anything-llm/collector/processSingleFile/convert/asAudio.js

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const fs = require("fs");
const path = require("path");
const { v4 } = require("uuid");
const {
createdDate,
trashFile,
writeToServerDocuments,
} = require("../../utils/files");
const { tokenizeString } = require("../../utils/tokenizer");
const { default: slugify } = require("slugify");
const { LocalWhisper } = require("../../utils/WhisperProviders/localWhisper");
async function asAudio({ fullFilePath = "", filename = "" }) {
const whisper = new LocalWhisper();
console.log(`-- Working ${filename} --`);
const transcriberPromise = new Promise((resolve) =>
whisper.client().then((client) => resolve(client))
);
const audioDataPromise = new Promise((resolve) =>
convertToWavAudioData(fullFilePath).then((audioData) => resolve(audioData))
);
const [audioData, transcriber] = await Promise.all([
audioDataPromise,
transcriberPromise,
]);
if (!audioData) {
console.error(`Failed to parse content from ${filename}.`);
trashFile(fullFilePath);
return {
success: false,
reason: `Failed to parse content from ${filename}.`,
};
}
console.log(`[Model Working]: Transcribing audio data to text`);
const { text: content } = await transcriber(audioData, {
chunk_length_s: 30,
stride_length_s: 5,
});
if (!content.length) {
console.error(`Resulting text content was empty for ${filename}.`);
trashFile(fullFilePath);
return { success: false, reason: `No text content found in ${filename}.` };
}
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const data = {
id: v4(),
url: "file://" + fullFilePath,
title: filename,
docAuthor: "no author found",
description: "No description found.",
docSource: "pdf file uploaded by the user.",
chunkSource: filename,
published: createdDate(fullFilePath),
wordCount: content.split(" ").length,
pageContent: content,
token_count_estimate: tokenizeString(content).length,
};
writeToServerDocuments(data, `${slugify(filename)}-${data.id}`);
trashFile(fullFilePath);
console.log(
`[SUCCESS]: ${filename} transcribed, converted & ready for embedding.\n`
);
return { success: true, reason: null };
}
async function convertToWavAudioData(sourcePath) {
try {
let buffer;
const wavefile = require("wavefile");
const ffmpeg = require("fluent-ffmpeg");
const outFolder = path.resolve(__dirname, `../../storage/tmp`);
if (!fs.existsSync(outFolder)) fs.mkdirSync(outFolder, { recursive: true });
const fileExtension = path.extname(sourcePath).toLowerCase();
if (fileExtension !== ".wav") {
console.log(
`[Conversion Required] ${fileExtension} file detected - converting to .wav`
);
const outputFile = path.resolve(outFolder, `${v4()}.wav`);
const convert = new Promise((resolve) => {
ffmpeg(sourcePath)
.toFormat("wav")
.on("error", (error) => {
console.error(`[Conversion Error] ${error.message}`);
resolve(false);
})
.on("progress", (progress) =>
console.log(
`[Conversion Processing]: ${progress.targetSize}KB converted`
)
)
.on("end", () => {
console.log("[Conversion Complete]: File converted to .wav!");
resolve(true);
})
.save(outputFile);
});
const success = await convert;
if (!success)
throw new Error(
"[Conversion Failed]: Could not convert file to .wav format!"
);
const chunks = [];
const stream = fs.createReadStream(outputFile);
for await (let chunk of stream) chunks.push(chunk);
buffer = Buffer.concat(chunks);
fs.rmSync(outputFile);
} else {
const chunks = [];
const stream = fs.createReadStream(sourcePath);
for await (let chunk of stream) chunks.push(chunk);
buffer = Buffer.concat(chunks);
}
const wavFile = new wavefile.WaveFile(buffer);
wavFile.toBitDepth("32f");
wavFile.toSampleRate(16000);
let audioData = wavFile.getSamples();
if (Array.isArray(audioData)) {
if (audioData.length > 1) {
const SCALING_FACTOR = Math.sqrt(2);
// Merge channels into first channel to save memory
for (let i = 0; i < audioData[0].length; ++i) {
audioData[0][i] =
(SCALING_FACTOR * (audioData[0][i] + audioData[1][i])) / 2;
}
}
audioData = audioData[0];
}
return audioData;
} catch (error) {
console.error(`convertToWavAudioData`, error);
return null;
}
}
module.exports = asAudio;