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| 1 | +/** |
| 2 | + * Example provided by https://github.com/Gan-Xing in https://github.com/fedirz/faster-whisper-server/issues/26 |
| 3 | + */ |
| 4 | +import fs from 'fs'; |
| 5 | +import WebSocket from 'ws'; |
| 6 | +import fetch from 'node-fetch'; |
| 7 | +import FormData from 'form-data'; |
| 8 | +import path from 'path'; |
| 9 | +import ffmpeg from 'fluent-ffmpeg'; |
| 10 | +import dotenv from 'dotenv'; |
| 11 | + |
| 12 | +dotenv.config(); |
| 13 | + |
| 14 | +const ffmpegPath = process.env.FFMPEG_PATH || '/usr/bin/ffmpeg'; |
| 15 | +ffmpeg.setFfmpegPath(ffmpegPath); |
| 16 | + |
| 17 | +/** |
| 18 | + * Transcribe an audio file using the HTTP endpoint. |
| 19 | + * Supported file types include wav, mp3, webm, and other types supported by the OpenAI API. |
| 20 | + * I have tested with these three types. |
| 21 | + * |
| 22 | + * @param {string} filePath - Path to the audio file |
| 23 | + * @param {string} model - Model name |
| 24 | + * @param {string} language - Language code |
| 25 | + * @param {string} responseFormat - Response format |
| 26 | + * @param {string} temperature - Temperature setting |
| 27 | + */ |
| 28 | +async function transcribeFile(filePath, model, language, responseFormat, temperature) { |
| 29 | + const formData = new FormData(); |
| 30 | + formData.append('file', fs.createReadStream(filePath)); |
| 31 | + formData.append('model', model); |
| 32 | + formData.append('language', language); |
| 33 | + formData.append('response_format', responseFormat); |
| 34 | + formData.append('temperature', temperature); |
| 35 | + |
| 36 | + const response = await fetch(`${process.env.TRANSCRIPTION_API_BASE_URL}/v1/audio/transcriptions`, { |
| 37 | + method: 'POST', |
| 38 | + body: formData, |
| 39 | + }); |
| 40 | + |
| 41 | + const transcription = await response.json(); |
| 42 | + console.log('Transcription Response:', transcription); |
| 43 | +} |
| 44 | + |
| 45 | +/** |
| 46 | + * Translate an audio file using the HTTP endpoint. |
| 47 | + * Only English is supported for translation. |
| 48 | + * Currently, I am using GLM-4-9b-int8 to translate various voices. |
| 49 | + * I am not sure if the author can add an endpoint for custom API+Key translation. |
| 50 | + * I plan to package my frontend, fast-whisper-server, and vllm+glm-4-9b-int8 into one Docker container for unified deployment. |
| 51 | + * |
| 52 | + * @param {string} filePath - Path to the audio file |
| 53 | + * @param {string} model - Model name |
| 54 | + * @param {string} responseFormat - Response format |
| 55 | + * @param {string} temperature - Temperature setting |
| 56 | + */ |
| 57 | +async function translateFile(filePath, model, responseFormat, temperature) { |
| 58 | + const formData = new FormData(); |
| 59 | + formData.append('file', fs.createReadStream(filePath)); |
| 60 | + formData.append('model', model); |
| 61 | + formData.append('response_format', responseFormat); |
| 62 | + formData.append('temperature', temperature); |
| 63 | + |
| 64 | + const response = await fetch(`${process.env.TRANSLATION_API_BASE_URL}/v1/audio/translations`, { |
| 65 | + method: 'POST', |
| 66 | + body: formData, |
| 67 | + }); |
| 68 | + |
| 69 | + const translation = await response.json(); |
| 70 | + console.log('Translation Response:', translation); |
| 71 | +} |
| 72 | + |
| 73 | +/** |
| 74 | + * Send audio data over WebSocket for transcription. |
| 75 | + * Currently, the supported file type for transcription is PCM. |
| 76 | + * I am not sure if other types are supported. |
| 77 | + * |
| 78 | + * @param {string} filePath - Path to the audio file |
| 79 | + * @param {string} model - Model name |
| 80 | + * @param {string} language - Language code |
| 81 | + * @param {string} responseFormat - Response format |
| 82 | + * @param {string} temperature - Temperature setting |
| 83 | + */ |
| 84 | +async function sendAudioOverWebSocket(filePath, model, language, responseFormat, temperature) { |
| 85 | + const wsUrl = `ws://100.105.162.69:8000/v1/audio/transcriptions?model=${encodeURIComponent(model)}&language=${encodeURIComponent(language)}&response_format=${encodeURIComponent(responseFormat)}&temperature=${encodeURIComponent(temperature)}`; |
| 86 | + const ws = new WebSocket(wsUrl); |
| 87 | + |
| 88 | + ws.on('open', async () => { |
| 89 | + const audioBuffer = fs.readFileSync(filePath); |
| 90 | + ws.send(audioBuffer); |
| 91 | + }); |
| 92 | + |
| 93 | + ws.on('message', (message) => { |
| 94 | + const response = JSON.parse(message); |
| 95 | + console.log('WebSocket Response:', response); |
| 96 | + }); |
| 97 | + |
| 98 | + ws.on('close', () => { |
| 99 | + console.log('WebSocket connection closed'); |
| 100 | + }); |
| 101 | + |
| 102 | + ws.on('error', (error) => { |
| 103 | + console.error('WebSocket error:', error); |
| 104 | + }); |
| 105 | +} |
| 106 | + |
| 107 | +/** |
| 108 | + * Convert audio file to PCM format. |
| 109 | + * |
| 110 | + * @param {string} filePath - Path to the audio file |
| 111 | + * @returns {string} - Path to the converted PCM file |
| 112 | + */ |
| 113 | +async function convertToPcm(filePath) { |
| 114 | + const pcmFilePath = filePath.replace(path.extname(filePath), '.pcm'); |
| 115 | + |
| 116 | + await new Promise((resolve, reject) => { |
| 117 | + ffmpeg(filePath) |
| 118 | + .audioChannels(1) |
| 119 | + .audioFrequency(16000) |
| 120 | + .audioCodec('pcm_s16le') |
| 121 | + .toFormat('s16le') |
| 122 | + .on('end', () => { |
| 123 | + console.log(`Audio file successfully converted to PCM: ${pcmFilePath}`); |
| 124 | + resolve(pcmFilePath); |
| 125 | + }) |
| 126 | + .on('error', (error) => { |
| 127 | + console.error(`Error converting audio to PCM: ${error.message}`); |
| 128 | + reject(error); |
| 129 | + }) |
| 130 | + .save(pcmFilePath); |
| 131 | + }); |
| 132 | + |
| 133 | + return pcmFilePath; |
| 134 | +} |
| 135 | + |
| 136 | +async function main() { |
| 137 | + const model = 'Systran/faster-whisper-large-v3'; |
| 138 | + const language = 'en'; |
| 139 | + const responseFormat = 'json'; |
| 140 | + const temperature = '0'; |
| 141 | + const filePath = './path/to/your/audio.webm'; // Replace with the actual file path |
| 142 | + |
| 143 | + // Convert the audio file to PCM format |
| 144 | + const pcmFilePath = await convertToPcm(filePath); |
| 145 | + |
| 146 | + // Transcribe the audio file using the HTTP endpoint |
| 147 | + await transcribeFile(pcmFilePath, model, language, responseFormat, temperature); |
| 148 | + |
| 149 | + // Translate the audio file using the HTTP endpoint |
| 150 | + await translateFile(pcmFilePath, model, responseFormat, temperature); |
| 151 | + |
| 152 | + // Transcribe the audio file using the WebSocket endpoint |
| 153 | + await sendAudioOverWebSocket(pcmFilePath, model, language, responseFormat, temperature); |
| 154 | +} |
| 155 | + |
| 156 | +// Make sure to use ffmpeg version 7 or above. The default apt-get install only installs version 4.x. Also, Ubuntu 22.04 or above is required to support version 7.x. |
| 157 | +main().catch(console.error); |
| 158 | + |
| 159 | +// Project URL: https://github.com/Gan-Xing/whisper |
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