second commit

layer1/ALL/SciEval-process.py

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+import json
+
+# 读取 JSON 文件
+def transform_json(file_path):
+    with open(file_path, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+    
+    new_json=[]
+
+    for item in data:
+        question = item["question"]
+        answer = item["answer"][0]
+        
+        parts = question.split("\n\nA.")
+        new_question = parts[0].strip()
+        options_block = "A." + parts[1]
+        
+        texts = []
+        labels = []
+        label_order = ["A", "B", "C", "D"]
+
+        current_label_index = 0
+        while current_label_index < len(label_order):
+            current_label = label_order[current_label_index]
+            next_label = label_order[current_label_index + 1] if current_label_index + 1 < len(label_order) else None
+            
+            if next_label:
+                parts = options_block.split(f"\n{next_label}.")
+                current_option = parts[0].replace(f"{current_label}.", "").strip()  # 去掉标签前缀并移除多余空格
+                options_block = next_label + "." + parts[1]  # 剩余的内容保留
+            else:
+                current_option = options_block.replace(f"{current_label}.", "").strip()  # 如果没有下一个标签，移除\n\nAnswer:
+                current_option = current_option.replace("\n\nAnswer:", "") 
+
+
+            # 添加当前选项到 texts 和 labels
+            texts.append(current_option)
+            labels.append(current_label)
+            
+            # 递增标签索引
+            current_label_index += 1
+        
+        transformed_data = {
+            "question": new_question,
+            "choices": {
+                "text": texts,
+                "label": labels
+                },
+            "answer": f"[ANSWER]{answer}[/ANSWER]",
+            "prompt": "You MUST include the letter(s) of the correct answer (separated by comma if there are many) within the following tags: [ANSWER] and [/ANSWER]. No explanations and other information. Only return the '[ANSWER]<answer>[/ANSWER]'. We require this because we use automatic parsing."
+        }
+        new_json.append(transformed_data)
+
+    return new_json
+
+input_path = '/home/ubuntu/50T/fsy/benchmark-dataset-third/ALL/SciEval-valid-mat.json'  
+output_path = '/home/ubuntu/50T/fsy/benchmark-dataset-third/ALL/13-Scieval-val.json'
+transformed_data = transform_json(input_path)
+
+with open(output_path, 'w', encoding='utf-8') as f:
+    json.dump(transformed_data, f, ensure_ascii= False, indent=2)