# Script Fidelity Benchmark - Python dependencies
#
# IMPORTANT: datasets must be <=2.x. Version 3+ removed support for dataset
# scripts, which google/fleurs still requires (fleurs.py). Installing 4.x will
# cause a RuntimeError on load_dataset('google/fleurs', ...).
#
# IMPORTANT: do NOT install torch from the default package index. It will pull
# the latest CUDA build (cu130+) which requires driver >=550. Most cloud GPU
# pods (vast.ai, RunPod) ship driver ~520 (CUDA 12.2). Use the cu121 index:
#
#   uv pip install torch --index-url https://download.pytorch.org/whl/cu121
#
# If torch.cuda.is_available() returns False and you see
# "NVIDIA driver too old (found version 12020)", this is the cause.
#
# Tested on Python 3.10, CUDA 12.1, driver 520, Tesla P100 16 GB.

datasets==2.21.0
fsspec[http]<=2024.6.1
evaluate>=0.4.0,<1.0
# transformers 5.x required for AutoModelForMultimodalLM (Gemma 4 audio support)
transformers>=5.0.0
protobuf>=4.25.0,<6
sentencepiece>=0.1.99
# torch: install separately; see note above
torch>=2.5.0
tqdm>=4.65.0
numpy>=1.24.0
pandas>=2.0.0
matplotlib>=3.7.0
seaborn>=0.13.0
huggingface_hub>=0.23.0
soundfile>=0.12.0
librosa>=0.10.0
jiwer>=3.0.0
sacrebleu>=2.4.0
langdetect>=1.0.9
# Required for Gemma 4 multimodal loading
accelerate>=0.27.0
torchvision>=0.15.0