Datasets:
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# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# this file is here for backward compatibility (e.g. for lm-evaluation-harness), when this dataset used to be named "hendrycks_test"
import json
import datasets
_CITATION = """
"""
_DESCRIPTION = """
"""
_HOMEPAGE = """
"""
_URL = """
"""
_LICENSE = """
"""
_DATASETS = [
'ConvFinQA',
'FinanceBench',
'FinDER',
'FinQA',
'FinQABench',
'MultiHeirtt',
'TATQA',
]
_SPLITS = ["corpus", "queries"]
_URLs = {dataset: f"{dataset}/" for dataset in _DATASETS for subset in _SPLITS}
class FinanceRAG(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name=f"{dataset}",
version=datasets.Version("1.0.0"),
description=f"{dataset} dataset."
)
for dataset in _DATASETS
]
def _info(self):
features = datasets.Features(
{
"_id": datasets.Value("string"),
"title": datasets.Value("string"),
"text": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
citation=_CITATION,
license=_LICENSE,
supervised_keys=None,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
my_urls = _URLs[self.config.name]
data_dir = dl_manager.download_and_extract(my_urls)
return [
datasets.SplitGenerator(
name=datasets.Split(split),
gen_kwargs={"filepath": data_dir + f"{split}.jsonl.gz"}
) for split in _SPLITS
]
# Copied from BeIR.
def _generate_examples(self, filepath):
with open(filepath, encoding="utf-8") as f:
texts = f.readlines()
for i, text in enumerate(texts):
text = json.loads(text)
if 'metadata' in text: del text['metadata']
if "title" not in text: text["title"] = ""
yield i, text |