cleanup setting prompt events & finish reasons

instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/patch.py

@@ -16,9 +16,11 @@
 from opentelemetry.trace import SpanKind, Span
 from opentelemetry.trace.status import Status, StatusCode
 from .span_attributes import LLMSpanAttributes
+from opentelemetry.semconv.attributes import (
+    error_attributes as ErrorAttributes,
+)
 from opentelemetry.semconv._incubating.attributes import (
     gen_ai_attributes as GenAIAttributes,
-    error_attributes as ErrorAttributes,
 )
 from .utils import (
     silently_fail,
@@ -28,8 +30,10 @@
     set_span_attribute,
     set_event_completion,
     extract_tools_prompt,
+    set_event_prompt,
 )
 from opentelemetry.trace import Tracer
+import json
 
 
 def chat_completions_create(tracer: Tracer):
@@ -43,16 +47,15 @@ def traced_method(wrapped, instance, args, kwargs):
             tools_prompt = extract_tools_prompt(item)
             llm_prompts.append(tools_prompt if tools_prompt else item)
 
-        span_attributes = {
-            **get_llm_request_attributes(kwargs, prompts=llm_prompts),
-        }
+        span_attributes = {**get_llm_request_attributes(kwargs)}
 
         attributes = LLMSpanAttributes(**span_attributes)
 
         span_name = f"{attributes.gen_ai_operation_name} {attributes.gen_ai_request_model}"
 
         span = tracer.start_span(name=span_name, kind=SpanKind.CLIENT)
         _set_input_attributes(span, attributes)
+        set_event_prompt(span, json.dumps(llm_prompts))
 
         try:
             result = wrapped(*args, **kwargs)
@@ -112,13 +115,15 @@ def _set_response_attributes(span, result):
             }
             for choice in choices
         ]
+        finish_reasons = []
         for choice in choices:
-            if choice.finish_reason:
-                set_span_attribute(
-                    span,
-                    GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS,
-                    choice.finish_reason,
-                )
+            finish_reasons.append(choice.finish_reason or "error")
+
+        set_span_attribute(
+            span,
+            GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS,
+            finish_reasons,
+        )
         set_event_completion(span, responses)
 
     if getattr(result, "id", None):
@@ -270,14 +275,15 @@ def build_streaming_response(self, chunk):
                         ):
                             content.append(tool_call.function.arguments)
 
+        finish_reasons = []
         for choice in choices:
-            finish_reason = choice.finish_reason
-            if finish_reason:
-                set_span_attribute(
-                    self.span,
-                    GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS,
-                    finish_reason,
-                )
+            finish_reasons.append(choice.finish_reason or "error")
+
+        set_span_attribute(
+            self.span,
+            GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS,
+            finish_reasons,
+        )
         if content:
             self.result_content.append(content[0])
 

instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/utils.py

@@ -127,10 +127,7 @@ def set_span_attribute(span: Span, name, value):
     if non_numerical_value_is_set(value) is False:
         return
 
-    if name == GenAIAttributes.GEN_AI_PROMPT:
-        set_event_prompt(span, value)
-    else:
-        span.set_attribute(name, value)
+    span.set_attribute(name, value)
 
 
 def is_streaming(kwargs):
@@ -143,37 +140,17 @@ def non_numerical_value_is_set(value: Optional[Union[bool, str]]):
 
 def get_llm_request_attributes(
     kwargs,
-    prompts=None,
     model=None,
     operation_name=GenAIAttributes.GenAiOperationNameValues.CHAT.value,
 ):
 
-    user = kwargs.get("user")
-    if prompts is None:
-        prompts = (
-            [{"role": user or "user", "content": kwargs.get("prompt")}]
-            if "prompt" in kwargs
-            else None
-        )
-    top_k = (
-        kwargs.get("n")
-        or kwargs.get("k")
-        or kwargs.get("top_k")
-        or kwargs.get("top_n")
-    )
-
-    top_p = kwargs.get("p") or kwargs.get("top_p")
-
     return {
         GenAIAttributes.GEN_AI_OPERATION_NAME: operation_name,
         GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiSystemValues.OPENAI.value,
         GenAIAttributes.GEN_AI_REQUEST_MODEL: model or kwargs.get("model"),
         GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE: kwargs.get("temperature"),
-        GenAIAttributes.GEN_AI_REQUEST_TOP_K: top_k,
-        GenAIAttributes.GEN_AI_PROMPT: (
-            json.dumps(prompts) if prompts else None
-        ),
-        GenAIAttributes.GEN_AI_REQUEST_TOP_P: top_p,
+        GenAIAttributes.GEN_AI_REQUEST_TOP_P: kwargs.get("p")
+        or kwargs.get("top_p"),
         GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS: kwargs.get("max_tokens"),
         GenAIAttributes.GEN_AI_REQUEST_PRESENCE_PENALTY: kwargs.get(
             "presence_penalty"