feat(llmobs): emitting reasoning tokens metric for openai integration

ddtrace/llmobs/_constants.py

@@ -43,6 +43,7 @@
 CACHE_WRITE_INPUT_TOKENS_METRIC_KEY = "cache_write_input_tokens"
 CACHE_READ_INPUT_TOKENS_METRIC_KEY = "cache_read_input_tokens"
 BILLABLE_CHARACTER_COUNT_METRIC_KEY = "billable_character_count"
+REASONING_OUTPUT_TOKENS_METRIC_KEY = "reasoning_output_tokens"
 
 EVAL_ENDPOINT = "/api/intake/llm-obs/v2/eval-metric"
 SPAN_ENDPOINT = "/api/v2/llmobs"

ddtrace/llmobs/_integrations/openai.py

@@ -19,6 +19,7 @@
 from ddtrace.llmobs._constants import OUTPUT_TOKENS_METRIC_KEY
 from ddtrace.llmobs._constants import OUTPUT_VALUE
 from ddtrace.llmobs._constants import PROXY_REQUEST
+from ddtrace.llmobs._constants import REASONING_OUTPUT_TOKENS_METRIC_KEY
 from ddtrace.llmobs._constants import SPAN_KIND
 from ddtrace.llmobs._constants import TOTAL_TOKENS_METRIC_KEY
 from ddtrace.llmobs._integrations.base import BaseLLMIntegration
@@ -221,6 +222,13 @@ def _extract_llmobs_metrics_tags(
             cached_tokens = _get_attr(prompt_tokens_details, "cached_tokens", None)
             if cached_tokens is not None:
                 metrics[CACHE_READ_INPUT_TOKENS_METRIC_KEY] = cached_tokens
+            # Chat completion returns `completion_tokens_details` while responses api returns `output_tokens_details`
+            reasoning_output_tokens_details = _get_attr(token_usage, "completion_tokens_details", {}) or _get_attr(
+                token_usage, "output_tokens_details", {}
+            )
+            reasoning_output_tokens = _get_attr(reasoning_output_tokens_details, "reasoning_tokens", None)
+            if reasoning_output_tokens is not None:
+                metrics[REASONING_OUTPUT_TOKENS_METRIC_KEY] = reasoning_output_tokens
             return metrics
         elif kwargs.get("stream") and resp is not None:
             prompt_tokens = _compute_prompt_tokens(kwargs.get("prompt", None), kwargs.get("messages", None))

ddtrace/llmobs/_integrations/utils.py

@@ -768,11 +768,6 @@ def openai_get_metadata_from_response(
         if value is not None:
             metadata[field] = load_data_value(value)
 
-    usage = getattr(response, "usage", None)
-    output_tokens_details = getattr(usage, "output_tokens_details", None)
-    reasoning_tokens = getattr(output_tokens_details, "reasoning_tokens", 0)
-    metadata["reasoning_tokens"] = reasoning_tokens
-
     return metadata
 
 
@@ -1181,6 +1176,8 @@ def llmobs_metrics(self) -> Optional[Dict[str, Any]]:
                 metrics["output_tokens"] = usage.output_tokens
             if hasattr(usage, "total_tokens"):
                 metrics["total_tokens"] = usage.total_tokens
+            if hasattr(usage, "reasoning_tokens"):
+                metrics["reasoning_tokens"] = usage.reasoning_tokens
 
         return metrics if metrics else None
 
@@ -1202,9 +1199,6 @@ def llmobs_metadata(self) -> Optional[Dict[str, Any]]:
             if hasattr(self.response, "text") and self.response.text:
                 metadata["text"] = load_data_value(self.response.text)
 
-            if hasattr(self.response, "usage") and hasattr(self.response.usage, "output_tokens_details"):
-                metadata["reasoning_tokens"] = self.response.usage.output_tokens_details.reasoning_tokens
-
         if self.span_type == "custom" and hasattr(self._raw_oai_span.span_data, "data"):
             custom_data = getattr(self._raw_oai_span.span_data, "data", None)
             if custom_data:

tests/contrib/openai/cassettes/v1/response_reasoning_tokens.yaml

@@ -0,0 +1,115 @@
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