Metadata-Version: 2.4
Name: aviary.lfrqa
Version: 0.33.0
Summary: LFRQA environment implemented with aviary
Author-email: FutureHouse technical staff <hello@futurehouse.org>
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: aviary.labbench
Requires-Dist: fhaviary
Requires-Dist: fhlmi
Requires-Dist: paper-qa>=5.14.0
Requires-Dist: pydantic~=2.0
Provides-Extra: csv
Requires-Dist: pandas; extra == "csv"
Provides-Extra: dev
Requires-Dist: aviary.lfrqa[csv]; extra == "dev"

# aviary.lfrqa

An environment designed to utilize PaperQA
for answering questions from the LFRQATaskDataset
Long-form RobustQA (LFRQA) is a human-annotated dataset introduced in the RAG-QA-Arena,
featuring over 1400 questions from various categories, including science.

## Installation

To install the LFRQA environment, run:

```bash
pip install 'fhaviary[lfrqa]'
```

## Usage

Refer to [this tutorial][2] for instructions on how to run the environment.

[2]: https://github.com/Future-House/paper-qa/blob/main/docs/tutorials/running_on_lfrqa.md

## References

[1] RAG-QA Arena (<https://arxiv.org/pdf/2407.13998>)
