diff --git a/sentry_sdk/consts.py b/sentry_sdk/consts.py index d402467e5e..d880845011 100644 --- a/sentry_sdk/consts.py +++ b/sentry_sdk/consts.py @@ -100,6 +100,17 @@ class CompressionAlgo(Enum): ] +class SPANTEMPLATE(str, Enum): + DEFAULT = "default" + AI_AGENT = "ai_agent" + AI_TOOL = "ai_tool" + AI_CHAT = "ai_chat" + + def __str__(self): + # type: () -> str + return self.value + + class INSTRUMENTER: SENTRY = "sentry" OTEL = "otel" diff --git a/sentry_sdk/tracing.py b/sentry_sdk/tracing.py index 92f7ae2073..c9b357305a 100644 --- a/sentry_sdk/tracing.py +++ b/sentry_sdk/tracing.py @@ -5,7 +5,7 @@ from enum import Enum import sentry_sdk -from sentry_sdk.consts import INSTRUMENTER, SPANSTATUS, SPANDATA +from sentry_sdk.consts import INSTRUMENTER, SPANSTATUS, SPANDATA, SPANTEMPLATE from sentry_sdk.profiler.continuous_profiler import get_profiler_id from sentry_sdk.utils import ( get_current_thread_meta, @@ -1365,8 +1365,10 @@ def _set_initial_sampling_decision(self, sampling_context): if TYPE_CHECKING: @overload - def trace(func=None, *, op=None, name=None, attributes=None): - # type: (None, Optional[str], Optional[str], Optional[dict[str, Any]]) -> Callable[[Callable[P, R]], Callable[P, R]] + def trace( + func=None, *, op=None, name=None, attributes=None, template=SPANTEMPLATE.DEFAULT + ): + # type: (None, Optional[str], Optional[str], Optional[dict[str, Any]], SPANTEMPLATE) -> Callable[[Callable[P, R]], Callable[P, R]] # Handles: @trace() and @trace(op="custom") pass @@ -1377,8 +1379,10 @@ def trace(func): pass -def trace(func=None, *, op=None, name=None, attributes=None): - # type: (Optional[Callable[P, R]], Optional[str], Optional[str], Optional[dict[str, Any]]) -> Union[Callable[P, R], Callable[[Callable[P, R]], Callable[P, R]]] +def trace( + func=None, *, op=None, name=None, attributes=None, template=SPANTEMPLATE.DEFAULT +): + # type: (Optional[Callable[P, R]], Optional[str], Optional[str], Optional[dict[str, Any]], SPANTEMPLATE) -> Union[Callable[P, R], Callable[[Callable[P, R]], Callable[P, R]]] """ Decorator to start a child span around a function call. @@ -1407,6 +1411,13 @@ def trace(func=None, *, op=None, name=None, attributes=None): attributes provide additional context about the span's execution. :type attributes: dict[str, Any] or None + :param template: The type of span to create. This determines what kind of + span instrumentation and data collection will be applied. Use predefined + constants from :py:class:`sentry_sdk.consts.SPANTEMPLATE`. + The default is `SPANTEMPLATE.DEFAULT` which is the right choice for most + use cases. + :type template: :py:class:`sentry_sdk.consts.SPANTEMPLATE` + :returns: When used as ``@trace``, returns the decorated function. When used as ``@trace(...)`` with parameters, returns a decorator function. :rtype: Callable or decorator function @@ -1414,7 +1425,7 @@ def trace(func=None, *, op=None, name=None, attributes=None): Example:: import sentry_sdk - from sentry_sdk.consts import OP + from sentry_sdk.consts import OP, SPANTEMPLATE # Simple usage with default values @sentry_sdk.trace @@ -1431,6 +1442,12 @@ def process_data(): def make_db_query(sql): # Function implementation pass + + # With a custom template + @sentry_sdk.trace(template=SPANTEMPLATE.AI_TOOL) + def calculate_interest_rate(amount, rate, years): + # Function implementation + pass """ from sentry_sdk.tracing_utils import create_span_decorator @@ -1438,6 +1455,7 @@ def make_db_query(sql): op=op, name=name, attributes=attributes, + template=template, ) if func: diff --git a/sentry_sdk/tracing_utils.py b/sentry_sdk/tracing_utils.py index 447a708d4d..b31d3d85c5 100644 --- a/sentry_sdk/tracing_utils.py +++ b/sentry_sdk/tracing_utils.py @@ -12,7 +12,7 @@ import uuid import sentry_sdk -from sentry_sdk.consts import OP, SPANDATA +from sentry_sdk.consts import OP, SPANDATA, SPANTEMPLATE from sentry_sdk.utils import ( capture_internal_exceptions, filename_for_module, @@ -20,6 +20,7 @@ logger, match_regex_list, qualname_from_function, + safe_repr, to_string, try_convert, is_sentry_url, @@ -770,15 +771,27 @@ def normalize_incoming_data(incoming_data): return data -def create_span_decorator(op=None, name=None, attributes=None): - # type: (Optional[str], Optional[str], Optional[dict[str, Any]]) -> Any +def create_span_decorator( + op=None, name=None, attributes=None, template=SPANTEMPLATE.DEFAULT +): + # type: (Optional[Union[str, OP]], Optional[str], Optional[dict[str, Any]], SPANTEMPLATE) -> Any """ Create a span decorator that can wrap both sync and async functions. :param op: The operation type for the span. + :type op: str or :py:class:`sentry_sdk.consts.OP` or None :param name: The name of the span. + :type name: str or None :param attributes: Additional attributes to set on the span. + :type attributes: dict or None + :param template: The type of span to create. This determines what kind of + span instrumentation and data collection will be applied. Use predefined + constants from :py:class:`sentry_sdk.consts.SPANTEMPLATE`. + The default is `SPANTEMPLATE.DEFAULT` which is the right choice for most + use cases. + :type template: :py:class:`sentry_sdk.consts.SPANTEMPLATE` """ + from sentry_sdk.scope import should_send_default_pii def span_decorator(f): # type: (Any) -> Any @@ -799,15 +812,24 @@ async def async_wrapper(*args, **kwargs): ) return await f(*args, **kwargs) - span_op = op or OP.FUNCTION - span_name = name or qualname_from_function(f) or "" + span_op = op or _get_span_op(template) + function_name = name or qualname_from_function(f) or "" + span_name = _get_span_name(template, function_name, kwargs) + send_pii = should_send_default_pii() with current_span.start_child( op=span_op, name=span_name, ) as span: span.update_data(attributes or {}) + _set_input_attributes( + span, template, send_pii, function_name, f, args, kwargs + ) + result = await f(*args, **kwargs) + + _set_output_attributes(span, template, send_pii, result) + return result try: @@ -828,15 +850,24 @@ def sync_wrapper(*args, **kwargs): ) return f(*args, **kwargs) - span_op = op or OP.FUNCTION - span_name = name or qualname_from_function(f) or "" + span_op = op or _get_span_op(template) + function_name = name or qualname_from_function(f) or "" + span_name = _get_span_name(template, function_name, kwargs) + send_pii = should_send_default_pii() with current_span.start_child( op=span_op, name=span_name, ) as span: span.update_data(attributes or {}) + _set_input_attributes( + span, template, send_pii, function_name, f, args, kwargs + ) + result = f(*args, **kwargs) + + _set_output_attributes(span, template, send_pii, result) + return result try: @@ -912,6 +943,241 @@ def _sample_rand_range(parent_sampled, sample_rate): return sample_rate, 1.0 +def _get_value(source, key): + # type: (Any, str) -> Optional[Any] + """ + Gets a value from a source object. The source can be a dict or an object. + It is checked for dictionary keys and object attributes. + """ + value = None + if isinstance(source, dict): + value = source.get(key) + else: + if hasattr(source, key): + try: + value = getattr(source, key) + except Exception: + value = None + return value + + +def _get_span_name(template, name, kwargs=None): + # type: (Union[str, SPANTEMPLATE], str, Optional[dict[str, Any]]) -> str + """ + Get the name of the span based on the template and the name. + """ + span_name = name + + if template == SPANTEMPLATE.AI_CHAT: + model = None + if kwargs: + for key in ("model", "model_name"): + if kwargs.get(key) and isinstance(kwargs[key], str): + model = kwargs[key] + break + + span_name = f"chat {model}" if model else "chat" + + elif template == SPANTEMPLATE.AI_AGENT: + span_name = f"invoke_agent {name}" + + elif template == SPANTEMPLATE.AI_TOOL: + span_name = f"execute_tool {name}" + + return span_name + + +def _get_span_op(template): + # type: (Union[str, SPANTEMPLATE]) -> str + """ + Get the operation of the span based on the template. + """ + mapping = { + SPANTEMPLATE.AI_CHAT: OP.GEN_AI_CHAT, + SPANTEMPLATE.AI_AGENT: OP.GEN_AI_INVOKE_AGENT, + SPANTEMPLATE.AI_TOOL: OP.GEN_AI_EXECUTE_TOOL, + } # type: dict[Union[str, SPANTEMPLATE], Union[str, OP]] + op = mapping.get(template, OP.FUNCTION) + + return str(op) + + +def _get_input_attributes(template, send_pii, args, kwargs): + # type: (Union[str, SPANTEMPLATE], bool, tuple[Any, ...], dict[str, Any]) -> dict[str, Any] + """ + Get input attributes for the given span template. + """ + attributes = {} # type: dict[str, Any] + + if template in [SPANTEMPLATE.AI_AGENT, SPANTEMPLATE.AI_TOOL, SPANTEMPLATE.AI_CHAT]: + mapping = { + "model": (SPANDATA.GEN_AI_REQUEST_MODEL, str), + "model_name": (SPANDATA.GEN_AI_REQUEST_MODEL, str), + "agent": (SPANDATA.GEN_AI_AGENT_NAME, str), + "agent_name": (SPANDATA.GEN_AI_AGENT_NAME, str), + "max_tokens": (SPANDATA.GEN_AI_REQUEST_MAX_TOKENS, int), + "frequency_penalty": (SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY, float), + "presence_penalty": (SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY, float), + "temperature": (SPANDATA.GEN_AI_REQUEST_TEMPERATURE, float), + "top_p": (SPANDATA.GEN_AI_REQUEST_TOP_P, float), + "top_k": (SPANDATA.GEN_AI_REQUEST_TOP_K, int), + } + + def _set_from_key(key, value): + # type: (str, Any) -> None + if key in mapping: + (attribute, data_type) = mapping[key] + if value is not None and isinstance(value, data_type): + attributes[attribute] = value + + for key, value in list(kwargs.items()): + if key == "prompt" and isinstance(value, str): + attributes.setdefault(SPANDATA.GEN_AI_REQUEST_MESSAGES, []).append( + {"role": "user", "content": value} + ) + continue + + if key == "system_prompt" and isinstance(value, str): + attributes.setdefault(SPANDATA.GEN_AI_REQUEST_MESSAGES, []).append( + {"role": "system", "content": value} + ) + continue + + _set_from_key(key, value) + + if template == SPANTEMPLATE.AI_TOOL and send_pii: + attributes[SPANDATA.GEN_AI_TOOL_INPUT] = safe_repr( + {"args": args, "kwargs": kwargs} + ) + + # Coerce to string + if SPANDATA.GEN_AI_REQUEST_MESSAGES in attributes: + attributes[SPANDATA.GEN_AI_REQUEST_MESSAGES] = safe_repr( + attributes[SPANDATA.GEN_AI_REQUEST_MESSAGES] + ) + + return attributes + + +def _get_usage_attributes(usage): + # type: (Any) -> dict[str, Any] + """ + Get usage attributes. + """ + attributes = {} + + def _set_from_keys(attribute, keys): + # type: (str, tuple[str, ...]) -> None + for key in keys: + value = _get_value(usage, key) + if value is not None and isinstance(value, int): + attributes[attribute] = value + + _set_from_keys( + SPANDATA.GEN_AI_USAGE_INPUT_TOKENS, + ("prompt_tokens", "input_tokens"), + ) + _set_from_keys( + SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS, + ("completion_tokens", "output_tokens"), + ) + _set_from_keys( + SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS, + ("total_tokens",), + ) + + return attributes + + +def _get_output_attributes(template, send_pii, result): + # type: (Union[str, SPANTEMPLATE], bool, Any) -> dict[str, Any] + """ + Get output attributes for the given span template. + """ + attributes = {} # type: dict[str, Any] + + if template in [SPANTEMPLATE.AI_AGENT, SPANTEMPLATE.AI_TOOL, SPANTEMPLATE.AI_CHAT]: + with capture_internal_exceptions(): + # Usage from result, result.usage, and result.metadata.usage + usage_candidates = [result] + + usage = _get_value(result, "usage") + usage_candidates.append(usage) + + meta = _get_value(result, "metadata") + usage = _get_value(meta, "usage") + usage_candidates.append(usage) + + for usage_candidate in usage_candidates: + if usage_candidate is not None: + attributes.update(_get_usage_attributes(usage_candidate)) + + # Response model + model_name = _get_value(result, "model") + if model_name is not None and isinstance(model_name, str): + attributes[SPANDATA.GEN_AI_RESPONSE_MODEL] = model_name + + model_name = _get_value(result, "model_name") + if model_name is not None and isinstance(model_name, str): + attributes[SPANDATA.GEN_AI_RESPONSE_MODEL] = model_name + + # Tool output + if template == SPANTEMPLATE.AI_TOOL and send_pii: + attributes[SPANDATA.GEN_AI_TOOL_OUTPUT] = safe_repr(result) + + return attributes + + +def _set_input_attributes(span, template, send_pii, name, f, args, kwargs): + # type: (Span, Union[str, SPANTEMPLATE], bool, str, Any, tuple[Any, ...], dict[str, Any]) -> None + """ + Set span input attributes based on the given span template. + + :param span: The span to set attributes on. + :param template: The template to use to set attributes on the span. + :param send_pii: Whether to send PII data. + :param f: The wrapped function. + :param args: The arguments to the wrapped function. + :param kwargs: The keyword arguments to the wrapped function. + """ + attributes = {} # type: dict[str, Any] + + if template == SPANTEMPLATE.AI_AGENT: + attributes = { + SPANDATA.GEN_AI_OPERATION_NAME: "invoke_agent", + SPANDATA.GEN_AI_AGENT_NAME: name, + } + elif template == SPANTEMPLATE.AI_CHAT: + attributes = { + SPANDATA.GEN_AI_OPERATION_NAME: "chat", + } + elif template == SPANTEMPLATE.AI_TOOL: + attributes = { + SPANDATA.GEN_AI_OPERATION_NAME: "execute_tool", + SPANDATA.GEN_AI_TOOL_NAME: name, + } + + docstring = f.__doc__ + if docstring is not None: + attributes[SPANDATA.GEN_AI_TOOL_DESCRIPTION] = docstring + + attributes.update(_get_input_attributes(template, send_pii, args, kwargs)) + span.update_data(attributes or {}) + + +def _set_output_attributes(span, template, send_pii, result): + # type: (Span, Union[str, SPANTEMPLATE], bool, Any) -> None + """ + Set span output attributes based on the given span template. + + :param span: The span to set attributes on. + :param template: The template to use to set attributes on the span. + :param send_pii: Whether to send PII data. + :param result: The result of the wrapped function. + """ + span.update_data(_get_output_attributes(template, send_pii, result) or {}) + + # Circular imports from sentry_sdk.tracing import ( BAGGAGE_HEADER_NAME, diff --git a/tests/tracing/test_decorator.py b/tests/tracing/test_decorator.py index 9a7074c470..15432f5862 100644 --- a/tests/tracing/test_decorator.py +++ b/tests/tracing/test_decorator.py @@ -3,6 +3,8 @@ import pytest +import sentry_sdk +from sentry_sdk.consts import SPANTEMPLATE from sentry_sdk.tracing import trace from sentry_sdk.tracing_utils import create_span_decorator from sentry_sdk.utils import logger @@ -117,3 +119,248 @@ async def _some_function_traced(a, b, c): assert inspect.getcallargs(_some_function, 1, 2, 3) == inspect.getcallargs( _some_function_traced, 1, 2, 3 ) + + +def test_span_templates_ai_dicts(sentry_init, capture_events): + sentry_init(traces_sample_rate=1.0) + events = capture_events() + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_TOOL) + def my_tool(arg1, arg2): + return { + "output": "my_tool_result", + "usage": { + "prompt_tokens": 10, + "completion_tokens": 20, + "total_tokens": 30, + }, + } + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_CHAT) + def my_chat(model=None, **kwargs): + return { + "content": "my_chat_result", + "usage": { + "input_tokens": 11, + "output_tokens": 22, + "total_tokens": 33, + }, + "model": f"{model}-v123", + } + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_AGENT) + def my_agent(): + my_tool(1, 2) + my_chat( + model="my-gpt-4o-mini", + prompt="What is the weather in Tokyo?", + system_prompt="You are a helpful assistant that can answer questions about the weather.", + max_tokens=100, + temperature=0.5, + top_p=0.9, + top_k=40, + frequency_penalty=1.0, + presence_penalty=2.0, + ) + + with sentry_sdk.start_transaction(name="test-transaction"): + my_agent() + + (event,) = events + (agent_span, tool_span, chat_span) = event["spans"] + + assert agent_span["op"] == "gen_ai.invoke_agent" + assert ( + agent_span["description"] + == "invoke_agent test_decorator.test_span_templates_ai_dicts..my_agent" + ) + assert agent_span["data"] == { + "gen_ai.agent.name": "test_decorator.test_span_templates_ai_dicts..my_agent", + "gen_ai.operation.name": "invoke_agent", + "thread.id": mock.ANY, + "thread.name": mock.ANY, + } + + assert tool_span["op"] == "gen_ai.execute_tool" + assert ( + tool_span["description"] + == "execute_tool test_decorator.test_span_templates_ai_dicts..my_tool" + ) + assert tool_span["data"] == { + "gen_ai.tool.name": "test_decorator.test_span_templates_ai_dicts..my_tool", + "gen_ai.operation.name": "execute_tool", + "gen_ai.usage.input_tokens": 10, + "gen_ai.usage.output_tokens": 20, + "gen_ai.usage.total_tokens": 30, + "thread.id": mock.ANY, + "thread.name": mock.ANY, + } + assert "gen_ai.tool.description" not in tool_span["data"] + + assert chat_span["op"] == "gen_ai.chat" + assert chat_span["description"] == "chat my-gpt-4o-mini" + assert chat_span["data"] == { + "gen_ai.operation.name": "chat", + "gen_ai.request.frequency_penalty": 1.0, + "gen_ai.request.max_tokens": 100, + "gen_ai.request.messages": "[{'role': 'user', 'content': 'What is the weather in Tokyo?'}, {'role': 'system', 'content': 'You are a helpful assistant that can answer questions about the weather.'}]", + "gen_ai.request.model": "my-gpt-4o-mini", + "gen_ai.request.presence_penalty": 2.0, + "gen_ai.request.temperature": 0.5, + "gen_ai.request.top_k": 40, + "gen_ai.request.top_p": 0.9, + "gen_ai.response.model": "my-gpt-4o-mini-v123", + "gen_ai.usage.input_tokens": 11, + "gen_ai.usage.output_tokens": 22, + "gen_ai.usage.total_tokens": 33, + "thread.id": mock.ANY, + "thread.name": mock.ANY, + } + + +def test_span_templates_ai_objects(sentry_init, capture_events): + sentry_init(traces_sample_rate=1.0) + events = capture_events() + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_TOOL) + def my_tool(arg1, arg2): + """This is a tool function.""" + mock_usage = mock.Mock() + mock_usage.prompt_tokens = 10 + mock_usage.completion_tokens = 20 + mock_usage.total_tokens = 30 + + mock_result = mock.Mock() + mock_result.output = "my_tool_result" + mock_result.usage = mock_usage + + return mock_result + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_CHAT) + def my_chat(model=None, **kwargs): + mock_result = mock.Mock() + mock_result.content = "my_chat_result" + mock_result.usage = mock.Mock( + input_tokens=11, + output_tokens=22, + total_tokens=33, + ) + mock_result.model = f"{model}-v123" + + return mock_result + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_AGENT) + def my_agent(): + my_tool(1, 2) + my_chat( + model="my-gpt-4o-mini", + prompt="What is the weather in Tokyo?", + system_prompt="You are a helpful assistant that can answer questions about the weather.", + max_tokens=100, + temperature=0.5, + top_p=0.9, + top_k=40, + frequency_penalty=1.0, + presence_penalty=2.0, + ) + + with sentry_sdk.start_transaction(name="test-transaction"): + my_agent() + + (event,) = events + (agent_span, tool_span, chat_span) = event["spans"] + + assert agent_span["op"] == "gen_ai.invoke_agent" + assert ( + agent_span["description"] + == "invoke_agent test_decorator.test_span_templates_ai_objects..my_agent" + ) + assert agent_span["data"] == { + "gen_ai.agent.name": "test_decorator.test_span_templates_ai_objects..my_agent", + "gen_ai.operation.name": "invoke_agent", + "thread.id": mock.ANY, + "thread.name": mock.ANY, + } + + assert tool_span["op"] == "gen_ai.execute_tool" + assert ( + tool_span["description"] + == "execute_tool test_decorator.test_span_templates_ai_objects..my_tool" + ) + assert tool_span["data"] == { + "gen_ai.tool.name": "test_decorator.test_span_templates_ai_objects..my_tool", + "gen_ai.tool.description": "This is a tool function.", + "gen_ai.operation.name": "execute_tool", + "gen_ai.usage.input_tokens": 10, + "gen_ai.usage.output_tokens": 20, + "gen_ai.usage.total_tokens": 30, + "thread.id": mock.ANY, + "thread.name": mock.ANY, + } + + assert chat_span["op"] == "gen_ai.chat" + assert chat_span["description"] == "chat my-gpt-4o-mini" + assert chat_span["data"] == { + "gen_ai.operation.name": "chat", + "gen_ai.request.frequency_penalty": 1.0, + "gen_ai.request.max_tokens": 100, + "gen_ai.request.messages": "[{'role': 'user', 'content': 'What is the weather in Tokyo?'}, {'role': 'system', 'content': 'You are a helpful assistant that can answer questions about the weather.'}]", + "gen_ai.request.model": "my-gpt-4o-mini", + "gen_ai.request.presence_penalty": 2.0, + "gen_ai.request.temperature": 0.5, + "gen_ai.request.top_k": 40, + "gen_ai.request.top_p": 0.9, + "gen_ai.response.model": "my-gpt-4o-mini-v123", + "gen_ai.usage.input_tokens": 11, + "gen_ai.usage.output_tokens": 22, + "gen_ai.usage.total_tokens": 33, + "thread.id": mock.ANY, + "thread.name": mock.ANY, + } + + +@pytest.mark.parametrize("send_default_pii", [True, False]) +def test_span_templates_ai_pii(sentry_init, capture_events, send_default_pii): + sentry_init(traces_sample_rate=1.0, send_default_pii=send_default_pii) + events = capture_events() + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_TOOL) + def my_tool(arg1, arg2, **kwargs): + """This is a tool function.""" + return "tool_output" + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_CHAT) + def my_chat(model=None, **kwargs): + return "chat_output" + + @sentry_sdk.trace(template=SPANTEMPLATE.AI_AGENT) + def my_agent(*args, **kwargs): + my_tool(1, 2, tool_arg1="3", tool_arg2="4") + my_chat( + model="my-gpt-4o-mini", + prompt="What is the weather in Tokyo?", + system_prompt="You are a helpful assistant that can answer questions about the weather.", + max_tokens=100, + temperature=0.5, + top_p=0.9, + top_k=40, + frequency_penalty=1.0, + presence_penalty=2.0, + ) + return "agent_output" + + with sentry_sdk.start_transaction(name="test-transaction"): + my_agent(22, 33, arg1=44, arg2=55) + + (event,) = events + (_, tool_span, _) = event["spans"] + + if send_default_pii: + assert ( + tool_span["data"]["gen_ai.tool.input"] + == "{'args': (1, 2), 'kwargs': {'tool_arg1': '3', 'tool_arg2': '4'}}" + ) + assert tool_span["data"]["gen_ai.tool.output"] == "'tool_output'" + else: + assert "gen_ai.tool.input" not in tool_span["data"] + assert "gen_ai.tool.output" not in tool_span["data"]