[pull] main from google:main

src/google/adk/telemetry/_instrumentation.py

@@ -106,7 +106,6 @@ def record_llm_response(
 def _record_agent_metrics(
     agent_name: str,
     elapsed_s: float,
-    user_content: object,
     events: object,
     caught_error: Exception | None,
 ) -> None:
@@ -116,8 +115,6 @@ def _record_agent_metrics(
         elapsed_s,
         caught_error,
     )
-    _metrics.record_agent_request_size(agent_name, user_content)
-    _metrics.record_agent_response_size(agent_name, events)
     _metrics.record_agent_workflow_steps(agent_name, events)
   except Exception:  # pylint: disable=broad-exception-caught
     logger.exception("Failed to record agent metrics for agent %s", agent_name)
@@ -145,7 +142,6 @@ async def record_agent_invocation(
     _record_agent_metrics(
         agent.name,
         _metrics.get_elapsed_s(span, start_time),
-        getattr(ctx, "user_content", None),
         getattr(getattr(ctx, "session", None), "events", []),
         caught_error,
     )

src/google/adk/telemetry/_metrics.py

@@ -21,7 +21,6 @@
 from google.adk import version
 from google.adk.telemetry import tracing
 from google.adk.telemetry._token_usage import TokenUsage
-from google.genai import types
 from opentelemetry import metrics
 from opentelemetry.semconv._incubating.attributes import gen_ai_attributes
 from opentelemetry.semconv._incubating.metrics import gen_ai_metrics
@@ -92,48 +91,6 @@
         81.92,
     ],
 )
-_agent_request_size = meter.create_histogram(
-    "gen_ai.agent.request.size",
-    unit="By",
-    description="Size of agent requests.",
-    explicit_bucket_boundaries_advisory=[
-        1,
-        4,
-        16,
-        64,
-        256,
-        1024,
-        4096,
-        16384,
-        65536,
-        262144,
-        1048576,
-        4194304,
-        16777216,
-        67108864,
-    ],
-)
-_agent_response_size = meter.create_histogram(
-    "gen_ai.agent.response.size",
-    unit="By",
-    description="Size of agent responses.",
-    explicit_bucket_boundaries_advisory=[
-        1,
-        4,
-        16,
-        64,
-        256,
-        1024,
-        4096,
-        16384,
-        65536,
-        262144,
-        1048576,
-        4194304,
-        16777216,
-        67108864,
-    ],
-)
 _agent_workflow_steps = meter.create_histogram(
     "gen_ai.agent.workflow.steps",
     unit="1",
@@ -191,28 +148,6 @@ def record_workflow_invocation_duration(
   _workflow_invocation_duration.record(elapsed_s, attributes=attrs)
 
 
-def record_agent_request_size(
-    agent_name: str, user_content: types.Content | None
-):
-  """Records the size of the agent request."""
-  size = _get_content_size(user_content)
-  attrs = {gen_ai_attributes.GEN_AI_AGENT_NAME: agent_name}
-  _agent_request_size.record(size, attributes=attrs)
-
-
-def record_agent_response_size(agent_name: str, events: list[Event]):
-  """Records the size of the agent response by extracting content from events."""
-  response_content: types.Content | None = None
-  for event in reversed(events):
-    if event.author == agent_name and event.content:
-      response_content = event.content
-      break
-
-  size = _get_content_size(response_content)
-  attrs = {gen_ai_attributes.GEN_AI_AGENT_NAME: agent_name}
-  _agent_response_size.record(size, attributes=attrs)
-
-
 def record_agent_workflow_steps(agent_name: str, events: list[Event]):
   """Records the number of steps in the agent workflow by counting the number of events."""
   attrs = {gen_ai_attributes.GEN_AI_AGENT_NAME: agent_name}
@@ -318,20 +253,6 @@ def record_client_token_usage(
     _client_token_usage.record(output_token_count, attributes=output_attrs)
 
 
-def _get_content_size(
-    content: types.Content | None,
-) -> int:
-  if not content or not content.parts:
-    return 0
-  size = 0
-  for part in content.parts:
-    if part.text is not None:
-      size += len(part.text.encode("utf-8"))
-    if part.inline_data and part.inline_data.data:
-      size += len(part.inline_data.data)
-  return size
-
-
 def _get_provider_name() -> str:
   return tracing._guess_gemini_system_name()
 

tests/unittests/telemetry/functional_node_test_cases.py

@@ -2597,18 +2597,6 @@
             value=NON_DETERMINISTIC,
         ),
     }),
-    "gen_ai.agent.request.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(USER_PROMPT),
-        ),
-    }),
-    "gen_ai.agent.response.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(FINAL_TEXT),
-        ),
-    }),
     "gen_ai.agent.workflow.steps": frozenset({
         MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=3),
     }),
@@ -2653,18 +2641,6 @@
             value=NON_DETERMINISTIC,
         ),
     }),
-    "gen_ai.agent.request.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(USER_PROMPT),
-        ),
-    }),
-    "gen_ai.agent.response.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(FINAL_TEXT),
-        ),
-    }),
     "gen_ai.agent.workflow.steps": frozenset({
         MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=3),
     }),

tests/unittests/telemetry/functional_test_cases.py

@@ -2291,18 +2291,6 @@
             value=NON_DETERMINISTIC,
         ),
     }),
-    "gen_ai.agent.request.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(USER_PROMPT),
-        ),
-    }),
-    "gen_ai.agent.response.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(FINAL_TEXT),
-        ),
-    }),
     "gen_ai.agent.workflow.steps": frozenset({
         MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=3),
     }),
@@ -2338,18 +2326,6 @@
             value=NON_DETERMINISTIC,
         ),
     }),
-    "gen_ai.agent.request.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(USER_PROMPT),
-        ),
-    }),
-    "gen_ai.agent.response.size": frozenset({
-        MetricPoint(
-            attributes={"gen_ai.agent.name": AGENT_NAME},
-            value=len(FINAL_TEXT),
-        ),
-    }),
     "gen_ai.agent.workflow.steps": frozenset({
         MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=3),
     }),

tests/unittests/telemetry/functional_test_helpers.py

@@ -314,16 +314,6 @@ class HistogramSpec(NamedTuple):
         attr="_tool_execution_duration",
         metric_name="gen_ai.execute_tool.duration",
     ),
-    HistogramSpec(
-        module=_metrics,
-        attr="_agent_request_size",
-        metric_name="gen_ai.agent.request.size",
-    ),
-    HistogramSpec(
-        module=_metrics,
-        attr="_agent_response_size",
-        metric_name="gen_ai.agent.response.size",
-    ),
     HistogramSpec(
         module=_metrics,
         attr="_agent_workflow_steps",

tests/unittests/telemetry/test_instrumentation.py

@@ -86,16 +86,16 @@ def test_get_elapsed_s_span_non_int_end():
 
 @pytest.mark.asyncio
 async def test_record_agent_invocation_tolerates_minimal_context():
-  """Tolerates context-likes that lack user_content or session.
+  """Tolerates context-likes that lack session.
 
   Test doubles, partial migrations, and external embedders can pass an
-  InvocationContext-like object without `user_content` or with a `session`
-  that has no `events` attribute. The telemetry path must not raise
-  AttributeError on the metrics call in those cases.
+  InvocationContext-like object with a `session` that has no `events`
+  attribute. The telemetry path must not raise AttributeError on the
+  metrics call in those cases.
   """
   agent = mock.MagicMock()
   agent.name = "test_agent"
-  # Bare object without `user_content` and without `session`.
+  # Bare object without `session`.
   bare_ctx = object()
 
   with (
@@ -112,7 +112,6 @@ async def test_record_agent_invocation_tolerates_minimal_context():
 
   mock_record.assert_called_once()
   call_args = mock_record.call_args
-  # positional: (agent_name, elapsed_s, user_content, events, caught_error)
+  # positional: (agent_name, elapsed_s, events, caught_error)
   assert call_args.args[0] == "test_agent"
-  assert call_args.args[2] is None  # user_content default
-  assert call_args.args[3] == []  # events default
+  assert call_args.args[2] == []  # events default