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sparc multi-turn data set processing script (eosphoros-ai#225)
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zhanghy-sketchzh authored Jan 27, 2024
1 parent 81d69d9 commit ff50c75
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5 changes: 4 additions & 1 deletion dbgpt_hub/configs/config.py
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# }
# ,
# {
# {
# "data_source": "sparc",
# "train_file": ["train.json"],
# "train_tables_file": "tables.json",
# "dev_tables_file": "tables.json",
# "dev_file": ["dev.json"],
# "tables_file": "tables.json",
# "db_id_name": "database_id",
# "is_multiple_turn": True,
# "output_name": "query",
# }
]
INSTRUCTION_PROMPT = """\
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44 changes: 44 additions & 0 deletions dbgpt_hub/data_process/multi_turn_process.py
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import json


def process_data(input_file_path):
# 读取原始数据
with open(input_file_path, "r") as file:
original_data = json.load(file)

# 新格式的数据列表
formatted_data = []

# 遍历原始数据
for entry in original_data:
merged_entry = []
instruction = entry["instruction"] + entry["input"]
history = entry["history"]

# 合并指令和历史记录
merged_entry.append(instruction)
merged_entry.append(entry["output"])

# 添加历史记录
for pair in history[1:]:
for item in pair:
merged_entry.append(item)

# 添加布尔值列表
boolean_flags = [True, False] * len(history)
formatted_entry = [merged_entry, boolean_flags]
formatted_data.append(formatted_entry)

# 将转换后的数据写入文件
with open(input_file_path, "w") as file:
json.dump(formatted_data, file, indent=4)

print(f"数据已成功转换并写入到文件:{input_file_path}")


# 指定输入和输出文件路径
train_file_path = "./dbgpt_hub/data/example_text2sql_train.json"
dev_file_path = "./dbgpt_hub/data/example_text2sql_dev.json"
# 处理数据
process_data(train_file_path)
process_data(dev_file_path)

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