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import atexit
import datetime
from flask import Flask, request, jsonify
from apscheduler.schedulers.background import BackgroundScheduler
import utils
app = Flask(__name__)
# Global variables (saves time on loading data)
state_vars = None
reload_timestamp = datetime.datetime.now().strftime('%D %T')
def load_data(test=False):
"""
Reload the state variables
"""
global state_vars, reload_timestamp
if test:
state_vars = utils.test_load_state_vars()
else:
state_vars = utils.load_state_vars()
reload_timestamp = datetime.datetime.now().strftime('%D %T')
print(f'Reloaded data at {reload_timestamp}')
def start_scheduler():
scheduler = BackgroundScheduler()
scheduler.add_job(func=load_data, trigger="interval", seconds=60*30)
scheduler.start()
# Shut down the scheduler when exiting the app
atexit.register(lambda: scheduler.shutdown())
@app.route('/', methods=['GET'])
def home():
return "Welcome to the Bittensor Pretraining Leaderboard API!"
@app.route('/updated', methods=['GET'])
def updated():
return reload_timestamp
@app.route('/benchmark', methods=['GET'])
def benchmark():
"""
Get the benchmarks and the timestamp
Returns:
- benchmarks: List of dicts (from pandas DataFrame)
- benchmark_timestamp: String
"""
benchmarks = state_vars.get("benchmarks", None)
benchmark_timestamp = state_vars.get("benchmark_timestamp", None)
return jsonify(
{
"benchmarks": benchmarks.to_dict(orient='records'),
"benchmark_timestamp": benchmark_timestamp.strftime('%Y-%m-%d %H:%M:%S')
}
)
@app.route('/metagraph', methods=['GET'])
def metagraph():
"""
Get the metagraph data
Returns:
- metagraph_data: List of dicts (from pandas DataFrame)
"""
metagraph = state_vars["metagraph"]
return jsonify(
utils.make_metagraph_dataframe(metagraph).to_dict(orient='records')
)
@app.route('/leaderboard', methods=['GET'])
def leaderboard():
"""
Get the leaderboard data
Returns:
- leaderboard_data: List of dicts (from pandas DataFrame)
"""
model_data = state_vars["model_data"]
scores = state_vars["scores"]
show_stale = request.args.get('show_stale')
return jsonify(
utils.leaderboard_data(model_data, scores, show_stale=show_stale)
)
@app.route('/loss', methods=['GET'])
def loss():
"""
Get the losses over time
Returns:
- losses_over_time: List of dicts (from pandas DataFrame)
"""
vali_runs = state_vars["vali_runs"]
return jsonify(
utils.get_losses_over_time(vali_runs).to_dict(orient='records')
)
@app.route('/validator', methods=['GET'])
def validator():
"""
Get the validator data
Returns:
- validator_data: List of dicts (from pandas DataFrame)
"""
model_data = state_vars["model_data"]
validator_df = state_vars["validator_df"]
validator_df = utils.make_validator_dataframe(validator_df, model_data)
json_data = [ row.dropna().to_dict()
for _, row in validator_df.iterrows() ]
return jsonify(json_data)
@app.route('/model-data', methods=['GET'])
def model_data():
"""
Get the model data
Returns:
- model_data: List of dicts (from list of ModelData)
- winner_data: dict containing top earning miners
"""
model_data = state_vars["model_data"]
winner_data = {
f"{c.namespace}/{c.name} ({c.commit[0:8]}) · (τ{round(c.emission, 2):,})": c.incentive
for c in model_data
if c.incentive
}
return jsonify({
'model_data': [md.to_dict() for md in model_data],
'winner_data': winner_data
})
if __name__ == '__main__':
load_data()
start_scheduler()
app.run(host='0.0.0.0', port=5000, debug=True)
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