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import gradio as gr
import pandas as pd
from data_labelling import main as label_data
def preview_data(file):
if file is None:
return "Please upload a CSV file."
df = pd.read_csv(file.name)
preview = df.head() # Show the first few lines of the dataset
return gr.DataFrame(preview), df.shape # Return the preview and the shape of the dataset
def run_labeling(input_file, output_file):
# Run the labeling script
labeled_file = label_data(input_file, output_file)
return labeled_file # Return the path to the labeled file
def main_interface():
with gr.Blocks() as demo:
gr.Markdown("# YouTube Comments Labeling")
with gr.Row():
file_input = gr.File(label="Upload your CSV file")
preview_button = gr.Button("Preview Data")
data_preview = gr.DataFrame()
data_shape = gr.Textbox(label="Dataset Shape", interactive=False)
preview_button.click(preview_data, inputs=file_input, outputs=[data_preview, data_shape])
with gr.Row():
label_option = gr.Radio(["No", "Yes"], label="Do you want to label your dataset?", value="No")
output_name = gr.Textbox(label="Output File Name (with .csv extension)", value="labeled_dataset.csv")
label_button = gr.Button("Run Labeling")
labeled_file_path = gr.Textbox(label="Labeled File Path", interactive=False)
download_button = gr.File(label="Download Labeled File")
def handle_labeling(input_file, label_choice, output_name):
if label_choice == "Yes":
labeled_file = run_labeling(input_file.name, output_name)
return labeled_file, labeled_file
else:
return None, None
label_button.click(
handle_labeling,
inputs=[file_input, label_option, output_name],
outputs=[labeled_file_path, download_button]
)
demo.launch()
if __name__ == "__main__":
main_interface()
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