app.py

import gradio as gr
from huggingface_hub import InferenceClient

from datasets import load_dataset
import duckdb

global ds


def load_new_dataset():
    gr.Info(message="Loading dataset...")
    ds = load_dataset("fka/awesome-chatgpt-prompts", split="train")

def run_query(input: str):
    try:
        df_results = duckdb.sql(
            query=f"""
            SELECT *
            FROM train
            WHERE act LIKE '%{input}%'
            """
        ).to_df()

        logging_message = f"Results for '{input}' found."
    except Exception as e:
        raise gr.Error(f"Error running query: {e}")
    
    return df_results, logging_message

#----------------------

with gr.Blocks() as demo:
    text_input = gr.Textbox(visible=True, label="Enter value for 'act':")
    btn_run = gr.Button(visible=True, value="Search")
    results_output = gr.Dataframe(label="Results", visible=True, wrap=True)
    logging_output = gr.Label(visible="True", value="My first logging message")
    
    btn_run.click(
        fn=run_query,  # Call the run_query function and update the label
        inputs=text_input,
        outputs=[results_output, logging_output]  # Update both the DataFrame and the label
    )

#----------------------

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