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https://github.com/BerriAI/litellm.git
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Merge pull request #4078 from BerriAI/litellm_low_raw_request_response_otel
[FEAT]- OTEL Log raw LLM request/response on OTEL
This commit is contained in:
Ishaan Jaff
GitHub
commit
8c5802d506
3 changed files with 257 additions and 80 deletions
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@ -1,6 +1,7 @@
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import os
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from dataclasses import dataclass
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from datetime import datetime
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import litellm
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from litellm.integrations.custom_logger import CustomLogger
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from litellm._logging import verbose_logger
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@ -22,6 +23,8 @@ LITELLM_TRACER_NAME = os.getenv("OTEL_TRACER_NAME", "litellm")
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LITELLM_RESOURCE = {
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"service.name": os.getenv("OTEL_SERVICE_NAME", "litellm"),
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}
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RAW_REQUEST_SPAN_NAME = "raw_gen_ai_request"
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LITELLM_REQUEST_SPAN_NAME = "litellm_request"
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@dataclass
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@ -194,6 +197,7 @@ class OpenTelemetry(CustomLogger):
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def _handle_sucess(self, kwargs, response_obj, start_time, end_time):
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from opentelemetry.trace import Status, StatusCode
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from opentelemetry import trace
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verbose_logger.debug(
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"OpenTelemetry Logger: Logging kwargs: %s, OTEL config settings=%s",
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@ -202,6 +206,7 @@ class OpenTelemetry(CustomLogger):
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)
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_parent_context, parent_otel_span = self._get_span_context(kwargs)
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# Span 1: Requst sent to litellm SDK
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span = self.tracer.start_span(
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name=self._get_span_name(kwargs),
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start_time=self._to_ns(start_time),
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@ -209,7 +214,23 @@ class OpenTelemetry(CustomLogger):
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)
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span.set_status(Status(StatusCode.OK))
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self.set_attributes(span, kwargs, response_obj)
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if litellm.turn_off_message_logging is True:
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pass
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else:
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# Span 2: Raw Request / Response to LLM
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raw_request_span = self.tracer.start_span(
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name=RAW_REQUEST_SPAN_NAME,
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start_time=self._to_ns(start_time),
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context=trace.set_span_in_context(span),
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)
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raw_request_span.set_status(Status(StatusCode.OK))
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self.set_raw_request_attributes(raw_request_span, kwargs, response_obj)
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raw_request_span.end(end_time=self._to_ns(end_time))
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span.end(end_time=self._to_ns(end_time))
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if parent_otel_span is not None:
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parent_otel_span.end(end_time=self._to_ns(datetime.now()))
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@ -225,6 +246,31 @@ class OpenTelemetry(CustomLogger):
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self.set_attributes(span, kwargs, response_obj)
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span.end(end_time=self._to_ns(end_time))
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def set_tools_attributes(self, span: Span, tools):
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from opentelemetry.semconv.ai import SpanAttributes
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import json
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if not tools:
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return
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try:
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for i, tool in enumerate(tools):
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function = tool.get("function")
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if not function:
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continue
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prefix = f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.{i}"
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span.set_attribute(f"{prefix}.name", function.get("name"))
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span.set_attribute(f"{prefix}.description", function.get("description"))
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span.set_attribute(
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f"{prefix}.parameters", json.dumps(function.get("parameters"))
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)
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except Exception as e:
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verbose_logger.error(
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"OpenTelemetry: Error setting tools attributes: %s", str(e)
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)
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pass
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def set_attributes(self, span: Span, kwargs, response_obj):
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from opentelemetry.semconv.ai import SpanAttributes
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@ -239,7 +285,8 @@ class OpenTelemetry(CustomLogger):
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#############################################
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# The name of the LLM a request is being made to
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span.set_attribute(SpanAttributes.LLM_REQUEST_MODEL, kwargs.get("model"))
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if kwargs.get("model"):
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span.set_attribute(SpanAttributes.LLM_REQUEST_MODEL, kwargs.get("model"))
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# The Generative AI Provider: Azure, OpenAI, etc.
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span.set_attribute(
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@ -248,64 +295,99 @@ class OpenTelemetry(CustomLogger):
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)
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# The maximum number of tokens the LLM generates for a request.
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span.set_attribute(
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SpanAttributes.LLM_REQUEST_MAX_TOKENS, optional_params.get("max_tokens")
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)
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if optional_params.get("max_tokens"):
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span.set_attribute(
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SpanAttributes.LLM_REQUEST_MAX_TOKENS, optional_params.get("max_tokens")
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)
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# The temperature setting for the LLM request.
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span.set_attribute(
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SpanAttributes.LLM_REQUEST_TEMPERATURE, optional_params.get("temperature")
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)
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if optional_params.get("temperature"):
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span.set_attribute(
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SpanAttributes.LLM_REQUEST_TEMPERATURE,
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optional_params.get("temperature"),
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)
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# The top_p sampling setting for the LLM request.
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span.set_attribute(
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SpanAttributes.LLM_REQUEST_TOP_P, optional_params.get("top_p")
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)
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span.set_attribute(
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SpanAttributes.LLM_IS_STREAMING, optional_params.get("stream")
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)
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span.set_attribute(
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SpanAttributes.LLM_REQUEST_FUNCTIONS,
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optional_params.get("tools"),
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)
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span.set_attribute(SpanAttributes.LLM_USER, optional_params.get("user"))
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for idx, prompt in enumerate(kwargs.get("messages")):
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if optional_params.get("top_p"):
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span.set_attribute(
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f"{SpanAttributes.LLM_PROMPTS}.{idx}.role",
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prompt.get("role"),
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)
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span.set_attribute(
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f"{SpanAttributes.LLM_PROMPTS}.{idx}.content",
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prompt.get("content"),
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SpanAttributes.LLM_REQUEST_TOP_P, optional_params.get("top_p")
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)
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span.set_attribute(
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SpanAttributes.LLM_IS_STREAMING, optional_params.get("stream", False)
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)
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if optional_params.get("tools"):
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tools = optional_params["tools"]
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self.set_tools_attributes(span, tools)
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if optional_params.get("user"):
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span.set_attribute(SpanAttributes.LLM_USER, optional_params.get("user"))
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if kwargs.get("messages"):
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for idx, prompt in enumerate(kwargs.get("messages")):
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if prompt.get("role"):
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span.set_attribute(
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f"{SpanAttributes.LLM_PROMPTS}.{idx}.role",
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prompt.get("role"),
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)
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if prompt.get("content"):
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if not isinstance(prompt.get("content"), str):
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prompt["content"] = str(prompt.get("content"))
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span.set_attribute(
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f"{SpanAttributes.LLM_PROMPTS}.{idx}.content",
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prompt.get("content"),
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)
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#############################################
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########## LLM Response Attributes ##########
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#############################################
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if response_obj.get("choices"):
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for idx, choice in enumerate(response_obj.get("choices")):
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if choice.get("finish_reason"):
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.finish_reason",
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choice.get("finish_reason"),
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)
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if choice.get("message"):
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if choice.get("message").get("role"):
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.role",
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choice.get("message").get("role"),
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)
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if choice.get("message").get("content"):
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if not isinstance(choice.get("message").get("content"), str):
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choice["message"]["content"] = str(
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choice.get("message").get("content")
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)
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.content",
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choice.get("message").get("content"),
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)
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for idx, choice in enumerate(response_obj.get("choices")):
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.finish_reason",
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choice.get("finish_reason"),
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)
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.role",
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choice.get("message").get("role"),
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)
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.content",
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choice.get("message").get("content"),
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)
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message = choice.get("message")
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if not isinstance(message, dict):
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message = message.dict()
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tool_calls = message.get("tool_calls")
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if tool_calls:
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.function_call.name",
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tool_calls[0].get("function").get("name"),
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)
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span.set_attribute(
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f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.function_call.arguments",
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tool_calls[0].get("function").get("arguments"),
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)
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# The unique identifier for the completion.
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span.set_attribute("gen_ai.response.id", response_obj.get("id"))
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if response_obj.get("id"):
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span.set_attribute("gen_ai.response.id", response_obj.get("id"))
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# The model used to generate the response.
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span.set_attribute(SpanAttributes.LLM_RESPONSE_MODEL, response_obj.get("model"))
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if response_obj.get("model"):
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span.set_attribute(
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SpanAttributes.LLM_RESPONSE_MODEL, response_obj.get("model")
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)
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usage = response_obj.get("usage")
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if usage:
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@ -326,11 +408,53 @@ class OpenTelemetry(CustomLogger):
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usage.get("prompt_tokens"),
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)
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def set_raw_request_attributes(self, span: Span, kwargs, response_obj):
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from opentelemetry.semconv.ai import SpanAttributes
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optional_params = kwargs.get("optional_params", {})
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litellm_params = kwargs.get("litellm_params", {}) or {}
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custom_llm_provider = litellm_params.get("custom_llm_provider", "Unknown")
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_raw_response = kwargs.get("original_response")
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_additional_args = kwargs.get("additional_args", {}) or {}
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complete_input_dict = _additional_args.get("complete_input_dict")
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#############################################
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########## LLM Request Attributes ###########
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#############################################
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# OTEL Attributes for the RAW Request to https://docs.anthropic.com/en/api/messages
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if complete_input_dict:
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for param, val in complete_input_dict.items():
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if not isinstance(val, str):
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val = str(val)
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span.set_attribute(
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f"llm.{custom_llm_provider}.{param}",
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val,
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)
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#############################################
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########## LLM Response Attributes ##########
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#############################################
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if _raw_response:
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# cast sr -> dict
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import json
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_raw_response = json.loads(_raw_response)
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for param, val in _raw_response.items():
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if not isinstance(val, str):
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val = str(val)
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span.set_attribute(
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f"llm.{custom_llm_provider}.{param}",
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val,
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)
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pass
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def _to_ns(self, dt):
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return int(dt.timestamp() * 1e9)
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def _get_span_name(self, kwargs):
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return f"litellm-{kwargs.get('call_type', 'completion')}"
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return LITELLM_REQUEST_SPAN_NAME
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def _get_span_context(self, kwargs):
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from opentelemetry.trace.propagation.tracecontext import (
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