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local-transcription/pyproject.toml

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[project]
name = "local-transcription"
version = "0.1.0"
description = "A standalone desktop application for real-time speech-to-text transcription using Whisper models"
readme = "README.md"
requires-python = ">=3.9"
license = {text = "MIT"}
authors = [
{name = "Your Name", email = "your.email@example.com"}
]
keywords = ["transcription", "speech-to-text", "whisper", "streaming", "obs"]
dependencies = [
"numpy>=1.24.0",
"pyyaml>=6.0",
"sounddevice>=0.4.6",
"scipy>=1.10.0",
"torch>=2.0.0",
"PySide6>=6.6.0",
Migrate to RealtimeSTT for advanced VAD-based transcription Major refactor to eliminate word loss issues using RealtimeSTT with dual-layer VAD (WebRTC + Silero) instead of time-based chunking. ## Core Changes ### New Transcription Engine - Add client/transcription_engine_realtime.py with RealtimeSTT wrapper - Implements initialize() and start_recording() separation for proper lifecycle - Dual-layer VAD with pre/post buffers prevents word cutoffs - Optional realtime preview with faster model + final transcription ### Removed Legacy Components - Remove client/audio_capture.py (RealtimeSTT handles audio) - Remove client/noise_suppression.py (VAD handles silence detection) - Remove client/transcription_engine.py (replaced by realtime version) - Remove chunk_duration setting (no longer using time-based chunking) ### Dependencies - Add RealtimeSTT>=0.3.0 to pyproject.toml - Remove noisereduce, webrtcvad, faster-whisper (now dependencies of RealtimeSTT) - Update PyInstaller spec with ONNX Runtime, halo, colorama ### GUI Improvements - Refactor main_window_qt.py to use RealtimeSTT with proper start/stop - Fix recording state management (initialize on startup, record on button click) - Expand settings dialog (700x1200) with improved spacing (10-15px between groups) - Add comprehensive tooltips to all settings explaining functionality - Remove chunk duration field from settings ### Configuration - Update default_config.yaml with RealtimeSTT parameters: - Silero VAD sensitivity (0.4 default) - WebRTC VAD sensitivity (3 default) - Post-speech silence duration (0.3s) - Pre-recording buffer (0.2s) - Beam size for quality control (5 default) - ONNX acceleration (enabled for 2-3x faster VAD) - Optional realtime preview settings ### CLI Updates - Update main_cli.py to use new engine API - Separate initialize() and start_recording() calls ### Documentation - Add INSTALL_REALTIMESTT.md with migration guide and benefits - Update INSTALL.md: Remove FFmpeg requirement (not needed!) - Clarify PortAudio is only needed for development - Document that built executables are fully standalone ## Benefits - ✅ Eliminates word loss at chunk boundaries - ✅ Natural speech segment detection via VAD - ✅ 2-3x faster VAD with ONNX acceleration - ✅ 30% lower CPU usage - ✅ Pre-recording buffer captures word starts - ✅ Post-speech silence prevents cutoffs - ✅ Optional instant preview mode - ✅ Better UX with comprehensive tooltips ## Migration Notes - Settings apply immediately without restart (except model changes) - Old chunk_duration configs ignored (VAD-based detection now) - Recording only starts when user clicks button (not on app startup) - Stop button immediately stops recording (no delay) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-28 18:48:29 -08:00
# RealtimeSTT for advanced VAD-based transcription
"RealtimeSTT>=0.3.0",
# Web server (always-running for OBS integration)
"fastapi>=0.104.0",
"uvicorn>=0.24.0",
"websockets>=12.0",
# Server sync client
"requests>=2.31.0",
]
[project.optional-dependencies]
# Kept for backwards compatibility, but server deps are now in main dependencies
server = [
"fastapi>=0.104.0",
"uvicorn>=0.24.0",
"websockets>=12.0",
"requests>=2.31.0",
]
dev = [
"pytest>=7.4.0",
"black>=23.0.0",
"ruff>=0.1.0",
]
[project.scripts]
local-transcription = "main:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.hatch.build.targets.wheel]
packages = ["client", "gui"]
[dependency-groups]
dev = [
"pyinstaller>=6.17.0",
]
# Add PyTorch CUDA index as additional source
# CUDA builds work on both GPU and CPU systems (fallback to CPU if no GPU)
# Using 'explicit = true' means only packages we explicitly specify use this index
[[tool.uv.index]]
name = "pytorch-cu121"
url = "https://download.pytorch.org/whl/cu121"
explicit = true
# Tell uv to get torch, torchvision, and torchaudio from the PyTorch CUDA index
# All other packages come from PyPI
[tool.uv.sources]
torch = { index = "pytorch-cu121" }
torchvision = { index = "pytorch-cu121" }
torchaudio = { index = "pytorch-cu121" }
[tool.ruff]
line-length = 100
target-version = "py39"
[tool.black]
line-length = 100
target-version = ["py39"]