# user_prompt = f"""You are an advanced semantic analyzer. For the given question, perform the following tasks step-by-step:

# 1. **Domain Identification**:
# - Determine the broad subject category (domain) this question belongs to.
# - Examples: film, history, biology, geography, politics, technology, etc (or any other suitable domain)

# 2. **Key Point Extraction**:
# - Identify 2-4 core semantic components that are crucial for answering
# - Include:
# • Key entities (e.g., films, people, locations)
# • Critical attributes (e.g., age, duration, population)
# • Core relationships (e.g., comparison, causality)
# • Measurement dimensions (e.g., time, quantity)
# - Exclude filler words and non-essential descriptors

# **Output Requirements**:
# - Use JSON format: {{"domain": "...", "key_points": [...]}}
# - Keep key_points concise (1-2 words each)
# - Use lowercase for all outputs
# - Separate multiple key_points with commas

# **Examples**:
# Question: "Which film whose director is younger, Charge It To Me or Danger: Diabolik?"
# Output: {{"domain": "film", "key_points": ["director", "age"]}}

# **Now process this question:**
# {{Question}}"""

# print(user_prompt.replace('{Question}', 'Which film whose director is younger, Charge It To Me or Danger: Diabolik?'))



# import json

# txt = "{'domain': 'film', 'key_points': ['directors', 'country', 'same']}"
# print(json.loads(txt))


# 使用ast.literal_eval解析Python风格字符串（需import ast）
# import ast
# py_style_txt = "{'domain': 'film', 'key_points': ['directors', 'country', 'same']}"
# print(ast.literal_eval(py_style_txt))  # 输出解析后的字典
import re
def extract_last_braced_content(s):
    """
    提取字符串中被 {} 包裹的内容，如果有多个则返回最后一个。
    
    :param s: 输入字符串
    :return: 最后一个被 {} 包裹的内容，如果没有则返回 None
    """
    # 使用正则表达式匹配所有被 {} 包裹的内容
    # matches = re.findall(r'\{(.*?)\}', s)
    matches = re.findall(r'\{.*?\}', s)
    
    # 如果有匹配的内容，返回最后一个；否则返回 None
    return matches[-1] if matches else None

# import json

# input_file_path = "/share/project/sunshuang/deep_search/data_syn/data/mixed_data/splits/tagged_domain_keypoints/final_selected_dataset.json"
# with open(input_file_path, 'r') as f:
#     data = json.load(f)

# print(len(data))

text = '{"domain": "development", "key_points": ["human development index", "adopted", "time", "employer"]}  \n*Note: The key point "human development index" exceeds the 1-2 word limit. To comply strictly, "hdi" (abbreviation) could be used instead for conciseness, but the original term is more precise. Adjusting for the requirement:*  \n{"domain": "development", "key_points": ["hdi", "adopted", "time", "employer"]}'
print(extract_last_braced_content(text))