prepare.py

import pandas as pd
import json
import re


def remove_prefix(text, prefix_pattern):
    """
    Removes the prefix matching the given pattern from the text.
    """
    return re.sub(prefix_pattern, "", text).strip()


def main():
    # Read the Excel file
    try:
        df = pd.read_excel("data/manabi.xlsx")
        print("Excel file read successfully.")
    except FileNotFoundError:
        print("The file 'data/manabi.xlsx' was not found. Please check the file path.")
        return
    except Exception as e:
        print(f"An error occurred while reading the Excel file: {e}")
        return

    # Check if the necessary columns exist
    if "質問" not in df.columns or "回答" not in df.columns:
        print("The Excel file must contain '質問' and '回答' columns.")
        return

    # Initialize the list to store processed data
    qa_list = []

    # Iterate over each row in the DataFrame
    for index, row in df.iterrows():
        raw_question = str(row["質問"])
        raw_answer = str(row["回答"])

        # Remove prefixes using regex patterns
        question = remove_prefix(raw_question, r"^Q\d+\.\s*")
        answer = remove_prefix(raw_answer, r"^A\.\s*")

        qa_list.append({"question": question, "answer": answer})

    # Save the list to a JSON file
    try:
        with open("data/qa_data.json", "w", encoding="utf-8") as json_file:
            json.dump(qa_list, json_file, ensure_ascii=False, indent=2)
        print("Data has been successfully saved to 'data/qa_data.json'.")
    except Exception as e:
        print(f"An error occurred while writing to JSON file: {e}")


if __name__ == "__main__":
    main()