belle

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#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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import pandas as pd
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import json
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import argparse
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def read_data(path):
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    datas = []
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    with open(path) as f:
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        for l in f.readlines():
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            datas.append(eval(l))  # json.loads(l) 在加载某些行数据存在问题，这里使用eval
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    return datas
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if __name__ == "__main__":
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    parser = argparse.ArgumentParser(
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        description="Finetune a transformers model on a causal language modeling task"
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    )
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    parser.add_argument(
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        "--prompt_path",
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        type=str,
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        default="eval_prompt.json",
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    )
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    parser.add_argument(
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        "--eval_set_path",
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        type=str,
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        default="eval_set.json",
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    )
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    parser.add_argument(
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        "--html_path",
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        type=str,
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        default="template_html/ChatGPT_Score.html.temp",
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    )
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    parser.add_argument(
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        "--output_html_path",
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        type=str,
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        default="ChatGPT_Score.html",
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    )
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    args = parser.parse_args()
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    prompt_path = args.prompt_path
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    eval_set_path = args.eval_set_path
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    output_html_path = args.output_html_path
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    html_path = args.html_path
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    prompt_data = read_data(prompt_path)
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    eval_set_data = read_data(eval_set_path)
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    eval_set_data = json.dumps(eval_set_data, ensure_ascii=False)
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    prompt_data = json.dumps(prompt_data, ensure_ascii=False)
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    eval_set_str = f"const eval_set = {eval_set_data}"
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    eval_prompt_str = f"const eval_prompt = {prompt_data}"
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    with open(html_path, "r") as f:
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        text = f.read()
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        text = text.replace("const eval_set = []", eval_set_str)
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        text = text.replace("const eval_prompt = []", eval_prompt_str)
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    with open(output_html_path, "w") as f:
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        f.write(text)
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