requirements.txt

# Core dependencies - pinned for DirectML stability (Dec 2025)
GitPython
Pillow>=9.5.0
accelerate>=0.21.0
blendmodes
clean-fid
diffusers>=0.20.0
diskcache
einops
facexlib
fastapi>=0.90.1
gradio==3.41.2                  # Keep this exact version - newer ones often break DirectML
inflection
jsonmerge
kornia
lark
numpy==1.26.4                   # Critical: Lock to 1.26.4 to prevent dtype size errors with scikit-image
omegaconf
open-clip-torch
piexif
protobuf==4.25.3                # Matches your original - safe with mediapipe 0.10.14
psutil
pytorch_lightning
requests
resize-right
safetensors
scikit-image==0.24.0            # Stable, compatible with numpy 1.26.4
tomesd
torch>=2.2.1,<2.3.0             # 2.2.x is most reliable on DirectML right now
torchdiffeq
torchsde
transformers==4.30.2
pillow-avif-plugin==1.4.3
onnx==1.16.2
onnxruntime-directml            # Use the DirectML-specific backend instead of generic onnxruntime
optimum[exporters]              # Optional but useful for ONNX export; add [exporters] for full features
olive-ai                        # Keep as requested

# Additional recommended pins to prevent future mediapipe/jax/ultralytics NumPy upgrades
mediapipe==0.10.14              # Prevents automatic numpy 2.x pull
ultralytics==8.2.98             # Older stable version before heavy numpy 2.x dependencies
jax==0.4.33                     # Compatible with numpy 1.26
jaxlib==0.4.33