Spaces:
Sleeping
Sleeping
import streamlit as st | |
import pandas as pd | |
import wandb | |
import time | |
from datetime import datetime, timedelta | |
import requests | |
def get_competitions(CONFIG_URL): | |
""" | |
Get competition names and their evaluation times from the config URL. | |
""" | |
competitions = [] | |
try: | |
config = requests.get(CONFIG_URL).json() | |
for competition in config: | |
# Extract competition name and evaluation times | |
competition_name = competition["competition_id"] | |
evaluation_times = competition.get("evaluation_times", []) | |
# Store competition name and evaluation times as a tuple | |
competitions.append((competition_name, evaluation_times)) | |
except Exception as e: | |
print(f"Error loading competition data: {str(e)}") | |
return competitions | |
def get_latest_evaluation_time(evaluation_times): | |
""" | |
Get the latest UTC evaluation time as a datetime object (either today or yesterday). | |
Args: | |
evaluation_times (list): List of evaluation times as strings (in HH:MM format). | |
Returns: | |
datetime: Latest evaluation time as a datetime object. | |
""" | |
# Get the current UTC date and time | |
current_utc_datetime = datetime.utcnow() | |
current_utc_time = current_utc_datetime.time() | |
# Convert evaluation times to datetime.time objects | |
eval_times = [datetime.strptime(time, "%H:%M").time() for time in evaluation_times] | |
# Sort the evaluation times to ensure they are in chronological order | |
eval_times.sort() | |
# Loop through the evaluation times in reverse to find the latest time that has passed | |
for eval_time in reversed(eval_times): | |
if current_utc_time >= eval_time: | |
# If the time has passed today, return today's date with that time | |
return current_utc_datetime.replace(hour=eval_time.hour, minute=eval_time.minute, second=0, microsecond=0) | |
# If none of the evaluation times have passed, return the latest one from the previous day | |
yesterday = current_utc_datetime - timedelta(days=1) | |
latest_eval_time = eval_times[-1] | |
# Return the latest evaluation time from yesterday as pd.Timestamp | |
latest_time = yesterday.replace(hour=latest_eval_time.hour, minute=latest_eval_time.minute, second=0, microsecond=0) | |
return pd.Timestamp(latest_time, tz='UTC') | |
def fetch_competition_summary(api, entity, project): | |
data = [] | |
# entity = projects[selected_project]["entity"] | |
# project = projects[selected_project]["project"] | |
runs = api.runs(f"{entity}/{project}") | |
for run in runs: | |
try: | |
summary = run.summary | |
if summary.get("validator_hotkey") and summary.get("winning_hotkey"): | |
data.append({ | |
"Created At": run.created_at, | |
"Validator ID": summary.get("validator_hotkey"), | |
"Winning Hotkey": summary.get("winning_hotkey"), | |
"Run Time (s)": summary.get("run_time_s"), | |
}) | |
except Exception as e: | |
st.write(f"Error processing run {run.id}: {str(e)}") | |
df = pd.DataFrame(data) | |
if not df.empty: | |
df['Created At'] = pd.to_datetime(df['Created At'], utc=True) | |
df = df.sort_values(by="Created At", ascending=False) | |
return df | |
def fetch_models_evaluation(api, entity, project): | |
data = [] | |
# entity = projects[selected_project]["entity"] | |
# project = projects[selected_project]["project"] | |
runs = api.runs(f"{entity}/{project}") | |
for run in runs: | |
try: | |
summary = run.summary | |
if summary.get("score") is not None: # Assuming runs with score are model evaluations | |
model_link = summary.get("hf_model_link", "") | |
if model_link: | |
# Create clickable link | |
model_link_html = f'<a href="{model_link}" target="_blank">Model Link</a>' | |
else: | |
model_link_html = "N/A" | |
data.append({ | |
"Created At": run.created_at, | |
"Miner hotkey": summary.get("miner_hotkey", "N/A"), | |
"F1-beta": summary.get("fbeta"), | |
"Accuracy": summary.get("accuracy"), | |
"Recall": summary.get("recall"), | |
"Precision": summary.get("precision"), | |
"Tested entries": summary.get("tested_entries"), | |
"ROC AUC": summary.get("roc_auc"), | |
"Confusion Matrix": summary.get("confusion_matrix"), | |
"Model link": model_link_html, | |
"Score": summary.get("score"), | |
#TODO link to huggingface model | |
}) | |
except Exception as e: | |
st.write(f"Error processing run {run.id}: {str(e)}") | |
df = pd.DataFrame(data) | |
if not df.empty: | |
df['Created At'] = pd.to_datetime(df['Created At'], utc=True) | |
df = df.sort_values(by="Created At", ascending=False) | |
return df | |
def highlight_score_column(s): | |
""" | |
Highlight the 'Score' column with a custom background color. | |
""" | |
return ['background-color: yellow' if s.name == 'Score' else '' for _ in s] | |