fix(openai): langchain streaming bug

packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/__init__.py

@@ -205,6 +205,7 @@ def _set_response_attributes(span, llm_request_type, response):
 def _build_from_streaming_response(span, llm_request_type, response):
  complete_response = {"choices": [], "model": ""}
  for item in response:
+ item_to_yield = item
  if is_openai_v1():
  item = item.__dict__
 
@@ -234,7 +235,7 @@ def _build_from_streaming_response(span, llm_request_type, response):
  else:
  complete_choice["text"] += choice.get("text")
 
- yield item
+ yield item_to_yield
 
  _set_response_attributes(
  span,

packages/traceloop-sdk/tests/test_langchain_instrumentation.py

@@ -1,5 +1,8 @@
 from langchain.prompts import PromptTemplate
 from langchain.llms import OpenAI
+from langchain.schema import StrOutputParser
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import PromptTemplate
 from langchain import LLMChain
 from langchain.chains import SequentialChain
 
@@ -38,7 +41,6 @@ def test_langchain(exporter):
  )
 
  spans = exporter.get_finished_spans()
- print([span.name for span in spans])
 
  assert set(
  [
@@ -48,3 +50,25 @@ def test_langchain(exporter):
  "langchain.workflow",
  ]
  ).issubset([span.name for span in spans])
+
+
+def test_langchain_streaming(exporter):
+ chat = ChatOpenAI(
+ model="gpt-4",
+ temperature=0,
+ streaming=True,
+ )
+
+ prompt = PromptTemplate.from_template(
+ "write 10 lines of random text about ${product}"
+ )
+ runnable = prompt | chat | StrOutputParser()
+ runnable.invoke({"product": "colorful socks"})
+
+ spans = exporter.get_finished_spans()
+
+ assert set(
+ [
+ "openai.chat",
+ ]
+ ).issubset([span.name for span in spans])