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fix(langchain): Set agent name as gen_ai.agent.name #5877

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fix(langchain): Set agent name as gen_ai.agent.name #5877

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154 changes: 60 additions & 94 deletions sentry_sdk/integrations/langchain.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
import contextvars
import itertools
import sys
import json
Expand Down Expand Up @@ -153,44 +152,6 @@ def _transform_langchain_message_content(content: "Any") -> "Any":
return content


# Contextvar to track agent names in a stack for re-entrant agent support
_agent_stack: "contextvars.ContextVar[Optional[List[Optional[str]]]]" = (
contextvars.ContextVar("langchain_agent_stack", default=None)
)


def _push_agent(agent_name: "Optional[str]") -> None:
"""Push an agent name onto the stack."""
stack = _agent_stack.get()
if stack is None:
stack = []
else:
# Copy the list to maintain contextvar isolation across async contexts
stack = stack.copy()
stack.append(agent_name)
_agent_stack.set(stack)


def _pop_agent() -> "Optional[str]":
"""Pop an agent name from the stack and return it."""
stack = _agent_stack.get()
if stack:
# Copy the list to maintain contextvar isolation across async contexts
stack = stack.copy()
agent_name = stack.pop()
_agent_stack.set(stack)
return agent_name
return None


def _get_current_agent() -> "Optional[str]":
"""Get the current agent name (top of stack) without removing it."""
stack = _agent_stack.get()
if stack:
return stack[-1]
return None


def _get_system_instructions(messages: "List[List[BaseMessage]]") -> "List[str]":
system_instructions = []

Expand Down Expand Up @@ -454,8 +415,8 @@ def on_chat_model_start(
elif "openai" in ai_type:
span.set_data(SPANDATA.GEN_AI_SYSTEM, "openai")

agent_name = _get_current_agent()
if agent_name:
agent_name = kwargs.get("metadata", {}).get("lc_agent_name")
if agent_name is not None:
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, agent_name)

for key, attribute in DATA_FIELDS.items():
Expand Down Expand Up @@ -654,8 +615,8 @@ def on_tool_start(
if tool_description is not None:
span.set_data(SPANDATA.GEN_AI_TOOL_DESCRIPTION, tool_description)

agent_name = _get_current_agent()
if agent_name:
agent_name = kwargs.get("metadata", {}).get("lc_agent_name")
if agent_name is not None:
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, agent_name)

if should_send_default_pii() and self.include_prompts:
Expand Down Expand Up @@ -782,9 +743,7 @@ def _record_token_usage(span: "Span", response: "Any") -> None:
span.set_data(SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS, total_tokens)


def _get_request_data(
obj: "Any", args: "Any", kwargs: "Any"
) -> "tuple[Optional[str], Optional[List[Any]]]":
def _get_available_tools(obj: "Any") -> "tuple[Optional[str], Optional[List[Any]]]":
"""
Get the agent name and available tools for the agent.
"""
Expand All @@ -799,6 +758,13 @@ def _get_request_data(
)
tools = tools if tools and len(tools) > 0 else None

return tools


def _get_run_name(obj: "Any", args: "Any"):
agent = getattr(obj, "agent", None)
runnable = getattr(agent, "runnable", None)
runnable_config = getattr(runnable, "config", {})
try:
agent_name = None
if len(args) > 1:
Expand All @@ -808,7 +774,7 @@ def _get_request_data(
except Exception:
pass

return (agent_name, tools)
return agent_name


def _simplify_langchain_tools(tools: "Any") -> "Optional[List[Any]]":
Expand Down Expand Up @@ -976,58 +942,53 @@ def new_invoke(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
if integration is None:
return f(self, *args, **kwargs)

agent_name, tools = _get_request_data(self, args, kwargs)
start_span_function = get_start_span_function()

run_name = _get_run_name(self, args)
with start_span_function(
op=OP.GEN_AI_INVOKE_AGENT,
name=f"invoke_agent {agent_name}" if agent_name else "invoke_agent",
name=run_name,
origin=LangchainIntegration.origin,
) as span:
_push_agent(agent_name)
try:
if agent_name:
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, agent_name)
if run_name:
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, run_name)

span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, False)
span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, False)

_set_tools_on_span(span, tools)
tools = _get_available_tools(self)
_set_tools_on_span(span, tools)

# Run the agent
result = f(self, *args, **kwargs)
# Run the agent
result = f(self, *args, **kwargs)

input = result.get("input")
if (
input is not None
and should_send_default_pii()
and integration.include_prompts
):
normalized_messages = normalize_message_roles([input])
scope = sentry_sdk.get_current_scope()
messages_data = truncate_and_annotate_messages(
normalized_messages, span, scope
input = result.get("input")
if (
input is not None
and should_send_default_pii()
and integration.include_prompts
):
normalized_messages = normalize_message_roles([input])
scope = sentry_sdk.get_current_scope()
messages_data = truncate_and_annotate_messages(
normalized_messages, span, scope
)
if messages_data is not None:
set_data_normalized(
span,
SPANDATA.GEN_AI_REQUEST_MESSAGES,
messages_data,
unpack=False,
)
if messages_data is not None:
set_data_normalized(
span,
SPANDATA.GEN_AI_REQUEST_MESSAGES,
messages_data,
unpack=False,
)

output = result.get("output")
if (
output is not None
and should_send_default_pii()
and integration.include_prompts
):
set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, output)
output = result.get("output")
if (
output is not None
and should_send_default_pii()
and integration.include_prompts
):
set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, output)

return result
finally:
# Ensure agent is popped even if an exception occurs
_pop_agent()
return result

return new_invoke

Expand All @@ -1039,24 +1000,31 @@ def new_stream(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
if integration is None:
return f(self, *args, **kwargs)

agent_name, tools = _get_request_data(self, args, kwargs)
start_span_function = get_start_span_function()

agent_name = kwargs.get("metadata", {}).get("lc_agent_name")
run_name = _get_run_name(self, args)

span_name = "invoke_agent"
if agent_name is not None:
span_name = f"invoke_agent {agent_name}"
elif run_name:
span_name = f"invoke_agent {run_name}"

span = start_span_function(
op=OP.GEN_AI_INVOKE_AGENT,
name=f"invoke_agent {agent_name}" if agent_name else "invoke_agent",
name=span_name,
origin=LangchainIntegration.origin,
)
span.__enter__()

_push_agent(agent_name)

if agent_name:
if agent_name is not None:
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, agent_name)

span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)

tools = _get_available_tools(self)
_set_tools_on_span(span, tools)

input = args[0].get("input") if len(args) >= 1 else None
Expand Down Expand Up @@ -1106,7 +1074,6 @@ def new_iterator() -> "Iterator[Any]":
raise
finally:
# Ensure cleanup happens even if iterator is abandoned or fails
_pop_agent()
span.__exit__(*exc_info)

async def new_iterator_async() -> "AsyncIterator[Any]":
Expand All @@ -1132,7 +1099,6 @@ async def new_iterator_async() -> "AsyncIterator[Any]":
raise
finally:
# Ensure cleanup happens even if iterator is abandoned or fails
_pop_agent()
span.__exit__(*exc_info)

if str(type(result)) == "<class 'async_generator'>":
Expand Down
6 changes: 6 additions & 0 deletions tests/integrations/langchain/test_langchain.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -254,6 +254,8 @@ def test_langchain_create_agent(
assert len(chat_spans) == 1
assert chat_spans[0]["origin"] == "auto.ai.langchain"

assert chat_spans[0]["data"]["gen_ai.agent.name"] == "word_length_agent"

assert chat_spans[0]["data"]["gen_ai.usage.input_tokens"] == 10
assert chat_spans[0]["data"]["gen_ai.usage.output_tokens"] == 20
assert chat_spans[0]["data"]["gen_ai.usage.total_tokens"] == 30
Expand Down Expand Up @@ -410,6 +412,10 @@ def test_tool_execution_span(
assert chat_spans[1]["origin"] == "auto.ai.langchain"
assert tool_exec_span["origin"] == "auto.ai.langchain"

assert chat_spans[0]["data"]["gen_ai.agent.name"] == "word_length_agent"
assert chat_spans[1]["data"]["gen_ai.agent.name"] == "word_length_agent"
assert tool_exec_span["data"]["gen_ai.agent.name"] == "word_length_agent"

assert chat_spans[0]["data"]["gen_ai.usage.input_tokens"] == 142
assert chat_spans[0]["data"]["gen_ai.usage.output_tokens"] == 50
assert chat_spans[0]["data"]["gen_ai.usage.total_tokens"] == 192
Expand Down
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