Python: [BREAKING] Observability updates

python/.env.example

@@ -33,7 +33,6 @@ ANTHROPIC_MODEL=""
 OLLAMA_ENDPOINT=""
 OLLAMA_MODEL=""
 # Observability
-ENABLE_OTEL=true
+ENABLE_INSTRUMENTATION=true
 ENABLE_SENSITIVE_DATA=true
-OTLP_ENDPOINT="http://localhost:4317/"
-# APPLICATIONINSIGHTS_CONNECTION_STRING="..."
+OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4317/"

python/packages/a2a/agent_framework_a2a/_agent.py

@@ -5,7 +5,7 @@
 import re
 import uuid
 from collections.abc import AsyncIterable, Sequence
-from typing import Any, cast
+from typing import Any, Final, cast
 
 import httpx
 from a2a.client import Client, ClientConfig, ClientFactory, minimal_agent_card
@@ -38,6 +38,7 @@
     UriContent,
     prepend_agent_framework_to_user_agent,
 )
+from agent_framework.observability import use_agent_instrumentation
 
 __all__ = ["A2AAgent"]
 
@@ -58,6 +59,7 @@ def _get_uri_data(uri: str) -> str:
     return match.group("base64_data")
 
 
+@use_agent_instrumentation
 class A2AAgent(BaseAgent):
     """Agent2Agent (A2A) protocol implementation.
 
@@ -69,6 +71,8 @@ class A2AAgent(BaseAgent):
     Can be initialized with a URL, AgentCard, or existing A2A Client instance.
     """
 
+    AGENT_PROVIDER_NAME: Final[str] = "A2A"
+
     def __init__(
         self,
         *,

python/packages/ag-ui/agent_framework_ag_ui/_client.py

@@ -23,7 +23,7 @@
 from agent_framework._middleware import use_chat_middleware
 from agent_framework._tools import use_function_invocation
 from agent_framework._types import BaseContent, Contents
-from agent_framework.observability import use_observability
+from agent_framework.observability import use_instrumentation
 
 from ._event_converters import AGUIEventConverter
 from ._http_service import AGUIHttpService
@@ -89,7 +89,7 @@ async def response_wrapper(self, *args: Any, **kwargs: Any) -> ChatResponse:
 
 @_apply_server_function_call_unwrap
 @use_function_invocation
-@use_observability
+@use_instrumentation
 @use_chat_middleware
 class AGUIChatClient(BaseChatClient):
     """Chat client for communicating with AG-UI compliant servers.

python/packages/anthropic/agent_framework_anthropic/_chat_client.py

@@ -35,7 +35,7 @@
 )
 from agent_framework._pydantic import AFBaseSettings
 from agent_framework.exceptions import ServiceInitializationError
-from agent_framework.observability import use_observability
+from agent_framework.observability import use_instrumentation
 from anthropic import AsyncAnthropic
 from anthropic.types.beta import (
     BetaContentBlock,
@@ -110,7 +110,7 @@ class AnthropicSettings(AFBaseSettings):
 
 
 @use_function_invocation
-@use_observability
+@use_instrumentation
 @use_chat_middleware
 class AnthropicClient(BaseChatClient):
     """Anthropic Chat client."""

python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py

@@ -43,7 +43,7 @@
     use_function_invocation,
 )
 from agent_framework.exceptions import ServiceInitializationError, ServiceResponseException
-from agent_framework.observability import use_observability
+from agent_framework.observability import use_instrumentation
 from azure.ai.agents.aio import AgentsClient
 from azure.ai.agents.models import (
     Agent,
@@ -107,7 +107,7 @@
 
 
 @use_function_invocation
-@use_observability
+@use_instrumentation
 @use_chat_middleware
 class AzureAIAgentClient(BaseChatClient):
     """Azure AI Agent Chat client."""

python/packages/azure-ai/agent_framework_azure_ai/_client.py

@@ -15,7 +15,7 @@
     use_function_invocation,
 )
 from agent_framework.exceptions import ServiceInitializationError, ServiceInvalidRequestError
-from agent_framework.observability import use_observability
+from agent_framework.observability import use_instrumentation
 from agent_framework.openai._responses_client import OpenAIBaseResponsesClient
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import (
@@ -49,7 +49,7 @@
 
 
 @use_function_invocation
-@use_observability
+@use_instrumentation
 @use_chat_middleware
 class AzureAIClient(OpenAIBaseResponsesClient):
     """Azure AI Agent client."""
@@ -164,27 +164,94 @@ def __init__(
         # Track whether we should close client connection
         self._should_close_client = should_close_client
 
-    async def setup_azure_ai_observability(self, enable_sensitive_data: bool | None = None) -> None:
-        """Use this method to setup tracing in your Azure AI Project.
+    async def configure_azure_monitor(
+        self,
+        enable_sensitive_data: bool = False,
+        **kwargs: Any,
+    ) -> None:
+        """Setup observability with Azure Monitor (Azure AI Foundry integration).
+
+        This method configures Azure Monitor for telemetry collection using the
+        connection string from the Azure AI project client.
 
-        This will take the connection string from the project project_client.
-        It will override any connection string that is set in the environment variables.
-        It will disable any OTLP endpoint that might have been set.
+        Args:
+            enable_sensitive_data: Enable sensitive data logging (prompts, responses).
+                Should only be enabled in development/test environments. Default is False.
+            **kwargs: Additional arguments passed to configure_azure_monitor().
+                Common options include:
+                - enable_live_metrics (bool): Enable Azure Monitor Live Metrics
+                - credential (TokenCredential): Azure credential for Entra ID auth
+                - resource (Resource): Custom OpenTelemetry resource
+                See https://learn.microsoft.com/python/api/azure-monitor-opentelemetry/azure.monitor.opentelemetry.configure_azure_monitor
+                for full list of options.
+
+        Raises:
+            ImportError: If azure-monitor-opentelemetry-exporter is not installed.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.azure import AzureAIClient
+                from azure.ai.projects.aio import AIProjectClient
+                from azure.identity.aio import DefaultAzureCredential
+
+                async with (
+                    DefaultAzureCredential() as credential,
+                    AIProjectClient(
+                        endpoint="https://your-project.api.azureml.ms", credential=credential
+                    ) as project_client,
+                    AzureAIClient(project_client=project_client) as client,
+                ):
+                    # Setup observability with defaults
+                    await client.configure_azure_monitor()
+
+                    # With live metrics enabled
+                    await client.configure_azure_monitor(enable_live_metrics=True)
+
+                    # With sensitive data logging (dev/test only)
+                    await client.configure_azure_monitor(enable_sensitive_data=True)
+
+        Note:
+            This method retrieves the Application Insights connection string from the
+            Azure AI project client automatically. You must have Application Insights
+            configured in your Azure AI project for this to work.
         """
+        # Get connection string from project client
         try:
             conn_string = await self.project_client.telemetry.get_application_insights_connection_string()
         except ResourceNotFoundError:
             logger.warning(
-                "No Application Insights connection string found for the Azure AI Project, "
-                "please call setup_observability() manually."
+                "No Application Insights connection string found for the Azure AI Project. "
+                "Please ensure Application Insights is configured in your Azure AI project, "
+                "or call configure_otel_providers() manually with custom exporters."
             )
             return
-        from agent_framework.observability import setup_observability
 
-        setup_observability(
-            applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data
+        # Import Azure Monitor with proper error handling
+        try:
+            from azure.monitor.opentelemetry import configure_azure_monitor
+        except ImportError as exc:
+            raise ImportError(
+                "azure-monitor-opentelemetry is required for Azure Monitor integration. "
+                "Install it with: pip install azure-monitor-opentelemetry"
+            ) from exc
+
+        from agent_framework.observability import create_metric_views, create_resource, enable_instrumentation
+
+        # Create resource if not provided in kwargs
+        if "resource" not in kwargs:
+            kwargs["resource"] = create_resource()
+
+        # Configure Azure Monitor with connection string and kwargs
+        configure_azure_monitor(
+            connection_string=conn_string,
+            views=create_metric_views(),
+            **kwargs,
         )
 
+        # Complete setup with core observability
+        enable_instrumentation(enable_sensitive_data=enable_sensitive_data)
+
     async def __aenter__(self) -> "Self":
         """Async context manager entry."""
         return self

python/packages/core/agent_framework/_agents.py

@@ -34,7 +34,7 @@
     ToolMode,
 )
 from .exceptions import AgentExecutionException, AgentInitializationError
-from .observability import use_agent_observability
+from .observability import use_agent_instrumentation
 
 if sys.version_info >= (3, 12):
     from typing import override  # type: ignore # pragma: no cover
@@ -516,8 +516,8 @@ def _prepare_context_providers(
 
 
 @use_agent_middleware
-@use_agent_observability
-class ChatAgent(BaseAgent):
+@use_agent_instrumentation(capture_usage=False)  # type: ignore[arg-type,misc]
+class ChatAgent(BaseAgent):  # type: ignore[misc]
     """A Chat Client Agent.
 
     This is the primary agent implementation that uses a chat client to interact
@@ -583,7 +583,7 @@ def get_weather(location: str) -> str:
                 print(update.text, end="")
     """
 
-    AGENT_SYSTEM_NAME: ClassVar[str] = "microsoft.agent_framework"
+    AGENT_PROVIDER_NAME: ClassVar[str] = "microsoft.agent_framework"
 
     def __init__(
         self,

python/packages/core/agent_framework/_clients.py

@@ -8,7 +8,6 @@
 from pydantic import BaseModel
 
 from ._logging import get_logger
-from ._mcp import MCPTool
 from ._memory import AggregateContextProvider, ContextProvider
 from ._middleware import (
     ChatMiddleware,
@@ -426,6 +425,8 @@ async def _normalize_tools(
             else [tools]
         )
         for tool in tools_list:  # type: ignore[reportUnknownType]
+            from ._mcp import MCPTool
+
             if isinstance(tool, MCPTool):
                 if not tool.is_connected:
                     await tool.connect()

python/packages/core/agent_framework/_memory.py

@@ -6,11 +6,13 @@
 from collections.abc import MutableSequence, Sequence
 from contextlib import AsyncExitStack
 from types import TracebackType
-from typing import Any, Final, cast
+from typing import TYPE_CHECKING, Any, Final, cast
 
-from ._tools import ToolProtocol
 from ._types import ChatMessage
 
+if TYPE_CHECKING:
+    from ._tools import ToolProtocol
+
 if sys.version_info >= (3, 12):
     from typing import override  # type: ignore # pragma: no cover
 else:
@@ -54,7 +56,7 @@ def __init__(
         self,
         instructions: str | None = None,
         messages: Sequence[ChatMessage] | None = None,
-        tools: Sequence[ToolProtocol] | None = None,
+        tools: Sequence["ToolProtocol"] | None = None,
     ):
         """Create a new Context object.
 
@@ -65,7 +67,7 @@ def __init__(
         """
         self.instructions = instructions
         self.messages: Sequence[ChatMessage] = messages or []
-        self.tools: Sequence[ToolProtocol] = tools or []
+        self.tools: Sequence["ToolProtocol"] = tools or []
 
 
 # region ContextProvider
@@ -247,7 +249,7 @@ async def invoking(self, messages: ChatMessage | MutableSequence[ChatMessage], *
         contexts = await asyncio.gather(*[provider.invoking(messages, **kwargs) for provider in self.providers])
         instructions: str = ""
         return_messages: list[ChatMessage] = []
-        tools: list[ToolProtocol] = []
+        tools: list["ToolProtocol"] = []
         for ctx in contexts:
             if ctx.instructions:
                 instructions += ctx.instructions

python/packages/core/agent_framework/_serialization.py

@@ -339,11 +339,17 @@ def to_dict(self, *, exclude: set[str] | None = None, exclude_none: bool = True)
                     continue
                 # Handle dicts containing SerializationProtocol values
                 if isinstance(value, dict):
+                    from datetime import date, datetime, time
+
                     serialized_dict: dict[str, Any] = {}
                     for k, v in value.items():
                         if isinstance(v, SerializationProtocol):
                             serialized_dict[k] = v.to_dict(exclude=exclude, exclude_none=exclude_none)
                             continue
+                        # Convert datetime objects to strings
+                        if isinstance(v, (datetime, date, time)):
+                            serialized_dict[k] = str(v)
+                            continue
                         # Check if the value is JSON serializable
                         if is_serializable(v):
                             serialized_dict[k] = v

python/packages/core/agent_framework/_types.py

@@ -1816,13 +1816,14 @@ def prepare_function_call_results(content: Contents | Any | list[Contents | Any]
     """Prepare the values of the function call results."""
     if isinstance(content, Contents):
         # For BaseContent objects, use to_dict and serialize to JSON
-        return json.dumps(content.to_dict(exclude={"raw_representation", "additional_properties"}))
+        # Use default=str to handle datetime and other non-JSON-serializable objects
+        return json.dumps(content.to_dict(exclude={"raw_representation", "additional_properties"}), default=str)
 
     dumpable = _prepare_function_call_results_as_dumpable(content)
     if isinstance(dumpable, str):
         return dumpable
-    # fallback
-    return json.dumps(dumpable)
+    # fallback - use default=str to handle datetime and other non-JSON-serializable objects
+    return json.dumps(dumpable, default=str)
 
 
 # region Chat Response constants

python/packages/core/agent_framework/azure/_chat_client.py

@@ -21,7 +21,7 @@
     use_function_invocation,
 )
 from agent_framework.exceptions import ServiceInitializationError
-from agent_framework.observability import use_observability
+from agent_framework.observability import use_instrumentation
 from agent_framework.openai._chat_client import OpenAIBaseChatClient
 
 from ._shared import (
@@ -41,7 +41,7 @@
 
 
 @use_function_invocation
-@use_observability
+@use_instrumentation
 @use_chat_middleware
 class AzureOpenAIChatClient(AzureOpenAIConfigMixin, OpenAIBaseChatClient):
     """Azure OpenAI Chat completion class."""

python/packages/core/agent_framework/azure/_responses_client.py

@@ -10,7 +10,7 @@
 
 from agent_framework import use_chat_middleware, use_function_invocation
 from agent_framework.exceptions import ServiceInitializationError
-from agent_framework.observability import use_observability
+from agent_framework.observability import use_instrumentation
 from agent_framework.openai._responses_client import OpenAIBaseResponsesClient
 
 from ._shared import (
@@ -22,7 +22,7 @@
 
 
 @use_function_invocation
-@use_observability
+@use_instrumentation
 @use_chat_middleware
 class AzureOpenAIResponsesClient(AzureOpenAIConfigMixin, OpenAIBaseResponsesClient):
     """Azure Responses completion class."""