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docs: fix latency_ms for datetime objects, drop unused time import

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LiteLLM passes datetime.datetime to log_success_event, not float.
The previous int((end - start) * 1000) raised TypeError because you
cannot multiply timedelta by int. Wrap in a small helper that uses
total_seconds() when available and falls back to numeric subtraction
for older paths that pass floats.
This commit is contained in:
João André Gomes Marques 2026-04-18 10:24:51 +02:00
parent cde1193f1b
commit 93a419cd5f
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1 changed files with 21 additions and 3 deletions
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24
docs/my-website/docs/observability/asqav_integration.md
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@ -40,13 +40,22 @@ The integration is a single LiteLLM `CustomLogger` subclass. Drop it into your p
```python
import os
import time
import uuid
import httpx
import litellm
from litellm.integrations.custom_logger import CustomLogger
def _latency_ms(start, end):
"""LiteLLM passes datetime objects; older paths may pass floats."""
if not start or not end:
return None
delta = end - start
if hasattr(delta, "total_seconds"):
return int(delta.total_seconds() * 1000)
return int(delta * 1000)
class AsqavLogger(CustomLogger):
"""Posts a signed audit record to Asqav after every LLM call."""
@ -73,7 +82,7 @@ class AsqavLogger(CustomLogger):
self._sign("llm:call", {
"model": kwargs.get("model"),
"message_count": len(kwargs.get("messages") or []),
"latency_ms": int((end_time - start_time) * 1000) if start_time and end_time else None,
"latency_ms": _latency_ms(start_time, end_time),
"prompt_tokens": getattr(usage, "prompt_tokens", None),
"completion_tokens": getattr(usage, "completion_tokens", None),
})
@ -110,6 +119,15 @@ import httpx
from litellm.integrations.custom_logger import CustomLogger
def _latency_ms(start, end):
if not start or not end:
return None
delta = end - start
if hasattr(delta, "total_seconds"):
return int(delta.total_seconds() * 1000)
return int(delta * 1000)
class AsqavLogger(CustomLogger):
def __init__(self) -> None:
self.api_key = os.environ["ASQAV_API_KEY"]
@ -133,7 +151,7 @@ class AsqavLogger(CustomLogger):
self._sign("llm:call", {
"model": kwargs.get("model"),
"message_count": len(kwargs.get("messages") or []),
"latency_ms": int((end_time - start_time) * 1000) if start_time and end_time else None,
"latency_ms": _latency_ms(start_time, end_time),
"prompt_tokens": getattr(usage, "prompt_tokens", None),
"completion_tokens": getattr(usage, "completion_tokens", None),
})