Metadata-Version: 2.4
Name: evalsense
Version: 0.1.2
Summary: Tools for evaluating large language models.
Project-URL: Homepage, https://github.com/nhsengland/evalsense
Project-URL: Issues, https://github.com/nhsengland/evalsense/issues
Author-email: Adam Dejl <adam.dejl18@imperial.ac.uk>
License-Expression: MIT
License-File: LICENCE
Keywords: Artificial Intelligence,LLM Benchmarking,LLM Evaluation,LLMs,Large Language Models,Machine Learning
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.12
Requires-Dist: accelerate>=1.4.0
Requires-Dist: bert-score>=0.3.13
Requires-Dist: datasets>=3.2.0
Requires-Dist: evaluate>=0.4.3
Requires-Dist: flashinfer-python<0.2.3
Requires-Dist: inspect-ai>=0.3.87
Requires-Dist: matplotlib>=3.10.0
Requires-Dist: numpy<2.0.0
Requires-Dist: openai>=1.65.3
Requires-Dist: pandas>=2.2.3
Requires-Dist: platformdirs>=4.3.6
Requires-Dist: polars>=1.22.0
Requires-Dist: pydantic>=2.10.6
Requires-Dist: pyyaml>=6.0.2
Requires-Dist: rouge-score>=0.1.2
Requires-Dist: seaborn>=0.13.2
Requires-Dist: tenacity>=9.0.0
Requires-Dist: torch>=2.6
Requires-Dist: tqdm>=4.67.1
Requires-Dist: transformers>=4.50.0
Requires-Dist: typer>=0.15.1
Requires-Dist: vllm>=0.8.2
Provides-Extra: interactive
Requires-Dist: ipywidgets>=8.1.5; extra == 'interactive'
Requires-Dist: jupyterlab>=4.3.5; extra == 'interactive'
Description-Content-Type: text/markdown

> [!WARNING]
> This project is a work in progress. Critical components may be missing, inoperative or incomplete, and the API can undergo major changes without any notice. Please check back later for a more stable version.

# EvalSense: LLM Evaluation

<div align="center">

[![status: experimental](https://github.com/GIScience/badges/raw/master/status/experimental.svg)](https://github.com/GIScience/badges#experimental)
[![PyPI package version](https://img.shields.io/pypi/v/evalsense)](https://pypi.org/project/evalsense/)
[![license: MIT](https://img.shields.io/badge/License-MIT-brightgreen)](https://github.com/nhsengland/evalsense/blob/main/LICENCE)
[![EvalSense status](https://github.com/nhsengland/evalsense/actions/workflows/evalsense.yml/badge.svg)](https://github.com/nhsengland/evalsense/actions/workflows/evalsense.yml)
[![Guide status](https://github.com/nhsengland/evalsense/actions/workflows/guide.yml/badge.svg)](https://github.com/nhsengland/evalsense/actions/workflows/guide.yml)
[![Python](https://img.shields.io/badge/Python-3776AB?logo=python&logoColor=fff)](https://www.python.org/)
[![TypeScript](https://img.shields.io/badge/TypeScript-3178C6?logo=typescript&logoColor=fff)](https://www.typescriptlang.org/)
[![React](https://img.shields.io/badge/-React-61DAFB?logo=react&logoColor=white&style=flat)](https://react.dev/)

</div>
<div align="center">

[![Python v3.12](https://img.shields.io/badge/python-3.12-blue)](https://www.python.org/downloads/)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Checked with pyright](https://microsoft.github.io/pyright/img/pyright_badge.svg)](https://microsoft.github.io/pyright/)
[![ESLint](https://img.shields.io/badge/ESLint-3A33D1?logo=eslint)](https://eslint.org/)

</div>

## About

This repository holds a Python package enabling systematic evaluation of large language models (LLMs) on open-ended generation tasks, with a particular focus on healthcare and summarisation. It also includes supplementary documentation and assets related to the NHS England project on LLM evaluation, such as the code for an interactive LLM evaluation guide (located in the `guide/` directory). You can find more information about the project in the [original project proposal](https://nhsx.github.io/nhsx-internship-projects/genai-eval/).

_**Note:** Only public or fake data are shared in this repository._

## Project Stucture

- The main code for the EvalSense Python package can be found under [`evalsense/`](https://github.com/nhsengland/evalsense/tree/main/evalsense).
- The accompanying documentation is available in the [`docs/`](https://github.com/nhsengland/evalsense/tree/main/docs) folder.
- Code for the interactive LLM evaluation guide is located under [`guide/`](https://github.com/nhsengland/evalsense/tree/main/guide).
- Jupyter notebooks with the evaluation experiments and examples are located under [`notebooks/`](https://github.com/nhsengland/evalsense/tree/main/notebooks).

## Getting Started

### Installation for Development

To install the project for local development, you can follow the steps below:

To clone the repo:

`git clone git@github.com:nhsengland/evalsense.git`

To setup the Python environment for the project:

- Install [uv](https://github.com/astral-sh/uv) if it's not installed already
- `uv sync --all-extras`
- `source .venv/bin/activate`
- `pre-commit install`

To setup the Node environment for the LLM evaluation guide (located under [`guide/`](https://github.com/nhsengland/evalsense/tree/main/guide)):

- Install [node](https://nodejs.org/en/download) if it's not installed already
- `npm install` in the `guide/` directory
- `npm run start` to run the development server

## Usage

For an example illustrating the usage of EvalSense, please check the [Demo notebook](https://github.com/nhsengland/evalsense/blob/main/notebooks/Demo.ipynb) under the `notebooks/` folder.

## Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/amazing-feature`)
3. Commit your Changes (`git commit -m 'Add some amazing feature'`)
4. Push to the Branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

_See [CONTRIBUTING.md](./CONTRIBUTING.md) for detailed guidance._

## License

Unless stated otherwise, the codebase is released under [the MIT Licence][mit].
This covers both the codebase and any sample code in the documentation.

_See [LICENSE](./LICENSE) for more information._

The documentation is [© Crown copyright][copyright] and available under the terms
of the [Open Government 3.0][ogl] licence.

[mit]: LICENCE
[copyright]: http://www.nationalarchives.gov.uk/information-management/re-using-public-sector-information/uk-government-licensing-framework/crown-copyright/
[ogl]: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

### Contact

To find out more about the [NHS England Data Science](https://nhsengland.github.io/datascience/) visit our [project website](https://nhsengland.github.io/datascience/our_work/) or get in touch at [datascience@nhs.net](mailto:datascience@nhs.net).

<!-- ### Acknowledgements -->
