mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 10:44:24 +00:00
741c8e8a45
* fix refactor dd to be an instance of custom logger * migrate dd logger to be async * clean up dd logging * add datadog sync and async code * use batching for datadog logger * add doc string for dd logging * add clear doc string * fix doc string * allow debugging intake url * clean up requirements.txt * allow setting custom batch size on logger * fix dd logging to use compression * fix linting * add dd load test * fix dd load test * fix dd url * add test_datadog_logging_http_request * fix test_datadog_logging_http_request
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
"""
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Custom Logger that handles batching logic
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Use this if you want your logs to be stored in memory and flushed periodically
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"""
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import asyncio
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import time
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from typing import List, Literal, Optional
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from litellm._logging import verbose_logger
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from litellm.integrations.custom_logger import CustomLogger
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DEFAULT_BATCH_SIZE = 512
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DEFAULT_FLUSH_INTERVAL_SECONDS = 5
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class CustomBatchLogger(CustomLogger):
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def __init__(
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self,
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flush_lock: Optional[asyncio.Lock] = None,
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batch_size: Optional[int] = DEFAULT_BATCH_SIZE,
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**kwargs,
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) -> None:
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"""
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Args:
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flush_lock (Optional[asyncio.Lock], optional): Lock to use when flushing the queue. Defaults to None. Only used for custom loggers that do batching
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"""
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self.log_queue: List = []
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self.flush_interval = DEFAULT_FLUSH_INTERVAL_SECONDS # 10 seconds
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self.batch_size: int = batch_size or DEFAULT_BATCH_SIZE
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self.last_flush_time = time.time()
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self.flush_lock = flush_lock
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super().__init__(**kwargs)
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pass
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async def periodic_flush(self):
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while True:
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await asyncio.sleep(self.flush_interval)
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verbose_logger.debug(
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f"CustomLogger periodic flush after {self.flush_interval} seconds"
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)
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await self.flush_queue()
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async def flush_queue(self):
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async with self.flush_lock:
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if self.log_queue:
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verbose_logger.debug(
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"CustomLogger: Flushing batch of %s events", len(self.log_queue)
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)
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await self.async_send_batch()
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self.log_queue.clear()
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self.last_flush_time = time.time()
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async def async_send_batch(self):
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pass
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