import pandas as pd
import os


def filepathInitalGroup(df: pd.DataFrame) -> pd.DataFrame:
    import os
    import pandas as pd
    from itertools import chain

    # 1. Split comma-separated filenames into lists
    df["filename_x"] = df["filename_x"].str.split(",")

    # 2. Explode so each filename has its own row
    df = df.explode("filename_x", ignore_index=True)

    # 3. Strip whitespace from filenames
    df["filename_x"] = df["filename_x"].str.strip()

    # 4. Split into directory and filename
    df["directory"] = df["filename_x"].apply(lambda x: os.path.dirname(x) if pd.notna(x) else "")
    df["filename"] = df["filename_x"].apply(lambda x: os.path.basename(x) if pd.notna(x) else "")

    # 5. Drop the original column
    df = df.drop(columns=["filename_x"])

    # 6. Ensure all columns are lists (except directory, which is the key)
    for col in df.columns:
        if col != "directory":
            df[col] = df[col].apply(lambda x: x if isinstance(x, list) else [x])

    # 7. Combine rows with the same directory, flatten lists, deduplicate
    def combine_lists(series):
        flat = list(chain.from_iterable(series))
        # deduplicate while preserving order
        return list(dict.fromkeys(flat))

    df = df.groupby("directory", as_index=False).agg(combine_lists)

    return df