- FasterWhisperProvider implementiert (CTranslate2): Modell prozessweit gecacht (lru_cache), Transkription in asyncio.to_thread; robuster CPU-Fallback wenn GPU/compute_type nicht verfuegbar - Config: FASTER_WHISPER_MODEL/DEVICE/COMPUTE_TYPE (Defaults base/auto/default) - pyproject: optionales Extra [local] = faster-whisper - Test: transcribe-Endpunkt nutzt jetzt einen Stub-STT (kein Platzhalter mehr) - Doku: Voraussetzungen, Hybrid-Beispiel (STT+LLM lokal, TTS remote), Architektur/README Live verifiziert: TTS->WAV->faster-whisper transkribiert korrekt (de); voller Hybrid ueber /ws/voice (faster-whisper + Ollama llama3.2 + OpenRouter-TTS) funktioniert. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
32 lines
752 B
TOML
32 lines
752 B
TOML
[project]
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name = "voice-assistant-gateway"
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version = "0.1.0"
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description = "Modular voice assistant gateway with pluggable audio endpoints and provider adapters"
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readme = "README.md"
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requires-python = ">=3.11"
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dependencies = [
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"fastapi>=0.116.0",
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"uvicorn[standard]>=0.35.0",
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"httpx>=0.28.0",
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"pydantic>=2.11.0",
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"pydantic-settings>=2.10.0",
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"python-multipart>=0.0.20"
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]
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[project.optional-dependencies]
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test = [
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"pytest>=8.0"
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]
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# Lokale KI-Module (optional, schwergewichtig): lokales STT via faster-whisper.
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local = [
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"faster-whisper>=1.0"
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]
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[build-system]
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requires = ["setuptools>=68", "wheel"]
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build-backend = "setuptools.build_meta"
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[tool.setuptools.packages.find]
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where = ["."]
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include = ["app*"]
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exclude = ["deploy*", "tests*"]
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