Agent framework extension update for input and output attributes

libraries/microsoft-agents-a365-observability-extensions-agentframework/microsoft_agents_a365/observability/extensions/agentframework/__init__.py

@@ -1,2 +1,10 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
+
+"""Agent Framework observability extensions for Agent365."""
+
+from .trace_instrumentor import AgentFrameworkInstrumentor
+
+__all__ = [
+    "AgentFrameworkInstrumentor",
+]

libraries/microsoft-agents-a365-observability-extensions-agentframework/microsoft_agents_a365/observability/extensions/agentframework/span_enricher.py

@@ -0,0 +1,51 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+from microsoft_agents_a365.observability.core.constants import (
+    EXECUTE_TOOL_OPERATION_NAME,
+    GEN_AI_INPUT_MESSAGES_KEY,
+    GEN_AI_OUTPUT_MESSAGES_KEY,
+    GEN_AI_TOOL_ARGS_KEY,
+    GEN_AI_TOOL_CALL_RESULT_KEY,
+    INVOKE_AGENT_OPERATION_NAME,
+)
+from microsoft_agents_a365.observability.core.exporters.enriched_span import EnrichedReadableSpan
+from opentelemetry.sdk.trace import ReadableSpan
+
+from .utils import extract_input_content, extract_output_content
+
+# Agent Framework specific attribute keys
+AF_TOOL_CALL_ARGUMENTS_KEY = "gen_ai.tool.call.arguments"
+AF_TOOL_CALL_RESULT_KEY = "gen_ai.tool.call.result"
+
+
+def enrich_agent_framework_span(span: ReadableSpan) -> ReadableSpan:
+    """
+    Enricher function for Agent Framework spans.
+    """
+    extra_attributes = {}
+    attributes = span.attributes or {}
+
+    # Only extract content for invoke_agent spans
+    if span.name.startswith(INVOKE_AGENT_OPERATION_NAME):
+        # Extract all text content from input messages
+        input_messages = attributes.get(GEN_AI_INPUT_MESSAGES_KEY)
+        if input_messages:
+            extra_attributes[GEN_AI_INPUT_MESSAGES_KEY] = extract_input_content(input_messages)
+
+        output_messages = attributes.get(GEN_AI_OUTPUT_MESSAGES_KEY)
+        if output_messages:
+            extra_attributes[GEN_AI_OUTPUT_MESSAGES_KEY] = extract_output_content(output_messages)
+
+    # Map tool attributes for execute_tool spans
+    elif span.name.startswith(EXECUTE_TOOL_OPERATION_NAME):
+        if AF_TOOL_CALL_ARGUMENTS_KEY in attributes:
+            extra_attributes[GEN_AI_TOOL_ARGS_KEY] = attributes[AF_TOOL_CALL_ARGUMENTS_KEY]
+
+        if AF_TOOL_CALL_RESULT_KEY in attributes:
+            extra_attributes[GEN_AI_TOOL_CALL_RESULT_KEY] = attributes[AF_TOOL_CALL_RESULT_KEY]
+
+    if extra_attributes:
+        return EnrichedReadableSpan(span, extra_attributes)
+
+    return span

libraries/microsoft-agents-a365-observability-extensions-agentframework/microsoft_agents_a365/observability/extensions/agentframework/span_processor.py

@@ -1,15 +1,12 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
 
-# Custom Span Processor
-
-from opentelemetry.sdk.trace.export import SpanProcessor
-
 from microsoft_agents_a365.observability.core.constants import (
-    GEN_AI_OPERATION_NAME_KEY,
     EXECUTE_TOOL_OPERATION_NAME,
     GEN_AI_EVENT_CONTENT,
+    GEN_AI_OPERATION_NAME_KEY,
 )
+from opentelemetry.sdk.trace.export import SpanProcessor
 
 
 class AgentFrameworkSpanProcessor(SpanProcessor):

libraries/microsoft-agents-a365-observability-extensions-agentframework/microsoft_agents_a365/observability/extensions/agentframework/trace_instrumentor.py

@@ -7,22 +7,28 @@
 from typing import Any
 
 from microsoft_agents_a365.observability.core.config import get_tracer_provider, is_configured
+from microsoft_agents_a365.observability.core.exporters.enriching_span_processor import (
+    register_span_enricher,
+    unregister_span_enricher,
+)
 from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
 
+from microsoft_agents_a365.observability.extensions.agentframework.span_enricher import (
+    enrich_agent_framework_span,
+)
 from microsoft_agents_a365.observability.extensions.agentframework.span_processor import (
     AgentFrameworkSpanProcessor,
 )
 
 # -----------------------------
 # 3) The Instrumentor class
 # -----------------------------
-_instruments = ("agent-framework-azure-ai >= 1.0.0b251114",)
+_instruments = ("agent-framework-azure-ai >= 1.0.0",)
 
 
 class AgentFrameworkInstrumentor(BaseInstrumentor):
     """
-    Instruments Agent Framework:
-      • Installs your custom OTel SpanProcessor
+    Instruments Agent Framework with Agent365 observability.
     """
 
     def __init__(self):
@@ -37,13 +43,28 @@ def instrumentation_dependencies(self) -> Collection[str]:
 
     def _instrument(self, **kwargs: Any) -> None:
         """
-        kwargs (all optional):
-        """
+        Instrument Agent Framework.
 
+        Args:
+            **kwargs: Optional configuration parameters.
+        """
         # Ensure we have an SDK TracerProvider
         provider = get_tracer_provider()
+
+        # Add processor for on_start modifications (rename spans, add attributes)
         self._processor = AgentFrameworkSpanProcessor()
         provider.add_span_processor(self._processor)
 
+        # Register enricher for on_end modifications
+        register_span_enricher(enrich_agent_framework_span)
+
     def _uninstrument(self, **kwargs: Any) -> None:
-        pass
+        """
+        Remove Agent Framework instrumentation.
+        """
+        # Unregister the enricher
+        unregister_span_enricher()
+
+        # Shutdown the processor
+        if hasattr(self, "_processor"):
+            self._processor.shutdown()

libraries/microsoft-agents-a365-observability-extensions-agentframework/microsoft_agents_a365/observability/extensions/agentframework/utils.py

@@ -0,0 +1,48 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+"""Utility functions for Agent Framework observability extensions."""
+
+from __future__ import annotations
+
+import json
+
+
+def extract_content_as_string_list(messages_json: str, role_filter: str | None = None) -> str:
+    """Extract content values from messages JSON and return as JSON string list."""
+    try:
+        messages = json.loads(messages_json)
+        if isinstance(messages, list):
+            contents = []
+            for msg in messages:
+                if isinstance(msg, dict):
+                    role = msg.get("role", "")
+
+                    # Filter by role if specified
+                    if role_filter and role != role_filter:
+                        continue
+
+                    # Handle Agent Framework format with "parts"
+                    parts = msg.get("parts")
+                    if parts and isinstance(parts, list):
+                        for part in parts:
+                            if isinstance(part, dict):
+                                part_type = part.get("type", "")
+                                # Only extract text content, not tool_call or tool_call_response
+                                if part_type == "text" and "content" in part:
+                                    contents.append(part["content"])
+            return json.dumps(contents)
+        return messages_json
+    except (json.JSONDecodeError, TypeError):
+        # If parsing fails, return as-is
+        return messages_json
+
+
+def extract_input_content(messages_json: str) -> str:
+    """Extract text content from user messages only."""
+    return extract_content_as_string_list(messages_json, role_filter="user")
+
+
+def extract_output_content(messages_json: str) -> str:
+    """Extract only assistant text content from output messages."""
+    return extract_content_as_string_list(messages_json, role_filter="assistant")

tests/observability/extensions/agentframework/__init__.py

@@ -0,0 +1,2 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.

tests/observability/extensions/agentframework/test_span_enricher.py

@@ -0,0 +1,68 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+"""Tests for Agent Framework span enricher."""
+
+import unittest
+from unittest.mock import Mock
+
+from microsoft_agents_a365.observability.core.constants import (
+    GEN_AI_INPUT_MESSAGES_KEY,
+    GEN_AI_OUTPUT_MESSAGES_KEY,
+    GEN_AI_TOOL_ARGS_KEY,
+    GEN_AI_TOOL_CALL_RESULT_KEY,
+)
+from microsoft_agents_a365.observability.extensions.agentframework.span_enricher import (
+    AF_TOOL_CALL_ARGUMENTS_KEY,
+    AF_TOOL_CALL_RESULT_KEY,
+    enrich_agent_framework_span,
+)
+
+
+class TestAgentFrameworkSpanEnricher(unittest.TestCase):
+    """Test suite for enrich_agent_framework_span function."""
+
+    def test_invoke_agent_span_enrichment(self):
+        """Test invoke_agent span extracts user input and assistant output text only."""
+        span = Mock(
+            name="invoke_agent Agent365Assistant",
+            attributes={
+                GEN_AI_INPUT_MESSAGES_KEY: '[{"role": "user", "parts": [{"type": "text", "content": "Compute 15 % 4"}]}]',
+                GEN_AI_OUTPUT_MESSAGES_KEY: '[{"role": "assistant", "parts": [{"type": "tool_call", "id": "c1"}]}, {"role": "tool", "parts": [{"type": "tool_call_response"}]}, {"role": "assistant", "parts": [{"type": "text", "content": "Result is 3."}]}]',
+            },
+        )
+        span.name = "invoke_agent Agent365Assistant"
+        result = enrich_agent_framework_span(span)
+        self.assertEqual(result.attributes[GEN_AI_INPUT_MESSAGES_KEY], '["Compute 15 % 4"]')
+        self.assertEqual(result.attributes[GEN_AI_OUTPUT_MESSAGES_KEY], '["Result is 3."]')
+
+    def test_execute_tool_span_enrichment(self):
+        """Test execute_tool span maps tool arguments and result to standard keys."""
+        span = Mock(
+            name="execute_tool calculate",
+            attributes={
+                AF_TOOL_CALL_ARGUMENTS_KEY: '{"expression": "2 + 2"}',
+                AF_TOOL_CALL_RESULT_KEY: "Result is 4",
+            },
+        )
+        span.name = "execute_tool calculate"
+        result = enrich_agent_framework_span(span)
+        self.assertEqual(result.attributes[GEN_AI_TOOL_ARGS_KEY], '{"expression": "2 + 2"}')
+        self.assertEqual(result.attributes[GEN_AI_TOOL_CALL_RESULT_KEY], "Result is 4")
+
+    def test_non_matching_and_edge_cases_return_original(self):
+        """Test non-matching, None, and empty attribute spans return unchanged."""
+        span = Mock(name="other_op", attributes={"key": "value"})
+        span.name = "other_op"
+        self.assertEqual(enrich_agent_framework_span(span), span)
+
+        span.name = "invoke_agent Test"
+        span.attributes = None
+        self.assertEqual(enrich_agent_framework_span(span), span)
+
+        span.attributes = {}
+        self.assertEqual(enrich_agent_framework_span(span), span)
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/observability/extensions/agentframework/test_utils.py

@@ -0,0 +1,35 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+"""Tests for Agent Framework utils."""
+
+import unittest
+
+from microsoft_agents_a365.observability.extensions.agentframework.utils import (
+    extract_content_as_string_list,
+    extract_input_content,
+    extract_output_content,
+)
+
+
+class TestAgentFrameworkUtils(unittest.TestCase):
+    """Test suite for Agent Framework utility functions."""
+
+    def test_extract_content_filters_text_by_role(self):
+        """Test text extraction with role filtering, ignoring tool calls."""
+        msgs = '[{"role": "user", "parts": [{"type": "text", "content": "Hi"}]}, {"role": "assistant", "parts": [{"type": "tool_call"}, {"type": "text", "content": "Hello"}]}]'
+        self.assertEqual(extract_content_as_string_list(msgs), '["Hi", "Hello"]')
+        self.assertEqual(extract_content_as_string_list(msgs, role_filter="user"), '["Hi"]')
+        self.assertEqual(extract_input_content(msgs), '["Hi"]')
+        self.assertEqual(extract_output_content(msgs), '["Hello"]')
+
+    def test_handles_invalid_and_edge_cases(self):
+        """Test invalid JSON and edge cases return appropriate values."""
+        self.assertEqual(extract_content_as_string_list("invalid"), "invalid")
+        self.assertEqual(extract_content_as_string_list('{"not": "list"}'), '{"not": "list"}')
+        self.assertEqual(extract_content_as_string_list("[]"), "[]")
+        self.assertEqual(extract_content_as_string_list('[{"role": "user"}]'), "[]")
+
+
+if __name__ == "__main__":
+    unittest.main()