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feat(langchain): Set gen_ai.operation.name and gen_ai.pipeline.name on LLM spans #5849

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Merged
ericapisani merged 4 commits into from
Mar 25, 2026
+13 −2
Merged

feat(langchain): Set gen_ai.operation.name and gen_ai.pipeline.name on LLM spans #5849

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840eced
test(langchain): Add pipeline name attribute assertions to on_llm_sta…
ericapisani Mar 24, 2026
97e60f3
Merge branch 'master' into ep/sdk-669-add-pipeline-to-span-attributes…
ericapisani Mar 25, 2026
940a455
Address CR comment
ericapisani Mar 25, 2026
16805b3
Merge branch 'master' into ep/sdk-669-add-pipeline-to-span-attributes…
ericapisani Mar 25, 2026
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6 changes: 6 additions & 0 deletions sentry_sdk/integrations/langchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -383,6 +383,12 @@ def on_llm_start(
)
span = watched_span.span

span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "generate_text")

pipeline_name = kwargs.get("name")
if pipeline_name:
span.set_data(SPANDATA.GEN_AI_PIPELINE_NAME, pipeline_name)

if model:
span.set_data(
SPANDATA.GEN_AI_REQUEST_MODEL,
Expand Down
9 changes: 7 additions & 2 deletions tests/integrations/langchain/test_langchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -147,7 +147,7 @@ def test_langchain_text_completion(
) as _:
with start_transaction():
input_text = "What is the capital of France?"
model.invoke(input_text)
model.invoke(input_text, config={"run_name": "my-snazzy-pipeline"})

tx = events[0]
assert tx["type"] == "transaction"
Expand All @@ -160,6 +160,7 @@ def test_langchain_text_completion(
llm_span = llm_spans[0]
assert llm_span["description"] == "generate_text gpt-3.5-turbo"
assert llm_span["data"]["gen_ai.system"] == "openai"
assert llm_span["data"]["gen_ai.pipeline.name"] == "my-snazzy-pipeline"
assert llm_span["data"]["gen_ai.request.model"] == "gpt-3.5-turbo"
assert llm_span["data"]["gen_ai.response.text"] == "The capital of France is Paris."
assert llm_span["data"]["gen_ai.usage.total_tokens"] == 25
Expand Down Expand Up @@ -1268,6 +1269,7 @@ def test_langchain_message_truncation(sentry_init, capture_events):
serialized=serialized,
prompts=prompts,
run_id=run_id,
name="my_pipeline",
invocation_params={
"temperature": 0.7,
"max_tokens": 100,
Expand Down Expand Up @@ -1297,8 +1299,10 @@ def test_langchain_message_truncation(sentry_init, capture_events):
assert len(llm_spans) > 0

llm_span = llm_spans[0]
assert SPANDATA.GEN_AI_REQUEST_MESSAGES in llm_span["data"]
assert llm_span["data"]["gen_ai.operation.name"] == "generate_text"
assert llm_span["data"][SPANDATA.GEN_AI_PIPELINE_NAME] == "my_pipeline"

assert SPANDATA.GEN_AI_REQUEST_MESSAGES in llm_span["data"]
messages_data = llm_span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
assert isinstance(messages_data, str)

Expand Down Expand Up @@ -2011,6 +2015,7 @@ def test_langchain_response_model_extraction(
assert len(llm_spans) > 0

llm_span = llm_spans[0]
assert llm_span["data"]["gen_ai.operation.name"] == "generate_text"

if expected_model is not None:
assert SPANDATA.GEN_AI_RESPONSE_MODEL in llm_span["data"]
Expand Down
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