Make tool_call one span for telemetry

Also renamed tool_call as execute_tool and added attributes as recommended in https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/#execute-tool-span.

PiperOrigin-RevId: 764594179

tests/unittests/flows/llm_flows/test_tool_telemetry.py

@@ -0,0 +1,99 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Any
+from typing import Dict
+from typing import Optional
+from unittest import mock
+
+from google.adk import telemetry
+from google.adk.agents import Agent
+from google.adk.events.event import Event
+from google.adk.flows.llm_flows.functions import handle_function_calls_async
+from google.adk.tools.function_tool import FunctionTool
+from google.genai import types
+
+from ... import testing_utils
+
+
+async def invoke_tool() -> Optional[Event]:
+  def simple_fn(**kwargs) -> Dict[str, Any]:
+    return {'result': 'test'}
+
+  tool = FunctionTool(simple_fn)
+  model = testing_utils.MockModel.create(responses=[])
+  agent = Agent(
+      name='agent',
+      model=model,
+      tools=[tool],
+  )
+  invocation_context = await testing_utils.create_invocation_context(
+      agent=agent, user_content=''
+  )
+  function_call = types.FunctionCall(name=tool.name, args={'a': 1, 'b': 2})
+  content = types.Content(parts=[types.Part(function_call=function_call)])
+  event = Event(
+      invocation_id=invocation_context.invocation_id,
+      author=agent.name,
+      content=content,
+  )
+  tools_dict = {tool.name: tool}
+  return await handle_function_calls_async(
+      invocation_context,
+      event,
+      tools_dict,
+  )
+
+
+async def test_simple_function_with_mocked_tracer(monkeypatch):
+  mock_start_as_current_span_func = mock.Mock()
+  returned_context_manager_mock = mock.MagicMock()
+  returned_context_manager_mock.__enter__.return_value = mock.Mock(
+      name='span_mock'
+  )
+  mock_start_as_current_span_func.return_value = returned_context_manager_mock
+
+  monkeypatch.setattr(
+      telemetry.tracer, 'start_as_current_span', mock_start_as_current_span_func
+  )
+
+  mock_adk_trace_tool_call = mock.Mock()
+  monkeypatch.setattr(
+      'google.adk.flows.llm_flows.functions.trace_tool_call',
+      mock_adk_trace_tool_call,
+  )
+
+  event = await invoke_tool()
+  assert event is not None
+
+  event = await invoke_tool()
+  assert event is not None
+
+  expected_span_name = 'execute_tool simple_fn'
+
+  assert mock_start_as_current_span_func.call_count == 2
+  mock_start_as_current_span_func.assert_any_call(expected_span_name)
+
+  assert returned_context_manager_mock.__enter__.call_count == 2
+  assert returned_context_manager_mock.__exit__.call_count == 2
+
+  assert mock_adk_trace_tool_call.call_count == 2
+  for call_args_item in mock_adk_trace_tool_call.call_args_list:
+    kwargs = call_args_item.kwargs
+    assert kwargs['tool'].name == 'simple_fn'
+    assert kwargs['args'] == {'a': 1, 'b': 2}
+    assert 'function_response_event' in kwargs
+    assert kwargs['function_response_event'].content.parts[
+        0
+    ].function_response.response == {'result': 'test'}