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"""
Database schema for Dynamic Highscores system.
This module defines the SQLite database schema for the Dynamic Highscores system,
which integrates benchmark selection, model evaluation, and leaderboard functionality.
"""
import sqlite3
import os
import json
from datetime import datetime, timedelta
import pandas as pd
class DynamicHighscoresDB:
"""Database manager for the Dynamic Highscores system."""
def __init__(self, db_path="dynamic_highscores.db"):
"""Initialize the database connection and create tables if they don't exist."""
self.db_path = db_path
self.conn = None
self.cursor = None
self.connect()
self.create_tables()
def connect(self):
"""Connect to the SQLite database."""
self.conn = sqlite3.connect(self.db_path)
self.conn.row_factory = sqlite3.Row
self.cursor = self.conn.cursor()
def close(self):
"""Close the database connection."""
if self.conn:
self.conn.close()
def create_tables(self):
"""Create all necessary tables if they don't exist."""
# Users table - stores user information
self.cursor.execute('''
CREATE TABLE IF NOT EXISTS users (
id INTEGER PRIMARY KEY AUTOINCREMENT,
username TEXT UNIQUE NOT NULL,
hf_user_id TEXT UNIQUE NOT NULL,
is_admin BOOLEAN DEFAULT 0,
last_submission_date TEXT,
created_at TEXT DEFAULT CURRENT_TIMESTAMP
)
''')
# Benchmarks table - stores information about available benchmarks
self.cursor.execute('''
CREATE TABLE IF NOT EXISTS benchmarks (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
dataset_id TEXT NOT NULL,
description TEXT,
metrics TEXT, -- JSON string of metrics
created_at TEXT DEFAULT CURRENT_TIMESTAMP
)
''')
# Models table - stores information about submitted models
self.cursor.execute('''
CREATE TABLE IF NOT EXISTS models (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
hf_model_id TEXT NOT NULL,
user_id INTEGER NOT NULL,
tag TEXT NOT NULL, -- One of: Merge, Agent, Reasoning, Coding, etc.
parameters TEXT, -- Number of parameters (can be NULL)
description TEXT,
created_at TEXT DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (user_id) REFERENCES users (id),
UNIQUE (hf_model_id, user_id)
)
''')
# Evaluations table - stores evaluation results
self.cursor.execute('''
CREATE TABLE IF NOT EXISTS evaluations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
model_id INTEGER NOT NULL,
benchmark_id INTEGER NOT NULL,
status TEXT NOT NULL, -- pending, running, completed, failed
results TEXT, -- JSON string of results
score REAL, -- Overall score (can be NULL)
submitted_at TEXT DEFAULT CURRENT_TIMESTAMP,
completed_at TEXT,
FOREIGN KEY (model_id) REFERENCES models (id),
FOREIGN KEY (benchmark_id) REFERENCES benchmarks (id)
)
''')
# Queue table - stores evaluation queue
self.cursor.execute('''
CREATE TABLE IF NOT EXISTS queue (
id INTEGER PRIMARY KEY AUTOINCREMENT,
evaluation_id INTEGER NOT NULL,
priority INTEGER DEFAULT 0, -- Higher number = higher priority
added_at TEXT DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (evaluation_id) REFERENCES evaluations (id)
)
''')
self.conn.commit()
# User management methods
def add_user(self, username, hf_user_id, is_admin=False):
"""Add a new user to the database."""
try:
self.cursor.execute(
"INSERT INTO users (username, hf_user_id, is_admin) VALUES (?, ?, ?)",
(username, hf_user_id, is_admin)
)
self.conn.commit()
return self.cursor.lastrowid
except sqlite3.IntegrityError:
# User already exists
self.cursor.execute(
"SELECT id FROM users WHERE hf_user_id = ?",
(hf_user_id,)
)
return self.cursor.fetchone()[0]
def get_user(self, hf_user_id):
"""Get user information by HuggingFace user ID."""
self.cursor.execute(
"SELECT * FROM users WHERE hf_user_id = ?",
(hf_user_id,)
)
return dict(self.cursor.fetchone()) if self.cursor.fetchone() else None
def can_submit_today(self, user_id):
"""Check if a user can submit a benchmark evaluation today."""
self.cursor.execute(
"SELECT is_admin, last_submission_date FROM users WHERE id = ?",
(user_id,)
)
result = self.cursor.fetchone()
if not result:
return False
user_data = dict(result)
# Admin can always submit
if user_data['is_admin']:
return True
# If no previous submission, user can submit
if not user_data['last_submission_date']:
return True
# Check if last submission was before today
last_date = datetime.fromisoformat(user_data['last_submission_date'])
today = datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
return last_date < today
def update_submission_date(self, user_id):
"""Update the last submission date for a user."""
current_time = datetime.now().isoformat()
self.cursor.execute(
"UPDATE users SET last_submission_date = ? WHERE id = ?",
(current_time, user_id)
)
self.conn.commit()
# Benchmark management methods
def add_benchmark(self, name, dataset_id, description="", metrics=None):
"""Add a new benchmark to the database."""
if metrics is None:
metrics = {}
metrics_json = json.dumps(metrics)
try:
self.cursor.execute(
"INSERT INTO benchmarks (name, dataset_id, description, metrics) VALUES (?, ?, ?, ?)",
(name, dataset_id, description, metrics_json)
)
self.conn.commit()
return self.cursor.lastrowid
except sqlite3.IntegrityError:
# Benchmark already exists with this dataset_id
self.cursor.execute(
"SELECT id FROM benchmarks WHERE dataset_id = ?",
(dataset_id,)
)
return self.cursor.fetchone()[0]
def get_benchmarks(self):
"""Get all available benchmarks."""
self.cursor.execute("SELECT * FROM benchmarks")
benchmarks = [dict(row) for row in self.cursor.fetchall()]
# Parse metrics JSON
for benchmark in benchmarks:
benchmark['metrics'] = json.loads(benchmark['metrics'])
return benchmarks
def get_benchmark(self, benchmark_id):
"""Get benchmark information by ID."""
self.cursor.execute(
"SELECT * FROM benchmarks WHERE id = ?",
(benchmark_id,)
)
benchmark = dict(self.cursor.fetchone()) if self.cursor.fetchone() else None
if benchmark:
benchmark['metrics'] = json.loads(benchmark['metrics'])
return benchmark
# Model management methods
def add_model(self, name, hf_model_id, user_id, tag, parameters=None, description=""):
"""Add a new model to the database."""
try:
self.cursor.execute(
"INSERT INTO models (name, hf_model_id, user_id, tag, parameters, description) VALUES (?, ?, ?, ?, ?, ?)",
(name, hf_model_id, user_id, tag, parameters, description)
)
self.conn.commit()
return self.cursor.lastrowid
except sqlite3.IntegrityError:
# Model already exists for this user
self.cursor.execute(
"SELECT id FROM models WHERE hf_model_id = ? AND user_id = ?",
(hf_model_id, user_id)
)
return self.cursor.fetchone()[0]
def get_models(self, tag=None):
"""Get all models, optionally filtered by tag."""
if tag:
self.cursor.execute(
"SELECT * FROM models WHERE tag = ?",
(tag,)
)
else:
self.cursor.execute("SELECT * FROM models")
return [dict(row) for row in self.cursor.fetchall()]
def get_model(self, model_id):
"""Get model information by ID."""
self.cursor.execute(
"SELECT * FROM models WHERE id = ?",
(model_id,)
)
return dict(self.cursor.fetchone()) if self.cursor.fetchone() else None
# Evaluation management methods
def add_evaluation(self, model_id, benchmark_id, priority=0):
"""Add a new evaluation to the database and queue."""
# First, add the evaluation
self.cursor.execute(
"INSERT INTO evaluations (model_id, benchmark_id, status) VALUES (?, ?, 'pending')",
(model_id, benchmark_id)
)
evaluation_id = self.cursor.lastrowid
# Then, add it to the queue
self.cursor.execute(
"INSERT INTO queue (evaluation_id, priority) VALUES (?, ?)",
(evaluation_id, priority)
)
self.conn.commit()
return evaluation_id
def update_evaluation_status(self, evaluation_id, status, results=None, score=None):
"""Update the status of an evaluation."""
params = [status, evaluation_id]
sql = "UPDATE evaluations SET status = ?"
if results is not None:
sql += ", results = ?"
params.insert(1, json.dumps(results))
if score is not None:
sql += ", score = ?"
params.insert(1 if results is None else 2, score)
if status in ['completed', 'failed']:
sql += ", completed_at = ?"
params.insert(1 if results is None and score is None else (2 if results is None or score is None else 3),
datetime.now().isoformat())
sql += " WHERE id = ?"
self.cursor.execute(sql, params)
self.conn.commit()
# If completed or failed, remove from queue
if status in ['completed', 'failed']:
self.cursor.execute(
"DELETE FROM queue WHERE evaluation_id = ?",
(evaluation_id,)
)
self.conn.commit()
def get_next_in_queue(self):
"""Get the next evaluation in the queue."""
self.cursor.execute("""
SELECT q.id as queue_id, q.evaluation_id, e.model_id, e.benchmark_id, m.hf_model_id, b.dataset_id
FROM queue q
JOIN evaluations e ON q.evaluation_id = e.id
JOIN models m ON e.model_id = m.id
JOIN benchmarks b ON e.benchmark_id = b.id
WHERE e.status = 'pending'
ORDER BY q.priority DESC, q.added_at ASC
LIMIT 1
""")
result = self.cursor.fetchone()
return dict(result) if result else None
def get_evaluation_results(self, model_id=None, benchmark_id=None, tag=None):
"""Get evaluation results, optionally filtered by model, benchmark, or tag."""
sql = """
SELECT e.id, e.model_id, e.benchmark_id, e.status, e.results, e.score,
e.submitted_at, e.completed_at, m.name as model_name, m.tag,
b.name as benchmark_name
FROM evaluations e
JOIN models m ON e.model_id = m.id
JOIN benchmarks b ON e.benchmark_id = b.id
WHERE e.status = 'completed'
"""
params = []
if model_id:
sql += " AND e.model_id = ?"
params.append(model_id)
if benchmark_id:
sql += " AND e.benchmark_id = ?"
params.append(benchmark_id)
if tag:
sql += " AND m.tag = ?"
params.append(tag)
sql += " ORDER BY e.completed_at DESC"
self.cursor.execute(sql, params)
results = [dict(row) for row in self.cursor.fetchall()]
# Parse results JSON
for result in results:
if result['results']:
result['results'] = json.loads(result['results'])
return results
def get_leaderboard_df(self, tag=None):
"""Get a pandas DataFrame of the leaderboard, optionally filtered by tag."""
results = self.get_evaluation_results(tag=tag)
if not results:
return pd.DataFrame()
# Create a list of dictionaries for the DataFrame
leaderboard_data = []
for result in results:
entry = {
'model_name': result['model_name'],
'model_id': result['model_id'],
'benchmark_name': result['benchmark_name'],
'benchmark_id': result['benchmark_id'],
'tag': result['tag'],
'score': result['score'],
'completed_at': result['completed_at']
}
# Add individual metrics from results
if result['results'] and isinstance(result['results'], dict):
for metric, value in result['results'].items():
if isinstance(value, (int, float)):
entry[f'metric_{metric}'] = value
leaderboard_data.append(entry)
return pd.DataFrame(leaderboard_data)
# Initialize the database
def init_db(db_path="dynamic_highscores.db"):
"""Initialize the database and return the database manager."""
db = DynamicHighscoresDB(db_path)
return db
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