dimension.count is added in get_llm_request_attributes

Author: drewby

instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2/patch.py

@@ -172,12 +172,6 @@ def traced_method(wrapped, instance, args, kwargs):
             )
         }
 
-        # Using a custom attribute "gen_ai.embeddings.dimension.count". Will propose to semantic conventions.
-        if "dimensions" in kwargs and kwargs["dimensions"] is not None:
-            span_attributes["gen_ai.embeddings.dimension.count"] = kwargs[
-                "dimensions"
-            ]
-
         span_name = f"{span_attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]} {span_attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL]}"
         with tracer.start_as_current_span(
             name=span_name,
@@ -235,12 +229,6 @@ async def traced_method(wrapped, instance, args, kwargs):
             )
         }
 
-        # Set embeddings dimensions if specified in the request
-        if "dimensions" in kwargs and kwargs["dimensions"] is not None:
-            span_attributes["gen_ai.embeddings.dimension.count"] = kwargs[
-                "dimensions"
-            ]
-
         span_name = f"{span_attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]} {span_attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL]}"
         with tracer.start_as_current_span(
             name=span_name,

instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2/utils.py

@@ -241,10 +241,8 @@ def get_llm_request_attributes(
         == GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value
     ):
         # Add embedding dimensions if specified
-        if "dimensions" in kwargs and kwargs["dimensions"] is not None:
-            attributes["gen_ai.embeddings.dimension.count"] = kwargs[
-                "dimensions"
-            ]
+        if (dimensions := kwargs.get("dimensions")) is not None:
+            attributes["gen_ai.embeddings.dimension.count"] = dimensions
 
         # Add encoding format if specified
         if "encoding_format" in kwargs: