- backend/coach: routing zu Sonnet (default) / Haiku / Groq Llama je nach sessionData.llmProvider. sort:latency für Anthropic-Modelle (-30..58% TTFB). - frontend: LlmProviderToggle (Sonnet/Haiku/Groq pills), llmProvider.ts Storage-Helper. sosStream.ts schickt llmProvider im /sos-session-Body. - bench: SosTtsBenchmark sammelt Marker (req->session, lyra-ttfb, lyra-done, tts-fired/headers/body/file, audio-loaded, first-audio); Output als console.table. - ops: backend/scripts/llm-bench.sh + Python-Variante für realistic SOS-Prompt. - speak-cartesia + speak-elevenlabs Endpoints (waren ungetracked, jetzt mit drin).
96 lines
3.0 KiB
TypeScript
96 lines
3.0 KiB
TypeScript
/**
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* POST /api/coach/speak-elevenlabs
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* ElevenLabs eleven_multilingual_v2 — voice via runtimeConfig.elevenlabsVoiceId
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* (default: Alexandra `kdmDKE6EkgrWrrykO9Qt` als Fallback wenn unset).
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*
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* Returns audio/mpeg. Voice ist deterministisch konstant über mehrere Calls
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* — identisch zu Gemini-Verhalten, kein Mode-Switch wie bei gpt-4o-mini-tts.
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*/
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const FALLBACK_VOICE_ID = "kdmDKE6EkgrWrrykO9Qt"; // Alexandra
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export default defineEventHandler(async (event) => {
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await requireUser(event);
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const body = await readBody(event);
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const { text } = body as { text: string };
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if (!text?.trim()) {
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throw createError({ statusCode: 400, message: "text fehlt" });
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}
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const config = useRuntimeConfig();
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// Fallback chain: runtimeConfig (Nuxt build-time) → process.env (runtime injection
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// via Infisical at pm2-start). Stellt sicher dass auch dann ein Key vorhanden ist
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// wenn nuxt's runtimeConfig-Inflate den process.env-Wert nicht mit-bundelt.
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const key =
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(config.elevenlabsApiKey as string) || process.env.ELEVENLABS_API_KEY || "";
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const voiceId =
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(config.elevenlabsVoiceId as string) ||
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process.env.ELEVENLABS_VOICE_ID ||
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FALLBACK_VOICE_ID;
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console.log(
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"[speak-elevenlabs] cfg-key:",
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!!config.elevenlabsApiKey,
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"env-key:",
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!!process.env.ELEVENLABS_API_KEY,
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"key-len:",
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key.length,
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"voice:",
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voiceId,
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);
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if (!key) {
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throw createError({
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statusCode: 503,
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message: "ELEVENLABS_API_KEY nicht konfiguriert",
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});
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}
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console.log("[speak-elevenlabs] CALL recv, text-len=", text?.length ?? 0, "voice=", voiceId);
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// /stream endpoint + optimize_streaming_latency=4 (max-latency-optimized,
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// marginal weniger Quality). ElevenLabs sendet erste Bytes ~200-300ms statt
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// 600-1000ms beim non-stream endpoint.
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const upstream = await fetch(
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`https://api.elevenlabs.io/v1/text-to-speech/${voiceId}/stream?optimize_streaming_latency=4`,
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{
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method: "POST",
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headers: {
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"xi-api-key": key,
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"Content-Type": "application/json",
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Accept: "audio/mpeg",
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},
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body: JSON.stringify({
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text: text.slice(0, 4096),
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// Turbo v2.5: ~50% schneller als multilingual_v2, marginal niedrigere
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// Quality — Trade-off lohnt sich für SOS (latency > Studio-Polish).
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model_id: "eleven_turbo_v2_5",
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voice_settings: {
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stability: 0.5,
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similarity_boost: 0.75,
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style: 0.3,
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use_speaker_boost: true,
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},
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output_format: "mp3_22050_32",
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}),
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},
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);
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if (!upstream.ok || !upstream.body) {
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const err = await upstream.text().catch(() => "");
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console.error("[speak-elevenlabs] error:", upstream.status, err);
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throw createError({
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statusCode: 502,
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message: "ElevenLabs TTS fehlgeschlagen",
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});
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}
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setHeader(event, "Content-Type", "audio/mpeg");
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setHeader(event, "Cache-Control", "no-store");
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const { Readable } = await import("node:stream");
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const nodeStream = Readable.fromWeb(upstream.body as never);
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return sendStream(event, nodeStream);
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});
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