import gradio as gr from urllib.parse import urlparse import subprocess import threading import sys import os from giskard.settings import settings LOG_FILE = "output.log" def read_logs(): sys.stdout.flush() try: with open(LOG_FILE, "r") as f: return f.read() except Exception: return "ML worker not running" previous_url = "" ml_worker = None def read_status(): if ml_worker: return f"ML worker serving {previous_url}" elif len(previous_url): return f"ML worker exited for {previous_url}" else: return "ML worker not started" def run_ml_worker(url, api_key, hf_token): global ml_worker, previous_url previous_url = url ml_worker = subprocess.Popen( [ "giskard", "worker", "start", "-u", f"{url}", "-k", f"{api_key}", "-t", f"{hf_token}" ], stdout=open(LOG_FILE, "w"), stderr=subprocess.STDOUT ) args = ml_worker.args print(f"Process {args} exited with {ml_worker.wait()}") ml_worker = None def stop_ml_worker(): global ml_worker, previous_url if ml_worker is not None: print(f"Stopping ML worker for {previous_url}") ml_worker.terminate() ml_worker = None print("ML worker stopped") return "ML worker stopped" return "ML worker not started" def start_ml_worker(url, api_key, hf_token): if not url or len(url) < 1: return "Please provide URL of Giskard" # Always run an external ML worker stop_ml_worker() print(f"Starting ML worker for {url}") thread = threading.Thread(target=run_ml_worker, args=(url, api_key, hf_token)) thread.start() return f"ML worker running for {url}" theme = gr.themes.Soft( primary_hue="green", ) with gr.Blocks(theme=theme) as iface: with gr.Row(): with gr.Column(): url_input = gr.Textbox( label="Giskard Hub URL", value=f"htts://{os.environ.get('SPACE_HOST')}" if os.environ.get("SPACE_HOST") else f"http://{settings.host}:{settings.ws_port}", ) api_key_input = gr.Textbox( label="Giskard Hub API Key", value=os.environ.get("GSK_API_KEY"), placeholder="gsk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx", ) hf_token_input = gr.Textbox( label="Hugging Face Spaces Token", info="if using a private Giskard Hub on Hugging Face Spaces", ) output = gr.Textbox(label="Status") with gr.Row(): run_btn = gr.Button("Run", variant="primary") run_btn.click(start_ml_worker, [url_input, api_key_input, hf_token_input], output) stop_btn = gr.Button("Stop", variant="stop") stop_btn.click(stop_ml_worker, None, output) logs = gr.Textbox(label="Giskard ML worker log:") iface.load(read_logs, None, logs, every=0.5) iface.load(read_status, None, output, every=5) iface.queue() iface.launch()