132 lines
4.8 KiB
Python
132 lines
4.8 KiB
Python
"""
|
||
对821道英文问题进行处理
|
||
1. 判断是否包含多个子问题，将问题拆分为完整子问题(去掉推理过程，只保留最后结果)
|
||
2. 判断题目类型
|
||
3. 将题目做成选择题
|
||
对计算题，在数值附近随机生成三个相似答案作为错误选项
|
||
对简答题，与标准答案最相近的其他问题的答案作为三个错误选项
|
||
4. 将正确和错误选项随机打乱，生成ABCD选择题的模型
|
||
5. 添加prompt，并将选择题包裹在[ANSWER]<answer>[/ANSWER]标签中
|
||
6. 模型打分
|
||
"""
|
||
import json
|
||
import time
|
||
from openai import OpenAI
|
||
import re
|
||
from prompts import SINGLE_QUESTION_PROMPTS, QA_TYPE_PROMPTS, ONLY_ANSWER_PROMPTS
|
||
|
||
API_KEY="sk-oYh3Xrhg8oDY2gW02c966f31C84449Ad86F9Cd9dF6E64a8d"
|
||
BASE_URL="https://vip.apiyi.com/v1"
|
||
MODEL_DEEPSEEK_V3="deepseek-chat"
|
||
|
||
def load_data(file_path):
|
||
with open(file_path, 'r', encoding='utf-8') as f:
|
||
data = json.load(f)
|
||
return data
|
||
|
||
def process_response(response):
|
||
"""Extract and parse JSON from a response."""
|
||
json_match = re.search(r'```(?:json)?\s*([\s\S]*?)\s*```', response)
|
||
json_str = json_match.group(1) if json_match else response.strip()
|
||
json_str = re.sub(r'(\$[^\$]*\$)', lambda m: m.group(1).replace('\\', '\\\\'), json_str)
|
||
json_str = json_str.replace('\\"', '"').replace("\\'", "'")
|
||
return json_str
|
||
|
||
def save_data(data, output_file):
|
||
with open(output_file, 'w', encoding='utf-8') as f:
|
||
json.dump(data, f, ensure_ascii=False, indent=2)
|
||
|
||
def split_complex_question(question, answer):
|
||
client = OpenAI(api_key = API_KEY,base_url = BASE_URL)
|
||
try:
|
||
response = client.chat.completions.create(
|
||
model= MODEL_DEEPSEEK_V3,
|
||
messages=[
|
||
{"role": "system", "content": "You are an expert in decomposing complex technical questions into independent sub-questions and providing corresponding complete answers with preserved context, precision, and technical terminology. "},
|
||
{"role": "user", "content": SINGLE_QUESTION_PROMPTS.replace("{question}",question).replace("{answer}",answer)}
|
||
],
|
||
stream = False,
|
||
temperature = 0
|
||
)
|
||
result = response.choices[0].message.content.strip()
|
||
# print(result)
|
||
return 1 if "It's a single issue." in result else json.loads(process_response(result))
|
||
except Exception as e:
|
||
print(f"API调用错误: {e}")
|
||
return [{"question": question, "answer": answer}]
|
||
|
||
def single_question_process(data):
|
||
single_question_data = []
|
||
total = len(data)
|
||
for i, item in enumerate(data):
|
||
print(f"处理第 {i+1}/{total} 条数据...")
|
||
question = item["question"]
|
||
answer = item["answer"]
|
||
split_data = split_complex_question(question, answer)
|
||
|
||
if isinstance(split_data, list):
|
||
for q_data in split_data:
|
||
single_question_data.append({
|
||
"idx":item["idx"],
|
||
"question": q_data["question"],
|
||
"answer": q_data["answer"]
|
||
})
|
||
else:
|
||
single_question_data.append({
|
||
"idx":item["idx"],
|
||
"question": question,
|
||
"answer": answer
|
||
})
|
||
|
||
if (i+1) % 10 == 0:
|
||
time.sleep(2)
|
||
return single_question_data
|
||
|
||
def classify_qa_type(question, answer):
|
||
client = OpenAI(api_key = API_KEY,base_url = BASE_URL)
|
||
try:
|
||
response = client.chat.completions.create(
|
||
model = MODEL_DEEPSEEK_V3,
|
||
messages=[
|
||
{"role": "system", "content": "You are a helpful assistant"},
|
||
{"role": "user", "content": QA_TYPE_PROMPTS.replace("{question}",question).replace("{answer}",answer)}
|
||
],
|
||
stream=False
|
||
)
|
||
result = response.choices[0].message.content.strip().lower()
|
||
# print(result)
|
||
return {"1": "Calculation", "2": "Multiple choice", "3": "True/False"}.get(result, "Other")
|
||
except Exception as e:
|
||
print(f"API调用错误: {e}")
|
||
return "Other"
|
||
|
||
def qa_type_process(data):
|
||
total = len(data)
|
||
for i, item in enumerate(data):
|
||
print(f"处理第 {i+1}/{total} 条数据...")
|
||
question = item["question"]
|
||
answer = item["answer"]
|
||
label = classify_qa_type(question, answer)
|
||
item["type"] = label
|
||
|
||
if (i+1) % 10 == 0:
|
||
time.sleep(2)
|
||
return data
|
||
|
||
def main():
|
||
input_file = "/home/ubuntu/50T/fsy/layer2/QA/code/821.json"
|
||
output_file = "/home/ubuntu/50T/fsy/layer2/QA/code/processed_data.json"
|
||
data = load_data(input_file)
|
||
|
||
# step:1
|
||
single_question_data = single_question_process(data)
|
||
# step:2
|
||
qa_type_data = qa_type_process(single_question_data)
|
||
# step:3
|
||
|
||
|
||
# save_data(processed_data, output_file)
|
||
print(f"处理完成，结果已保存到 {output_file}")
|
||
|
||
if __name__ == "__main__":
|
||
main() |