Update app.py

app.py

@@ -5,9 +5,12 @@ from bittensor.extrinsics.serving import get_metadata
 from dataclasses import dataclass
 import requests
 import math
+import os
 import datetime
 import time
 from dotenv import load_dotenv
+from huggingface_hub import HfApi
+from apscheduler.schedulers.background import BackgroundScheduler
 
 load_dotenv()
 
@@ -17,6 +20,8 @@ IMAGE = """<a href="https://discord.gg/jqVphNsB4H" target="_blank"><img src="htt
 HEADER = """<h2 align="center" class="typewriter"><a href="https://github.com/NousResearch/finetuning-subnet" target="_blank">Subnet 6</a> is a <a href="https://bittensor.com/" target="_blank">Bittensor</a> subnet that incentivizes the creation of the best open models by evaluating submissions on a constant stream of newly generated synthetic GPT-4 data. The models with the best <a href="https://github.com/NousResearch/finetuning-subnet/blob/master/docs/validator.md" target="_blank">head-to-head loss</a> on the evaluation data receive a steady emission of TAO.</h3>"""
 EVALUATION_DETAILS = """<b>Name</b> is the 🤗 Hugging Face model name (click to go to the model card). <b>Rewards / Day</b> are the expected rewards per day for each model. <b>Perplexity</b> is represents the loss on all of the evaluation data for the model as calculated by the validator (lower is better). <b>UID</b> is the Bittensor user id of the submitter. <b>Block</b> is the Bittensor block that the model was submitted in. More stats on <a href="https://taostats.io/subnets/netuid-6/" target="_blank">taostats</a>."""
 EVALUATION_HEADER = """<h3 align="center">Shows the latest internal evaluation statistics as calculated by a validator run by Nous Research</h3>"""
+H4_TOKEN = os.environ.get("H4_TOKEN", None)
+API = HfApi(token=H4_TOKEN)
 REPO_ID = "NousResearch/finetuning_subnet_leaderboard"
 METAGRAPH_RETRIES = 5
 METAGRAPH_DELAY_SECS = 3
@@ -202,4 +207,11 @@ with demo:
             visible=True,
         )
 
+def restart_space():
+    API.restart_space(repo_id=REPO_ID, token=H4_TOKEN)
+
+scheduler = BackgroundScheduler()
+scheduler.add_job(restart_space, "interval", seconds=60 * 10) # restart every 10 minutes
+scheduler.start()
+
 demo.launch()