phoenix/litellm-mirror
0
0
Fork 1
mirror of https://github.com/BerriAI/litellm.git synced 2025-04-26 03:04:13 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

[Fix] OTEL - Don't log messages when callback settings disable message logging (#5875)

Browse source 
* fix otel dont log messages

* otel fix redis failure hook logging
This commit is contained in:
Ishaan Jaff 2024-09-24 18:29:52 -07:00 • committed by GitHub
parent d37c8b5c6b
commit 3ccdb42d26
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
2 changed files with 60 additions and 43 deletions
Download patch file Download diff file Expand all files Collapse all files

72
litellm/integrations/opentelemetry.py
View file

@ -409,13 +409,51 @@ class OpenTelemetry(CustomLogger):
str(optional_params.get("stream", False)),
)
if optional_params.get("user"):
span.set_attribute(SpanAttributes.LLM_USER, optional_params.get("user"))
# The unique identifier for the completion.
if response_obj.get("id"):
span.set_attribute("gen_ai.response.id", response_obj.get("id"))
# The model used to generate the response.
if response_obj.get("model"):
span.set_attribute(
SpanAttributes.LLM_RESPONSE_MODEL, response_obj.get("model")
)
usage = response_obj.get("usage")
if usage:
span.set_attribute(
SpanAttributes.LLM_USAGE_TOTAL_TOKENS,
usage.get("total_tokens"),
)
# The number of tokens used in the LLM response (completion).
span.set_attribute(
SpanAttributes.LLM_USAGE_COMPLETION_TOKENS,
usage.get("completion_tokens"),
)
# The number of tokens used in the LLM prompt.
span.set_attribute(
SpanAttributes.LLM_USAGE_PROMPT_TOKENS,
usage.get("prompt_tokens"),
)
########################################################################
########## LLM Request Medssages / tools / content Attributes ###########
#########################################################################
if litellm.turn_off_message_logging is True:
return
if self.message_logging is not True:
return
if optional_params.get("tools"):
tools = optional_params["tools"]
self.set_tools_attributes(span, tools)
if optional_params.get("user"):
span.set_attribute(SpanAttributes.LLM_USER, optional_params.get("user"))
if kwargs.get("messages"):
for idx, prompt in enumerate(kwargs.get("messages")):
if prompt.get("role"):
@ -472,34 +510,6 @@ class OpenTelemetry(CustomLogger):
tool_calls[0].get("function").get("arguments"),
)
# The unique identifier for the completion.
if response_obj.get("id"):
span.set_attribute("gen_ai.response.id", response_obj.get("id"))
# The model used to generate the response.
if response_obj.get("model"):
span.set_attribute(
SpanAttributes.LLM_RESPONSE_MODEL, response_obj.get("model")
)
usage = response_obj.get("usage")
if usage:
span.set_attribute(
SpanAttributes.LLM_USAGE_TOTAL_TOKENS,
usage.get("total_tokens"),
)
# The number of tokens used in the LLM response (completion).
span.set_attribute(
SpanAttributes.LLM_USAGE_COMPLETION_TOKENS,
usage.get("completion_tokens"),
)
# The number of tokens used in the LLM prompt.
span.set_attribute(
SpanAttributes.LLM_USAGE_PROMPT_TOKENS,
usage.get("prompt_tokens"),
)
except Exception as e:
verbose_logger.error(
"OpenTelemetry logging error in set_attributes %s", str(e)