Metadata-Version: 2.4
Name: llm_evaluation_in_reasoning
Version: 1.4.1
Summary: A project for evaluating reasoning capabilities in large language models (LLMs).
Author-email: Sheng Ren <rensheng0410@gamil.com>, Xiya Pang <sianing0531@gmail.com>
License: MIT License
        
        Copyright (c) 2024 Sheng Ren and Xiya Pang
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
License-File: LICENSE
Keywords: evaluation,llm,reasoning
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.11
Requires-Dist: datasets
Requires-Dist: fire
Requires-Dist: litellm==1.54.1
Requires-Dist: pathlib
Requires-Dist: python-dotenv
Requires-Dist: rich
Requires-Dist: sympy
Description-Content-Type: text/markdown

# llm_evaluation_in_reasoning

[![example workflow](https://github.com/ashengstd/llm_evaluation_in_reasoning/actions/workflows/publish-pypi-release.yml/badge.svg)](https://github.com/ashengstd/llm_evaluation_in_reasoning) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/llm_evaluation_in_reasoning)](https://pypi.org/project/llm_evaluation_in_reasoning) [![PyPI](https://img.shields.io/pypi/v/llm_evaluation_in_reasoning.svg)](https://pypi.org/project/llm_evaluation_in_reasoning/) [![PyPI - Downloads](https://img.shields.io/pypi/dm/llm_evaluation_in_reasoning.svg)](https://pypi.org/project/llm_evaluation_in_reasoning/) [![GitHub License](https://img.shields.io/github/license/ashengstd/llm_evaluation_in_reasoning)](https://github.com/ashengstd/llm_evaluation_in_reasoning) [![GitHub Release](https://img.shields.io/github/v/release/ashengstd/llm_evaluation_in_reasoning)](https://github.com/ashengstd/llm_evaluation_in_reasoning)

A project for evaluating reasoning capabilities in large language models (LLMs).

**Read this in other languages: [English](https://github.com/ashengstd/llm_evaluation_in_reasoning/blob/main/README.md), [中文](https://github.com/ashengstd/llm_evaluation_in_reasoning/blob/main/README_zh.md).**

## Run the eval

### Install the package

```shell
pip install llm_evaluation_in_reasoning
```

### Create the `.env` file

Create a `.env` file with the following:

```
OPENAI_API_KEY=<your key>
ANTHROPIC_API_KEY=<your key>
...
```

The api key you provided will be used to fetch the valid models supported by `Litellm`.

### Run Instructions

Support `GSM-Symbolic`, `GSM8K`, `MMLU`, `SimpleBench`
To run a benchmark:

```shell
llm_eval --model_name=ollama/qwen2.5:0.5b --dataset=SimpleBench # run llm_eval --help to see help information
```

## Model support

Model support is based on `Litellm`, see the docs here [Litellm Providers](https://docs.litellm.ai/docs/providers)

## Build the project

### Setup Instructions

Clone the github repo and cd into it.

```shell
git clone https://github.com/ashengstd/llm_evaluation_in_reasoning.git
cd llm_evaluation_in_reasoning
```

### Install uv:

The best way to install dependencies is to use `uv`.
If you don't have it installed in your environment, you can install it with the following:

```shell
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS and Linux
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" # Windows
```

### Sync the dependencies

```shell
uv sync --all-extra
```
