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"""SQLite database handler for storing user interactions"""
import sqlite3
import json
from datetime import datetime
from typing import List, Dict, Optional, Tuple
import os
from config import DATABASE_PATH
class VedaDatabase:
"""Database handler for Veda Programming LLM"""
def __init__(self, db_path: str = DATABASE_PATH):
self.db_path = db_path
self._init_database()
def _get_connection(self):
"""Get database connection"""
conn = sqlite3.connect(self.db_path)
conn.row_factory = sqlite3.Row
return conn
def _init_database(self):
"""Initialize database tables"""
conn = self._get_connection()
cursor = conn.cursor()
# User interactions table
cursor.execute('''
CREATE TABLE IF NOT EXISTS interactions (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
prompt TEXT NOT NULL,
generated_code TEXT NOT NULL,
temperature REAL,
max_tokens INTEGER,
feedback INTEGER DEFAULT 0,
is_approved BOOLEAN DEFAULT 0,
is_used_for_training BOOLEAN DEFAULT 0,
session_id TEXT,
user_edited_code TEXT
)
''')
# Training history table
cursor.execute('''
CREATE TABLE IF NOT EXISTS training_history (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
samples_used INTEGER,
epochs INTEGER,
final_loss REAL,
final_accuracy REAL,
model_version TEXT,
notes TEXT
)
''')
# Code samples table (curated training data)
cursor.execute('''
CREATE TABLE IF NOT EXISTS code_samples (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
code TEXT NOT NULL,
source TEXT,
category TEXT,
quality_score REAL DEFAULT 0,
times_used INTEGER DEFAULT 0
)
''')
# Statistics table
cursor.execute('''
CREATE TABLE IF NOT EXISTS statistics (
id INTEGER PRIMARY KEY AUTOINCREMENT,
date DATE UNIQUE,
total_generations INTEGER DEFAULT 0,
positive_feedback INTEGER DEFAULT 0,
negative_feedback INTEGER DEFAULT 0,
training_runs INTEGER DEFAULT 0
)
''')
conn.commit()
conn.close()
print(f"Database initialized at {self.db_path}")
# ==================== Interactions ====================
def save_interaction(
self,
prompt: str,
generated_code: str,
temperature: float = 0.7,
max_tokens: int = 100,
session_id: str = None
) -> int:
"""Save a user interaction"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('''
INSERT INTO interactions
(prompt, generated_code, temperature, max_tokens, session_id)
VALUES (?, ?, ?, ?, ?)
''', (prompt, generated_code, temperature, max_tokens, session_id))
interaction_id = cursor.lastrowid
# Update daily statistics
today = datetime.now().date()
cursor.execute('''
INSERT INTO statistics (date, total_generations)
VALUES (?, 1)
ON CONFLICT(date) DO UPDATE SET
total_generations = total_generations + 1
''', (today,))
conn.commit()
conn.close()
return interaction_id
def update_feedback(self, interaction_id: int, feedback: int,
user_edited_code: str = None):
"""Update feedback for an interaction (1 = positive, -1 = negative)"""
conn = self._get_connection()
cursor = conn.cursor()
is_approved = feedback > 0
cursor.execute('''
UPDATE interactions
SET feedback = ?, is_approved = ?, user_edited_code = ?
WHERE id = ?
''', (feedback, is_approved, user_edited_code, interaction_id))
# Update daily statistics
today = datetime.now().date()
if feedback > 0:
cursor.execute('''
INSERT INTO statistics (date, positive_feedback)
VALUES (?, 1)
ON CONFLICT(date) DO UPDATE SET
positive_feedback = positive_feedback + 1
''', (today,))
elif feedback < 0:
cursor.execute('''
INSERT INTO statistics (date, negative_feedback)
VALUES (?, 1)
ON CONFLICT(date) DO UPDATE SET
negative_feedback = negative_feedback + 1
''', (today,))
conn.commit()
conn.close()
def get_approved_samples(self, limit: int = None,
not_used: bool = False) -> List[Dict]:
"""Get approved samples for training"""
conn = self._get_connection()
cursor = conn.cursor()
query = '''
SELECT id, prompt,
COALESCE(user_edited_code, generated_code) as code
FROM interactions
WHERE is_approved = 1
'''
if not_used:
query += ' AND is_used_for_training = 0'
query += ' ORDER BY timestamp DESC'
if limit:
query += f' LIMIT {limit}'
cursor.execute(query)
rows = cursor.fetchall()
conn.close()
return [dict(row) for row in rows]
def mark_as_used_for_training(self, interaction_ids: List[int]):
"""Mark interactions as used for training"""
conn = self._get_connection()
cursor = conn.cursor()
placeholders = ','.join('?' * len(interaction_ids))
cursor.execute(f'''
UPDATE interactions
SET is_used_for_training = 1
WHERE id IN ({placeholders})
''', interaction_ids)
conn.commit()
conn.close()
def get_pending_samples_count(self) -> int:
"""Get count of approved but unused samples"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('''
SELECT COUNT(*) FROM interactions
WHERE is_approved = 1 AND is_used_for_training = 0
''')
count = cursor.fetchone()[0]
conn.close()
return count
# ==================== Code Samples ====================
def add_code_sample(self, code: str, source: str = "user",
category: str = "general") -> int:
"""Add a curated code sample"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('''
INSERT INTO code_samples (code, source, category)
VALUES (?, ?, ?)
''', (code, source, category))
sample_id = cursor.lastrowid
conn.commit()
conn.close()
return sample_id
def get_all_code_samples(self) -> List[Dict]:
"""Get all code samples"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('SELECT * FROM code_samples ORDER BY quality_score DESC')
rows = cursor.fetchall()
conn.close()
return [dict(row) for row in rows]
# ==================== Training History ====================
def save_training_run(
self,
samples_used: int,
epochs: int,
final_loss: float,
final_accuracy: float,
model_version: str,
notes: str = ""
) -> int:
"""Save training run information"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('''
INSERT INTO training_history
(samples_used, epochs, final_loss, final_accuracy, model_version, notes)
VALUES (?, ?, ?, ?, ?, ?)
''', (samples_used, epochs, final_loss, final_accuracy, model_version, notes))
run_id = cursor.lastrowid
# Update daily statistics
today = datetime.now().date()
cursor.execute('''
INSERT INTO statistics (date, training_runs)
VALUES (?, 1)
ON CONFLICT(date) DO UPDATE SET
training_runs = training_runs + 1
''', (today,))
conn.commit()
conn.close()
return run_id
def get_training_history(self, limit: int = 10) -> List[Dict]:
"""Get recent training history"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('''
SELECT * FROM training_history
ORDER BY timestamp DESC
LIMIT ?
''', (limit,))
rows = cursor.fetchall()
conn.close()
return [dict(row) for row in rows]
# ==================== Statistics ====================
def get_statistics(self) -> Dict:
"""Get overall statistics"""
conn = self._get_connection()
cursor = conn.cursor()
# Total counts
cursor.execute('SELECT COUNT(*) FROM interactions')
total_interactions = cursor.fetchone()[0]
cursor.execute('SELECT COUNT(*) FROM interactions WHERE feedback > 0')
positive_count = cursor.fetchone()[0]
cursor.execute('SELECT COUNT(*) FROM interactions WHERE feedback < 0')
negative_count = cursor.fetchone()[0]
cursor.execute('SELECT COUNT(*) FROM interactions WHERE is_approved = 1')
approved_count = cursor.fetchone()[0]
cursor.execute('SELECT COUNT(*) FROM training_history')
training_runs = cursor.fetchone()[0]
cursor.execute('SELECT COUNT(*) FROM code_samples')
code_samples = cursor.fetchone()[0]
# Recent stats (last 7 days)
cursor.execute('''
SELECT SUM(total_generations), SUM(positive_feedback), SUM(negative_feedback)
FROM statistics
WHERE date >= date('now', '-7 days')
''')
recent = cursor.fetchone()
conn.close()
return {
'total_interactions': total_interactions,
'positive_feedback': positive_count,
'negative_feedback': negative_count,
'approved_samples': approved_count,
'training_runs': training_runs,
'code_samples': code_samples,
'recent_generations': recent[0] or 0,
'recent_positive': recent[1] or 0,
'recent_negative': recent[2] or 0,
'approval_rate': (positive_count / total_interactions * 100) if total_interactions > 0 else 0
}
def get_recent_interactions(self, limit: int = 20) -> List[Dict]:
"""Get recent interactions"""
conn = self._get_connection()
cursor = conn.cursor()
cursor.execute('''
SELECT id, timestamp, prompt, generated_code, feedback, is_approved
FROM interactions
ORDER BY timestamp DESC
LIMIT ?
''', (limit,))
rows = cursor.fetchall()
conn.close()
return [dict(row) for row in rows]
# Singleton instance
db = VedaDatabase() |