apps/peertube-runner/src/server/process/shared/process-transcription.ts
import { hasAudioStream } from '@peertube/peertube-ffmpeg'
import { RunnerJobTranscriptionPayload, TranscriptionSuccess } from '@peertube/peertube-models'
import { buildSUUID } from '@peertube/peertube-node-utils'
import { TranscriptionModel, WhisperBuiltinModel, transcriberFactory } from '@peertube/peertube-transcription'
import { remove } from 'fs-extra/esm'
import { join } from 'path'
import { ConfigManager } from '../../../shared/config-manager.js'
import { logger } from '../../../shared/index.js'
import { ProcessOptions, downloadInputFile, scheduleTranscodingProgress } from './common.js'
import { getWinstonLogger } from './winston-logger.js'
export async function processVideoTranscription (options: ProcessOptions<RunnerJobTranscriptionPayload>) {
const { server, job, runnerToken } = options
const config = ConfigManager.Instance.getConfig().transcription
const payload = job.payload
let inputPath: string
const updateProgressInterval = scheduleTranscodingProgress({
job,
server,
runnerToken,
progressGetter: () => undefined
})
const outputPath = join(ConfigManager.Instance.getTranscriptionDirectory(), buildSUUID())
const transcriber = transcriberFactory.createFromEngineName({
engineName: config.engine,
enginePath: config.enginePath,
logger: getWinstonLogger()
})
try {
logger.info(`Downloading input file ${payload.input.videoFileUrl} for transcription job ${job.jobToken}`)
inputPath = await downloadInputFile({ url: payload.input.videoFileUrl, runnerToken, job })
logger.info(`Downloaded input file ${payload.input.videoFileUrl} for job ${job.jobToken}. Running transcription.`)
if (await hasAudioStream(inputPath) !== true) {
await server.runnerJobs.error({
jobToken: job.jobToken,
jobUUID: job.uuid,
runnerToken,
message: 'This input file does not contain audio'
})
return
}
const transcriptFile = await transcriber.transcribe({
mediaFilePath: inputPath,
model: config.modelPath
? await TranscriptionModel.fromPath(config.modelPath)
: new WhisperBuiltinModel(config.model),
format: 'vtt',
transcriptDirectory: outputPath
})
const successBody: TranscriptionSuccess = {
inputLanguage: transcriptFile.language,
vttFile: transcriptFile.path
}
await server.runnerJobs.success({
jobToken: job.jobToken,
jobUUID: job.uuid,
runnerToken,
payload: successBody
})
} finally {
if (inputPath) await remove(inputPath)
if (outputPath) await remove(outputPath)
if (updateProgressInterval) clearInterval(updateProgressInterval)
}
}