Web-UI / TTS:
- Geräte-TTS ("📱 Gerät"): Antwort wird on-device vorgelesen (Web Speech
API), Server sendet nur Text (text_only) -> spart Bandbreite/Kosten.
Mobil-Default, geräte-lokale Speicherung, iOS-Autoplay-Freischaltung.
- Vorlese-Symbol (🔊) je Bubble: Hybrid-Replay (Assistent-PCM gecacht,
Eingabe via /api/speak); SVG-Icon mit kontrastreicher Farbe.
- Kombiniertes Sprachmenü (Flex + feste Sprachen) statt separatem Modus-Menü.
- "Neues Gespräch"-Button (frische Session gegen Sprach-Trägheit).
- Dark-Mode: lesbare <option>-Popups (Kontrast-Fix).
- Favicon (SVG + PNG-Fallbacks) aus mund.png.
TTS-Backend:
- Sprache wird an alle TTS-Provider durchgereicht; Piper-Stimme folgt der
Sprache; Chatterbox mehrsprachig + cross-lingual.
- Native Referenz-Stimmen je Sprache (config/voices/<lang>.wav, FLEURS CC-BY),
loudness-normalisiert.
LLM-Sprache:
- Antwort folgt zuverlässig der gewählten Sprache (verstärkte Anweisung +
Erinnerung an der letzten Nutzer-Nachricht gegen History-Trägheit).
Admin / Auth:
- Wörterbuch: alle 8 Sprachen, Zeilen editierbar, alphabetische Sortierung.
- Web-UI hinter Auth-Gate (Redirect auf SSO_LOGIN_URL / 401); Favicons offen.
- Log-Tab: Hinweis, wenn der systemd-Dienst nicht aktiv ist.
- Einstellungen: Hinweis "pro Nutzer überschreibbar" bei Sprache/Modus/Qualität.
Doku (BEDIENUNGSANLEITUNG.md): Geräte-TTS §6.5.0, Fix/Flex §6.6, native
Stimmen §6.5.3, llama.cpp<->Ollama-Wechsel §4.7, Auth/SSO §7.4.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
129 lines
4.4 KiB
Python
129 lines
4.4 KiB
Python
import asyncio
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import pytest
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from fastapi.testclient import TestClient
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import app.dependencies as deps
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from app.main import app
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from app.config import settings
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from app.metrics import metrics
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from app.providers.fallback import FallbackLLMProvider
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client = TestClient(app)
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def _run(coro):
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return asyncio.run(coro)
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# --- Fallback-Einheiten ----------------------------------------------------
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def test_llm_fallback_uses_second_on_error():
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class BadLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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raise RuntimeError("down")
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class GoodLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "ok"
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chain = FallbackLLMProvider("llm", [("bad", BadLLM()), ("good", GoodLLM())])
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assert _run(chain.complete("x")) == "ok"
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counters = metrics.snapshot()["counters"]
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assert any("provider_fallback_total" in key for key in counters)
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assert any('provider_error_total{module="llm",provider="bad"}' in key for key in counters)
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def test_llm_fallback_all_fail_raises():
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class BadLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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raise RuntimeError("x")
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chain = FallbackLLMProvider("llm", [("a", BadLLM()), ("b", BadLLM())])
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with pytest.raises(RuntimeError):
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_run(chain.complete("x"))
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def test_llm_stream_fallback_before_first_token():
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class BadStream:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "x"
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async def stream(self, text, history=None, session_id=None, language=None):
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raise RuntimeError("boom")
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yield # macht die Funktion zum Generator
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class GoodStream:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "ok"
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async def stream(self, text, history=None, session_id=None, language=None):
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yield "he"
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yield "llo"
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chain = FallbackLLMProvider("llm", [("bad", BadStream()), ("good", GoodStream())])
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async def collect():
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return [delta async for delta in chain.stream("x")]
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assert _run(collect()) == ["he", "llo"]
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# --- Fallback ueber Config + Endpunkt --------------------------------------
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def test_config_llm_fallback_applied(monkeypatch):
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class BadLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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raise RuntimeError("primary down")
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class GoodLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "rescued"
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class StubTTS:
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async def synthesize(self, text, voice=None, audio_format="pcm", language=None):
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return b"A"
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monkeypatch.setitem(deps.LLM_REGISTRY, "bad", lambda s: BadLLM())
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monkeypatch.setitem(deps.LLM_REGISTRY, "good", lambda s: GoodLLM())
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monkeypatch.setitem(deps.TTS_REGISTRY, "t", lambda s: StubTTS())
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monkeypatch.setattr(settings, "llm_fallback", "good")
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resp = client.post(
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"/api/chat?debug=true",
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json={"text": "x", "llm_provider": "bad", "tts_provider": "t"},
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)
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assert resp.status_code == 200
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assert resp.json()["trace"]["semantic_response"] == "rescued"
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# --- Metriken --------------------------------------------------------------
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def test_metrics_endpoint_records_requests_and_stages(monkeypatch):
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class StubLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "hi"
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class StubTTS:
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async def synthesize(self, text, voice=None, audio_format="pcm", language=None):
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return b"A"
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monkeypatch.setitem(deps.LLM_REGISTRY, "l", lambda s: StubLLM())
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monkeypatch.setitem(deps.TTS_REGISTRY, "t", lambda s: StubTTS())
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resp = client.post(
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"/api/chat?debug=true", json={"text": "x", "llm_provider": "l", "tts_provider": "t"}
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)
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assert resp.status_code == 200
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snap = client.get("/api/metrics").json()
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assert any("http_requests_total" in k and "chat" in k for k in snap["counters"])
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assert any('stage_duration_seconds{stage="llm"}' in k for k in snap["timers"])
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assert any('stage_duration_seconds{stage="tts"}' in k for k in snap["timers"])
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def test_metrics_prometheus_format(monkeypatch):
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client.get("/health")
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text = client.get("/api/metrics?format=prometheus").text
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assert "http_requests_total" in text
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