dschlueter
d1971049ce
- chatterbox_cli_v4.py: cooperative stop/interrupt via threading.Event; fix force_split_sentence (word boundary instead of mid-word cut); fix synthesize_streaming normalization order (split before preprocess) - tts_service.py: FastAPI service with job queue, model cache, worker thread; LAN-accessible on 0.0.0.0:9999; audio_device default None (auto) - mcp_adapter.py: MCP adapter (stdio + streamable-http) wrapping REST API; update docstring and default TTS_URL to port 9999 - requirements.txt: add fastapi, uvicorn, httpx, mcp - README.md, BEDIENUNGSANLEITUNG.md: document service, MCP, AI integrations (Claude, Ollama, Open WebUI, llama.cpp, Home Assistant), systemd autostart - CLAUDE.md: reflect current architecture (service + adapter now implemented) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
25 lines
730 B
Text
25 lines
730 B
Text
# Chatterbox TTS CLI — Abhängigkeiten
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# Getestet mit Python 3.11, CUDA 12.x, Ubuntu 22.04/24.04
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#
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# PyTorch separat installieren (passende CUDA-Version via pytorch.org):
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# pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu124
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# --- TTS-Kern ---
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chatterbox-tts>=0.1.7
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# --- Audio-Ausgabe (Linux/PipeWire/PulseAudio) ---
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sounddevice>=0.4.0
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# --- Pitch-erhaltende Zeitstreckung (--speed != 1.0) ---
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# Systempaket zusätzlich erforderlich: sudo apt install rubberband-cli
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pyrubberband>=0.4.0
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# --- HTTP-Service (tts_service.py) ---
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fastapi>=0.115.0
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uvicorn[standard]>=0.32.0
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# --- HTTP-Client (mcp_adapter.py → tts_service.py) ---
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httpx>=0.28.0
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# --- MCP-Adapter (mcp_adapter.py) ---
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mcp>=1.0.0
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