Initial commit: Javis project

requirements.txt

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+# Core
+pyyaml>=6.0
+ruamel.yaml>=0.18      # comment-preserving config.yaml writes from the GUI
+loguru>=0.7
+httpx>=0.27
+numpy>=1.24,<2.0
+pydantic>=2.5
+
+# Audio I/O
+sounddevice>=0.4.6
+soundfile>=0.12
+scipy>=1.11
+
+# Wake word + VAD
+silero-vad>=5.1
+openwakeword>=0.6.0
+onnxruntime>=1.17
+
+# STT
+# BatchedInferencePipeline (4× GPU speedup) requires >=1.1; Silero-VAD v6 in >=1.2.1
+faster-whisper>=1.1
+
+# HuggingFace – hf_xet enables fast Xet-storage downloads (avoids HTTP fallback warning)
+hf_xet>=1.0
+
+# Speaker identification
+speechbrain>=1.0
+
+# TTS — Piper VITS (CPU ONNX inference, fast and low-overhead)
+# piper-tts 2.x requires Python >=3.11; 1.7.0 has the same API surface
+piper-tts>=1.7.0,<2.0
+# For voice training only (not needed for inference):
+#   pip install piper-train
+# espeak-ng is required for training (German phonemisation):
+#   https://github.com/espeak-ng/espeak-ng/releases  — install the Windows binary and add to PATH
+
+# MCP
+mcp>=1.2
+
+# Slave-device API server (javis-slave companion app)
+fastapi>=0.110
+uvicorn>=0.29
+python-multipart>=0.0.9
+
+# Optional: F5-TTS voice cloning backend (pip install f5-tts)
+# Requires CC-BY-NC model weights downloaded from Hugging Face on first run.
+# Switch backend via:  tts.backend: f5  in config.yaml
+# f5-tts>=1.1.20
+
+# Optional: DeepFilterNet neural noise reduction (pip install deepfilternet)
+# Automatically denoises mic input before STT when installed.
+# deepfilternet>=0.5.6
+
+# GUI
+PySide6>=6.6
+qasync>=0.27
+
+# CUDA (install separately based on driver version)
+# CUDA 13.2 (current): pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu132
+# CUDA 12.4:           pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu124
+# CUDA 12.1:           pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu121
+# Or let the app auto-detect: python -m javis --install-deps
+#
+# NOTE: CTranslate2 (faster-whisper STT) requires cublas64_12.dll at runtime.
+# Option A (pip — lightweight, recommended):
+#   pip install nvidia-cublas-cu12 nvidia-cudnn-cu12 nvidia-cuda-runtime-cu12
+# Option B: install the full CUDA 12 Toolkit from NVIDIA:
+#   https://developer.nvidia.com/cuda-12-0-1-download-archive
+# Javis auto-discovers option-A DLLs via os.add_dll_directory() at startup.