|
import gradio as gr |
|
|
|
from urllib.parse import urlparse |
|
|
|
import subprocess |
|
import threading |
|
|
|
import sys |
|
|
|
LOG_FILE = "output.log" |
|
|
|
def read_logs(): |
|
sys.stdout.flush() |
|
with open(LOG_FILE, "r") as f: |
|
return f.read() |
|
|
|
|
|
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()}") |
|
|
|
|
|
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() |
|
print("ML worker stopped") |
|
return "ML worker stopped" |
|
return "ML worker not started" |
|
|
|
|
|
def start_ml_worker(url, api_key, hf_token): |
|
|
|
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}" |
|
|
|
|
|
with gr.Blocks() as iface: |
|
with gr.Row(): |
|
with gr.Column(): |
|
url_input = gr.Textbox(label="Giskard Hub URL") |
|
api_key_input = gr.Textbox(label="Giskard Hub API Key", placeholder="gsk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx") |
|
hf_token_input = gr.Textbox(label="Hugging Face Spaces Token") |
|
|
|
output = gr.Textbox(label="Status") |
|
with gr.Row(): |
|
run_btn = gr.Button("Run") |
|
run_btn.click(start_ml_worker, [url_input, api_key_input, hf_token_input], output) |
|
|
|
stop_btn = gr.Button("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() |
|
|
