Add support for OTel GenAI Semantic Convention patterns in LLO handler

Author: mxiamxia

aws-opentelemetry-distro/src/amazon/opentelemetry/distro/llo_handler.py

@@ -16,6 +16,7 @@
 ROLE_SYSTEM = "system"
 ROLE_USER = "user"
 ROLE_ASSISTANT = "assistant"
+ROLE_TOOL = "tool"
 
 _logger = logging.getLogger(__name__)
 
@@ -137,6 +138,35 @@ class PatternConfig(TypedDict, total=False):
         "role": ROLE_USER,
         "source": "prompt",
     },
+    # OTel GenAI Semantic Convention used by the latest Strands SDK
+    # References:
+    # - OTel GenAI SemConv: https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-events/
+    # - Strands SDK PR: https://github.com/strands-agents/sdk-python/pull/319
+    "gen_ai.user.message": {
+        "type": PatternType.DIRECT,
+        "role": ROLE_USER,
+        "source": "prompt",
+    },
+    "gen_ai.assistant.message": {
+        "type": PatternType.DIRECT,
+        "role": ROLE_ASSISTANT,
+        "source": "output",
+    },
+    "gen_ai.system.message": {
+        "type": PatternType.DIRECT,
+        "role": ROLE_SYSTEM,
+        "source": "prompt",
+    },
+    "gen_ai.tool.message": {
+        "type": PatternType.DIRECT,
+        "role": ROLE_USER,
+        "source": "prompt",
+    },
+    "gen_ai.choice": {
+        "type": PatternType.DIRECT,
+        "role": ROLE_ASSISTANT,
+        "source": "output",
+    },
 }
 
 
@@ -279,6 +309,12 @@ def _collect_llo_attributes_from_span(self, span: ReadableSpan) -> Dict[str, Any
         # Collect from span events
         if span.events:
             for event in span.events:
+                # Check if event name itself is an LLO pattern (e.g., "gen_ai.user.message")
+                if self._is_llo_attribute(event.name):
+                    # Put all event attributes as the content as LLO in log event
+                    all_llo_attributes[event.name] = dict(event.attributes) if event.attributes else {}
+
+                # Also check traditional pattern - LLO attributes within event attributes
                 if event.attributes:
                     for key, value in event.attributes.items():
                         if self._is_llo_attribute(key):
@@ -372,6 +408,10 @@ def _filter_span_events(self, span: ReadableSpan) -> None:
         updated_events = []
 
         for event in span.events:
+            # Skip entire event if event name is an LLO pattern
+            if self._is_llo_attribute(event.name):
+                continue
+
             if not event.attributes:
                 updated_events.append(event)
                 continue

aws-opentelemetry-distro/tests/amazon/opentelemetry/distro/llo_handler/test_llo_handler_events.py

@@ -7,7 +7,7 @@
 from test_llo_handler_base import LLOHandlerTestBase
 
 
-class TestLLOHandlerEvents(LLOHandlerTestBase):
+class TestLLOHandlerEvents(LLOHandlerTestBase):  # pylint: disable=too-many-public-methods
     """Test event emission and formatting functionality."""
 
     def test_emit_llo_attributes(self):
@@ -649,3 +649,302 @@ def test_emit_llo_attributes_with_session_id_and_other_attributes(self):
         self.assertNotIn("other.attribute", emitted_event.attributes)
         self.assertNotIn("gen_ai.prompt", emitted_event.attributes)
         self.assertNotIn("gen_ai.completion", emitted_event.attributes)
+
+    def test_emit_llo_attributes_otel_genai_patterns(self):
+        """
+        Test the new GenAI patterns from Strands SDK that follow OTel GenAI Semantic Convention.
+        """
+        attributes = {
+            "gen_ai.user.message": "What is machine learning?",
+            "gen_ai.assistant.message": (
+                "Machine learning is a subset of AI that enables computers to learn patterns from data."
+            ),
+            "gen_ai.system.message": "You are a helpful AI assistant specializing in technology topics.",
+            "gen_ai.tool.message": "Searching knowledge base for machine learning definitions...",
+            "gen_ai.choice": "Best answer: Machine learning uses algorithms to find patterns in data.",
+        }
+
+        span = self._create_mock_span(attributes)
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "strands.genai.scope"
+
+        self.llo_handler._emit_llo_attributes(span, attributes)
+
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        self.assertEqual(emitted_event.name, "strands.genai.scope")
+        self.assertEqual(emitted_event.timestamp, span.end_time)
+
+        event_body = emitted_event.body
+        self.assertIn("input", event_body)
+        self.assertIn("output", event_body)
+
+        # Check input messages (system, user, and tool messages)
+        input_messages = event_body["input"]["messages"]
+        self.assertEqual(len(input_messages), 3)
+
+        input_contents = [msg["content"] for msg in input_messages]
+        self.assertIn("What is machine learning?", input_contents)
+        self.assertIn("You are a helpful AI assistant specializing in technology topics.", input_contents)
+        self.assertIn("Searching knowledge base for machine learning definitions...", input_contents)
+
+        # Verify roles for input messages
+        user_msg = next((msg for msg in input_messages if msg["content"] == "What is machine learning?"), None)
+        self.assertIsNotNone(user_msg)
+        self.assertEqual(user_msg["role"], "user")
+
+        system_msg = next((msg for msg in input_messages if "helpful AI assistant" in msg["content"]), None)
+        self.assertIsNotNone(system_msg)
+        self.assertEqual(system_msg["role"], "system")
+
+        tool_msg = next((msg for msg in input_messages if "Searching knowledge base" in msg["content"]), None)
+        self.assertIsNotNone(tool_msg)
+        self.assertEqual(tool_msg["role"], "user")
+
+        # Check output messages (assistant message and choice)
+        output_messages = event_body["output"]["messages"]
+        self.assertEqual(len(output_messages), 2)
+
+        output_contents = [msg["content"] for msg in output_messages]
+        self.assertIn(
+            "Machine learning is a subset of AI that enables computers to learn patterns from data.", output_contents
+        )
+        self.assertIn("Best answer: Machine learning uses algorithms to find patterns in data.", output_contents)
+
+        # Verify all output messages have assistant role
+        for msg in output_messages:
+            self.assertEqual(msg["role"], "assistant")
+
+    def test_emit_llo_attributes_genai_user_message_only(self):
+        """
+        Test event generation with only gen_ai.user.message attribute.
+        """
+        attributes = {
+            "gen_ai.user.message": "Hello, how are you today?",
+        }
+
+        span = self._create_mock_span(attributes)
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "test.scope"
+
+        self.llo_handler._emit_llo_attributes(span, attributes)
+
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        event_body = emitted_event.body
+        self.assertIn("input", event_body)
+        self.assertNotIn("output", event_body)
+
+        input_messages = event_body["input"]["messages"]
+        self.assertEqual(len(input_messages), 1)
+        self.assertEqual(input_messages[0]["content"], "Hello, how are you today?")
+        self.assertEqual(input_messages[0]["role"], "user")
+
+    def test_emit_llo_attributes_genai_assistant_message_only(self):
+        """
+        Test event generation with only gen_ai.assistant.message attribute.
+        """
+        attributes = {
+            "gen_ai.assistant.message": "I'm doing well, thank you for asking!",
+        }
+
+        span = self._create_mock_span(attributes)
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "test.scope"
+
+        self.llo_handler._emit_llo_attributes(span, attributes)
+
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        event_body = emitted_event.body
+        self.assertNotIn("input", event_body)
+        self.assertIn("output", event_body)
+
+        output_messages = event_body["output"]["messages"]
+        self.assertEqual(len(output_messages), 1)
+        self.assertEqual(output_messages[0]["content"], "I'm doing well, thank you for asking!")
+        self.assertEqual(output_messages[0]["role"], "assistant")
+
+    def test_emit_llo_attributes_genai_system_message_only(self):
+        """
+        Test event generation with only gen_ai.system.message attribute.
+        """
+        attributes = {
+            "gen_ai.system.message": "You are a creative writing assistant. Help users write stories.",
+        }
+
+        span = self._create_mock_span(attributes)
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "test.scope"
+
+        self.llo_handler._emit_llo_attributes(span, attributes)
+
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        event_body = emitted_event.body
+        self.assertIn("input", event_body)
+        self.assertNotIn("output", event_body)
+
+        input_messages = event_body["input"]["messages"]
+        self.assertEqual(len(input_messages), 1)
+        self.assertEqual(
+            input_messages[0]["content"], "You are a creative writing assistant. Help users write stories."
+        )
+        self.assertEqual(input_messages[0]["role"], "system")
+
+    def test_emit_llo_attributes_genai_tool_message_only(self):
+        """
+        Test event generation with only gen_ai.tool.message attribute.
+        """
+        attributes = {
+            "gen_ai.tool.message": "Executing search function with query: 'latest news'",
+        }
+
+        span = self._create_mock_span(attributes)
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "test.scope"
+
+        self.llo_handler._emit_llo_attributes(span, attributes)
+
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        event_body = emitted_event.body
+        self.assertIn("input", event_body)
+        self.assertNotIn("output", event_body)
+
+        input_messages = event_body["input"]["messages"]
+        self.assertEqual(len(input_messages), 1)
+        self.assertEqual(input_messages[0]["content"], "Executing search function with query: 'latest news'")
+        self.assertEqual(input_messages[0]["role"], "user")
+
+    def test_emit_llo_attributes_genai_choice_only(self):
+        """
+        Test event generation with only gen_ai.choice attribute.
+        """
+        attributes = {
+            "gen_ai.choice": "Selected option: Continue with the current approach.",
+        }
+
+        span = self._create_mock_span(attributes)
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "test.scope"
+
+        self.llo_handler._emit_llo_attributes(span, attributes)
+
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        event_body = emitted_event.body
+        self.assertNotIn("input", event_body)
+        self.assertIn("output", event_body)
+
+        output_messages = event_body["output"]["messages"]
+        self.assertEqual(len(output_messages), 1)
+        self.assertEqual(output_messages[0]["content"], "Selected option: Continue with the current approach.")
+        self.assertEqual(output_messages[0]["role"], "assistant")
+
+    def test_emit_llo_attributes_from_span_events(self):
+        """
+        Test that LLO attributes are collected from span events when event names match LLO patterns.
+        """
+        # Create span with normal attributes
+        span_attributes = {"normal.attribute": "value"}
+
+        # Create span events where event names are LLO patterns
+        user_event = MagicMock()
+        user_event.name = "gen_ai.user.message"
+        user_event.attributes = {"content": "What is the weather today?", "other": "metadata"}
+        user_event.timestamp = 1234567890
+
+        assistant_event = MagicMock()
+        assistant_event.name = "gen_ai.assistant.message"
+        assistant_event.attributes = {"content": "It's sunny and 75°F", "confidence": 0.95}
+        assistant_event.timestamp = 1234567891
+
+        system_event = MagicMock()
+        system_event.name = "gen_ai.system.message"
+        system_event.attributes = {"content": "You are a weather assistant"}
+        system_event.timestamp = 1234567892
+
+        span = self._create_mock_span(span_attributes)
+        span.events = [user_event, assistant_event, system_event]
+        span.end_time = 1234567899
+        span.instrumentation_scope = MagicMock()
+        span.instrumentation_scope.name = "event.patterns.scope"
+
+        # Collect LLO attributes and emit event
+        all_llo_attrs = self.llo_handler._collect_llo_attributes_from_span(span)
+        self.llo_handler._emit_llo_attributes(span, all_llo_attrs)
+
+        # Should emit event because LLO attributes were collected from span events
+        self.event_logger_mock.emit.assert_called_once()
+        emitted_event = self.event_logger_mock.emit.call_args[0][0]
+
+        event_body = emitted_event.body
+        self.assertIn("input", event_body)
+        self.assertIn("output", event_body)
+
+        # Check input messages (user and system)
+        input_messages = event_body["input"]["messages"]
+        self.assertEqual(len(input_messages), 2)
+
+        # User message should contain all event attributes as content
+        user_msg = next((msg for msg in input_messages if msg["role"] == "user"), None)
+        self.assertIsNotNone(user_msg)
+        self.assertEqual(user_msg["content"], {"content": "What is the weather today?", "other": "metadata"})
+
+        # System message should contain all event attributes as content
+        system_msg = next((msg for msg in input_messages if msg["role"] == "system"), None)
+        self.assertIsNotNone(system_msg)
+        self.assertEqual(system_msg["content"], {"content": "You are a weather assistant"})
+
+        # Check output messages (assistant)
+        output_messages = event_body["output"]["messages"]
+        self.assertEqual(len(output_messages), 1)
+        self.assertEqual(output_messages[0]["role"], "assistant")
+        self.assertEqual(output_messages[0]["content"], {"content": "It's sunny and 75°F", "confidence": 0.95})
+
+    def test_filter_span_events_removes_llo_pattern_events(self):
+        """
+        Test that span events are completely removed when their names match LLO patterns.
+        """
+        # Create span events
+        normal_event = MagicMock()
+        normal_event.name = "normal.event"
+        normal_event.attributes = {"data": "keep this"}
+
+        llo_event1 = MagicMock()
+        llo_event1.name = "gen_ai.user.message"
+        llo_event1.attributes = {"content": "remove this event"}
+
+        llo_event2 = MagicMock()
+        llo_event2.name = "gen_ai.assistant.message"
+        llo_event2.attributes = {"content": "remove this too"}
+
+        another_normal_event = MagicMock()
+        another_normal_event.name = "another.normal.event"
+        another_normal_event.attributes = {"info": "keep this too"}
+
+        span = self._create_mock_span({})
+        span.events = [normal_event, llo_event1, llo_event2, another_normal_event]
+
+        self.llo_handler._filter_span_events(span)
+
+        # Should only have normal events left
+        self.assertEqual(len(span._events), 2)
+        remaining_names = [event.name for event in span._events]
+        self.assertIn("normal.event", remaining_names)
+        self.assertIn("another.normal.event", remaining_names)
+        self.assertNotIn("gen_ai.user.message", remaining_names)
+        self.assertNotIn("gen_ai.assistant.message", remaining_names)