Python: Clean up imports (#2318)

* chore: tidy imports

* Update python/packages/azurefunctions/agent_framework_azurefunctions/_errors.py

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

* Update python/packages/azurefunctions/agent_framework_azurefunctions/_callbacks.py

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

* chore: revert stub file change

* chore: trigger pre-commit hook, re-add `annotations` import

---------

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

python/samples/demos/chatkit-integration/app.py

@@ -250,7 +250,7 @@ class WeatherChatKitServer(ChatKitServer[dict[str, Any]]):
             context: The context dictionary.
         """
         logger.info(f"Attempting to update thread title for thread: {thread.id}")
-        
+
         if not thread_items:
             logger.debug("No thread items available for title generation")
             return

python/samples/getting_started/agents/ollama/ollama_with_openai_chat_client.py

@@ -33,7 +33,7 @@ async def non_streaming_example() -> None:
     print("=== Non-streaming Response Example ===")
 
     agent = OpenAIChatClient(
-        api_key="ollama", # Just a placeholder, Ollama doesn't require API key
+        api_key="ollama",  # Just a placeholder, Ollama doesn't require API key
         base_url=os.getenv("OLLAMA_ENDPOINT"),
         model_id=os.getenv("OLLAMA_MODEL"),
     ).create_agent(
@@ -53,7 +53,7 @@ async def streaming_example() -> None:
     print("=== Streaming Response Example ===")
 
     agent = OpenAIChatClient(
-        api_key="ollama", # Just a placeholder, Ollama doesn't require API key
+        api_key="ollama",  # Just a placeholder, Ollama doesn't require API key
         base_url=os.getenv("OLLAMA_ENDPOINT"),
         model_id=os.getenv("OLLAMA_MODEL"),
     ).create_agent(

python/samples/getting_started/azure_functions/01_single_agent/function_app.py

@@ -10,6 +10,8 @@ from typing import Any
 
 from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient
 from azure.identity import AzureCliCredential
+
+
 # 1. Instantiate the agent with the chosen deployment and instructions.
 def _create_agent() -> Any:
     """Create the Joker agent."""

python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py

@@ -40,6 +40,7 @@ class EmailPayload(BaseModel):
     email_id: str
     email_content: str
 
+
 # 2. Instantiate both agents so they can be registered with AgentFunctionApp.
 def _create_agents() -> list[Any]:
     chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())

python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py

@@ -275,7 +275,7 @@ async def get_orchestration_status(
         show_history_output=False,
         show_input=True,
     )
-    
+
     # Check if status is None or if the instance doesn't exist (runtime_status is None)
     if status is None or getattr(status, "runtime_status", None) is None:
         return func.HttpResponse(

python/samples/getting_started/devui/weather_agent_azure/agent.py

@@ -15,9 +15,9 @@ from agent_framework import (
     FunctionInvocationContext,
     Role,
     TextContent,
+    ai_function,
     chat_middleware,
     function_middleware,
-    ai_function
 )
 from agent_framework.azure import AzureOpenAIChatClient
 from agent_framework_devui import register_cleanup
@@ -122,6 +122,7 @@ def get_forecast(
 
     return f"Weather forecast for {location}:\n" + "\n".join(forecast)
 
+
 @ai_function(approval_mode="always_require")
 def send_email(
     recipient: Annotated[str, "The email address of the recipient."],
@@ -131,6 +132,7 @@ def send_email(
     """Simulate sending an email."""
     return f"Email sent to {recipient} with subject '{subject}'."
 
+
 # Agent instance following Agent Framework conventions
 agent = ChatAgent(
     name="AzureWeatherAgent",

python/samples/getting_started/multimodal_input/azure_chat_multimodal.py

@@ -13,6 +13,7 @@ def create_sample_image() -> str:
     png_data = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
     return f"data:image/png;base64,{png_data}"
 
+
 async def test_image() -> None:
     """Test image analysis with Azure OpenAI."""
     # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
@@ -37,5 +38,6 @@ async def main() -> None:
     print("Testing image analysis (supported by Chat Completions API)")
     await test_image()
 
+
 if __name__ == "__main__":
     asyncio.run(main())

python/samples/getting_started/purview_agent/sample_purview_agent.py

@@ -20,7 +20,6 @@ Environment variables:
 - PURVIEW_CERT_PASSWORD (optional)
 - PURVIEW_DEFAULT_USER_ID (optional, user ID for Purview evaluation)
 """
-from __future__ import annotations
 
 import asyncio
 import os
@@ -28,18 +27,17 @@ from typing import Any
 
 from agent_framework import AgentRunResponse, ChatAgent, ChatMessage, Role
 from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.microsoft import (
+    PurviewChatPolicyMiddleware,
+    PurviewPolicyMiddleware,
+    PurviewSettings,
+)
 from azure.identity import (
     AzureCliCredential,
     CertificateCredential,
     InteractiveBrowserCredential,
 )
 
-from agent_framework.microsoft import (
-    PurviewPolicyMiddleware,
-    PurviewChatPolicyMiddleware,
-    PurviewSettings,
-)
-
 JOKER_NAME = "Joker"
 JOKER_INSTRUCTIONS = "You are good at telling jokes. Keep responses concise."
 
@@ -96,7 +94,6 @@ class SimpleDictCacheProvider:
             print(f"[CustomCache] Removed key: {key[:50]}...")
 
 
-
 def _get_env(name: str, *, required: bool = True, default: str | None = None) -> str:
     val = os.environ.get(name, default)
     if required and not val:
@@ -176,7 +173,7 @@ async def run_with_chat_middleware() -> None:
 
     deployment = os.environ.get("AZURE_OPENAI_DEPLOYMENT_NAME", default="gpt-4o-mini")
     user_id = os.environ.get("PURVIEW_DEFAULT_USER_ID")
-    
+
     chat_client = AzureOpenAIChatClient(
         deployment_name=deployment,
         endpoint=endpoint,
@@ -216,6 +213,7 @@ async def run_with_chat_middleware() -> None:
     )
     print("Second response (chat middleware):\n", second)
 
+
 async def run_with_custom_cache_provider() -> None:
     """Demonstrate implementing and using a custom cache provider."""
     endpoint = os.environ.get("AZURE_OPENAI_ENDPOINT")
@@ -246,7 +244,7 @@ async def run_with_custom_cache_provider() -> None:
 
     print("-- Custom Cache Provider Path --")
     print("Using SimpleDictCacheProvider")
-    
+
     first: AgentRunResponse = await agent.run(
         ChatMessage(role=Role.USER, text="Tell me a joke about a programmer.", additional_properties={"user_id": user_id})
     )
@@ -256,7 +254,7 @@ async def run_with_custom_cache_provider() -> None:
         ChatMessage(role=Role.USER, text="That's hilarious! One more?", additional_properties={"user_id": user_id})
     )
     print("Second response (custom provider):\n", second)
-    
+
     """Demonstrate using the default built-in cache."""
     endpoint = os.environ.get("AZURE_OPENAI_ENDPOINT")
     if not endpoint:
@@ -286,7 +284,7 @@ async def run_with_custom_cache_provider() -> None:
 
     print("-- Default Cache Path --")
     print("Using default InMemoryCacheProvider with settings-based configuration")
-    
+
     first: AgentRunResponse = await agent.run(
         ChatMessage(role=Role.USER, text="Tell me a joke about AI.", additional_properties={"user_id": user_id})
     )
@@ -300,7 +298,7 @@ async def run_with_custom_cache_provider() -> None:
 
 async def main() -> None:
     print("== Purview Agent Sample (Middleware with Automatic Caching) ==")
-    
+
     try:
         await run_with_agent_middleware()
     except Exception as ex:  # pragma: no cover - demo resilience

python/samples/getting_started/tools/ai_function_from_dict_with_dependency_injection.py

@@ -50,7 +50,7 @@ async def main() -> None:
     # Create the AIFunction tool using dependency injection
     # The 'definition' dictionary contains the serialized tool configuration,
     # while the actual function implementation is provided via dependencies.
-    # 
+    #
     # Dependency structure: {"ai_function": {"name:add_numbers": {"func": func}}}
     # - "ai_function": matches the tool type identifier
     # - "name:add_numbers": instance-specific injection targeting tools with name="add_numbers"

python/samples/getting_started/tools/ai_function_with_approval_and_threads.py

@@ -45,7 +45,7 @@ async def approval_example() -> None:
     # Check for approval requests
     if result.user_input_requests:
         for request in result.user_input_requests:
-            print(f"\nApproval needed:")
+            print("\nApproval needed:")
             print(f"  Function: {request.function_call.name}")
             print(f"  Arguments: {request.function_call.arguments}")
 
@@ -79,12 +79,12 @@ async def rejection_example() -> None:
 
     if result.user_input_requests:
         for request in result.user_input_requests:
-            print(f"\nApproval needed:")
+            print("\nApproval needed:")
             print(f"  Function: {request.function_call.name}")
             print(f"  Arguments: {request.function_call.arguments}")
 
             # User rejects
-            print(f"  Decision: Rejected")
+            print("  Decision: Rejected")
 
             # Send rejection response
             rejection_response = request.create_response(approved=False)

python/samples/semantic-kernel-migration/azure_ai_agent/01_basic_azure_ai_agent.py

@@ -13,32 +13,30 @@ async def run_semantic_kernel() -> None:
     from azure.identity.aio import AzureCliCredential
     from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings
 
-    async with AzureCliCredential() as credential:
-        async with AzureAIAgent.create_client(credential=credential) as client:
-            settings = AzureAIAgentSettings()  # Reads env vars for region/deployment.
-            # SK builds the remote agent definition then wraps it with AzureAIAgent.
-            definition = await client.agents.create_agent(
-                model=settings.model_deployment_name,
-                name="Support",
-                instructions="Answer customer questions in one paragraph.",
-            )
-            agent = AzureAIAgent(client=client, definition=definition)
-            response = await agent.get_response("How do I upgrade my plan?")
-            print("[SK]", response.message.content)
+    async with AzureCliCredential() as credential, AzureAIAgent.create_client(credential=credential) as client:
+        settings = AzureAIAgentSettings()  # Reads env vars for region/deployment.
+        # SK builds the remote agent definition then wraps it with AzureAIAgent.
+        definition = await client.agents.create_agent(
+            model=settings.model_deployment_name,
+            name="Support",
+            instructions="Answer customer questions in one paragraph.",
+        )
+        agent = AzureAIAgent(client=client, definition=definition)
+        response = await agent.get_response("How do I upgrade my plan?")
+        print("[SK]", response.message.content)
 
 
 async def run_agent_framework() -> None:
-    from azure.identity.aio import AzureCliCredential
     from agent_framework.azure import AzureAIAgentClient
+    from azure.identity.aio import AzureCliCredential
 
-    async with AzureCliCredential() as credential:
-        async with AzureAIAgentClient(async_credential=credential).create_agent(
-            name="Support",
-            instructions="Answer customer questions in one paragraph.",
-        ) as agent:
-            # AF client returns an asynchronous context manager for remote agents.
-            reply = await agent.run("How do I upgrade my plan?")
-            print("[AF]", reply.text)
+    async with AzureCliCredential() as credential, AzureAIAgentClient(async_credential=credential).create_agent(
+        name="Support",
+        instructions="Answer customer questions in one paragraph.",
+    ) as agent:
+        # AF client returns an asynchronous context manager for remote agents.
+        reply = await agent.run("How do I upgrade my plan?")
+        print("[AF]", reply.text)
 
 
 async def main() -> None:

python/samples/semantic-kernel-migration/azure_ai_agent/02_azure_ai_agent_with_code_interpreter.py

@@ -13,39 +13,37 @@ async def run_semantic_kernel() -> None:
     from azure.identity.aio import AzureCliCredential
     from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings
 
-    async with AzureCliCredential() as credential:
-        async with AzureAIAgent.create_client(credential=credential) as client:
-            settings = AzureAIAgentSettings()
-            # Register the hosted code interpreter tool with the remote agent.
-            definition = await client.agents.create_agent(
-                model=settings.model_deployment_name,
-                name="Analyst",
-                instructions="Use the code interpreter for numeric work.",
-                tools=[{"type": "code_interpreter"}],
-            )
-            agent = AzureAIAgent(client=client, definition=definition)
-            response = await agent.get_response(
-                "Use Python to compute 42 ** 2 and explain the result.",
-            )
-            print("[SK]", response.message.content)
+    async with AzureCliCredential() as credential, AzureAIAgent.create_client(credential=credential) as client:
+        settings = AzureAIAgentSettings()
+        # Register the hosted code interpreter tool with the remote agent.
+        definition = await client.agents.create_agent(
+            model=settings.model_deployment_name,
+            name="Analyst",
+            instructions="Use the code interpreter for numeric work.",
+            tools=[{"type": "code_interpreter"}],
+        )
+        agent = AzureAIAgent(client=client, definition=definition)
+        response = await agent.get_response(
+            "Use Python to compute 42 ** 2 and explain the result.",
+        )
+        print("[SK]", response.message.content)
 
 
 async def run_agent_framework() -> None:
-    from azure.identity.aio import AzureCliCredential
     from agent_framework.azure import AzureAIAgentClient, HostedCodeInterpreterTool
+    from azure.identity.aio import AzureCliCredential
 
-    async with AzureCliCredential() as credential:
-        async with AzureAIAgentClient(async_credential=credential).create_agent(
-            name="Analyst",
-            instructions="Use the code interpreter for numeric work.",
-            tools=[HostedCodeInterpreterTool()],
-        ) as agent:
-            # HostedCodeInterpreterTool mirrors the built-in Azure AI capability.
-            reply = await agent.run(
-                "Use Python to compute 42 ** 2 and explain the result.",
-                tool_choice="auto",
-            )
-            print("[AF]", reply.text)
+    async with AzureCliCredential() as credential, AzureAIAgentClient(async_credential=credential).create_agent(
+        name="Analyst",
+        instructions="Use the code interpreter for numeric work.",
+        tools=[HostedCodeInterpreterTool()],
+    ) as agent:
+        # HostedCodeInterpreterTool mirrors the built-in Azure AI capability.
+        reply = await agent.run(
+            "Use Python to compute 42 ** 2 and explain the result.",
+            tool_choice="auto",
+        )
+        print("[AF]", reply.text)
 
 
 async def main() -> None:

python/samples/semantic-kernel-migration/azure_ai_agent/03_azure_ai_agent_threads_and_followups.py

@@ -8,53 +8,51 @@ async def run_semantic_kernel() -> None:
     from azure.identity.aio import AzureCliCredential
     from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings, AzureAIAgentThread
 
-    async with AzureCliCredential() as credential:
-        async with AzureAIAgent.create_client(credential=credential) as client:
-            settings = AzureAIAgentSettings()
-            definition = await client.agents.create_agent(
-                model=settings.model_deployment_name,
-                name="Planner",
-                instructions="Track follow-up questions within the same thread.",
-            )
-            agent = AzureAIAgent(client=client, definition=definition)
+    async with AzureCliCredential() as credential, AzureAIAgent.create_client(credential=credential) as client:
+        settings = AzureAIAgentSettings()
+        definition = await client.agents.create_agent(
+            model=settings.model_deployment_name,
+            name="Planner",
+            instructions="Track follow-up questions within the same thread.",
+        )
+        agent = AzureAIAgent(client=client, definition=definition)
 
-            thread: AzureAIAgentThread | None = None
-            # SK returns the updated AzureAIAgentThread on each response.
-            first = await agent.get_response("Outline the onboarding checklist.", thread=thread)
-            thread = first.thread
-            print("[SK][turn1]", first.message.content)
+        thread: AzureAIAgentThread | None = None
+        # SK returns the updated AzureAIAgentThread on each response.
+        first = await agent.get_response("Outline the onboarding checklist.", thread=thread)
+        thread = first.thread
+        print("[SK][turn1]", first.message.content)
 
-            second = await agent.get_response(
-                "Highlight the items that require legal review.",
-                thread=thread,
-            )
-            print("[SK][turn2]", second.message.content)
-            if thread is not None:
-                print("[SK][thread-id]", thread.id)
+        second = await agent.get_response(
+            "Highlight the items that require legal review.",
+            thread=thread,
+        )
+        print("[SK][turn2]", second.message.content)
+        if thread is not None:
+            print("[SK][thread-id]", thread.id)
 
 
 async def run_agent_framework() -> None:
-    from azure.identity.aio import AzureCliCredential
     from agent_framework.azure import AzureAIAgentClient
+    from azure.identity.aio import AzureCliCredential
 
-    async with AzureCliCredential() as credential:
-        async with AzureAIAgentClient(async_credential=credential).create_agent(
-            name="Planner",
-            instructions="Track follow-up questions within the same thread.",
-        ) as agent:
-            thread = agent.get_new_thread()
-            # AF threads are explicit and can be serialized for external storage.
-            first = await agent.run("Outline the onboarding checklist.", thread=thread)
-            print("[AF][turn1]", first.text)
+    async with AzureCliCredential() as credential, AzureAIAgentClient(async_credential=credential).create_agent(
+        name="Planner",
+        instructions="Track follow-up questions within the same thread.",
+    ) as agent:
+        thread = agent.get_new_thread()
+        # AF threads are explicit and can be serialized for external storage.
+        first = await agent.run("Outline the onboarding checklist.", thread=thread)
+        print("[AF][turn1]", first.text)
 
-            second = await agent.run(
-                "Highlight the items that require legal review.",
-                thread=thread,
-            )
-            print("[AF][turn2]", second.text)
+        second = await agent.run(
+            "Highlight the items that require legal review.",
+            thread=thread,
+        )
+        print("[AF][turn2]", second.text)
 
-            serialized = await thread.serialize()
-            print("[AF][thread-json]", serialized)
+        serialized = await thread.serialize()
+        print("[AF][thread-json]", serialized)
 
 
 async def main() -> None: