sparc multi-turn data set processing script

dbgpt_hub/configs/config.py

@@ -86,12 +86,15 @@
     # }
     # ,
     # {
+    # {
     #     "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 = """\

dbgpt_hub/data_process/multi_turn_process.py

@@ -0,0 +1,44 @@
+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)