app.py

import gradio as gr
from gradio_client import Client

client = Client("Renecto/parallel_en2fr")

def fetch_result(ens):
    result = client.predict(
		ens=ens
		api_name="/ens2frs"
    )
    return result

def ens2frs(ens1, ens2, ens3):
    tasks = [ens1, ens2, ens3]
    with concurrent.futures.ThreadPoolExecutor() as executor:
        results = list(executor.map(fetch_result, tasks))
    frs = []
    for result, duration in results:
        print(f"Result:{result}, Time taken: {duration:.2f} seconds")
        frs.extend([result, duration])
        acum += duration

    end_total = time.time()
    duration_total = end_total - start_total
    print(f"total time:  {duration_total:.2f} seconds")
    print(f"acum time:  {acum:.2f} seconds")
    print(f"Efficiency:  {acum/duration_total*100:.1f} %")
    return frs
    

with gr.Blocks() as app:
    ens1 = gr.TextArea(
           """love
book
world
wide""")
    ens2 = gr.TextArea(
           """hate
television
local
narrow""")
    ens3 = gr.TextArea(
           """neutral
radio
urban
normal""")
    button1 = gr.Button("↓en2fr")
    output = gr.Dataframe(label="result")

    button1.click(ens2frs, inputs=ens, outputs=output)

app.launch(debug=True, share=True)