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import gradio as gr |
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from giskard.ml_worker.ml_worker import MLWorker |
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from pydantic import AnyHttpUrl |
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from giskard.settings import settings |
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from urllib.parse import urlparse |
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import asyncio |
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import threading |
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import sys |
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LOG_FILE = "output.log" |
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class Logger: |
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def __init__(self, filename): |
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self.terminal = sys.stdout |
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self.log = open(filename, "w") |
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def write(self, message): |
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self.terminal.write(message) |
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self.log.write(message) |
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def flush(self): |
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self.terminal.flush() |
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self.log.flush() |
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def isatty(self): |
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return False |
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sys.stdout = Logger(LOG_FILE) |
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def read_logs(): |
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sys.stdout.flush() |
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with open(LOG_FILE, "r") as f: |
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return f.read() |
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previous_url = "" |
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ml_worker = None |
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def run_ml_worker(ml_worker: MLWorker): |
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loop = asyncio.new_event_loop() |
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asyncio.set_event_loop(loop) |
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loop.run_until_complete(ml_worker.start()) |
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loop.close() |
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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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print(f"Stopping ML worker for {previous_url}") |
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ml_worker.stop() |
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print("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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global ml_worker, previous_url |
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stop_ml_worker() |
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parsed_url = urlparse(url) |
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backend_url = AnyHttpUrl( |
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url=f"{parsed_url.scheme if parsed_url.scheme else 'http'}://{parsed_url.hostname}" |
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f"/{parsed_url.path if parsed_url.path and len(parsed_url.path) else settings.ws_path}", |
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scheme=parsed_url.scheme, |
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host=parsed_url.hostname, |
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path=parsed_url.path if parsed_url.path and len(parsed_url.path) else settings.ws_path, |
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) |
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print(f"Starting ML worker for {backend_url}") |
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ml_worker = MLWorker(False, backend_url, api_key, hf_token) |
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previous_url = backend_url |
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thread = threading.Thread(target=run_ml_worker, args=(ml_worker,)) |
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thread.start() |
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return f"ML worker running for {backend_url}" |
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with gr.Blocks() as iface: |
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with gr.Row(): |
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with gr.Column(): |
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url_input = gr.Textbox(label="Giskard Hub URL") |
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api_key_input = gr.Textbox(label="Giskard Hub API Key", placeholder="gsk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx") |
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hf_token_input = gr.Textbox(label="Hugging Face Spaces Token") |
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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") |
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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") |
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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.queue() |
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iface.launch() |
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