fix(openai): read chat completion reasoning tokens from completion_tokens_details

agentops/instrumentation/providers/openai/wrappers/chat.py

@@ -197,9 +197,9 @@ def handle_chat_attributes(
                 attributes[SpanAttributes.LLM_USAGE_COMPLETION_TOKENS] = usage["completion_tokens"]
 
             # Reasoning tokens
-            output_details = usage.get("output_tokens_details", {})
-            if isinstance(output_details, dict) and "reasoning_tokens" in output_details:
-                attributes[SpanAttributes.LLM_USAGE_REASONING_TOKENS] = output_details["reasoning_tokens"]
+            completion_details = usage.get("completion_tokens_details")
+            if isinstance(completion_details, dict) and completion_details.get("reasoning_tokens") is not None:
+                attributes[SpanAttributes.LLM_USAGE_REASONING_TOKENS] = completion_details["reasoning_tokens"]
 
         # Choices
         if should_send_prompts() and "choices" in response_dict:

tests/unit/instrumentation/openai_core/test_chat_attributes.py

@@ -0,0 +1,41 @@
+from openai.types.chat import ChatCompletion
+
+from agentops.instrumentation.providers.openai.wrappers.chat import handle_chat_attributes
+from agentops.semconv import SpanAttributes
+
+
+def _chat_completion(usage):
+    return ChatCompletion.model_validate(
+        {
+            "id": "chatcmpl-123",
+            "object": "chat.completion",
+            "created": 0,
+            "model": "o3-mini",
+            "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "hi"}}],
+            "usage": usage,
+        }
+    )
+
+
+class TestChatAttributes:
+    def test_reasoning_tokens_from_completion_tokens_details(self):
+        response = _chat_completion(
+            {
+                "prompt_tokens": 10,
+                "completion_tokens": 200,
+                "total_tokens": 210,
+                "completion_tokens_details": {"reasoning_tokens": 192},
+            }
+        )
+
+        attributes = handle_chat_attributes(kwargs={"model": "o3-mini"}, return_value=response)
+
+        assert attributes[SpanAttributes.LLM_USAGE_COMPLETION_TOKENS] == 200
+        assert attributes[SpanAttributes.LLM_USAGE_REASONING_TOKENS] == 192
+
+    def test_no_reasoning_tokens_without_completion_tokens_details(self):
+        response = _chat_completion({"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15})
+
+        attributes = handle_chat_attributes(kwargs={"model": "gpt-4o"}, return_value=response)
+
+        assert SpanAttributes.LLM_USAGE_REASONING_TOKENS not in attributes