# ── Core environment runtime ────────────────────────────────────────────────
pydantic>=2.0
numpy>=1.24

# ── HTTP server (Hugging Face Space, OpenEnv contract) ──────────────────────
fastapi>=0.100.0
uvicorn>=0.23.0
python-multipart>=0.0.6

# ── LLM client (used by inference.py for OpenAI-compatible API rollouts) ────
openai>=1.0

# ── Replay rendering / dashboards ───────────────────────────────────────────
matplotlib>=3.7
imageio>=2.28
Pillow>=9.0

# ── Test suite ──────────────────────────────────────────────────────────────
pytest>=7.0
pytest-cov>=4.0

# ── Optional extras for evaluating a trained adapter locally ────────────────
# (Training itself is run on Colab/HF Space JupyterLab; see training/grpo_v2_colab.ipynb,
#  which installs unsloth + trl + datasets inline. These pins here are purely so
#  `python scripts/eval_trained_model.py` works in a stock Python venv.)
# torch>=2.1
# transformers>=4.45
# accelerate>=0.30
# peft>=0.10
# safetensors>=0.4