mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-14 02:20:12 +01:00
0ada882991
* Support External Transcription providers * patch files * update docs * fix return data
178 lines
5.4 KiB
JavaScript
178 lines
5.4 KiB
JavaScript
const fs = require("fs");
|
|
const path = require("path");
|
|
const { v4 } = require("uuid");
|
|
|
|
class LocalWhisper {
|
|
constructor() {
|
|
// Model Card: https://huggingface.co/Xenova/whisper-small
|
|
this.model = "Xenova/whisper-small";
|
|
this.cacheDir = path.resolve(
|
|
process.env.STORAGE_DIR
|
|
? path.resolve(process.env.STORAGE_DIR, `models`)
|
|
: path.resolve(__dirname, `../../../server/storage/models`)
|
|
);
|
|
|
|
this.modelPath = path.resolve(this.cacheDir, "Xenova", "whisper-small");
|
|
|
|
// Make directory when it does not exist in existing installations
|
|
if (!fs.existsSync(this.cacheDir))
|
|
fs.mkdirSync(this.cacheDir, { recursive: true });
|
|
|
|
this.#log("Initialized.");
|
|
}
|
|
|
|
#log(text, ...args) {
|
|
console.log(`\x1b[32m[LocalWhisper]\x1b[0m ${text}`, ...args);
|
|
}
|
|
|
|
async #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") {
|
|
this.#log(
|
|
`File 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) => {
|
|
this.#log(`Conversion Error! ${error.message}`);
|
|
resolve(false);
|
|
})
|
|
.on("progress", (progress) =>
|
|
this.#log(
|
|
`Conversion Processing! ${progress.targetSize}KB converted`
|
|
)
|
|
)
|
|
.on("end", () => {
|
|
this.#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;
|
|
}
|
|
}
|
|
|
|
async client() {
|
|
if (!fs.existsSync(this.modelPath)) {
|
|
this.#log(
|
|
`The native whisper model has never been run and will be downloaded right now. Subsequent runs will be faster. (~250MB)`
|
|
);
|
|
}
|
|
|
|
try {
|
|
// Convert ESM to CommonJS via import so we can load this library.
|
|
const pipeline = (...args) =>
|
|
import("@xenova/transformers").then(({ pipeline }) =>
|
|
pipeline(...args)
|
|
);
|
|
return await pipeline("automatic-speech-recognition", this.model, {
|
|
cache_dir: this.cacheDir,
|
|
...(!fs.existsSync(this.modelPath)
|
|
? {
|
|
// Show download progress if we need to download any files
|
|
progress_callback: (data) => {
|
|
if (!data.hasOwnProperty("progress")) return;
|
|
console.log(
|
|
`\x1b[34m[Embedding - Downloading Model Files]\x1b[0m ${
|
|
data.file
|
|
} ${~~data?.progress}%`
|
|
);
|
|
},
|
|
}
|
|
: {}),
|
|
});
|
|
} catch (error) {
|
|
this.#log("Failed to load the native whisper model:", error);
|
|
throw error;
|
|
}
|
|
}
|
|
|
|
async processFile(fullFilePath, filename) {
|
|
try {
|
|
const transcriberPromise = new Promise((resolve) =>
|
|
this.client().then((client) => resolve(client))
|
|
);
|
|
const audioDataPromise = new Promise((resolve) =>
|
|
this.#convertToWavAudioData(fullFilePath).then((audioData) =>
|
|
resolve(audioData)
|
|
)
|
|
);
|
|
const [audioData, transcriber] = await Promise.all([
|
|
audioDataPromise,
|
|
transcriberPromise,
|
|
]);
|
|
|
|
if (!audioData) {
|
|
this.#log(`Failed to parse content from ${filename}.`);
|
|
return {
|
|
content: null,
|
|
error: `Failed to parse content from ${filename}.`,
|
|
};
|
|
}
|
|
|
|
this.#log(`Transcribing audio data to text...`);
|
|
const { text } = await transcriber(audioData, {
|
|
chunk_length_s: 30,
|
|
stride_length_s: 5,
|
|
});
|
|
|
|
return { content: text, error: null };
|
|
} catch (error) {
|
|
return { content: null, error: error.message };
|
|
}
|
|
}
|
|
}
|
|
|
|
module.exports = {
|
|
LocalWhisper,
|
|
};
|