fix(langfuse_otel_attributes.py): log tools and other optional params

litellm/integrations/arize/_utils.py

@@ -20,12 +20,14 @@ class ArizeOTELAttributes(BaseLLMObsOTELAttributes):
 
     @staticmethod
     @override
-    def set_messages(span: "Span", messages: List[Dict[str, Any]]):
+    def set_messages(span: "Span", kwargs: Dict[str, Any]):
         from litellm.integrations._types.open_inference import (
             MessageAttributes,
             SpanAttributes,
         )
 
+        messages = kwargs.get("messages")
+
         # for /chat/completions
         # https://docs.arize.com/arize/large-language-models/tracing/semantic-conventions
         if messages:
@@ -205,9 +207,7 @@ def set_attributes(
             SpanAttributes.OPENINFERENCE_SPAN_KIND,
             OpenInferenceSpanKindValues.LLM.value,
         )
-        messages = kwargs.get("messages")
-
-        attributes.set_messages(span, messages)
+        attributes.set_messages(span, kwargs)
 
         # Capture tools (function definitions) used in the LLM call.
         tools = optional_params.get("tools")

litellm/integrations/langfuse/langfuse_otel_attributes.py

@@ -1,25 +1,104 @@
-import json
-from typing import TYPE_CHECKING, Any, Dict, List
+"""
+If the LLM Obs has any specific attributes to log request or response, we can add them here.
 
+Relevant Issue: https://github.com/BerriAI/litellm/issues/13764
+"""
+
+import json
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
+
+from numpy import isin
 from pydantic import BaseModel
 from typing_extensions import override
 
+import litellm
 from litellm.integrations.opentelemetry_utils.base_otel_llm_obs_attributes import (
     BaseLLMObsOTELAttributes,
     safe_set_attribute,
 )
+from litellm.types.llms.openai import HttpxBinaryResponseContent, ResponsesAPIResponse
+from litellm.types.utils import (
+    EmbeddingResponse,
+    ImageResponse,
+    ModelResponse,
+    RerankResponse,
+    TextCompletionResponse,
+    TranscriptionResponse,
+)
 
 if TYPE_CHECKING:
     from opentelemetry.trace import Span
 
 
+def get_output_content_by_type(
+    response_obj: Union[
+        None,
+        dict,
+        EmbeddingResponse,
+        ModelResponse,
+        TextCompletionResponse,
+        ImageResponse,
+        TranscriptionResponse,
+        RerankResponse,
+        HttpxBinaryResponseContent,
+        ResponsesAPIResponse,
+        list,
+    ],
+    kwargs: Optional[Dict[str, Any]] = None,
+) -> str:
+    """
+    Extract output content from response objects based on their type.
+
+    This utility function handles the type-specific logic for converting
+    various response objects into appropriate output formats for Langfuse logging.
+
+    Args:
+        response_obj: The response object returned by the function
+        kwargs: Optional keyword arguments containing call_type and other metadata
+
+    Returns:
+        The formatted output content suitable for Langfuse logging, or None
+    """
+    if response_obj is None:
+        return ""
+
+    kwargs = kwargs or {}
+    call_type = kwargs.get("call_type", None)
+
+    # Embedding responses - no output content
+    if call_type == "embedding" or isinstance(response_obj, EmbeddingResponse):
+        return "embedding-output"
+
+    # Binary/Speech responses
+    if isinstance(response_obj, HttpxBinaryResponseContent):
+        return "speech-output"
+
+    if isinstance(response_obj, BaseModel):
+        return response_obj.model_dump_json()
+
+    if response_obj and (
+        isinstance(response_obj, dict) or isinstance(response_obj, list)
+    ):
+        return json.dumps(response_obj)
+    else:
+        return ""
+
+
 class LangfuseLLMObsOTELAttributes(BaseLLMObsOTELAttributes):
     @staticmethod
     @override
-    def set_messages(span: "Span", messages: List[Dict[str, Any]]):
-        safe_set_attribute(
-            span, "langfuse.observation.input", json.dumps({"messages": messages})
-        )
+    def set_messages(span: "Span", kwargs: Dict[str, Any]):
+        prompt = {"messages": kwargs.get("messages")}
+        optional_params = kwargs.get("optional_params", {})
+        functions = optional_params.get("functions")
+        tools = optional_params.get("tools")
+        if functions is not None:
+            prompt["functions"] = functions
+        if tools is not None:
+            prompt["tools"] = tools
+
+        input = prompt
+        safe_set_attribute(span, "langfuse.observation.input", json.dumps(input))
 
     @staticmethod
     @override
@@ -27,9 +106,5 @@ class LangfuseLLMObsOTELAttributes(BaseLLMObsOTELAttributes):
         safe_set_attribute(
             span,
             "langfuse.observation.output",
-            (
-                response_obj.model_dump_json()
-                if isinstance(response_obj, BaseModel)
-                else response_obj
-            ),
+            get_output_content_by_type(response_obj),
         )

litellm/integrations/opentelemetry_utils/base_otel_llm_obs_attributes.py

@@ -7,7 +7,7 @@ if TYPE_CHECKING:
 
 class BaseLLMObsOTELAttributes(ABC):
     @staticmethod
-    def set_messages(span: "Span", messages: List[Dict[str, Any]]):
+    def set_messages(span: "Span", kwargs: Dict[str, Any]):
         pass
 
     @staticmethod