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refactor(stt): pivot client-serveur — STT-server in-cluster + client pipx
Sépare STT en deux : - stt/client/ : commande `stt` (pipx), voix locale (Whisper/Piper) + HUD ; envoie le texte au serveur via api.py (ServerClient → POST /v1/ask). URL serveur paramétrable, pas de cerveau local (suppression du routeur 3 modes). - stt/server/ : STT-server FastAPI (conteneur), /healthz + /v1/ask → LiteLLM (Qwen3/Claude). Déploiement cluster : - k8s/apps/stt/ : Deployment, Service, IngressRoute (stt.lab.local), litellm-ext (Service + Endpoints → 192.168.10.1:4000 pour joindre LiteLLM hors cluster) - k8s/apps-of-apps/apps/stt.yaml : Application ArgoCD (depuis main) - .github/workflows/build-stt-server.yml : build/push image → ghcr.io/alkatrazz24/funk-stt-server Inférence/chat seulement (outils Hermes 'agir sur Funk' = phase ultérieure, API :8080 à spécifier). Vérifié : py_compile client+serveur, YAML manifests, ServerClient. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_013FmcxGsyXZXogiAHQLjnZT
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stt/client/pyproject.toml
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32
stt/client/pyproject.toml
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[project]
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name = "stt"
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version = "0.1.0"
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description = "STT — client vocal Jarvis du homelab Funk (voix + HUD, parle au STT-server)"
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requires-python = ">=3.11"
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readme = "README.md"
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# Client : voix locale + HUD. L'inférence est déléguée au STT-server (pas d'anthropic/qdrant ici).
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dependencies = [
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"faster-whisper>=1.0.0", # STT local
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"sounddevice>=0.4.6", # capture micro
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"numpy>=1.24.0",
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"requests>=2.31.0", # appels HTTP vers le STT-server
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"webrtcvad-wheels>=2.0.10",# VAD / wake word
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"websockets>=12.0", # backend ↔ HUD
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"tomli-w>=1.0.0", # écriture config TOML
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]
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[project.scripts]
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stt = "stt.cli:main"
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[build-system]
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requires = ["setuptools>=68"]
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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 = ["stt*"]
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# Le HUD (assets web) est livré comme données du package stt/
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[tool.setuptools.package-data]
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stt = ["hud/*", "hud/**/*"]
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