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data-prepare/05-data-csv-swift-sft.py

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import json
import csv
def convert_to_alpaca_format(input_file, output_file):
"""
读取csv文件提取其中的question和answer列的数据并转换为 Alpaca 格式
输入csv格式:
question,A,B,C,D,E,F,G,H,I,J,answer
输出格式 (swift):
{
"system": "你是个优秀的论文分类师",
"conversation": [
{
"human": "Based on the title...",
"assistant": "D"
}
]
}
"""
choice_text=", A. quant-ph\nB. physics.chem-ph\nC. physics.atom-ph\nD. cond-mat.soft\nE. cs.RO\nF. cs.CL\nG. cs.SE\nH. cs.IR\nI. hep-th\nJ. hep-ph\nK. physics.optics\nL. cs.AI\nM. cs.CV\nN. nucl-th\nO. astro-ph\nP. math.PR\nQ. cs.OS\nR. eess.SP\nS. math.OC\nT. math.DS\nU. math.DG\nV. math.MP\nW. cs.MM\nX. stat.ME\nY. math.CO\nZ. cs.NE"
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print(f"转换数据: {input_file} -> {output_file}")
converted_data = []
with open(input_file, "r", encoding="utf-8-sig") as f:
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csv_reader = csv.DictReader(f)
for row in csv_reader:
try:
# 检查必要的列是否存在
if "question" not in row or "answer" not in row:
print(f"警告: 数据缺少必要列: {row}")
continue
# 创建新的 swift 格式数据
new_data = {
"system": "你是个优秀的论文分类师",
"conversation": [
{
"human": row["question"]+choice_text,
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"assistant": row["answer"]
}
]
}
converted_data.append(new_data)
except Exception as e:
print(f"处理行时发生错误: {str(e)}")
# 写入输出文件
with open(output_file, "w", encoding="utf-8") as f:
for item in converted_data:
f.write(json.dumps(item, ensure_ascii=False) + "\n")
print(f"转换完成! 共转换 {len(converted_data)} 条数据")
if __name__ == "__main__":
input_file = "G:\\11\\data-prepare\\eval_oc_data-26gai.csv"
output_file = "G:\\11\\data-prepare\\newformat_sft_test_data--swift-sft-26.jsonl" # 输出文件路径
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convert_to_alpaca_format(input_file, output_file)