Compare commits
2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| abd290246c | |||
| ca66e8e304 |
18
README.md
18
README.md
@@ -3,7 +3,7 @@
|
||||
<br />
|
||||
|
||||
<!-- Logo -->
|
||||
<img src="https://git.zakscode.com/repo-avatars/a90851ca730480ec37a5c0c2c4f1b4609eee5eadf806eaf16c83ac4cb7493aa9" alt="Logo" width="200" height="200">
|
||||
<img alt="Logo" width="200" height="200" src="https://git.zakscode.com/repo-avatars/a82d423674763e7a0c1c945bdbb07e249b2bb786d3c9beae76d5b196a10f5c0f">
|
||||
|
||||
<!-- Title -->
|
||||
### @ztimson/ai-utils
|
||||
@@ -53,13 +53,15 @@ A TypeScript library that provides a unified interface for working with multiple
|
||||
- **Provider Abstraction**: Switch between AI providers without changing your code
|
||||
|
||||
### Built With
|
||||
[](https://anthropic.com/)
|
||||
[](https://openai.com/)
|
||||
[](https://ollama.com/)
|
||||
[](https://tensorflow.org/)
|
||||
[](https://tesseract-ocr.github.io/)
|
||||
[](https://anthropic.com/)
|
||||
[](https://github.com/ggml-org/llama.cpp)
|
||||
[](https://openai.com/)
|
||||
[](https://github.com/pyannote)
|
||||
[](https://tensorflow.org/)
|
||||
[](https://tesseract-ocr.github.io/)
|
||||
[](https://huggingface.co/docs/transformers.js/en/index)
|
||||
[](https://typescriptlang.org/)
|
||||
[](https://github.com/ggerganov/whisper.cpp)
|
||||
[](https://github.com/ggerganov/whisper.cpp)
|
||||
|
||||
## Setup
|
||||
|
||||
@@ -88,6 +90,8 @@ A TypeScript library that provides a unified interface for working with multiple
|
||||
|
||||
#### Prerequisites
|
||||
- [Node.js](https://nodejs.org/en/download)
|
||||
- _[Whisper.cpp](https://github.com/ggml-org/whisper.cpp/releases/tag) (ASR)_
|
||||
- _[Pyannote](https://github.com/pyannote) (ASR Diarization):_ `pip install pyannote.audio`
|
||||
|
||||
#### Instructions
|
||||
1. Install the dependencies: `npm i`
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "0.7.11",
|
||||
"version": "0.8.1",
|
||||
"description": "AI Utility library",
|
||||
"author": "Zak Timson",
|
||||
"license": "MIT",
|
||||
|
||||
214
src/audio.ts
214
src/audio.ts
@@ -1,7 +1,8 @@
|
||||
import {execSync, spawn} from 'node:child_process';
|
||||
import {mkdtempSync} from 'node:fs';
|
||||
import fs, {rm} from 'node:fs/promises';
|
||||
import fs from 'node:fs/promises';
|
||||
import {tmpdir} from 'node:os';
|
||||
import * as path from 'node:path';
|
||||
import Path, {join} from 'node:path';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
|
||||
@@ -34,27 +35,155 @@ print(json.dumps(segments))
|
||||
`;
|
||||
}
|
||||
|
||||
private async addPunctuation(timestampData: any, llm?: boolean, cadence = 150): Promise<string> {
|
||||
const countSyllables = (word: string): number => {
|
||||
word = word.toLowerCase().replace(/[^a-z]/g, '');
|
||||
if(word.length <= 3) return 1;
|
||||
const matches = word.match(/[aeiouy]+/g);
|
||||
let count = matches ? matches.length : 1;
|
||||
if(word.endsWith('e')) count--;
|
||||
return Math.max(1, count);
|
||||
};
|
||||
|
||||
let result = '';
|
||||
timestampData.transcription.filter((word, i) => {
|
||||
let skip = false;
|
||||
const prevWord = timestampData.transcription[i - 1];
|
||||
const nextWord = timestampData.transcription[i + 1];
|
||||
if(!word.text && nextWord) {
|
||||
nextWord.offsets.from = word.offsets.from;
|
||||
nextWord.timestamps.from = word.offsets.from;
|
||||
} else if(word.text && word.text[0] != ' ' && prevWord) {
|
||||
prevWord.offsets.to = word.offsets.to;
|
||||
prevWord.timestamps.to = word.timestamps.to;
|
||||
prevWord.text += word.text;
|
||||
skip = true;
|
||||
}
|
||||
return !!word.text && !skip;
|
||||
}).forEach((word: any) => {
|
||||
const capital = /^[A-Z]/.test(word.text.trim());
|
||||
const length = word.offsets.to - word.offsets.from;
|
||||
const syllables = countSyllables(word.text.trim());
|
||||
const expected = syllables * cadence;
|
||||
if(capital && length > expected * 2 && word.text[0] == ' ') result += '.';
|
||||
result += word.text;
|
||||
});
|
||||
if(!llm) return result.trim();
|
||||
return this.ai.language.ask(result, {
|
||||
system: 'Remove any misplaced punctuation from the following ASR transcript using the replace tool. Avoid modifying words unless there is an obvious typo',
|
||||
temperature: 0.1,
|
||||
tools: [{
|
||||
name: 'replace',
|
||||
description: 'Use find and replace to fix errors',
|
||||
args: {
|
||||
find: {type: 'string', description: 'Text to find', required: true},
|
||||
replace: {type: 'string', description: 'Text to replace', required: true}
|
||||
},
|
||||
fn: (args) => result = result.replace(args.find, args.replace)
|
||||
}]
|
||||
}).then(() => result);
|
||||
}
|
||||
|
||||
private async diarizeTranscript(timestampData: any, speakers: any[], llm: boolean): Promise<string> {
|
||||
const speakerMap = new Map();
|
||||
let speakerCount = 0;
|
||||
speakers.forEach((seg: any) => {
|
||||
if(!speakerMap.has(seg.speaker)) speakerMap.set(seg.speaker, ++speakerCount);
|
||||
});
|
||||
|
||||
const punctuatedText = await this.addPunctuation(timestampData, llm);
|
||||
const sentences = punctuatedText.match(/[^.!?]+[.!?]+/g) || [punctuatedText];
|
||||
const words = timestampData.transcription.filter((w: any) => w.text.trim());
|
||||
|
||||
// Assign speaker to each sentence
|
||||
const sentencesWithSpeakers = sentences.map(sentence => {
|
||||
sentence = sentence.trim();
|
||||
if(!sentence) return null;
|
||||
|
||||
const sentenceWords = sentence.toLowerCase().replace(/[^\w\s]/g, '').split(/\s+/);
|
||||
const speakerWordCount = new Map<number, number>();
|
||||
|
||||
sentenceWords.forEach(sw => {
|
||||
const word = words.find((w: any) => sw === w.text.trim().toLowerCase().replace(/[^\w]/g, ''));
|
||||
if(!word) return;
|
||||
|
||||
const wordTime = word.offsets.from / 1000;
|
||||
const speaker = speakers.find((seg: any) => wordTime >= seg.start && wordTime <= seg.end);
|
||||
if(speaker) {
|
||||
const spkNum = speakerMap.get(speaker.speaker);
|
||||
speakerWordCount.set(spkNum, (speakerWordCount.get(spkNum) || 0) + 1);
|
||||
}
|
||||
});
|
||||
|
||||
let bestSpeaker = 1;
|
||||
let maxWords = 0;
|
||||
speakerWordCount.forEach((count, speaker) => {
|
||||
if(count > maxWords) {
|
||||
maxWords = count;
|
||||
bestSpeaker = speaker;
|
||||
}
|
||||
});
|
||||
|
||||
return {speaker: bestSpeaker, text: sentence};
|
||||
}).filter(s => s !== null);
|
||||
|
||||
// Merge adjacent sentences from same speaker
|
||||
const merged: Array<{speaker: number, text: string}> = [];
|
||||
sentencesWithSpeakers.forEach(item => {
|
||||
const last = merged[merged.length - 1];
|
||||
if(last && last.speaker === item.speaker) {
|
||||
last.text += ' ' + item.text;
|
||||
} else {
|
||||
merged.push({...item});
|
||||
}
|
||||
});
|
||||
|
||||
let transcript = merged.map(item => `[Speaker ${item.speaker}]: ${item.text}`).join('\n').trim();
|
||||
if(!llm) return transcript;
|
||||
let chunks = this.ai.language.chunk(transcript, 500, 0);
|
||||
if(chunks.length > 4) chunks = [...chunks.slice(0, 3), <string>chunks.at(-1)];
|
||||
const names = await this.ai.language.json(chunks.join('\n'), '{1: "Detected Name", 2: "Second Name"}', {
|
||||
system: 'Use the following transcript to identify speakers. Only identify speakers you are positive about, dont mention speakers you are unsure about in your response',
|
||||
temperature: 0.1,
|
||||
});
|
||||
Object.entries(names).forEach(([speaker, name]) => transcript = transcript.replaceAll(`[Speaker ${speaker}]`, `[${name}]`));
|
||||
return transcript;
|
||||
}
|
||||
|
||||
private runAsr(file: string, opts: {model?: string, diarization?: boolean} = {}): AbortablePromise<any> {
|
||||
let proc: any;
|
||||
const p = new Promise<any>((resolve, reject) => {
|
||||
this.downloadAsrModel(opts.model).then(m => {
|
||||
let output = '';
|
||||
const args = [opts.diarization ? '-owts' : '-nt', '-m', m, '-f', file];
|
||||
proc = spawn(<string>this.ai.options.whisper, args, {stdio: ['ignore', 'pipe', 'ignore']});
|
||||
proc.on('error', (err: Error) => reject(err));
|
||||
proc.stdout.on('data', (data: Buffer) => output += data.toString());
|
||||
proc.on('close', (code: number) => {
|
||||
if(code === 0) {
|
||||
if(opts.diarization) {
|
||||
let output = path.join(path.dirname(file), 'transcript');
|
||||
proc = spawn(<string>this.ai.options.whisper,
|
||||
['-m', m, '-f', file, '-np', '-ml', '1', '-oj', '-of', output],
|
||||
{stdio: ['ignore', 'ignore', 'pipe']}
|
||||
);
|
||||
proc.on('error', (err: Error) => reject(err));
|
||||
proc.on('close', async (code: number) => {
|
||||
if(code === 0) {
|
||||
output = await fs.readFile(output + '.json', 'utf-8');
|
||||
fs.rm(output + '.json').catch(() => { });
|
||||
try { resolve(JSON.parse(output)); }
|
||||
catch(e) { reject(new Error('Failed to parse whisper JSON')); }
|
||||
} else {
|
||||
resolve(output.trim() || null);
|
||||
}
|
||||
} else {
|
||||
reject(new Error(`Exit code ${code}`));
|
||||
}
|
||||
});
|
||||
} else {
|
||||
let output = '';
|
||||
proc = spawn(<string>this.ai.options.whisper, ['-m', m, '-f', file, '-np', '-nt']);
|
||||
proc.on('error', (err: Error) => reject(err));
|
||||
proc.stdout.on('data', (data: Buffer) => output += data.toString());
|
||||
proc.on('close', async (code: number) => {
|
||||
if(code === 0) {
|
||||
resolve(output.trim() || null);
|
||||
} else {
|
||||
reject(new Error(`Exit code ${code}`));
|
||||
}
|
||||
});
|
||||
}
|
||||
});
|
||||
});
|
||||
return <any>Object.assign(p, {abort: () => proc?.kill('SIGTERM')});
|
||||
@@ -64,7 +193,7 @@ print(json.dumps(segments))
|
||||
let aborted = false, abort = () => { aborted = true; };
|
||||
const checkPython = (cmd: string) => {
|
||||
return new Promise<boolean>((resolve) => {
|
||||
const proc = spawn(cmd, ['-c', 'import pyannote.audio']);
|
||||
const proc = spawn(cmd, ['-W', 'ignore', '-c', 'import pyannote.audio']);
|
||||
proc.on('close', (code: number) => resolve(code === 0));
|
||||
proc.on('error', () => resolve(false));
|
||||
});
|
||||
@@ -79,7 +208,7 @@ print(json.dumps(segments))
|
||||
return new Promise((resolve, reject) => {
|
||||
if(aborted) return;
|
||||
let output = '';
|
||||
const proc = spawn(binary, ['-c', this.pyannote, file]);
|
||||
const proc = spawn(binary, ['-W', 'ignore', '-c', this.pyannote, file]);
|
||||
proc.stdout.on('data', (data: Buffer) => output += data.toString());
|
||||
proc.stderr.on('data', (data: Buffer) => console.error(data.toString()));
|
||||
proc.on('close', (code: number) => {
|
||||
@@ -97,61 +226,28 @@ print(json.dumps(segments))
|
||||
return <any>Object.assign(p, {abort});
|
||||
}
|
||||
|
||||
private combineSpeakerTranscript(transcript: 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 = '';
|
||||
transcript.transcription.forEach((word: any) => {
|
||||
const time = word.offsets.from / 1000; // Convert ms to seconds
|
||||
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 = word.text;
|
||||
} else {
|
||||
currentText += ' ' + word.text;
|
||||
}
|
||||
});
|
||||
if(currentText) lines.push(`[Speaker ${currentSpeaker}]: ${currentText.trim()}`);
|
||||
return lines.join('\n');
|
||||
}
|
||||
|
||||
asr(file: string, options: { model?: string; diarization?: boolean | 'id' } = {}): AbortablePromise<string | null> {
|
||||
asr(file: string, options: { model?: string; diarization?: boolean | 'llm' } = {}): AbortablePromise<string | null> {
|
||||
if(!this.ai.options.whisper) throw new Error('Whisper not configured');
|
||||
|
||||
const tmp = join(mkdtempSync(join(tmpdir(), 'audio-')), 'converted.wav');
|
||||
execSync(`ffmpeg -i "${file}" -ar 16000 -ac 1 -f wav "${tmp}"`, { stdio: 'ignore' });
|
||||
const clean = () => rm(Path.dirname(tmp), { recursive: true, force: true }).catch(() => {});
|
||||
const transcript = this.runAsr(tmp, {model: options.model, diarization: !!options.diarization});
|
||||
const diarization: any = options.diarization ? this.runDiarization(tmp) : Promise.resolve(null);
|
||||
const clean = () => fs.rm(Path.dirname(tmp), {recursive: true, force: true}).catch(() => {});
|
||||
|
||||
if(!options.diarization) return this.runAsr(tmp, {model: options.model});
|
||||
const timestamps = this.runAsr(tmp, {model: options.model, diarization: true});
|
||||
const diarization = this.runDiarization(tmp);
|
||||
let aborted = false, abort = () => {
|
||||
aborted = true;
|
||||
transcript.abort();
|
||||
diarization?.abort?.();
|
||||
timestamps.abort();
|
||||
diarization.abort();
|
||||
clean();
|
||||
};
|
||||
|
||||
const response = Promise.all([transcript, diarization]).then(async ([t, d]) => {
|
||||
if(aborted || !options.diarization) return t;
|
||||
t = this.combineSpeakerTranscript(t, d);
|
||||
if(!aborted && options.diarization === 'id') {
|
||||
if(!this.ai.language.defaultModel) throw new Error('Configure an LLM for advanced ASR speaker detection');
|
||||
let chunks = this.ai.language.chunk(t, 500, 0);
|
||||
if(chunks.length > 4) chunks = [...chunks.slice(0, 3), <string>chunks.at(-1)];
|
||||
const names = await this.ai.language.json(chunks.join('\n'), '{1: "Detected Name", 2: "Second Name"}', {
|
||||
system: 'Use the following transcript to identify speakers. Only identify speakers you are positive about, dont mention speakers you are unsure about in your response',
|
||||
temperature: 0.1,
|
||||
});
|
||||
Object.entries(names).forEach(([speaker, name]) => t = t.replaceAll(`[Speaker ${speaker}]`, `[${name}]`));
|
||||
}
|
||||
return t;
|
||||
const response = Promise.allSettled([timestamps, diarization]).then(async ([ts, d]) => {
|
||||
if(ts.status == 'rejected') throw new Error('Whisper.cpp timestamps:\n' + ts.reason);
|
||||
if(d.status == 'rejected') throw new Error('Pyannote:\n' + d.reason);
|
||||
if(aborted || !options.diarization) return ts.value;
|
||||
return this.diarizeTranscript(ts.value, d.value, options.diarization == 'llm');
|
||||
}).finally(() => clean());
|
||||
return <any>Object.assign(response, {abort});
|
||||
}
|
||||
|
||||
24
src/llm.ts
24
src/llm.ts
@@ -145,7 +145,7 @@ class LLM {
|
||||
|
||||
// Handle compression and memory extraction
|
||||
if(options.compress || options.memory) {
|
||||
let compressed = null;
|
||||
let compressed: any = null;
|
||||
if(options.compress) {
|
||||
compressed = await this.ai.language.compressHistory(options.history, options.compress.max, options.compress.min, options);
|
||||
options.history.splice(0, options.history.length, ...compressed.history);
|
||||
@@ -164,6 +164,15 @@ class LLM {
|
||||
}), {abort});
|
||||
}
|
||||
|
||||
async code(message: string, options?: LLMRequest): Promise<any> {
|
||||
const resp = await this.ask(message, {...options, system: [
|
||||
options?.system,
|
||||
'Return your response in a code block'
|
||||
].filter(t => !!t).join(('\n'))});
|
||||
const codeBlock = /```(?:.+)?\s*([\s\S]*?)```/.exec(resp);
|
||||
return codeBlock ? codeBlock[1].trim() : null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Compress chat history to reduce context size
|
||||
* @param {LLMMessage[]} history Chatlog that will be compressed
|
||||
@@ -343,14 +352,11 @@ class LLM {
|
||||
* @returns {Promise<{} | {} | RegExpExecArray | null>}
|
||||
*/
|
||||
async json(text: string, schema: string, options?: LLMRequest): Promise<any> {
|
||||
let resp = await this.ask(text, {...options, system: (options?.system ? `${options.system}\n` : '') + `Only respond using a JSON code block matching this schema:
|
||||
\`\`\`json
|
||||
${schema}
|
||||
\`\`\``});
|
||||
if(!resp) return {};
|
||||
const codeBlock = /```(?:.+)?\s*([\s\S]*?)```/.exec(resp);
|
||||
const jsonStr = codeBlock ? codeBlock[1].trim() : resp;
|
||||
return JSONAttemptParse(jsonStr, {});
|
||||
const code = await this.code(text, {...options, system: [
|
||||
options?.system,
|
||||
`Only respond using JSON matching this schema:\n\`\`\`json\n${schema}\n\`\`\``
|
||||
].filter(t => !!t).join('\n')});
|
||||
return code ? JSONAttemptParse(code, {}) : null;
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@@ -15,6 +15,7 @@
|
||||
"noEmit": true,
|
||||
|
||||
/* Linting */
|
||||
"strict": true
|
||||
"strict": true,
|
||||
"noImplicitAny": false
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user