#!/usr/bin/python3
# -*- coding: utf-8 -*-
import argparse
import json
from pathlib import Path

import pandas as pd
from tqdm import tqdm

from project_settings import project_path


def get_args():
    parser = argparse.ArgumentParser()

    parser.add_argument(
        "--data_dir",
        default=(project_path / "original_data/weibo-400w").as_posix(),
        type=str
    )
    parser.add_argument(
        "--output_file",
        default=(project_path / "data/weibo.jsonl"),
        type=str
    )

    args = parser.parse_args()
    return args


def main():
    args = get_args()

    data_dir = Path(args.data_dir)

    questions = list()
    with open(data_dir / "stc_weibo_train_post", "r", encoding="utf-8") as f:
        for row in f:
            row = str(row).strip()
            row = "".join(row.split())
            questions.append(row)

    answers = list()
    with open(data_dir / "stc_weibo_train_response.part", "r", encoding="utf-8") as f:
        for row in f:
            row = str(row).strip()
            row = "".join(row.split())
            answers.append(row)

    if len(questions) != len(answers):
        raise AssertionError

    with open(args.output_file, "w", encoding="utf-8") as f:
        for question, answer in tqdm(zip(questions, answers)):
            row = {
                "conversation": [
                    {"role": "human", "message": question},
                    {"role": "assistant", "message": answer},
                ],
                "category": None,
                "data_source": "weibo",
            }
            row = json.dumps(row, ensure_ascii=False)
            f.write("{}\n".format(row))
    return


if __name__ == '__main__':
    main()