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import gradio as gr |
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import logging |
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import subprocess |
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import threading |
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import sys |
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import os |
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from giskard.settings import settings |
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logger = logging.getLogger(__name__) |
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logging.getLogger().setLevel(logging.INFO) |
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logging.getLogger("giskard").setLevel(logging.INFO) |
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GSK_HUB_URL = 'GSK_HUB_URL' |
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GSK_API_KEY = 'GSK_API_KEY' |
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HF_SPACE_HOST = 'SPACE_HOST' |
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HF_SPACE_TOKEN = 'GSK_HUB_HFS' |
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READONLY = os.environ.get("READONLY") if os.environ.get("READONLY") else False |
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LOG_FILE = "output.log" |
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def read_logs(): |
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sys.stdout.flush() |
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try: |
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with open(LOG_FILE, "r") as f: |
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return f.read() |
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except Exception: |
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return "ML worker not running" |
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previous_url = "" |
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ml_worker = None |
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def read_status(): |
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if ml_worker: |
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return f"ML worker serving {previous_url}" |
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elif len(previous_url): |
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return f"ML worker exited for {previous_url}" |
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else: |
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return "ML worker not started" |
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def run_ml_worker(url, api_key, hf_token): |
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global ml_worker, previous_url |
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previous_url = url |
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ml_worker = subprocess.Popen( |
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[ |
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"giskard", "worker", "start", |
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"-u", f"{url}", "-k", f"{api_key}", "-t", f"{hf_token}" |
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], |
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stdout=open(LOG_FILE, "w"), stderr=subprocess.STDOUT |
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) |
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args = ml_worker.args[:3] |
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logging.info(f"Process {args} exited with {ml_worker.wait()}") |
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ml_worker = None |
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def stop_ml_worker(): |
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global ml_worker, previous_url |
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if ml_worker is not None: |
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logging.info(f"Stopping ML worker for {previous_url}") |
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ml_worker.terminate() |
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ml_worker = None |
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logging.info("ML worker stopped") |
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return "ML worker stopped" |
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return "ML worker not started" |
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def start_ml_worker(url, api_key, hf_token): |
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if not url or len(url) < 1: |
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return "Please provide URL of Giskard" |
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stop_ml_worker() |
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logging.info(f"Starting ML worker for {url}") |
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thread = threading.Thread(target=run_ml_worker, args=(url, api_key, hf_token)) |
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thread.start() |
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return f"ML worker running for {url}" |
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theme = gr.themes.Soft( |
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primary_hue="green", |
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) |
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with gr.Blocks(theme=theme) as iface: |
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with gr.Row(): |
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with gr.Column(): |
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url = os.environ.get(GSK_HUB_URL) if os.environ.get(GSK_HUB_URL) else f"http://{settings.host}:{settings.ws_port}" |
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url_input = gr.Textbox( |
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label="Giskard Hub URL", |
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interactive=not READONLY, |
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value=url, |
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) |
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api_key_input = gr.Textbox( |
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label="Giskard Hub API Key", |
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interactive=not READONLY, |
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type="password", |
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value=os.environ.get(GSK_API_KEY), |
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placeholder="gsk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx", |
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) |
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hf_token_input = gr.Textbox( |
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label="Hugging Face Spaces Token", |
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interactive=not READONLY, |
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type="password", |
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value=os.environ.get(HF_SPACE_TOKEN), |
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info="if using a private Giskard Hub on Hugging Face Spaces", |
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) |
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output = gr.Textbox(label="Status") |
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with gr.Row(): |
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run_btn = gr.Button("Run", variant="primary") |
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run_btn.click(start_ml_worker, [url_input, api_key_input, hf_token_input], output) |
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stop_btn = gr.Button("Stop", variant="stop", interactive=not READONLY) |
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stop_btn.click(stop_ml_worker, None, output) |
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logs = gr.Textbox(label="Giskard ML worker log:") |
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iface.load(read_logs, None, logs, every=0.5) |
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iface.load(read_status, None, output, every=5) |
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if os.environ.get(GSK_HUB_URL) and os.environ.get(GSK_API_KEY): |
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start_ml_worker(os.environ.get(GSK_HUB_URL), os.environ.get(GSK_API_KEY), os.environ.get(HF_SPACE_TOKEN)) |
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iface.queue() |
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iface.launch() |
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