diff --git a/scripts/data_process/qa_search_test_merge.py b/scripts/data_process/qa_search_test_merge.py
new file mode 100644
index 0000000..6bc98b8
--- /dev/null
+++ b/scripts/data_process/qa_search_test_merge.py
@@ -0,0 +1,115 @@
+# Copyright 2024 Bytedance Ltd. and/or its affiliates
+#
+# 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.
+"""
+Preprocess the QA dataset to parquet format
+"""
+
+import re
+import os
+import datasets
+
+from verl.utils.hdfs_io import copy, makedirs
+import argparse
+
+
+def make_prefix(dp, template_type):
+ question = dp['question']
+
+ # NOTE: also need to change reward_score/countdown.py
+ if template_type == 'base':
+ """This works for any base model"""
+ prefix = f"""Answer the given question. \
+You must conduct reasoning inside and first every time you get new information. \
+After reasoning, if you find you lack some knowledge, you can call a search engine by query and it will return the top searched results between and . \
+You can search as many times as your want. \
+If you find no further external knowledge needed, you can directly provide the answer inside and , without detailed illustrations. For example, Beijing . Question: {question}\n"""
+ else:
+ raise NotImplementedError
+ return prefix
+
+
+if __name__ == '__main__':
+ parser = argparse.ArgumentParser()
+ parser.add_argument('--local_dir', default='./data/nq_search')
+ parser.add_argument('--hdfs_dir', default=None)
+ parser.add_argument('--template_type', type=str, default='base')
+ parser.add_argument('--data_sources', default='nq')
+
+ args = parser.parse_args()
+
+ data_sources = args.data_sources.split(',')
+ all_dataset = []
+
+ for data_source in data_sources:
+
+ if data_source != 'strategyqa':
+ dataset = datasets.load_dataset('RUC-NLPIR/FlashRAG_datasets', data_source)
+ else:
+ dataset = datasets.load_dataset('json', data_files="/home/peterjin/mnt/data/strategyqa/test_correct.jsonl")
+
+ if 'test' in dataset:
+ print(f'Using the {data_source} test dataset...')
+ test_dataset = dataset['test']
+ elif 'dev' in dataset:
+ print(f'Using the {data_source} dev dataset...')
+ test_dataset = dataset['dev']
+ else:
+ print(f'Using the {data_source} train dataset...')
+ test_dataset = dataset['train']
+
+ # add a row to each data item that represents a unique id
+ def make_map_fn(split):
+
+ def process_fn(example, idx):
+ example['question'] = example['question'].strip()
+ if example['question'][-1] != '?':
+ example['question'] += '?'
+ question = make_prefix(example, template_type=args.template_type)
+ solution = {
+ "target": example['golden_answers'],
+ }
+
+ data = {
+ "data_source": data_source,
+ "prompt": [{
+ "role": "user",
+ "content": question,
+ }],
+ "ability": "fact-reasoning",
+ "reward_model": {
+ "style": "rule",
+ "ground_truth": solution
+ },
+ "extra_info": {
+ 'split': split,
+ 'index': idx,
+ }
+ }
+ return data
+
+ return process_fn
+
+ test_dataset = test_dataset.map(function=make_map_fn('test'), with_indices=True)
+ all_dataset.append(test_dataset)
+
+ local_dir = args.local_dir
+ hdfs_dir = args.hdfs_dir
+
+ all_test_dataset = datasets.concatenate_datasets(all_dataset)
+ all_test_dataset.to_parquet(os.path.join(local_dir, 'test.parquet'))
+
+ if hdfs_dir is not None:
+ makedirs(hdfs_dir)
+
+ copy(src=local_dir, dst=hdfs_dir)
diff --git a/scripts/data_process/qa_search_train_merge.py b/scripts/data_process/qa_search_train_merge.py
new file mode 100644
index 0000000..ac8de65
--- /dev/null
+++ b/scripts/data_process/qa_search_train_merge.py
@@ -0,0 +1,105 @@
+# Copyright 2024 Bytedance Ltd. and/or its affiliates
+#
+# 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.
+"""
+Preprocess the QA dataset to parquet format
+"""
+
+import re
+import os
+import datasets
+
+from verl.utils.hdfs_io import copy, makedirs
+import argparse
+
+
+def make_prefix(dp, template_type):
+ question = dp['question']
+
+ # NOTE: also need to change reward_score/countdown.py
+ if template_type == 'base':
+ """This works for any base model"""
+ prefix = f"""Answer the given question. \
+You must conduct reasoning inside and first every time you get new information. \
+After reasoning, if you find you lack some knowledge, you can call a search engine by query and it will return the top searched results between and . \
+You can search as many times as your want. \
+If you find no further external knowledge needed, you can directly provide the answer inside and , without detailed illustrations. For example, Beijing . Question: {question}\n"""
+ else:
+ raise NotImplementedError
+ return prefix
+
+
+if __name__ == '__main__':
+ parser = argparse.ArgumentParser()
+ parser.add_argument('--local_dir', default='./data/nq_search')
+ parser.add_argument('--hdfs_dir', default=None)
+ parser.add_argument('--template_type', type=str, default='base')
+ parser.add_argument('--data_sources', default='nq')
+
+ args = parser.parse_args()
+
+ # data_source = 'nq'
+ data_sources = args.data_sources.split(',')
+ all_dataset = []
+
+ for data_source in data_sources:
+
+ dataset = datasets.load_dataset('RUC-NLPIR/FlashRAG_datasets', data_source)
+
+ train_dataset = dataset['train']
+
+ # add a row to each data item that represents a unique id
+ def make_map_fn(split):
+
+ def process_fn(example, idx):
+ example['question'] = example['question'].strip()
+ if example['question'][-1] != '?':
+ example['question'] += '?'
+ question = make_prefix(example, template_type=args.template_type)
+ solution = {
+ "target": example['golden_answers'],
+ }
+
+ data = {
+ "data_source": data_source,
+ "prompt": [{
+ "role": "user",
+ "content": question,
+ }],
+ "ability": "fact-reasoning",
+ "reward_model": {
+ "style": "rule",
+ "ground_truth": solution
+ },
+ "extra_info": {
+ 'split': split,
+ 'index': idx,
+ }
+ }
+ return data
+
+ return process_fn
+
+ train_dataset = train_dataset.map(function=make_map_fn('train'), with_indices=True)
+ all_dataset.append(train_dataset)
+
+ local_dir = args.local_dir
+ hdfs_dir = args.hdfs_dir
+
+ all_train_dataset = datasets.concatenate_datasets(all_dataset)
+ all_train_dataset.to_parquet(os.path.join(local_dir, 'train.parquet'))
+
+ if hdfs_dir is not None:
+ makedirs(hdfs_dir)
+
+ copy(src=local_dir, dst=hdfs_dir)
diff --git a/scripts/nq_hotpotqa/data_process.sh b/scripts/nq_hotpotqa/data_process.sh
new file mode 100644
index 0000000..ae1b45b
--- /dev/null
+++ b/scripts/nq_hotpotqa/data_process.sh
@@ -0,0 +1,10 @@
+WORK_DIR=your/work/dir
+LOCAL_DIR=$WORK_DIR/data/nq_hotpotqa_train
+
+## process multiple dataset search format train file
+DATA=nq,hotpotqa
+python $WORK_DIR/scripts/data_process/qa_search_train_merge.py --local_dir $LOCAL_DIR --data_sources $DATA
+
+## process multiple dataset search format test file
+DATA=nq,triviaqa,popqa,hotpotqa,2wikimultihopqa,musique,bamboogle
+python $WORK_DIR/scripts/data_process/qa_search_test_merge.py --local_dir $LOCAL_DIR --data_sources $DATA