Python: Add samples syntax checking with pyright

python/AGENTS.md

@@ -72,6 +72,12 @@ from agent_framework.azure import AzureOpenAIChatClient, AzureAIAgentClient
 
 When modifying samples, update associated README files in the same or parent folders.
 
+### Samples Syntax Checking
+
+Run `uv run poe samples-syntax` to check samples for syntax errors and missing imports from `agent_framework`. This uses a relaxed pyright configuration that validates imports without strict type checking.
+
+Some samples depend on external packages (e.g., `azure.ai.agentserver.agentframework`, `microsoft_agents`) that are not installed in the dev environment. These are excluded in `pyrightconfig.samples.json`. When adding or modifying these excluded samples, add them to the exclude list and manually verify they have no import errors from `agent_framework` packages by temporarily removing them from the exclude list and running the check.
+
 ## Package Documentation
 
 ### Core

python/pyproject.toml

@@ -227,6 +227,7 @@ format.ref = "fmt"
 lint = "python run_tasks_in_packages_if_exists.py lint"
 pyright = "python run_tasks_in_packages_if_exists.py pyright"
 mypy = "python run_tasks_in_packages_if_exists.py mypy"
+samples-syntax = "pyright -p pyrightconfig.samples.json --warnings"
 typing = ["pyright", "mypy"]
 # cleaning
 clean-dist-packages = "python run_tasks_in_packages_if_exists.py clean-dist"
@@ -238,7 +239,7 @@ build-meta = "python -m flit build"
 build = ["build-packages", "build-meta"]
 publish = "uv publish"
 # combined checks
-check = ["fmt", "lint", "pyright", "mypy", "test", "markdown-code-lint"]
+check = ["fmt", "lint", "pyright", "mypy", "samples-syntax", "test", "markdown-code-lint"]
 
 [tool.poe.tasks.all-tests-cov]
 cmd = """
@@ -323,7 +324,8 @@ sequence = [
     { ref = "fmt" },
     { ref = "lint" },
     { ref = "pre-commit-pyright ${files}" },
-    { ref = "pre-commit-markdown-code-lint ${files}" }
+    { ref = "pre-commit-markdown-code-lint ${files}" },
+    { ref = "samples-syntax" }
 ]
 args = [{ name = "files", default = ".", positional = true, multiple = true }]
 

python/pyrightconfig.samples.json

@@ -0,0 +1,13 @@
+{
+    "include": ["samples"],
+    "exclude": [
+        "**/autogen/**",
+        "**/autogen-migration/**",
+        "**/semantic-kernel-migration/**",
+        "**/demos/**",
+        "**/agent_with_foundry_tracing.py"
+    ],
+    "typeCheckingMode": "off",
+    "reportMissingImports": "error",
+    "reportAttributeAccessIssue": "error"
+}

python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py

@@ -55,7 +55,7 @@ async def run_autogen() -> None:
 
 async def run_agent_framework() -> None:
     """Agent Framework's SequentialBuilder for sequential agent orchestration."""
-    from agent_framework import SequentialBuilder
+    from agent_framework_orchestrations import SequentialBuilder
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")

python/samples/autogen-migration/orchestrations/02_selector_group_chat.py

@@ -61,7 +61,7 @@ async def run_autogen() -> None:
 
 async def run_agent_framework() -> None:
     """Agent Framework's GroupChatBuilder with LLM-based speaker selection."""
-    from agent_framework import GroupChatBuilder
+    from agent_framework_orchestrations import GroupChatBuilder
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")

python/samples/autogen-migration/orchestrations/03_swarm.py

@@ -7,7 +7,8 @@
 
 import asyncio
 
-from agent_framework import AgentResponseUpdate, HandoffAgentUserRequest, WorkflowOutputEvent
+from agent_framework import AgentResponseUpdate, WorkflowOutputEvent
+from agent_framework_orchestrations import HandoffAgentUserRequest
 
 
 async def run_autogen() -> None:
@@ -98,11 +99,11 @@ async def run_autogen() -> None:
 async def run_agent_framework() -> None:
     """Agent Framework's HandoffBuilder for agent coordination."""
     from agent_framework import (
-        HandoffBuilder,
         RequestInfoEvent,
         WorkflowRunState,
         WorkflowStatusEvent,
     )
+    from agent_framework_orchestrations import HandoffBuilder
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")

python/samples/autogen-migration/orchestrations/04_magentic_one.py

@@ -12,10 +12,9 @@
 from agent_framework import (
     AgentResponseUpdate,
     ChatMessage,
-    MagenticOrchestratorEvent,
-    MagenticProgressLedger,
     WorkflowOutputEvent,
 )
+from agent_framework_orchestrations import MagenticOrchestratorEvent, MagenticProgressLedger
 
 
 async def run_autogen() -> None:
@@ -67,7 +66,7 @@ async def run_autogen() -> None:
 
 async def run_agent_framework() -> None:
     """Agent Framework's MagenticBuilder for orchestrated collaboration."""
-    from agent_framework import MagenticBuilder
+    from agent_framework_orchestrations import MagenticBuilder
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
@@ -123,7 +122,7 @@ async def run_agent_framework() -> None:
             print(event.data, end="", flush=True)
 
         elif isinstance(event, MagenticOrchestratorEvent):
-            print(f"\n[Magentic Orchestrator Event] Type: {event.event_type.name}")
+            print(f"\n[Magentic Orchestrator Event] Type: {event.event_type.name}")  # type: ignore[union-attr]
             if isinstance(event.data, ChatMessage):
                 print(f"Please review the plan:\n{event.data.text}")
             elif isinstance(event.data, MagenticProgressLedger):

python/samples/autogen-migration/single_agent/04_agent_as_tool.py

@@ -48,7 +48,7 @@ async def run_autogen() -> None:
 
 async def run_agent_framework() -> None:
     """Agent Framework's as_tool() for hierarchical agents with streaming."""
-    from agent_framework import FunctionCallContent, FunctionResultContent
+    from agent_framework import Content
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
@@ -78,7 +78,7 @@ async def run_agent_framework() -> None:
     print("[Agent Framework]")
 
     # Track accumulated function calls (they stream in incrementally)
-    accumulated_calls: dict[str, FunctionCallContent] = {}
+    accumulated_calls: dict[str, Content] = {}
 
     async for chunk in coordinator.run("Create a tagline for a coffee shop", stream=True):
         # Stream text tokens
@@ -88,7 +88,7 @@ async def run_agent_framework() -> None:
         # Process streaming function calls and results
         if chunk.contents:
             for content in chunk.contents:
-                if isinstance(content, FunctionCallContent):
+                if content.type == "function_call":
                     # Accumulate function call content as it streams in
                     call_id = content.call_id
                     if call_id in accumulated_calls:
@@ -105,7 +105,7 @@ async def run_agent_framework() -> None:
                     current_args = accumulated_calls[call_id].arguments
                     print(f"  Arguments: {current_args}", flush=True)
 
-                elif isinstance(content, FunctionResultContent):
+                elif content.type == "function_result":
                     # Tool result - shows writer's response
                     result_text = content.result if isinstance(content.result, str) else str(content.result)
                     if result_text.strip():

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

@@ -18,7 +18,7 @@
 import uvicorn
 
 # Agent Framework imports
-from agent_framework import AgentResponseUpdate, ChatAgent, ChatMessage, FunctionResultContent, Role, tool
+from agent_framework import AgentResponseUpdate, ChatAgent, ChatMessage, tool
 from agent_framework.azure import AzureOpenAIChatClient
 
 # Agent Framework ChatKit integration
@@ -332,7 +332,6 @@ async def respond(
         runs the agent, converts the response back to ChatKit events using stream_agent_response,
         and creates interactive weather widgets when weather data is queried.
         """
-        from agent_framework import FunctionResultContent
 
         if input_user_message is None:
             logger.debug("Received None user message, skipping")
@@ -375,7 +374,7 @@ async def intercept_stream() -> AsyncIterator[AgentResponseUpdate]:
                     # Check for function results in the update
                     if update.contents:
                         for content in update.contents:
-                            if isinstance(content, FunctionResultContent):
+                            if content.type == "function_result":
                                 result = content.result
 
                                 # Check if it's a WeatherResponse (string subclass with weather_data attribute)
@@ -472,7 +471,7 @@ async def intercept_stream() -> AsyncIterator[AgentResponseUpdate]:
                     # Check for function results in the update
                     if update.contents:
                         for content in update.contents:
-                            if isinstance(content, FunctionResultContent):
+                            if content.type == "function_result":
                                 result = content.result
 
                                 # Check if it's a WeatherResponse (string subclass with weather_data attribute)
@@ -585,7 +584,7 @@ async def upload_file(attachment_id: str, file: UploadFile = File(...)):
         attachment = await data_store.load_attachment(attachment_id, {"user_id": DEFAULT_USER_ID})
 
         # Clear the upload_url since upload is complete
-        attachment.upload_url = None
+        attachment.upload_url = None  # type: ignore[union-attr]
 
         # Save the updated attachment back to the store
         await data_store.save_attachment(attachment, {"user_id": DEFAULT_USER_ID})

python/samples/demos/hosted_agents/agents_in_workflow/main.py

@@ -1,6 +1,6 @@
 # Copyright (c) Microsoft. All rights reserved.
 
-from agent_framework import ConcurrentBuilder
+from agent_framework_orchestrations import ConcurrentBuilder
 from agent_framework.azure import AzureOpenAIChatClient
 from azure.ai.agentserver.agentframework import from_agent_framework
 from azure.identity import DefaultAzureCredential  # pyright: ignore[reportUnknownVariableType]

python/samples/demos/workflow_evaluation/create_workflow.py

@@ -48,9 +48,9 @@
 from agent_framework import (
     AgentExecutorResponse,
     AgentResponseUpdate,
-    AgentRunUpdateEvent,
     ChatMessage,
     Executor,
+    ExecutorEvent,
     WorkflowBuilder,
     WorkflowContext,
     WorkflowOutputEvent,
@@ -364,7 +364,7 @@ async def _process_workflow_events(events, conversation_ids, response_ids):
                 output_str = str(event.data).encode("ascii", "replace").decode("ascii")
                 print(f"\nWorkflow Output: {output_str}\n")
 
-        elif isinstance(event, AgentRunUpdateEvent):
+        elif isinstance(event, ExecutorEvent):
             _track_agent_ids(event, event.executor_id, response_ids, conversation_ids)
 
     return workflow_output
@@ -379,14 +379,14 @@ def _track_agent_ids(event, agent, response_ids, conversation_ids):
             raw = event.data.raw_representation
 
             # Try conversation_id directly on raw representation
-            if hasattr(raw, "conversation_id") and raw.conversation_id:
+            if hasattr(raw, "conversation_id") and raw.conversation_id:  # type: ignore[union-attr]
                 # Only add if not already in the list
-                if raw.conversation_id not in conversation_ids[agent]:
-                    conversation_ids[agent].append(raw.conversation_id)
+                if raw.conversation_id not in conversation_ids[agent]:  # type: ignore[union-attr]
+                    conversation_ids[agent].append(raw.conversation_id)  # type: ignore[union-attr]
 
             # Extract response_id from the OpenAI event (available from first event)
-            if hasattr(raw, "raw_representation") and raw.raw_representation:
-                openai_event = raw.raw_representation
+            if hasattr(raw, "raw_representation") and raw.raw_representation:  # type: ignore[union-attr]
+                openai_event = raw.raw_representation  # type: ignore[union-attr]
 
                 # Check if event has response object with id
                 if hasattr(openai_event, "response") and hasattr(openai_event.response, "id"):

python/samples/getting_started/agents/anthropic/anthropic_advanced.py

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from agent_framework import HostedMCPTool, HostedWebSearchTool, TextReasoningContent, UsageContent
+from agent_framework import Content, HostedMCPTool, HostedWebSearchTool
 from agent_framework.anthropic import AnthropicChatOptions, AnthropicClient
 
 """
@@ -40,9 +40,9 @@ async def main() -> None:
     print("Agent: ", end="", flush=True)
     async for chunk in agent.run(query, stream=True):
         for content in chunk.contents:
-            if isinstance(content, TextReasoningContent):
+            if content.type == "text_reasoning":
                 print(f"\033[32m{content.text}\033[0m", end="", flush=True)
-            if isinstance(content, UsageContent):
+            if content.type == "usage":
                 print(f"\n\033[34m[Usage so far: {content.usage_details}]\033[0m\n", end="", flush=True)
         if chunk.text:
             print(chunk.text, end="", flush=True)

python/samples/getting_started/agents/anthropic/anthropic_foundry.py

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from agent_framework import HostedMCPTool, HostedWebSearchTool, TextReasoningContent, UsageContent
+from agent_framework import Content, HostedMCPTool, HostedWebSearchTool
 from agent_framework.anthropic import AnthropicClient
 from anthropic import AsyncAnthropicFoundry
 
@@ -51,9 +51,9 @@ async def main() -> None:
     print("Agent: ", end="", flush=True)
     async for chunk in agent.run(query, stream=True):
         for content in chunk.contents:
-            if isinstance(content, TextReasoningContent):
+            if content.type == "text_reasoning":
                 print(f"\033[32m{content.text}\033[0m", end="", flush=True)
-            if isinstance(content, UsageContent):
+            if content.type == "usage":
                 print(f"\n\033[34m[Usage so far: {content.usage_details}]\033[0m\n", end="", flush=True)
         if chunk.text:
             print(chunk.text, end="", flush=True)

python/samples/getting_started/agents/anthropic/anthropic_skills.py

@@ -4,7 +4,7 @@
 import logging
 from pathlib import Path
 
-from agent_framework import HostedCodeInterpreterTool, HostedFileContent
+from agent_framework import Content, HostedCodeInterpreterTool
 from agent_framework.anthropic import AnthropicChatOptions, AnthropicClient
 
 logger = logging.getLogger(__name__)
@@ -52,7 +52,7 @@ async def main() -> None:
     query = "Create a presentation about renewable energy with 5 slides"
     print(f"User: {query}")
     print("Agent: ", end="", flush=True)
-    files: list[HostedFileContent] = []
+    files: list[Content] = []
     async for chunk in agent.run(query, stream=True):
         for content in chunk.contents:
             match content.type: