pyproject.toml

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

[build-system]
requires = ["setuptools>=45", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "openenv-ShopManagerEng"
version = "0.1.0"
description = "Shopmanagereng environment for OpenEnv"
requires-python = ">=3.10"
dependencies = [
    # Core OpenEnv runtime (provides FastAPI server + HTTP client types)
    # install from github
    # "openenv-core[core] @ git+https://github.com/meta-pytorch/OpenEnv.git",
    "openenv-core[core]>=0.2.2",
    "yfinance>=0.2.40",
    "python-dotenv>=1.0.0",
    "requests>=2.28.0",
    "streamlit>=1.30.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=8.0.0",
    "pytest-cov>=4.0.0",
]

# GRPO training stack. Install only on a GPU host (vLLM is GPU-only).
#   pip install -e '.[train]'
# Mirrors openenv-course Module 5 versions. trl>=0.17 is the cutoff that
# introduced trl.experimental.openenv.generate_rollout_completions.
train = [
    "trl>=0.17.0",
    "transformers>=4.46.0",
    "datasets>=2.20.0",
    "accelerate>=1.0.0",
    # Pin to TRL's supported window. vllm 0.19+ changes the sampling-logprob
    # path and breaks GRPO importance sampling (ratio collapses to ~0,
    # grad_norm goes to 0, model stops learning). Keep <=0.18.0 until TRL
    # bumps its supported range.
    "vllm>=0.11.0,<=0.18.0",
    "trackio",
    "torch>=2.4.0",
    # Local plotting of loss + reward curves (hackathon submission evidence).
    "matplotlib>=3.7",
]

[project.scripts]
# Server entry point - enables running via: uv run --project . server
# or: python -m ShopManagerEng.server.app
server = "ShopManagerEng.server.app:main"

[tool.setuptools]
include-package-data = true
packages = ["ShopManagerEng", "ShopManagerEng.server", "ShopManagerEng.training"]
package-dir = { "ShopManagerEng" = ".", "ShopManagerEng.server" = "server", "ShopManagerEng.training" = "training" }