concurrent_client.py

from gradio_client import Client, handle_file
import concurrent.futures
import time
from pathlib import Path


def make_prediction(client, image_url):
    """Make a single prediction"""
    try:
        result = client.predict(
            # image_list=handle_file(image_url),
            image_list=handle_file(image_url),
            api_name="/predict",
        )
        return result
    except Exception as e:
        return f"Error: {str(e)}"


def main(requests=16):
    # Single test image URL
    image_url = "https://img.freepik.com/free-photo/closeup-shot-cute-grey-kitty-isolated-white-background_181624-35013.jpg?ga=GA1.1.302994776.1729496489&semt=ais_hybrid"

    # Initialize client
    client = Client("http://127.0.0.1:7860/")

    print("\nSending 16 concurrent requests with the same image...")
    start_time = time.time()

    # Use ThreadPoolExecutor to send 16 requests concurrently
    with concurrent.futures.ThreadPoolExecutor(max_workers=16) as executor:
        futures = [
            executor.submit(make_prediction, client, image_url) for _ in range(requests)
        ]

        # Collect results as they complete
        results = []
        for i, future in enumerate(concurrent.futures.as_completed(futures)):
            try:
                result = future.result()
                results.append(result)
                print(f"Completed prediction {i+1}/{requests}")
            except Exception as e:
                print(f"Error in request {i+1}: {str(e)}")

    end_time = time.time()

    # Print results
    print(f"\nAll predictions completed in {end_time - start_time:.2f} seconds")
    print("\nResults:")
    for i, result in enumerate(results):
        print(f"\nRequest {i+1}:")
        print(result)


if __name__ == "__main__":
    main(16)