import gradio as gr
import pandas as pd
from io import BytesIO

def convert_file(input_file, conversion_type):
    # Check if a file was uploaded
    if input_file is None:
        raise ValueError("Please upload a file.")

    file_name = input_file.name
    file_extension = file_name.lower().split('.')[-1]
    file_bytes = input_file.read()

    df = None
    output_file = None
    converted_format = None

    # Conversion: CSV to Parquet
    if conversion_type == "CSV to Parquet":
        if file_extension != "csv":
            raise ValueError("For CSV to Parquet conversion, please upload a CSV file.")
        df = pd.read_csv(BytesIO(file_bytes))
        output_file = "output.parquet"
        df.to_parquet(output_file, index=False)
        converted_format = "Parquet"
    # Conversion: Parquet to CSV
    elif conversion_type == "Parquet to CSV":
        if file_extension != "parquet":
            raise ValueError("For Parquet to CSV conversion, please upload a Parquet file.")
        df = pd.read_parquet(BytesIO(file_bytes))
        output_file = "output.csv"
        df.to_csv(output_file, index=False)
        converted_format = "CSV"
    else:
        raise ValueError("Invalid conversion type selected.")

    # Generate a preview of the top 10 rows
    preview = df.head(10).to_string(index=False)
    info_message = (
        f"Input file: {file_name}\n"
        f"Converted file format: {converted_format}\n\n"
        f"Preview (Top 10 Rows):\n{preview}"
    )
    return output_file, info_message

demo = gr.Interface(
    fn=convert_file,
    inputs=[
        gr.File(label="Upload CSV or Parquet File"),
        gr.Radio(choices=["CSV to Parquet", "Parquet to CSV"], label="Conversion Type")
    ],
    outputs=[
        gr.File(label="Converted File"),
        gr.Textbox(label="Preview (Top 10 Rows)", lines=15)
    ],
    title="CSV <-> Parquet Converter",
    description=(
        "Upload a CSV or Parquet file and select the conversion type. "
        "The app converts the file to the opposite format and displays a preview of the top 10 rows."
    )
)

if __name__ == "__main__":
    demo.launch()