nomyo-router/tokens.py

177 lines
7.1 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

"""Token-count write-behind pipeline.
``token_worker`` drains ``token_queue`` into the in-memory buffer (and into
``token_usage_counts`` for immediate SSE reporting). ``flush_buffer``
periodically persists the buffer to SQLite via ``TokenDatabase``.
``flush_remaining_buffers`` is invoked on shutdown to drain whatever is left.
The lock order is ``buffer_lock`` then ``token_usage_lock`` — see
choose_endpoint for why we never combine them with usage_lock.
"""
import asyncio
from datetime import datetime, timezone
from state import (
token_queue,
token_buffer,
time_series_buffer,
buffer_lock,
token_usage_counts,
token_usage_lock,
FLUSH_INTERVAL,
)
from sse import _capture_snapshot, _distribute_snapshot
from db import get_db
async def token_worker() -> None:
try:
while True:
endpoint, model, prompt, comp = await token_queue.get()
# Calculate timestamp once before acquiring lock
now = datetime.now(tz=timezone.utc)
timestamp = int(datetime(now.year, now.month, now.day, now.hour, now.minute, tzinfo=timezone.utc).timestamp())
# Accumulate counts in memory buffer (protected by lock)
async with buffer_lock:
token_buffer[endpoint][model] = (
token_buffer[endpoint].get(model, (0, 0))[0] + prompt,
token_buffer[endpoint].get(model, (0, 0))[1] + comp
)
# Add to time series buffer with timestamp (UTC)
time_series_buffer.append({
'endpoint': endpoint,
'model': model,
'input_tokens': prompt,
'output_tokens': comp,
'total_tokens': prompt + comp,
'timestamp': timestamp
})
# Update in-memory counts for immediate reporting
async with token_usage_lock:
token_usage_counts[endpoint][model] += (prompt + comp)
snapshot = _capture_snapshot()
await _distribute_snapshot(snapshot)
except asyncio.CancelledError:
# Gracefully handle task cancellation during shutdown
print("[token_worker] Task cancelled, processing remaining queue items...")
# Process any remaining items in the queue before exiting
while not token_queue.empty():
try:
endpoint, model, prompt, comp = token_queue.get_nowait()
# Calculate timestamp once before acquiring lock
now = datetime.now(tz=timezone.utc)
timestamp = int(datetime(now.year, now.month, now.day, now.hour, now.minute, tzinfo=timezone.utc).timestamp())
async with buffer_lock:
token_buffer[endpoint][model] = (
token_buffer[endpoint].get(model, (0, 0))[0] + prompt,
token_buffer[endpoint].get(model, (0, 0))[1] + comp
)
time_series_buffer.append({
'endpoint': endpoint,
'model': model,
'input_tokens': prompt,
'output_tokens': comp,
'total_tokens': prompt + comp,
'timestamp': timestamp
})
async with token_usage_lock:
token_usage_counts[endpoint][model] += (prompt + comp)
snapshot = _capture_snapshot()
await _distribute_snapshot(snapshot)
except asyncio.QueueEmpty:
break
print("[token_worker] Task cancelled, remaining items processed.")
raise
async def flush_buffer() -> None:
"""Periodically flush accumulated token counts to the database."""
try:
while True:
await asyncio.sleep(FLUSH_INTERVAL)
# Flush token counts and time series (protected by lock)
async with buffer_lock:
if token_buffer:
# Copy buffer before releasing lock for DB operation
buffer_copy = {ep: dict(models) for ep, models in token_buffer.items()}
token_buffer.clear()
else:
buffer_copy = None
if time_series_buffer:
ts_copy = list(time_series_buffer)
time_series_buffer.clear()
else:
ts_copy = None
# Perform DB operations outside the lock to avoid blocking
db = get_db()
if buffer_copy:
await db.update_batched_counts(buffer_copy)
if ts_copy:
await db.add_batched_time_series(ts_copy)
except asyncio.CancelledError:
# Gracefully handle task cancellation during shutdown
print("[flush_buffer] Task cancelled, flushing remaining buffers...")
# Flush any remaining data before exiting
try:
async with buffer_lock:
if token_buffer:
buffer_copy = {ep: dict(models) for ep, models in token_buffer.items()}
token_buffer.clear()
else:
buffer_copy = None
if time_series_buffer:
ts_copy = list(time_series_buffer)
time_series_buffer.clear()
else:
ts_copy = None
db = get_db()
if buffer_copy:
await db.update_batched_counts(buffer_copy)
if ts_copy:
await db.add_batched_time_series(ts_copy)
print("[flush_buffer] Task cancelled, remaining buffers flushed.")
except Exception as e:
print(f"[flush_buffer] Error during shutdown flush: {e}")
raise
async def flush_remaining_buffers() -> None:
"""
Flush any in-memory buffers to the database on shutdown.
This is designed to be safely invoked during shutdown and should not raise.
"""
try:
flushed_entries = 0
async with buffer_lock:
if token_buffer:
buffer_copy = {ep: dict(models) for ep, models in token_buffer.items()}
flushed_entries += sum(len(v) for v in token_buffer.values())
token_buffer.clear()
else:
buffer_copy = None
if time_series_buffer:
ts_copy = list(time_series_buffer)
flushed_entries += len(time_series_buffer)
time_series_buffer.clear()
else:
ts_copy = None
# Perform DB operations outside the lock
db = get_db()
if buffer_copy:
await db.update_batched_counts(buffer_copy)
if ts_copy:
await db.add_batched_time_series(ts_copy)
if flushed_entries:
print(f"[shutdown] Flushed {flushed_entries} in-memory entries to DB on shutdown.")
else:
print("[shutdown] No in-memory entries to flush on shutdown.")
except Exception as e:
# Do not raise during shutdown log and continue teardown
print(f"[shutdown] Error flushing remaining buffers: {e}")