Python: [BREAKING] Replaced AIProjectClient with AgentsClient in Foundry (#1936)

* Replaced AIProjectClient with AgentsClient in Foundry

* Update python/samples/getting_started/observability/azure_ai_agent_observability.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/samples/getting_started/observability/azure_ai_chat_client_with_observability.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Small fix

* Removed TODO item

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

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

@@ -2,7 +2,8 @@
 
 import importlib.metadata
 
-from ._chat_client import AzureAIAgentClient, AzureAISettings
+from ._chat_client import AzureAIAgentClient
+from ._shared import AzureAISettings
 
 try:
     __version__ = importlib.metadata.version(__name__)

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

@@ -40,9 +40,9 @@ from agent_framework import (
     use_chat_middleware,
     use_function_invocation,
 )
-from agent_framework._pydantic import AFBaseSettings
 from agent_framework.exceptions import ServiceInitializationError, ServiceResponseException
 from agent_framework.observability import use_observability
+from azure.ai.agents.aio import AgentsClient
 from azure.ai.agents.models import (
     Agent,
     AgentsNamedToolChoice,
@@ -85,11 +85,11 @@ from azure.ai.agents.models import (
     ToolDefinition,
     ToolOutput,
 )
-from azure.ai.projects.aio import AIProjectClient
 from azure.core.credentials_async import AsyncTokenCredential
-from azure.core.exceptions import HttpResponseError, ResourceNotFoundError
 from pydantic import ValidationError
 
+from ._shared import AzureAISettings
+
 if sys.version_info >= (3, 11):
     from typing import Self  # pragma: no cover
 else:
@@ -99,47 +99,6 @@ else:
 logger = get_logger("agent_framework.azure")
 
 
-class AzureAISettings(AFBaseSettings):
-    """Azure AI Project settings.
-
-    The settings are first loaded from environment variables with the prefix 'AZURE_AI_'.
-    If the environment variables are not found, the settings can be loaded from a .env file
-    with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
-    are ignored; however, validation will fail alerting that the settings are missing.
-
-    Keyword Args:
-        project_endpoint: The Azure AI Project endpoint URL.
-            Can be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
-        model_deployment_name: The name of the model deployment to use.
-            Can be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
-        env_file_path: If provided, the .env settings are read from this file path location.
-        env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
-
-    Examples:
-        .. code-block:: python
-
-            from agent_framework_azure_ai import AzureAISettings
-
-            # Using environment variables
-            # Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
-            # Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
-            settings = AzureAISettings()
-
-            # Or passing parameters directly
-            settings = AzureAISettings(
-                project_endpoint="https://your-project.cognitiveservices.azure.com", model_deployment_name="gpt-4"
-            )
-
-            # Or loading from a .env file
-            settings = AzureAISettings(env_file_path="path/to/.env")
-    """
-
-    env_prefix: ClassVar[str] = "AZURE_AI_"
-
-    project_endpoint: str | None = None
-    model_deployment_name: str | None = None
-
-
 TAzureAIAgentClient = TypeVar("TAzureAIAgentClient", bound="AzureAIAgentClient")
 
 
@@ -154,7 +113,7 @@ class AzureAIAgentClient(BaseChatClient):
     def __init__(
         self,
         *,
-        project_client: AIProjectClient | None = None,
+        agents_client: AgentsClient | None = None,
         agent_id: str | None = None,
         agent_name: str | None = None,
         thread_id: str | None = None,
@@ -169,16 +128,16 @@ class AzureAIAgentClient(BaseChatClient):
         """Initialize an Azure AI Agent client.
 
         Keyword Args:
-            project_client: An existing AIProjectClient to use. If not provided, one will be created.
-            agent_id: The ID of an existing agent to use. If not provided and project_client is provided,
-                a new agent will be created (and deleted after the request). If neither project_client
+            agents_client: An existing AgentsClient to use. If not provided, one will be created.
+            agent_id: The ID of an existing agent to use. If not provided and agents_client is provided,
+                a new agent will be created (and deleted after the request). If neither agents_client
                 nor agent_id is provided, both will be created and managed automatically.
             agent_name: The name to use when creating new agents.
             thread_id: Default thread ID to use for conversations. Can be overridden by
                 conversation_id property when making a request.
             project_endpoint: The Azure AI Project endpoint URL.
                 Can also be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
-                Ignored when a project_client is passed.
+                Ignored when a agents_client is passed.
             model_deployment_name: The model deployment name to use for agent creation.
                 Can also be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
             async_credential: Azure async credential to use for authentication.
@@ -221,9 +180,9 @@ class AzureAIAgentClient(BaseChatClient):
         except ValidationError as ex:
             raise ServiceInitializationError("Failed to create Azure AI settings.", ex) from ex
 
-        # If no project_client is provided, create one
+        # If no agents_client is provided, create one
         should_close_client = False
-        if project_client is None:
+        if agents_client is None:
             if not azure_ai_settings.project_endpoint:
                 raise ServiceInitializationError(
                     "Azure AI project endpoint is required. Set via 'project_endpoint' parameter "
@@ -238,8 +197,8 @@ class AzureAIAgentClient(BaseChatClient):
 
             # Use provided credential
             if not async_credential:
-                raise ServiceInitializationError("Azure credential is required when project_client is not provided.")
-            project_client = AIProjectClient(
+                raise ServiceInitializationError("Azure credential is required when agents_client is not provided.")
+            agents_client = AgentsClient(
                 endpoint=azure_ai_settings.project_endpoint,
                 credential=async_credential,
                 user_agent=AGENT_FRAMEWORK_USER_AGENT,
@@ -250,7 +209,7 @@ class AzureAIAgentClient(BaseChatClient):
         super().__init__(**kwargs)
 
         # Initialize instance variables
-        self.project_client = project_client
+        self.agents_client = agents_client
         self.credential = async_credential
         self.agent_id = agent_id
         self.agent_name = agent_name
@@ -261,27 +220,6 @@ class AzureAIAgentClient(BaseChatClient):
         self._should_close_client = should_close_client  # Track whether we should close client connection
         self._agent_definition: Agent | None = None  # Cached definition for existing agent
 
-    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.
-
-        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.
-        """
-        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."
-            )
-            return
-        from agent_framework.observability import setup_observability
-
-        setup_observability(
-            applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data
-        )
-
     async def __aenter__(self) -> "Self":
         """Async context manager entry."""
         return self
@@ -291,7 +229,7 @@ class AzureAIAgentClient(BaseChatClient):
         await self.close()
 
     async def close(self) -> None:
-        """Close the project_client and clean up any agents we created."""
+        """Close the agents_client and clean up any agents we created."""
         await self._cleanup_agent_if_needed()
         await self._close_client_if_needed()
 
@@ -303,7 +241,7 @@ class AzureAIAgentClient(BaseChatClient):
             settings: A dictionary of settings for the service.
         """
         return cls(
-            project_client=settings.get("project_client"),
+            agents_client=settings.get("agents_client"),
             agent_id=settings.get("agent_id"),
             thread_id=settings.get("thread_id"),
             project_endpoint=settings.get("project_endpoint"),
@@ -380,11 +318,14 @@ class AzureAIAgentClient(BaseChatClient):
                 args["instructions"] = run_options["instructions"]
             if "response_format" in run_options:
                 args["response_format"] = run_options["response_format"]
+
             if "temperature" in run_options:
                 args["temperature"] = run_options["temperature"]
             if "top_p" in run_options:
                 args["top_p"] = run_options["top_p"]
-            created_agent = await self.project_client.agents.create_agent(**args)
+
+            created_agent = await self.agents_client.create_agent(**args)
+
             self.agent_id = str(created_agent.id)
             self._agent_definition = created_agent
             self._agent_created = True
@@ -428,7 +369,7 @@ class AzureAIAgentClient(BaseChatClient):
                 args["tool_outputs"] = tool_outputs
             if tool_approvals:
                 args["tool_approvals"] = tool_approvals
-            await self.project_client.agents.runs.submit_tool_outputs_stream(**args)  # type: ignore[reportUnknownMemberType]
+            await self.agents_client.runs.submit_tool_outputs_stream(**args)  # type: ignore[reportUnknownMemberType]
             # Pass the handler to the stream to continue processing
             stream = handler  # type: ignore
             final_thread_id = thread_run.thread_id
@@ -438,7 +379,7 @@ class AzureAIAgentClient(BaseChatClient):
 
             # Now create a new run and stream the results.
             run_options.pop("conversation_id", None)
-            stream = await self.project_client.agents.runs.stream(  # type: ignore[reportUnknownMemberType]
+            stream = await self.agents_client.runs.stream(  # type: ignore[reportUnknownMemberType]
                 final_thread_id, agent_id=agent_id, **run_options
             )
 
@@ -449,9 +390,7 @@ class AzureAIAgentClient(BaseChatClient):
         if thread_id is None:
             return None
 
-        async for run in self.project_client.agents.runs.list(
-            thread_id=thread_id, limit=1, order=ListSortOrder.DESCENDING
-        ):  # type: ignore[reportUnknownMemberType]
+        async for run in self.agents_client.runs.list(thread_id=thread_id, limit=1, order=ListSortOrder.DESCENDING):  # type: ignore[reportUnknownMemberType]
             if run.status not in [
                 RunStatus.COMPLETED,
                 RunStatus.CANCELLED,
@@ -468,12 +407,12 @@ class AzureAIAgentClient(BaseChatClient):
         if thread_id is not None:
             if thread_run is not None:
                 # There was an active run; we need to cancel it before starting a new run.
-                await self.project_client.agents.runs.cancel(thread_id, thread_run.id)
+                await self.agents_client.runs.cancel(thread_id, thread_run.id)
 
             return thread_id
 
         # No thread ID was provided, so create a new thread.
-        thread = await self.project_client.agents.threads.create(
+        thread = await self.agents_client.threads.create(
             tool_resources=run_options.get("tool_resources"), metadata=run_options.get("metadata")
         )
         thread_id = thread.id
@@ -482,7 +421,7 @@ class AzureAIAgentClient(BaseChatClient):
         # once fixed, in the function above, readd:
         # `messages=run_options.pop("additional_messages")`
         for msg in run_options.pop("additional_messages", []):
-            await self.project_client.agents.messages.create(
+            await self.agents_client.messages.create(
                 thread_id=thread_id, role=msg.role, content=msg.content, metadata=msg.metadata
             )
         # and remove until here.
@@ -715,21 +654,21 @@ class AzureAIAgentClient(BaseChatClient):
         return []
 
     async def _close_client_if_needed(self) -> None:
-        """Close project_client session if we created it."""
+        """Close agents_client session if we created it."""
         if self._should_close_client:
-            await self.project_client.close()
+            await self.agents_client.close()
 
     async def _cleanup_agent_if_needed(self) -> None:
         """Clean up the agent if we created it."""
         if self._agent_created and self.should_cleanup_agent and self.agent_id is not None:
-            await self.project_client.agents.delete_agent(self.agent_id)
+            await self.agents_client.delete_agent(self.agent_id)
             self.agent_id = None
             self._agent_created = False
 
     async def _load_agent_definition_if_needed(self) -> Agent | None:
         """Load and cache agent details if not already loaded."""
         if self._agent_definition is None and self.agent_id is not None:
-            self._agent_definition = await self.project_client.agents.get_agent(self.agent_id)
+            self._agent_definition = await self.agents_client.get_agent(self.agent_id)
         return self._agent_definition
 
     def _prepare_tool_choice(self, chat_options: ChatOptions) -> None:
@@ -919,59 +858,34 @@ class AzureAIAgentClient(BaseChatClient):
                         config_args["market"] = market
                     if set_lang := additional_props.get("set_lang"):
                         config_args["set_lang"] = set_lang
-                    # Bing Grounding (support both connection_id and connection_name)
+                    # Bing Grounding
                     connection_id = additional_props.get("connection_id") or os.getenv("BING_CONNECTION_ID")
-                    connection_name = additional_props.get("connection_name") or os.getenv("BING_CONNECTION_NAME")
                     # Custom Bing Search
-                    custom_connection_name = additional_props.get("custom_connection_name") or os.getenv(
-                        "BING_CUSTOM_CONNECTION_NAME"
+                    custom_connection_id = additional_props.get("custom_connection_id") or os.getenv(
+                        "BING_CUSTOM_CONNECTION_ID"
                     )
-                    custom_configuration_name = additional_props.get("custom_instance_name") or os.getenv(
+                    custom_instance_name = additional_props.get("custom_instance_name") or os.getenv(
                         "BING_CUSTOM_INSTANCE_NAME"
                     )
                     bing_search: BingGroundingTool | BingCustomSearchTool | None = None
-                    if (
-                        (connection_id or connection_name)
-                        and not custom_connection_name
-                        and not custom_configuration_name
-                    ):
+                    if (connection_id) and not custom_connection_id and not custom_instance_name:
                         if connection_id:
                             conn_id = connection_id
-                        elif connection_name:
-                            try:
-                                bing_connection = await self.project_client.connections.get(name=connection_name)
-                            except HttpResponseError as err:
-                                raise ServiceInitializationError(
-                                    f"Bing connection '{connection_name}' not found in the Azure AI Project.",
-                                    err,
-                                ) from err
-                            else:
-                                conn_id = bing_connection.id
                         else:
-                            raise ServiceInitializationError("Neither connection_id nor connection_name provided.")
+                            raise ServiceInitializationError("Parameter connection_id is not provided.")
                         bing_search = BingGroundingTool(connection_id=conn_id, **config_args)
-                    if custom_connection_name and custom_configuration_name:
-                        try:
-                            bing_custom_connection = await self.project_client.connections.get(
-                                name=custom_connection_name
-                            )
-                        except HttpResponseError as err:
-                            raise ServiceInitializationError(
-                                f"Bing custom connection '{custom_connection_name}' not found in the Azure AI Project.",
-                                err,
-                            ) from err
-                        else:
-                            bing_search = BingCustomSearchTool(
-                                connection_id=bing_custom_connection.id,
-                                instance_name=custom_configuration_name,
-                                **config_args,
-                            )
+                    if custom_connection_id and custom_instance_name:
+                        bing_search = BingCustomSearchTool(
+                            connection_id=custom_connection_id,
+                            instance_name=custom_instance_name,
+                            **config_args,
+                        )
                     if not bing_search:
                         raise ServiceInitializationError(
-                            "Bing search tool requires either 'connection_id' or 'connection_name' for Bing Grounding "
-                            "or both 'custom_connection_name' and 'custom_instance_name' for Custom Bing Search. "
+                            "Bing search tool requires either 'connection_id' for Bing Grounding "
+                            "or both 'custom_connection_id' and 'custom_instance_name' for Custom Bing Search. "
                             "These can be provided via additional_properties or environment variables: "
-                            "'BING_CONNECTION_ID', 'BING_CONNECTION_NAME', 'BING_CUSTOM_CONNECTION_NAME', "
+                            "'BING_CONNECTION_ID', 'BING_CUSTOM_CONNECTION_ID', "
                             "'BING_CUSTOM_INSTANCE_NAME'"
                         )
                     tool_definitions.extend(bing_search.definitions)
@@ -1062,4 +976,4 @@ class AzureAIAgentClient(BaseChatClient):
         Returns:
             The service URL for the chat client, or None if not set.
         """
-        return self.project_client._config.endpoint
+        return self.agents_client._config.endpoint  # type: ignore

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

@@ -0,0 +1,46 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from typing import ClassVar
+
+from agent_framework._pydantic import AFBaseSettings
+
+
+class AzureAISettings(AFBaseSettings):
+    """Azure AI Project settings.
+
+    The settings are first loaded from environment variables with the prefix 'AZURE_AI_'.
+    If the environment variables are not found, the settings can be loaded from a .env file
+    with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
+    are ignored; however, validation will fail alerting that the settings are missing.
+
+    Keyword Args:
+        project_endpoint: The Azure AI Project endpoint URL.
+            Can be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
+        model_deployment_name: The name of the model deployment to use.
+            Can be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
+        env_file_path: If provided, the .env settings are read from this file path location.
+        env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework.azure import AzureAISettings
+
+            # Using environment variables
+            # Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
+            # Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
+            settings = AzureAISettings()
+
+            # Or passing parameters directly
+            settings = AzureAISettings(
+                project_endpoint="https://your-project.cognitiveservices.azure.com", model_deployment_name="gpt-4"
+            )
+
+            # Or loading from a .env file
+            settings = AzureAISettings(env_file_path="path/to/.env")
+    """
+
+    env_prefix: ClassVar[str] = "AZURE_AI_"
+
+    project_endpoint: str | None = None
+    model_deployment_name: str | None = None

python/packages/azure-ai/tests/conftest.py

@@ -44,31 +44,30 @@ def azure_ai_unit_test_env(monkeypatch, exclude_list, override_env_param_dict):
 
 
 @fixture
-def mock_ai_project_client() -> MagicMock:
-    """Fixture that provides a mock AIProjectClient."""
+def mock_agents_client() -> MagicMock:
+    """Fixture that provides a mock AgentsClient."""
     mock_client = MagicMock()
 
     # Mock agents property
-    mock_client.agents = MagicMock()
-    mock_client.agents.create_agent = AsyncMock()
-    mock_client.agents.delete_agent = AsyncMock()
+    mock_client.create_agent = AsyncMock()
+    mock_client.delete_agent = AsyncMock()
 
     # Mock agent creation response
     mock_agent = MagicMock()
     mock_agent.id = "test-agent-id"
-    mock_client.agents.create_agent.return_value = mock_agent
+    mock_client.create_agent.return_value = mock_agent
 
     # Mock threads property
-    mock_client.agents.threads = MagicMock()
-    mock_client.agents.threads.create = AsyncMock()
-    mock_client.agents.messages.create = AsyncMock()
+    mock_client.threads = MagicMock()
+    mock_client.threads.create = AsyncMock()
+    mock_client.messages.create = AsyncMock()
 
     # Mock runs property
-    mock_client.agents.runs = MagicMock()
-    mock_client.agents.runs.list = AsyncMock()
-    mock_client.agents.runs.cancel = AsyncMock()
-    mock_client.agents.runs.stream = AsyncMock()
-    mock_client.agents.runs.submit_tool_outputs_stream = AsyncMock()
+    mock_client.runs = MagicMock()
+    mock_client.runs.list = AsyncMock()
+    mock_client.runs.cancel = AsyncMock()
+    mock_client.runs.stream = AsyncMock()
+    mock_client.runs.submit_tool_outputs_stream = AsyncMock()
 
     return mock_client
 

python/packages/lab/gaia/samples/azure_ai_agent.py

@@ -10,8 +10,6 @@ Required Environment Variables:
     AZURE_AI_MODEL_DEPLOYMENT_NAME: Name of the model deployment to use
 
 Optional Environment Variables:
-    BING_CONNECTION_NAME: Name of the Bing connection for web search
-        OR
     BING_CONNECTION_ID: ID of the Bing connection for web search
 
 Authentication:
@@ -21,7 +19,7 @@ Authentication:
 Example:
     export AZURE_AI_PROJECT_ENDPOINT="https://your-project.azure.com"
     export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o"
-    export BING_CONNECTION_NAME="bing-grounding-connection"
+    export BING_CONNECTION_ID="connection-id"
     az login
 """
 

python/samples/getting_started/agents/azure_ai/README.md

@@ -38,10 +38,8 @@ Before running the examples, you need to set up your environment variables. You
    AZURE_AI_MODEL_DEPLOYMENT_NAME="your-model-deployment-name"
    ```
 
-3. For samples using Bing Grounding search (like `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`), you'll also need either:
+3. For samples using Bing Grounding search (like `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`), you'll also need:
    ```
-   BING_CONNECTION_NAME="bing-grounding-connection"
-   # OR
    BING_CONNECTION_ID="your-bing-connection-id"
    ```
 
@@ -49,7 +47,7 @@ Before running the examples, you need to set up your environment variables. You
    - Go to [Azure AI Foundry portal](https://ai.azure.com)
    - Navigate to your project's "Connected resources" section
    - Add a new connection for "Grounding with Bing Search"
-   - Copy either the connection name or ID
+   - Copy the ID
 
 ### Option 2: Using environment variables directly
 
@@ -58,9 +56,7 @@ Set the environment variables in your shell:
 ```bash
 export AZURE_AI_PROJECT_ENDPOINT="your-project-endpoint"
 export AZURE_AI_MODEL_DEPLOYMENT_NAME="your-model-deployment-name"
-export BING_CONNECTION_NAME="your-bing-connection-name"  # Optional, only needed for web search samples
-# OR
-export BING_CONNECTION_ID="your-bing-connection-id"  # Alternative to BING_CONNECTION_NAME
+export BING_CONNECTION_ID="your-bing-connection-id"
 ```
 
 ### Required Variables
@@ -70,4 +66,4 @@ export BING_CONNECTION_ID="your-bing-connection-id"  # Alternative to BING_CONNE
 
 ### Optional Variables
 
-- `BING_CONNECTION_NAME` or `BING_CONNECTION_ID`: Your Bing connection name or ID (required for `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`)
+- `BING_CONNECTION_ID`: Your Bing connection ID (required for `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`)

python/samples/getting_started/agents/azure_ai/azure_ai_with_azure_ai_search.py

@@ -5,6 +5,7 @@ import os
 
 from agent_framework import ChatAgent, CitationAnnotation
 from agent_framework.azure import AzureAIAgentClient
+from azure.ai.agents.aio import AgentsClient
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import ConnectionType
 from azure.identity.aio import AzureCliCredential
@@ -38,16 +39,17 @@ async def main() -> None:
     # Create the client and manually create an agent with Azure AI Search tool
     async with (
         AzureCliCredential() as credential,
-        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
+        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
+        AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
     ):
         ai_search_conn_id = ""
-        async for connection in client.connections.list():
+        async for connection in project_client.connections.list():
             if connection.type == ConnectionType.AZURE_AI_SEARCH:
                 ai_search_conn_id = connection.id
                 break
 
         # 1. Create Azure AI agent with the search tool
-        azure_ai_agent = await client.agents.create_agent(
+        azure_ai_agent = await project_client.agents.create_agent(
             model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
             name="HotelSearchAgent",
             instructions=(
@@ -69,7 +71,7 @@ async def main() -> None:
         )
 
         # 2. Create chat client with the existing agent
-        chat_client = AzureAIAgentClient(project_client=client, agent_id=azure_ai_agent.id)
+        chat_client = AzureAIAgentClient(agents_client=agents_client, agent_id=azure_ai_agent.id)
 
         try:
             async with ChatAgent(
@@ -112,7 +114,7 @@ async def main() -> None:
 
         finally:
             # Clean up the agent manually
-            await client.agents.delete_agent(azure_ai_agent.id)
+            await project_client.agents.delete_agent(azure_ai_agent.id)
 
 
 if __name__ == "__main__":

python/samples/getting_started/agents/azure_ai/azure_ai_with_bing_grounding.py

@@ -12,8 +12,7 @@ uses Bing Grounding search to find real-time information from the web.
 
 Prerequisites:
 1. A connected Grounding with Bing Search resource in your Azure AI project
-2. Set either BING_CONNECTION_NAME or BING_CONNECTION_ID environment variable
-   Example: BING_CONNECTION_NAME="bing-grounding-connection"
+2. Set BING_CONNECTION_ID environment variable
    Example: BING_CONNECTION_ID="your-bing-connection-id"
 
 To set up Bing Grounding:
@@ -27,7 +26,7 @@ To set up Bing Grounding:
 async def main() -> None:
     """Main function demonstrating Azure AI agent with Bing Grounding search."""
     # 1. Create Bing Grounding search tool using HostedWebSearchTool
-    # The connection_name or ID will be automatically picked up from environment variable
+    # The connection ID will be automatically picked up from environment variable
     bing_search_tool = HostedWebSearchTool(
         name="Bing Grounding Search",
         description="Search the web for current information using Bing",

python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_agent.py

@@ -5,6 +5,7 @@ import os
 
 from agent_framework import ChatAgent
 from agent_framework.azure import AzureAIAgentClient
+from azure.ai.agents.aio import AgentsClient
 from azure.ai.projects.aio import AIProjectClient
 from azure.identity.aio import AzureCliCredential
 
@@ -22,16 +23,17 @@ async def main() -> None:
     # Create the client
     async with (
         AzureCliCredential() as credential,
-        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
+        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
+        AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
     ):
-        azure_ai_agent = await client.agents.create_agent(
+        azure_ai_agent = await project_client.agents.create_agent(
             model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
             # Create remote agent with default instructions
             # These instructions will persist on created agent for every run.
             instructions="End each response with [END].",
         )
 
-        chat_client = AzureAIAgentClient(project_client=client, agent_id=azure_ai_agent.id)
+        chat_client = AzureAIAgentClient(agents_client=agents_client, agent_id=azure_ai_agent.id)
 
         try:
             async with ChatAgent(
@@ -50,7 +52,7 @@ async def main() -> None:
                 print(f"Agent: {result}\n")
         finally:
             # Clean up the agent manually
-            await client.agents.delete_agent(azure_ai_agent.id)
+            await project_client.agents.delete_agent(azure_ai_agent.id)
 
 
 if __name__ == "__main__":

python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_thread.py

@@ -7,7 +7,7 @@ from typing import Annotated
 
 from agent_framework import ChatAgent
 from agent_framework.azure import AzureAIAgentClient
-from azure.ai.projects.aio import AIProjectClient
+from azure.ai.agents.aio import AgentsClient
 from azure.identity.aio import AzureCliCredential
 from pydantic import Field
 
@@ -33,16 +33,16 @@ async def main() -> None:
     # Create the client
     async with (
         AzureCliCredential() as credential,
-        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
+        AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
     ):
         # Create an thread that will persist
-        created_thread = await client.agents.threads.create()
+        created_thread = await agents_client.threads.create()
 
         try:
             async with ChatAgent(
                 # passing in the client is optional here, so if you take the agent_id from the portal
                 # you can use it directly without the two lines above.
-                chat_client=AzureAIAgentClient(project_client=client),
+                chat_client=AzureAIAgentClient(agents_client=agents_client),
                 instructions="You are a helpful weather agent.",
                 tools=get_weather,
             ) as agent:
@@ -52,7 +52,7 @@ async def main() -> None:
                 print(f"Result: {result}\n")
         finally:
             # Clean up the thread manually
-            await client.agents.threads.delete(created_thread.id)
+            await agents_client.threads.delete(created_thread.id)
 
 
 if __name__ == "__main__":

python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py

@@ -44,8 +44,6 @@ async def main() -> None:
         AzureCliCredential() as credential,
         AzureAIAgentClient(async_credential=credential) as chat_client,
     ):
-        # enable azure-ai observability
-        await chat_client.setup_azure_ai_observability()
         agent = chat_client.create_agent(
             name="DocsAgent",
             instructions="You are a helpful assistant that can help with microsoft documentation questions.",

python/samples/getting_started/agents/azure_ai/azure_ai_with_multiple_tools.py

@@ -69,8 +69,6 @@ async def main() -> None:
         AzureCliCredential() as credential,
         AzureAIAgentClient(async_credential=credential) as chat_client,
     ):
-        # enable azure-ai observability
-        await chat_client.setup_azure_ai_observability()
         agent = chat_client.create_agent(
             name="DocsAgent",
             instructions="You are a helpful assistant that can help with microsoft documentation questions.",

python/samples/getting_started/observability/azure_ai_agent_observability.py

@@ -9,7 +9,9 @@ import dotenv
 from agent_framework import ChatAgent
 from agent_framework.azure import AzureAIAgentClient
 from agent_framework.observability import get_tracer
+from azure.ai.agents.aio import AgentsClient
 from azure.ai.projects.aio import AIProjectClient
+from azure.core.exceptions import ResourceNotFoundError
 from azure.identity.aio import AzureCliCredential
 from opentelemetry.trace import SpanKind
 from opentelemetry.trace.span import format_trace_id
@@ -38,16 +40,36 @@ async def get_weather(
     return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
 
 
+async def setup_azure_ai_observability(
+    project_client: AIProjectClient, enable_sensitive_data: bool | None = None
+) -> None:
+    """Use this method to setup tracing in your Azure AI Project.
+
+    This will take the connection string from the AIProjectClient.
+    It will override any connection string that is set in the environment variables.
+    It will disable any OTLP endpoint that might have been set.
+    """
+    try:
+        conn_string = await project_client.telemetry.get_application_insights_connection_string()
+    except ResourceNotFoundError:
+        print("No Application Insights connection string found for the Azure AI Project.")
+        return
+    from agent_framework.observability import setup_observability
+
+    setup_observability(applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data)
+
+
 async def main():
     async with (
         AzureCliCredential() as credential,
-        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project,
-        AzureAIAgentClient(project_client=project) as client,
+        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
+        AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
+        AzureAIAgentClient(agents_client=agents_client) as client,
     ):
         # This will enable tracing and configure the application to send telemetry data to the
         # Application Insights instance attached to the Azure AI project.
         # This will override any existing configuration.
-        await client.setup_azure_ai_observability()
+        await setup_azure_ai_observability(project_client)
 
         questions = ["What's the weather in Amsterdam?", "and in Paris, and which is better?", "Why is the sky blue?"]
 

python/samples/getting_started/observability/azure_ai_chat_client_with_observability.py

@@ -9,7 +9,9 @@ import dotenv
 from agent_framework import HostedCodeInterpreterTool
 from agent_framework.azure import AzureAIAgentClient
 from agent_framework.observability import get_tracer
+from azure.ai.agents.aio import AgentsClient
 from azure.ai.projects.aio import AIProjectClient
+from azure.core.exceptions import ResourceNotFoundError
 from azure.identity.aio import AzureCliCredential
 from opentelemetry.trace import SpanKind
 from opentelemetry.trace.span import format_trace_id
@@ -42,6 +44,25 @@ async def get_weather(
     return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
 
 
+async def setup_azure_ai_observability(
+    project_client: AIProjectClient, enable_sensitive_data: bool | None = None
+) -> None:
+    """Use this method to setup tracing in your Azure AI Project.
+
+    This will take the connection string from the AIProjectClient instance.
+    It will override any connection string that is set in the environment variables.
+    It will disable any OTLP endpoint that might have been set.
+    """
+    try:
+        conn_string = await project_client.telemetry.get_application_insights_connection_string()
+    except ResourceNotFoundError:
+        print("No Application Insights connection string found for the Azure AI Project.")
+        return
+    from agent_framework.observability import setup_observability
+
+    setup_observability(applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data)
+
+
 async def main() -> None:
     """Run an AI service.
 
@@ -62,13 +83,14 @@ async def main() -> None:
     ]
     async with (
         AzureCliCredential() as credential,
-        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project,
-        AzureAIAgentClient(project_client=project) as client,
+        AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
+        AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
+        AzureAIAgentClient(agents_client=agents_client) as client,
     ):
         # This will enable tracing and configure the application to send telemetry data to the
         # Application Insights instance attached to the Azure AI project.
         # This will override any existing configuration.
-        await client.setup_azure_ai_observability()
+        await setup_azure_ai_observability(project_client)
 
         with get_tracer().start_as_current_span(
             name="Foundry Telemetry from Agent Framework", kind=SpanKind.CLIENT