 @@ export default defineConfig({
build: { build: {
lib: { lib: {
entry: { entry: {
asr: './src/asr.ts',
index: './src/index.ts', index: './src/index.ts',
embedder: './src/embedder.ts', embedder: './src/embedder.ts',
}, },