Create RareBench.py

RareBench.py

@@ -0,0 +1,88 @@
+# 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.
+
+
+import json
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+RareBench is a pioneering benchmark designed to systematically evaluate the capabilities of LLMs within the realm of rare diseases.
+"""
+
+_HOMEPAGE = "https://github.com/chenxz1111/RareBench"
+
+_URL = r"https://huggingface.co/datasets/chenxz/RareBench/resolve/main/data.zip"
+
+data_list = [
+    "RAMEDIS",
+    "HMS",
+    "MME",
+    "LIRICAL",
+    "PUMCH_ADM"
+]
+
+class RareBenchConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
+
+
+class RareBench(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        RareBenchConfig(
+            name=data_name,
+        )
+        for data_name in data_list
+    ]
+    
+    def _info(self):
+        features = datasets.Features(
+            {
+                "Phenotype": [datasets.Value("string")], 
+                "RareDisease": [datasets.Value("string")],
+                # "Department": datasets.Value("string"), 
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_URL)
+        data_name = self.config.name
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, "data", f"{data_name}.jsonl"
+                    ),
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for idx, line in enumerate(f):
+                key = f"{self.config.name}-{idx}"
+                item = json.loads(line)
+                yield key, {
+                    "Phenotype": item["Phenotype"],
+                    "RareDisease": item["RareDisease"],
+                    # "Department": item["Department"],
+                }