File size: 9,700 Bytes
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Database module for The Sentinel Interface.
Uses SQLite for lightweight persistent storage of sessions and performance data.
"""
import sqlite3
import os
import json
from datetime import datetime
DB_PATH = os.path.join(os.path.dirname(__file__), "sentinel.db")
def get_connection():
conn = sqlite3.connect(DB_PATH)
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
return conn
def init_db():
"""Create tables if they don't exist."""
conn = get_connection()
cursor = conn.cursor()
cursor.executescript("""
CREATE TABLE IF NOT EXISTS sessions (
id INTEGER PRIMARY KEY AUTOINCREMENT,
student_id TEXT NOT NULL DEFAULT 'default',
start_time TEXT NOT NULL,
end_time TEXT,
avg_engagement REAL DEFAULT 0,
dominant_emotion TEXT DEFAULT 'neutral',
notes TEXT DEFAULT ''
);
CREATE TABLE IF NOT EXISTS emotion_logs (
id INTEGER PRIMARY KEY AUTOINCREMENT,
session_id INTEGER NOT NULL,
timestamp TEXT NOT NULL,
source TEXT NOT NULL,
emotion TEXT NOT NULL,
confidence REAL NOT NULL,
raw_data TEXT DEFAULT '{}',
FOREIGN KEY (session_id) REFERENCES sessions(id)
);
CREATE TABLE IF NOT EXISTS student_performance (
id INTEGER PRIMARY KEY AUTOINCREMENT,
student_id TEXT NOT NULL,
session_id INTEGER,
date TEXT NOT NULL,
engagement_score REAL NOT NULL,
face_emotion TEXT DEFAULT '{}',
speech_emotion TEXT DEFAULT '{}',
text_sentiment TEXT DEFAULT '{}',
overall_summary TEXT DEFAULT '',
FOREIGN KEY (session_id) REFERENCES sessions(id)
);
""")
conn.commit()
conn.close()
def create_session(student_id="default", start_time=None):
conn = get_connection()
cursor = conn.cursor()
now = start_time if start_time else datetime.now().isoformat()
cursor.execute(
"INSERT INTO sessions (student_id, start_time) VALUES (?, ?)",
(student_id, now)
)
conn.commit()
session_id = cursor.lastrowid
conn.close()
return session_id
def end_session(session_id, avg_engagement, dominant_emotion):
conn = get_connection()
now = datetime.now().isoformat()
conn.execute(
"UPDATE sessions SET end_time=?, avg_engagement=?, dominant_emotion=? WHERE id=?",
(now, avg_engagement, dominant_emotion, session_id)
)
conn.commit()
conn.close()
def log_emotion(session_id, source, emotion, confidence, raw_data=None):
conn = get_connection()
now = datetime.now().isoformat()
conn.execute(
"INSERT INTO emotion_logs (session_id, timestamp, source, emotion, confidence, raw_data) VALUES (?, ?, ?, ?, ?, ?)",
(session_id, now, source, emotion, confidence, json.dumps(raw_data or {}))
)
conn.commit()
conn.close()
def save_performance(student_id, session_id, engagement_score, face_emotion=None, speech_emotion=None, text_sentiment=None, summary=""):
conn = get_connection()
now = datetime.now().strftime("%Y-%m-%d")
conn.execute(
"INSERT INTO student_performance (student_id, session_id, date, engagement_score, face_emotion, speech_emotion, text_sentiment, overall_summary) VALUES (?, ?, ?, ?, ?, ?, ?, ?)",
(student_id, session_id, now, engagement_score,
json.dumps(face_emotion or {}), json.dumps(speech_emotion or {}),
json.dumps(text_sentiment or {}), summary)
)
conn.commit()
conn.close()
def get_student_performance(student_id="default"):
conn = get_connection()
if student_id.lower() == 'all':
rows = conn.execute(
"SELECT * FROM student_performance ORDER BY session_id DESC, id DESC LIMIT 50"
).fetchall()
else:
rows = conn.execute(
"SELECT * FROM student_performance WHERE student_id=? ORDER BY session_id DESC, id DESC LIMIT 50",
(student_id,)
).fetchall()
conn.close()
return [dict(r) for r in rows]
def get_all_sessions(student_id=None):
conn = get_connection()
if student_id and student_id.lower() != 'all':
rows = conn.execute(
"SELECT * FROM sessions WHERE student_id=? ORDER BY id DESC LIMIT 50",
(student_id,)
).fetchall()
else:
rows = conn.execute(
"SELECT * FROM sessions ORDER BY id DESC LIMIT 50"
).fetchall()
conn.close()
return [dict(r) for r in rows]
def delete_session(session_id):
"""
Deletes a session and its associated logs, then shifts down all subsequent
session IDs by 1 so the IDs remain perfectly contiguous.
"""
conn = get_connection()
try:
# Cascade delete
conn.execute("DELETE FROM emotion_logs WHERE session_id=?", (session_id,))
conn.execute("DELETE FROM student_performance WHERE session_id=?", (session_id,))
conn.execute("DELETE FROM sessions WHERE id=?", (session_id,))
# Dynamic re-indexing to close the gap
conn.execute("UPDATE sessions SET id = id - 1 WHERE id > ?", (session_id,))
conn.execute("UPDATE student_performance SET session_id = session_id - 1 WHERE session_id > ?", (session_id,))
conn.execute("UPDATE emotion_logs SET session_id = session_id - 1 WHERE session_id > ?", (session_id,))
# Reset the AUTOINCREMENT sequence so the next inserted ID is MAX(id) + 1
conn.execute("UPDATE sqlite_sequence SET seq = (SELECT MAX(id) FROM sessions) WHERE name = 'sessions'")
conn.commit()
return True
except Exception as e:
conn.rollback()
print(f"Error deleting session: {e}")
return False
finally:
conn.close()
def get_session_emotions(session_id):
conn = get_connection()
rows = conn.execute(
"SELECT * FROM emotion_logs WHERE session_id=? ORDER BY timestamp ASC",
(session_id,)
).fetchall()
conn.close()
return [dict(r) for r in rows]
def get_overall_stats(student_id="default"):
conn = get_connection()
if student_id.lower() == 'all':
row = conn.execute(
"SELECT COUNT(*) as total_sessions, AVG(engagement_score) as avg_engagement, MAX(engagement_score) as peak_engagement, MIN(engagement_score) as min_engagement FROM student_performance"
).fetchone()
else:
row = conn.execute(
"SELECT COUNT(*) as total_sessions, AVG(engagement_score) as avg_engagement, MAX(engagement_score) as peak_engagement, MIN(engagement_score) as min_engagement FROM student_performance WHERE student_id=?",
(student_id,)
).fetchone()
conn.close()
if row and row['total_sessions'] > 0:
return dict(row)
return {"total_sessions": 0, "avg_engagement": 0, "peak_engagement": 0, "min_engagement": 0}
def get_session_details(session_id):
import re
from datetime import datetime, timedelta
conn = get_connection()
session = conn.execute("SELECT s.*, p.overall_summary FROM sessions s LEFT JOIN student_performance p ON s.id=p.session_id WHERE s.id=?", (session_id,)).fetchone()
if not session:
conn.close()
return None
session = dict(session)
logs_rows = conn.execute("SELECT timestamp, confidence FROM emotion_logs WHERE session_id=? AND confidence IS NOT NULL", (session_id,)).fetchall()
conn.close()
if logs_rows:
scores = [l['confidence'] for l in logs_rows]
session['peak_engagement'] = max(scores)
session['min_engagement'] = min(scores)
session['avg_engagement'] = sum(scores) / len(scores)
else:
# Fallback if no logs
session['peak_engagement'] = session['avg_engagement']
session['min_engagement'] = session['avg_engagement']
# Calculate duration
try:
start_str = session.get('start_time', '').replace('Z', '')
start = datetime.fromisoformat(start_str) if start_str else datetime.now()
diff_seconds = 0
parsed_from_summary = False
# ALWAYS prioritize parsing the true duration from the summary if available
if session.get('overall_summary'):
match = re.search(r'(?:lasted\s*(\d+)\s*minutes|Session:\s*(\d+)min)', session['overall_summary'])
if match:
val = match.group(1) or match.group(2)
diff_seconds = int(val) * 60
parsed_from_summary = True
# Fallback to timestamp delta if no summary matched
if not parsed_from_summary:
end_str = session.get('end_time', '').replace('Z', '')
end = datetime.fromisoformat(end_str) if end_str else start
if end < start: end = start
diff_seconds = (end - start).total_seconds()
# User explicitly requested that end_time must mathematically align with start_time + duration
calculated_end = start + timedelta(seconds=diff_seconds)
session['end_time'] = calculated_end.isoformat()
if diff_seconds < 60:
session['duration_mins'] = "0 minutes"
else:
mins = round(diff_seconds / 60.0, 1)
session['duration_mins'] = f"{mins} minutes"
session['date_time'] = start.strftime("%b %d, %Y %H:%M")
except Exception:
session['duration_mins'] = "0 seconds"
session['date_time'] = session.get('start_time', 'Unknown Date')
return session
# Initialize database on import
init_db()
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