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import gradio as gr | |
import asyncio | |
from giskard.ml_worker.ml_worker import MLWorker | |
from pydantic import AnyHttpUrl | |
from giskard.settings import settings | |
from urllib.parse import urlparse | |
def run_ml_worker(url, api_key, hf_token): | |
# Always run an external ML worker | |
parsed_url = urlparse(url) | |
backend_url = AnyHttpUrl( | |
url=f"{parsed_url.scheme if parsed_url.scheme else 'http'}://{parsed_url.hostname}" | |
f"/{parsed_url.path if parsed_url.path and len(parsed_url.path) else settings.ws_path}", | |
scheme=parsed_url.scheme, | |
host=parsed_url.hostname, | |
path=parsed_url.path if parsed_url.path and len(parsed_url.path) else settings.ws_path, | |
) | |
print(f"Starting ML worker for {backend_url}") | |
ml_worker = MLWorker(False, backend_url, api_key, hf_token) | |
asyncio.run(ml_worker.start()) | |
return "ML worker finished its work" | |
iface = gr.Interface(fn=run_ml_worker, inputs=["text", "text", "text"], outputs="text") | |
iface.launch() | |