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from transformers import BertTokenizer, BertForQuestionAnswering
import torch

# 加载预训练模型和分词器
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForQuestionAnswering.from_pretrained('bert-base-uncased')

def answer_question(question, context):
    inputs = tokenizer.encode_plus(question, context, add_special_tokens=True, return_tensors="pt")
    input_ids = inputs["input_ids"].tolist()[0]

    outputs = model(**inputs)
    answer_start = torch.argmax(outputs.start_logits)
    answer_end = torch.argmax(outputs.end_logits) + 1

    answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(input_ids[answer_start:answer_end]))
    return answer

# 示例使用
question = "What is the capital of France?"
context = "Paris is the capital of France."
print(answer_question(question, context))