alpha-nerd-nomyo
34d6abd28b
- Refactored token aggregation query in db.py to use a single SQL query with SUM() instead of iterating through rows, improving performance - Combined import statements in db.py and router.py to reduce lines of code - Enhanced chat proxy in router.py to handle "moe-" prefixed models with multiple query execution and critique generation - Added last_user_content() helper function to extract user content from messages - Improved code readability and maintainability through these structural changes
268 lines
12 KiB
Python
268 lines
12 KiB
Python
import aiosqlite, asyncio
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from typing import Optional
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from pathlib import Path
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from datetime import datetime, timezone
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from collections import defaultdict
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class TokenDatabase:
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def __init__(self, db_path: str = "token_counts.db"):
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self.db_path = db_path
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self._db: Optional[aiosqlite.Connection] = None
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self._db_lock = asyncio.Lock()
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self._operation_lock = asyncio.Lock()
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def _ensure_db_directory(self):
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"""Ensure the directory for the database exists."""
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db_dir = Path(self.db_path).parent
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if not db_dir.exists():
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db_dir.mkdir(parents=True, exist_ok=True)
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async def _get_connection(self) -> aiosqlite.Connection:
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"""Return a persistent connection with WAL mode and FK enforcement enabled."""
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if self._db is None:
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async with self._db_lock:
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if self._db is None:
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self._ensure_db_directory()
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self._db = await aiosqlite.connect(self.db_path)
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# Enable WAL and foreign keys for reliability and integrity
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await self._db.execute("PRAGMA journal_mode=WAL;")
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await self._db.execute("PRAGMA foreign_keys = ON;")
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await self._db.commit()
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return self._db
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async def close(self):
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"""Close the persistent database connection, if open."""
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if self._db is not None:
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await self._db.close()
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self._db = None
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async def init_db(self):
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"""Initialize the database tables."""
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db = await self._get_connection()
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async with self._operation_lock:
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await db.execute('''
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CREATE TABLE IF NOT EXISTS token_counts (
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endpoint TEXT,
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model TEXT,
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input_tokens INTEGER DEFAULT 0,
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output_tokens INTEGER DEFAULT 0,
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total_tokens INTEGER DEFAULT 0,
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PRIMARY KEY(endpoint, model)
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)
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''')
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await db.execute('''
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CREATE TABLE IF NOT EXISTS token_time_series (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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endpoint TEXT,
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model TEXT,
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input_tokens INTEGER,
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output_tokens INTEGER,
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total_tokens INTEGER,
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timestamp INTEGER,
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FOREIGN KEY(endpoint, model) REFERENCES token_counts(endpoint, model)
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)
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''')
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await db.commit()
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async def update_token_counts(self, endpoint: str, model: str, input_tokens: int, output_tokens: int):
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"""Update token counts for a specific endpoint and model."""
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total_tokens = input_tokens + output_tokens
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db = await self._get_connection()
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async with self._operation_lock:
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await db.execute('''
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INSERT INTO token_counts (endpoint, model, input_tokens, output_tokens, total_tokens)
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VALUES (?, ?, ?, ?, ?)
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ON CONFLICT (endpoint, model) DO UPDATE SET
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input_tokens = input_tokens + ?,
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output_tokens = output_tokens + ?,
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total_tokens = total_tokens + ?
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''', (endpoint, model, input_tokens, output_tokens, total_tokens, input_tokens, output_tokens, total_tokens))
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await db.commit()
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async def add_time_series_entry(self, endpoint: str, model: str, input_tokens: int, output_tokens: int):
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"""Add a time series entry with approximate timestamp."""
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total_tokens = input_tokens + output_tokens
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# Use current minute/hour as approximate timestamp in UTC
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now = datetime.now(tz=timezone.utc)
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timestamp = int(datetime(now.year, now.month, now.day, now.hour, now.minute).timestamp())
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db = await self._get_connection()
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async with self._operation_lock:
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await db.execute('''
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INSERT INTO token_time_series (endpoint, model, input_tokens, output_tokens, total_tokens, timestamp)
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VALUES (?, ?, ?, ?, ?, ?)
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''', (endpoint, model, input_tokens, output_tokens, total_tokens, timestamp))
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await db.commit()
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async def update_batched_counts(self, counts: dict):
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"""Update multiple token counts in a single transaction."""
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if not counts:
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return
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db = await self._get_connection()
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async with self._operation_lock:
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try:
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await db.execute('BEGIN')
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for endpoint, models in counts.items():
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for model, (input_tokens, output_tokens) in models.items():
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total_tokens = input_tokens + output_tokens
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await db.execute('''
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INSERT INTO token_counts (endpoint, model, input_tokens, output_tokens, total_tokens)
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VALUES (?, ?, ?, ?, ?)
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ON CONFLICT (endpoint, model) DO UPDATE SET
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input_tokens = input_tokens + ?,
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output_tokens = output_tokens + ?,
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total_tokens = total_tokens + ?
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''', (endpoint, model, input_tokens, output_tokens, total_tokens,
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input_tokens, output_tokens, total_tokens))
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await db.commit()
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except Exception:
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# Rollback on error to maintain consistency
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try:
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await db.execute('ROLLBACK')
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except Exception:
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pass
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raise
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async def add_batched_time_series(self, entries: list):
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"""Add multiple time series entries in a single transaction."""
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db = await self._get_connection()
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async with self._operation_lock:
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try:
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await db.execute('BEGIN')
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for entry in entries:
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await db.execute('''
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INSERT INTO token_time_series (endpoint, model, input_tokens, output_tokens, total_tokens, timestamp)
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VALUES (?, ?, ?, ?, ?, ?)
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''', (entry['endpoint'], entry['model'], entry['input_tokens'],
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entry['output_tokens'], entry['total_tokens'], entry['timestamp']))
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await db.commit()
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except Exception:
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try:
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await db.execute('ROLLBACK')
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except Exception:
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pass
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raise
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async def load_token_counts(self):
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"""Load all token counts from database."""
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db = await self._get_connection()
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async with self._operation_lock:
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async with db.execute('SELECT endpoint, model, input_tokens, output_tokens, total_tokens FROM token_counts') as cursor:
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async for row in cursor:
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yield {
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'endpoint': row[0],
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'model': row[1],
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'input_tokens': row[2],
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'output_tokens': row[3],
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'total_tokens': row[4]
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}
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async def get_latest_time_series(self, limit: int = 100):
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"""Get the latest time series entries."""
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db = await self._get_connection()
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async with self._operation_lock:
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async with db.execute('''
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SELECT endpoint, model, input_tokens, output_tokens, total_tokens, timestamp
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FROM token_time_series
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ORDER BY timestamp DESC
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LIMIT ?
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''', (limit,)) as cursor:
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async for row in cursor:
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yield {
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'endpoint': row[0],
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'model': row[1],
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'input_tokens': row[2],
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'output_tokens': row[3],
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'total_tokens': row[4],
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'timestamp': row[5]
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}
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async def get_token_counts_for_model(self, model):
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"""Get token counts for a specific model, aggregated across all endpoints."""
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db = await self._get_connection()
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async with self._operation_lock:
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async with db.execute('''
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SELECT
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'aggregated' as endpoint,
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? as model,
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SUM(input_tokens) as input_tokens,
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SUM(output_tokens) as output_tokens,
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SUM(total_tokens) as total_tokens
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FROM token_counts
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WHERE model = ?
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''', (model, model)) as cursor:
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row = await cursor.fetchone()
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if row is not None:
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return {
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'endpoint': row[0],
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'model': row[1],
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'input_tokens': row[2],
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'output_tokens': row[3],
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'total_tokens': row[4]
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}
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return None
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async def aggregate_time_series_older_than(self, days: int, trim_old: bool = False) -> int:
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"""
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Aggregate time_series entries older than 'days' days into daily aggregates by
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endpoint, model and UTC date (YYYY-MM-DD). The results are stored in
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token_time_series_daily with a UNIQUE constraint on (endpoint, model, date).
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Returns the number of aggregated groups (distinct (endpoint, model, date) tuples)
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that were created/updated.
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"""
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if not isinstance(days, int) or days <= 0:
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days = 30
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cutoff_ts = int(datetime.now(tz=timezone.utc).timestamp()) - (days * 86400)
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db = await self._get_connection()
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aggregated_count = 0
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async with self._operation_lock:
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# Ensure daily table exists
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await db.execute('''
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CREATE TABLE IF NOT EXISTS token_time_series_daily (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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endpoint TEXT,
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model TEXT,
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date TEXT,
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input_tokens INTEGER DEFAULT 0,
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output_tokens INTEGER DEFAULT 0,
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total_tokens INTEGER DEFAULT 0,
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UNIQUE(endpoint, model, date)
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)
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''')
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await db.commit()
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cursor = await db.execute('''
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SELECT endpoint, model, date(timestamp, 'unixepoch') as day,
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SUM(input_tokens) as in_sum,
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SUM(output_tokens) as out_sum,
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SUM(total_tokens) as tot_sum
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FROM token_time_series
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WHERE timestamp < ?
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GROUP BY endpoint, model, day
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''', (cutoff_ts,))
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rows = await cursor.fetchall()
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for row in rows:
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endpoint, model, day, in_sum, out_sum, tot_sum = row
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await db.execute('''
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INSERT INTO token_time_series_daily (endpoint, model, date, input_tokens, output_tokens, total_tokens)
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VALUES (?, ?, ?, ?, ?, ?)
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ON CONFLICT (endpoint, model, date) DO UPDATE SET
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input_tokens = input_tokens + ?,
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output_tokens = output_tokens + ?,
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total_tokens = total_tokens + ?
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''', (endpoint, model, day, int(in_sum or 0), int(out_sum or 0), int(tot_sum or 0),
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int(in_sum or 0), int(out_sum or 0), int(tot_sum or 0)))
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aggregated_count += 1
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# Trim old entries if requested
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if trim_old:
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await db.execute('DELETE FROM token_time_series WHERE timestamp < ?', (cutoff_ts,))
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await db.commit()
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return aggregated_count
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