81d4cf6fd8
Bisher wurde `language` zwar an STT/TTS übergeben, aber nie an den LLM.
Lokales Modell antwortete deshalb immer auf Englisch/Deutsch, egal ob
Französisch, Spanisch o.a. eingestellt war.
Lösung: `language`-Parameter durch die gesamte LLM-Schicht gezogen:
- base.py: `lang_instruction()` helper + Signatur erweitert
- local_openai_compatible.py: Sprachanweisung ("Respond in Français.")
wird als letzter System-Part in den Message-Stack eingefügt
- openrouter.py: Explizite Sprachanweisung ergänzt den bestehenden
"Answer in the same language as the user"-Prompt
- fallback.py: FallbackLLMProvider leitet `language` durch
- orchestrator.py: alle 3 LLM-Aufrufstellen übergeben `language`
- Tests: alle Stub-LLMs um `language=None` ergänzt
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
129 lines
4.2 KiB
Python
129 lines
4.2 KiB
Python
import array
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import asyncio
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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.audio.vad import rms, EnergyVAD
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client = TestClient(app)
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def _pcm(amplitude: int, n_samples: int) -> bytes:
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return array.array("h", [amplitude] * n_samples).tobytes()
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# --- VAD-Unit-Tests --------------------------------------------------------
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def test_rms_silence_vs_loud():
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assert rms(b"") == 0.0
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assert rms(_pcm(0, 100)) == 0.0
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assert rms(_pcm(3000, 100)) > 2000
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def test_energy_vad_ends_after_speech_then_silence():
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vad = EnergyVAD(sample_rate=16000, threshold=500, silence_ms=300)
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loud = _pcm(3000, 1600) # 100 ms Sprache
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silent = _pcm(0, 1600) # 100 ms Stille
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assert vad.feed(loud) is False
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assert vad.feed(silent) is False # 100 ms
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assert vad.feed(silent) is False # 200 ms
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assert vad.feed(silent) is True # 300 ms -> Ende
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def test_energy_vad_ignores_silence_without_speech():
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vad = EnergyVAD(sample_rate=16000, threshold=500, silence_ms=100)
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for _ in range(10):
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assert vad.feed(_pcm(0, 1600)) is False
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# --- Barge-in --------------------------------------------------------------
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def _install_slow_stream(monkeypatch):
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class SlowLLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "fertig"
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async def stream(self, text, history=None, session_id=None, language=None):
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for i in range(200):
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await asyncio.sleep(0.005)
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yield f"t{i} "
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class StubTTS:
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async def synthesize(self, text, voice=None, audio_format="pcm"):
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return b"A"
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monkeypatch.setitem(deps.LLM_REGISTRY, "slow", lambda s: SlowLLM())
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monkeypatch.setitem(deps.TTS_REGISTRY, "stub", lambda s: StubTTS())
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return {
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"llm_provider": "slow",
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"tts_provider": "stub",
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"output_endpoint": "loopback",
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"stream": True,
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}
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def test_ws_chat_interrupt_cancels_response(monkeypatch):
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base = _install_slow_stream(monkeypatch)
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with client.websocket_connect("/ws/chat") as ws:
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ws.send_json({"text": "Hallo", **base})
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assert ws.receive_json()["type"] == "ack"
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assert ws.receive_json()["type"] == "token" # Antwort laeuft
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ws.send_json({"type": "interrupt"})
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event = None
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for _ in range(500):
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event = ws.receive_json()
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if event["type"] in ("interrupted", "done"):
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break
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assert event["type"] == "interrupted" # abgebrochen, nicht fertig
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# --- VAD im WebSocket ------------------------------------------------------
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def _install_voice_stubs(monkeypatch):
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class STT:
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async def transcribe(self, audio_bytes, fmt, language=None):
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return "ok"
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class LLM:
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async def complete(self, text, history=None, session_id=None, language=None):
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return "antwort"
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class TTS:
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async def synthesize(self, text, voice=None, audio_format="pcm"):
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return b"A"
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monkeypatch.setitem(deps.STT_REGISTRY, "s", lambda x: STT())
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monkeypatch.setitem(deps.LLM_REGISTRY, "l", lambda x: LLM())
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monkeypatch.setitem(deps.TTS_REGISTRY, "t", lambda x: TTS())
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return {"stt_provider": "s", "llm_provider": "l", "tts_provider": "t", "output_endpoint": "loopback"}
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def test_ws_voice_vad_auto_segments_utterance(monkeypatch):
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opts = _install_voice_stubs(monkeypatch)
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start = {
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"type": "start",
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"vad": True,
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"sample_rate": 16000,
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"vad_silence_ms": 200,
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"format": "pcm",
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**opts,
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}
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loud = _pcm(3000, 1600) # 100 ms Sprache
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silent = _pcm(0, 1600) # je 100 ms Stille
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with client.websocket_connect("/ws/voice") as ws:
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ws.send_json(start)
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ws.send_bytes(loud)
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ws.send_bytes(silent) # 100 ms
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ws.send_bytes(silent) # 200 ms -> VAD-Ende, Turn startet automatisch
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transcript = ws.receive_json()
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assert transcript["type"] == "transcript" and transcript["text"] == "ok"
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assert ws.receive_json()["type"] == "ack"
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assert ws.receive_json()["type"] == "semantic"
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assert ws.receive_bytes() == b"A"
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assert ws.receive_json()["type"] == "done"
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