[NET-1411] fix: Capture usage for OpenAI Response API when stream ends due token limit

CHANGELOG.md

@@ -4,7 +4,7 @@ All notable changes to this project will be documented in this file.
 
 The format is based on Keep a Changelog and this project adheres to Semantic Versioning.
 
-## [0.1.97b1] - 2026-07-28
+## [0.1.97] -
 
 - **Label evaluation/simulation traces on the root span** - Root spans produced by evaluation test runs (`Netra.evaluation`) and simulation runs (`Netra.simulation`) now carry a `netra.trace.origin` attribute set to `evaluation`, letting the backend and frontend distinguish these traces from normal workflow invocations.
 
@@ -24,6 +24,8 @@ The format is based on Keep a Changelog and this project adheres to Semantic Ver
 
 - **Refactor stream wrapper architecture to use callback injection** - `stream_utils` is now a pure utility module with no Netra-internal imports. The commit logic (serialize and set attribute on root span) is injected as a callback from `SessionManager`, eliminating the circular dependency between `stream_utils` and `SessionManager`.
 
+- **Fix OpenAI Responses API stream handling** — `Response API` instrumentation spans now include token usage and completion output when a stream ends due to reaching the token limit (`incomplete` status).
+
 ## [0.1.96] - 2026-07-23
 
 - **Reparent children of blocked root instruments instead of dropping the subtree** - When an instrumentation is not allowed to emit root-level spans, its children are now re-parented onto the nearest valid ancestor rather than dropping the entire subtree, so downstream spans are preserved.
@@ -336,4 +338,4 @@ Users can be now overwrite the input and ouput attributes of spans created by in
 
 - Added utility to set input and output data for any active span in a trace
 
-[0.1.97b1]: https://github.com/KeyValueSoftwareSystems/netra-sdk-py/tree/main
+[0.1.97]: https://github.com/KeyValueSoftwareSystems/netra-sdk-py/tree/main

netra/instrumentation/openai/wrappers.py

@@ -397,7 +397,10 @@ def _process_chunk(self, chunk: Any) -> None:
             record_span_timing(self._span, RELATIVE_TIME_TO_FIRST_TOKEN, first_token_time, use_root_span=True)
         if chunk_dict.get("response"):
             response = chunk_dict.get("response", {})
-            if response.get("status") == "completed":
+            if response.get("status") in ("completed", "incomplete"):
+                if response.get("model"):
+                    self._complete_response["model"] = response["model"]
+
                 response_output = response.get("output") or []
                 for output in response_output:
                     if output.get("type") == "function_call":
@@ -547,7 +550,10 @@ def _process_chunk(self, chunk: Any) -> None:
             record_span_timing(self._span, RELATIVE_TIME_TO_FIRST_TOKEN, first_token_time, use_root_span=True)
         if chunk_dict.get("response"):
             response = chunk_dict.get("response", {})
-            if response.get("status") == "completed":
+            if response.get("status") in ("completed", "incomplete"):
+                if response.get("model"):
+                    self._complete_response["model"] = response["model"]
+
                 response_output = response.get("output") or []
                 for output in response_output:
                     if output.get("type") == "function_call":

netra/version.py

@@ -1 +1 @@
-__version__ = "0.1.97b1"
+__version__ = "0.1.97dev1"

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [project]
 name = "netra-sdk"
-version = "0.1.97b1"
+version = "0.1.97dev1"
 description = "A Python SDK for AI application observability that provides OpenTelemetry-based monitoring, tracing, and PII protection for LLM and vector database applications. Enables easy instrumentation, session tracking, and privacy-focused data collection for AI systems in production environments."
 authors = [
     {name = "Sooraj Thomas",email = "sooraj@keyvalue.systems"}