[build-system] requires = ["setuptools>=68.0", "setuptools-scm>=8.0"] build-backend = "setuptools.build_meta" [project] name = "legex" version = "0.1.0" description = "Extract structured data from legal decisions with LLMs." requires-python = ">=3.11" dependencies = [ "pydantic>=2.0", "pydantic-settings>=2.0", "requests>=2.32", "datasets>=2.0", "huggingface-hub>=0.24", "pandas>=2.0", "pyarrow>=15.0", "python-dotenv>=1.2.2", "openpyxl>=3.1", "pdfplumber>=0.11", "pypdf>=6.10.2", "litellm[google]>=1.50", "fpdf2>=2.8", "beautifulsoup4>=4.12", "lxml>=5.0", "pyyaml>=6.0", "playwright>=1.60.0", "scipy>=1.11", ] [project.optional-dependencies] dev = [ "pytest>=8.0", "pytest-asyncio>=0.23", "ruff>=0.4", ] # Figures: legex-plots and scripts/appendix_frequencies.py need matplotlib, # scripts/diversity_stats.py additionally needs wordcloud # (or run with `uv run --with wordcloud ...`). plots = [ "matplotlib>=3.8", "wordcloud>=1.9", ] [project.scripts] legex-run = "legex.main:main" legex-classify = "legex.inference:main" legex-evaluate = "legex.evaluation:main" legex-harvey-ingest = "legex.harvey:main" legex-india-extract = "legex.scrapers.in_:_extract_cli" # Full-text acquisition legex-build-fulltext = "legex.fulltext.build_full_text:main" legex-render-fulltext = "legex.fulltext.render_full_text:main" # Evaluation & analysis legex-analysis = "legex.analysis.aggregate:main" legex-analysis-report = "legex.analysis.report:main" legex-iaa = "legex.analysis.iaa:main" legex-quant-results = "legex.analysis.quant_results:main" legex-plots = "legex.analysis.plots:main" legex-goldenset-quality = "legex.analysis.goldenset_quality:main" # Refusal cleaning legex-refusals-scan = "legex.evaluation.cleaning:scan_main" legex-refusals-apply = "legex.evaluation.cleaning:apply_main" [tool.setuptools.packages.find] include = ["legex*"] [tool.ruff] line-length = 100 [tool.pytest.ini_options] testpaths = ["tests"] asyncio_mode = "auto" [dependency-groups] dev = [ "matplotlib>=3.10.9", "pytest>=9.0.2", "pytest-asyncio>=1.3.0", "ruff>=0.15.8", ]