app.py

import time 
import gradio as gr
import pandas as pd


def load_and_analyze_csv(file, text_field):
    df = pd.read_csv(file.name)
    
    if text_field not in df.columns:
        raise gr.Error(f"Error: Enter text column'{text_field}' not in CSV file.")
    
    fire_related = gr.CheckboxGroup(choices=df['text'].to_list()[:5])
    flood_related = gr.CheckboxGroup(choices=df['text'].to_list()[:7])
    not_related = gr.CheckboxGroup(choices=df['text'].to_list())
    time.sleep(5)
    return fire_related, flood_related, not_related

def analyze_selected_texts(selections):
    selected_texts = selections
    
    analysis_results = [f"Word Count: {len(text.split())}" for text in selected_texts]
    
    result_df = pd.DataFrame({"Selected Text": selected_texts, "Analysis": analysis_results})
    return result_df


with gr.Blocks() as demo:
    event_models = ["jayebaku/distilbert-base-multilingual-cased-crexdata-relevance-classifier"]
    
    with gr.Tab("Event Type Classification"):
        with gr.Row(equal_height=True):
            with gr.Column(scale=4):
                file_input = gr.File(label="Upload CSV File")
                
            with gr.Column(scale=6):
                text_field = gr.Textbox(label="Text field name", value="text")
                event_model = gr.Dropdown(event_models, label="Select classification model")
                predict_button = gr.Button("Start Prediction")
        
        with gr.Row(): # XXX confirm this is not a problem later --equal_height=True
            with gr.Column():
                gr.Markdown("""### Flood-related""")
                fire_checkbox_output = gr.CheckboxGroup(label="Select ONLY incorrect classifications")
                
            with gr.Column():
                gr.Markdown("""### Fire-related""")
                flood_checkbox_output = gr.CheckboxGroup(label="Select ONLY incorrect classifications")
                
            with gr.Column():
                gr.Markdown("""### None""")
                none_checkbox_output = gr.CheckboxGroup(label="Select ONLY incorrect classifications") 
                
            predict_button.click(load_and_analyze_csv, inputs=[file_input, text_field], outputs=[fire_checkbox_output, flood_checkbox_output, none_checkbox_output])           
                
    with gr.Tab("Question Answering"):
        # XXX Add some button disabling here, if the classification process is not completed first XXX
        
        analysis_button = gr.Button("Analyze Selected Texts")
        analysis_output = gr.DataFrame(headers=["Selected Text", "Analysis"])
        analysis_button.click(analyze_selected_texts, inputs=fire_checkbox_output, outputs=analysis_output)

demo.launch()