# Core dependencies
flask>=3.0.0
flask-cors>=4.0.0
gradio>=4.0.0
huggingface-hub==0.24.0  # Required by transformers 4.47.1
numpy>=1.24.0
scipy>=1.10.0
librosa>=0.10.0
soundfile>=0.12.0
pydantic>=2.0.0
python-dotenv>=1.0.0
pyyaml>=6.0
requests>=2.31.0

# PyTorch - CPU mode for compatibility
# Note: DiffRhythm2 requires torch>=2.4 which is incompatible with torch-directml
# Using CPU mode to avoid version conflicts. For GPU acceleration, use NVIDIA CUDA.
torch==2.4.0
torchaudio==2.4.0

# DiffRhythm 2 core dependencies
torchdiffeq>=0.2.4  # Required for CFM (flow matching)
phonemizer>=3.2.0
muq>=0.1.0  # MuQ-MuLan style encoder for music generation
jieba>=0.42.0  # Chinese text segmentation
pypinyin>=0.50.0  # Chinese to pinyin conversion
cn2an>=0.5.0  # Chinese number to text
onnxruntime>=1.15.0  # For g2p Chinese model
pykakasi>=2.3.0  # Japanese text processing
pyopenjtalk; python_version < "3.12"  # Japanese phonetics (Python 3.11 compatible)
unidecode>=1.3.0  # Text normalization
py3langid>=0.2.2  # Language detection
inflect>=7.0.0  # English text normalization (required by g2p)

# AI Model dependencies
transformers==4.47.1  # Pinned for DiffRhythm2 compatibility
diffusers>=0.21.0
sentencepiece>=0.1.99
protobuf>=3.20.0
accelerate==0.33.0
einops==0.8.0
omegaconf==2.3.0

# Audio processing
pedalboard==0.9.9
pydub==0.25.1
resampy==0.4.3
mutagen==1.47.0

# Audio quality enhancement
demucs==4.0.1  # Stem separation

# MSD Integration (v1.0.2)
h5py==3.10.0  # For reading MSD HDF5 files
tqdm==4.66.5  # Progress bars for data import
noisereduce==3.0.2  # Noise reduction

# LoRA Training dependencies
peft==0.11.0  # Parameter-Efficient Fine-Tuning (LoRA adapters)
datasets==2.19.0  # HuggingFace datasets for training data management
tensorboard==2.16.2  # Training monitoring and visualization
wandb==0.17.0  # Optional: Advanced experiment tracking

# Utilities
safetensors==0.4.3
gitpython==3.1.43