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from warnings import filterwarnings
filterwarnings('ignore')
import os
import uuid
import joblib
import json
import gradio as gr
import pandas as pd
from huggingface_hub import CommitScheduler
from pathlib import Path
# Configure the logging functionality
log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"
log_folder = log_file.parent
repo_id = "operand-logs"
# Create a commit scheduler
scheduler = CommitScheduler(
repo_id=repo_id,
repo_type="dataset",
folder_path=log_folder,
path_in_repo="data",
every=2
)
def dprocess(command):
with scheduler.lock:
with log_file.open("a") as f:
f.write(json.dumps(
{
'result': 42
}
))
f.write("\n")
return 42
# Set-up the Gradio UI
textbox = gr.Textbox(label='Command:')
company = gr.Radio(label='Company:',
choices=["aws", "google", "IBM", "Meta", "msft"],
value="aws")
# Create Gradio interface
# For the inputs parameter of Interface provide [textbox,company] with outputs parameter of Interface provide prediction
demo = gr.Interface(fn=dprocess,
inputs=[textbox, company],
outputs="text",
title="operand data automation CLI",
description="",
theme=gr.themes.Soft())
demo.queue()
demo.launch() |