[tool.poetry]
name = "teaching-assistant"
version = "0.1.0"
description = "High-quality audio translation web application"
authors = ["Your Name <your.email@example.com>"]
license = "MIT"
keywords = ["nlp", "translation", "speech-processing"]

[tool.poetry.dependencies]
python = "^3.9"

# Core dependencies
streamlit = "^1.31.1"
pydub = "^0.25.1"
python-dotenv = "^1.0.0"
nltk = "^3.8.1"          # Text segmentation
librosa = "^0.10.1"      # Advanced audio processing
soundfile = "^0.12.1"    # Audio file I/O
ffmpeg-python = "^0.2.0" # FFmpeg integration

# Machine learning frameworks
torch = { version = "^2.2.1", source = "pytorch" }
transformers = { version = "^4.38.2", extras = ["audio"] }

# Text-to-speech engine
TTS = "^0.21.0"

# Platform-specific dependencies
torchaudio = { version = "^2.2.1", source = "pytorch", optional = true }

[tool.poetry.group.dev.dependencies]
black = "^24.3.0"
flake8 = "^6.1.0"
mypy = "^1.8.0"
pytest = "^8.0.2"

[[tool.poetry.source]]
name = "pytorch"
url = "https://download.pytorch.org/whl/cpu"
priority = "supplemental"

[[tool.poetry.source]]
name = "tsinghua"
url = "https://pypi.tuna.tsinghua.edu.cn/simple"
priority = "primary"

[build-system]
requires = ["poetry-core>=1.3.2"]
build-backend = "poetry.core.masonry.api"

[tool.poetry.extras]
gpu = ["torchaudio"]

[tool.poetry.scripts]
start = "app:main"

[project.urls]
Documentation = "https://github.com/yourusername/audio-translator/wiki"
Issue-Tracker = "https://github.com/yourusername/audio-translator/issues"

# Configuration notes:
# 1. Torch dependencies are sourced from PyTorch's official repository
# 2. Transformers include audio processing extras
# 3. GPU support can be enabled via: poetry install --extras "gpu"
# 4. Platform-specific dependencies are handled through optional groups