feat: certificates, landing pages, ai tutor, website update, compliance
This commit is contained in:
Rotimi Best
@@ -0,0 +1,254 @@
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import { stat } from 'node:fs/promises';
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import { getJobStep, getMediaJobById, updateMediaJob, upsertJobStep, upsertMediaTranscript } from '@cio/db/queries';
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import { ZTranscribeAudioPayload, type TTranscribeAudioPayload } from '@cio/jobs/payloads/media';
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import { env } from '../../config/env';
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import {
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AudioFileTooLargeError,
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WHISPER_MAX_FILE_BYTES,
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transcribeAudioFile,
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type TranscriptionSegment
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} from '../../services/transcription/openai';
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import { segmentsToWebVtt } from '../../services/transcription/vtt';
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import { downloadObjectToTempFile, mediaBucket, safeUnlink, uploadBufferToBucket } from '../../utils/storage';
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import { errorMessage, throwIfCancelRequested } from '../../utils/cancel';
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import { log } from '../../utils/logger';
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const STEP_KEY = 'transcribe-audio';
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const DOMAIN = 'media';
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const EXTRACT_STEP_KEY = 'extract-audio';
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interface TranscribeResult {
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provider: 'openai' | 'assemblyai' | 'deepgram' | 'skipped';
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text: string;
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language?: string;
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durationSeconds?: number;
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costCents?: number;
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}
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function transcriptionCostCents(durationSeconds: number): number {
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return Math.ceil((durationSeconds / 60) * 0.6);
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}
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async function mergeJobWarnings(mediaJobId: string, extra: string[]): Promise<void> {
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const job = await getMediaJobById(mediaJobId);
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const prior = job?.warnings ?? [];
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await updateMediaJob(mediaJobId, { warnings: [...prior, ...extra] });
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}
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/**
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* OpenAI Whisper (`whisper-1`) with verbose segment timestamps; persists VTT +
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* `media_transcript` row. Skips cleanly when `OPENAI_API_KEY` is unset or when
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* extracted audio exceeds the 25 MB API limit.
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*/
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export async function processTranscribeAudio(rawData: unknown): Promise<TranscribeResult> {
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const payload: TTranscribeAudioPayload = ZTranscribeAudioPayload.parse(rawData);
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const { mediaJobId, assetId, actorContext } = payload;
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const existing = await getJobStep(DOMAIN, mediaJobId, STEP_KEY);
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if (existing?.status === 'completed' && existing.result) {
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log.info('transcribe-audio-skip', { mediaJobId, reason: 'ledger-completed' });
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return existing.result as unknown as TranscribeResult;
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}
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await throwIfCancelRequested(mediaJobId);
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await updateMediaJob(mediaJobId, { stage: 'transcribing', progressPercent: 90 });
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'running',
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startedAt: new Date().toISOString(),
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attempt: (existing?.attempt ?? 0) + 1
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});
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try {
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if (!env.OPENAI_API_KEY) {
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const result: TranscribeResult = { provider: 'skipped', text: '' };
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'completed',
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finishedAt: new Date().toISOString(),
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result: result as unknown as Record<string, unknown>
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});
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await mergeJobWarnings(mediaJobId, ['transcription-skipped-no-openai-key']);
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await updateMediaJob(mediaJobId, {
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status: 'completed',
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stage: 'done',
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progressPercent: 100
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});
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log.info('transcribe-audio-skipped', { mediaJobId, reason: 'no-openai-key' });
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return result;
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}
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const extractStep = await getJobStep(DOMAIN, mediaJobId, EXTRACT_STEP_KEY);
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const extractResult = extractStep?.result as { bucket?: string; key?: string; fileSizeBytes?: number } | null;
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if (!extractResult?.bucket || !extractResult?.key) {
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const message = 'extract-audio step missing or incomplete';
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log.error('transcribe-audio-failed', { mediaJobId, error: message });
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'failed',
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finishedAt: new Date().toISOString(),
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error: { code: 'EXTRACT_AUDIO_MISSING', message }
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});
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throw new Error(message);
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}
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let localPath: string | undefined;
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try {
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localPath = await downloadObjectToTempFile(extractResult.bucket, extractResult.key, 'whisper-input.mp3');
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const localStat = await stat(localPath);
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if (localStat.size > WHISPER_MAX_FILE_BYTES) {
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'failed',
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finishedAt: new Date().toISOString(),
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error: {
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code: 'AUDIO_TOO_LARGE',
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message: `Audio ${localStat.size} bytes exceeds ${WHISPER_MAX_FILE_BYTES}`
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}
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});
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await mergeJobWarnings(mediaJobId, ['transcription-skipped-audio-too-large']);
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await updateMediaJob(mediaJobId, {
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status: 'completed',
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stage: 'done',
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progressPercent: 100
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});
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log.warn('transcribe-audio-skipped-audio-too-large', { mediaJobId, fileSizeBytes: localStat.size });
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return { provider: 'skipped', text: '' };
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}
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await throwIfCancelRequested(mediaJobId);
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const whisper = await transcribeAudioFile({
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apiKey: env.OPENAI_API_KEY,
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localPath
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});
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const normalizedSegments: TranscriptionSegment[] = whisper.segments.map((segment) => ({
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start: segment.start,
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end: segment.end,
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text: segment.text
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}));
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const vttBody = segmentsToWebVtt(normalizedSegments);
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const vttKey = `transcripts/${assetId}/${mediaJobId}.vtt`;
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const bucket = mediaBucket();
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await uploadBufferToBucket(
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bucket,
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vttKey,
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Buffer.from(vttBody, 'utf8'),
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'text/vtt; charset=utf-8',
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'private, max-age=0'
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);
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const transcriptCost = transcriptionCostCents(whisper.durationSeconds);
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const jobRow = await getMediaJobById(mediaJobId);
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const priorCost = jobRow?.costCents ?? 0;
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await upsertMediaTranscript({
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organizationId: actorContext.organizationId,
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assetId,
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mediaJobId,
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language: whisper.language,
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provider: 'openai',
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model: 'whisper-1',
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text:
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whisper.fullText ||
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normalizedSegments
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.map((segment) => segment.text)
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.join(' ')
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.trim(),
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segments: normalizedSegments,
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vttStorageKey: vttKey,
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vttBucket: bucket,
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durationSeconds: Math.round(whisper.durationSeconds),
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costCents: transcriptCost
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});
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const result: TranscribeResult = {
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provider: 'openai',
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text: whisper.fullText,
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language: whisper.language,
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durationSeconds: whisper.durationSeconds,
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costCents: transcriptCost
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};
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'completed',
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finishedAt: new Date().toISOString(),
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result: {
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language: whisper.language,
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segmentCount: normalizedSegments.length,
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vttKey,
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costCents: transcriptCost
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} as Record<string, unknown>,
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providerId: null
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});
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await updateMediaJob(mediaJobId, {
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status: 'completed',
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stage: 'done',
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progressPercent: 100,
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costCents: priorCost + transcriptCost
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});
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log.info('transcribe-audio-done', {
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mediaJobId,
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language: whisper.language,
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segmentCount: normalizedSegments.length
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});
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return result;
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} catch (error) {
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if (error instanceof AudioFileTooLargeError) {
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'failed',
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finishedAt: new Date().toISOString(),
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error: { code: 'AUDIO_TOO_LARGE', message: error.message }
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});
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await mergeJobWarnings(mediaJobId, ['transcription-skipped-audio-too-large']);
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await updateMediaJob(mediaJobId, {
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status: 'completed',
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stage: 'done',
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progressPercent: 100
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});
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log.warn('transcribe-audio-skipped-audio-too-large', { mediaJobId, fileSizeBytes: error.fileSizeBytes });
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return { provider: 'skipped', text: '' };
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}
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throw error;
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} finally {
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await safeUnlink(localPath);
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}
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} catch (error) {
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log.error('transcribe-audio-failed', { mediaJobId, error: errorMessage(error) });
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await upsertJobStep({
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domain: DOMAIN,
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runId: mediaJobId,
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stepKey: STEP_KEY,
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status: 'failed',
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finishedAt: new Date().toISOString(),
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error: { code: 'TRANSCRIBE_FAILED', message: errorMessage(error) }
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});
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throw error;
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}
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}
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