Python: Fix sample bugs: incorrect API params, wrong client types, and invalid options (#4983)

giles17 · Copilot · web-flow · commit 7c2dae8855b7 · 2026-03-31T16:58:51.000Z
* Fix sample bugs: incorrect API params, wrong client types, and invalid options

- typed_options.py: Fix AnthropicClient model-&gt;model_id, wrap raw strings in Message objects for get_response(), fix reasoning_effort-&gt;reasoning dict, fix budget_tokens minimum (1024), use OpenAIChatClient not FoundryChatClient, remove unused import

- client_reasoning.py: Fix deprecated model_id to model param

- client_with_hosted_mcp.py: Remove invalid store=True kwarg from Agent.run()

- code_defined_skill.py: Fix precision kwarg to use function_invocation_kwargs

- Various other samples: Fix deprecated API usage and incorrect params

Co-authored-by: Copilot &lt;223556219+Copilot@users.noreply.github.com&gt;

* Address PR review comments

- client_with_hosted_mcp.py: Fix remaining store=True kwarg on line 68 to use options dict

- client_with_session.py: Change store=True to store=False to match in-memory persistence demo intent

- typed_options.py: Remove non-existent import and model key from docstring example

Co-authored-by: Copilot &lt;223556219+Copilot@users.noreply.github.com&gt;

* new sample fixes

---------

Co-authored-by: Copilot &lt;223556219+Copilot@users.noreply.github.com&gt;
diff --git a/python/samples/02-agents/background_responses.py b/python/samples/02-agents/background_responses.py
@@ -3,7 +3,7 @@
 import asyncio
 
 from agent_framework import Agent
-from agent_framework.openai import OpenAIResponsesClient
+from agent_framework.openai import OpenAIChatClient
 from dotenv import load_dotenv
 
 # Load environment variables from .env file
@@ -29,7 +29,7 @@
 agent = Agent(
     name="researcher",
     instructions="You are a helpful research assistant. Be concise.",
-    client=OpenAIResponsesClient(model="o3"),
+    client=OpenAIChatClient(model="o3"),
 )
 
 
diff --git a/python/samples/02-agents/chat_client/chat_response_cancellation.py b/python/samples/02-agents/chat_client/chat_response_cancellation.py
@@ -4,6 +4,7 @@
 
 from agent_framework import Message
 from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
 from dotenv import load_dotenv
 
 # Load environment variables from .env file
@@ -26,7 +27,7 @@ async def main() -> None:
     - OpenAI model ID: Use "model_id" parameter or "OPENAI_MODEL" environment variable
     - OpenAI API key: Use "api_key" parameter or "OPENAI_API_KEY" environment variable
     """
-    client = FoundryChatClient()
+    client = FoundryChatClient(credential=AzureCliCredential())
 
     try:
         task = asyncio.create_task(
diff --git a/python/samples/02-agents/providers/anthropic/anthropic_basic.py b/python/samples/02-agents/providers/anthropic/anthropic_basic.py
@@ -35,7 +35,7 @@ async def non_streaming_example() -> None:
     print("=== Non-streaming Response Example ===")
 
     agent = Agent(
-        client=AnthropicClient(),
+        client=AnthropicClient(model_id="claude-sonnet-4-5-20250929"),
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,
@@ -52,7 +52,7 @@ async def streaming_example() -> None:
     print("=== Streaming Response Example ===")
 
     agent = Agent(
-        client=AnthropicClient(),
+        client=AnthropicClient(model_id="claude-sonnet-4-5-20250929"),
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,
diff --git a/python/samples/02-agents/providers/custom/custom_agent.py b/python/samples/02-agents/providers/custom/custom_agent.py
@@ -51,9 +51,9 @@ def __init__(
         super().__init__(
             name=name,
             description=description,
-            echo_prefix=echo_prefix,  # type: ignore
             **kwargs,
         )
+        self.echo_prefix = echo_prefix
 
     def run(
         self,
diff --git a/python/samples/02-agents/providers/openai/client_reasoning.py b/python/samples/02-agents/providers/openai/client_reasoning.py
@@ -25,7 +25,7 @@
 
 
 agent = Agent(
-    client=OpenAIChatClient[OpenAIChatOptions](model_id="gpt-5"),
+    client=OpenAIChatClient[OpenAIChatOptions](model="gpt-5"),
     name="MathHelper",
     instructions="You are a personal math tutor. When asked a math question, "
     "reason over how best to approach the problem and share your thought process.",
diff --git a/python/samples/02-agents/providers/openai/client_with_hosted_mcp.py b/python/samples/02-agents/providers/openai/client_with_hosted_mcp.py
@@ -50,7 +50,7 @@ async def handle_approvals_with_session(query: str, agent: "SupportsAgentRun", s
     """Here we let the session deal with the previous responses, and we just rerun with the approval."""
     from agent_framework import Message
 
-    result = await agent.run(query, session=session, store=True)
+    result = await agent.run(query, session=session, options={"store": True})
     while len(result.user_input_requests) > 0:
         new_input: list[Any] = []
         for user_input_needed in result.user_input_requests:
@@ -65,7 +65,7 @@ async def handle_approvals_with_session(query: str, agent: "SupportsAgentRun", s
                     contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")],
                 )
             )
-        result = await agent.run(new_input, session=session, store=True)
+        result = await agent.run(new_input, session=session, options={"store": True})
     return result
 
 
diff --git a/python/samples/02-agents/providers/openai/client_with_session.py b/python/samples/02-agents/providers/openai/client_with_session.py
@@ -75,19 +75,19 @@ async def example_with_session_persistence_in_memory() -> None:
     # First conversation
     query1 = "What's the weather like in Tokyo?"
     print(f"User: {query1}")
-    result1 = await agent.run(query1, session=session, store=False)
+    result1 = await agent.run(query1, session=session, options={"store": False})
     print(f"Agent: {result1.text}")
 
     # Second conversation using the same session - maintains context
     query2 = "How about London?"
     print(f"\nUser: {query2}")
-    result2 = await agent.run(query2, session=session, store=False)
+    result2 = await agent.run(query2, session=session, options={"store": False})
     print(f"Agent: {result2.text}")
 
     # Third conversation - agent should remember both previous cities
     query3 = "Which of the cities I asked about has better weather?"
     print(f"\nUser: {query3}")
-    result3 = await agent.run(query3, session=session, store=False)
+    result3 = await agent.run(query3, session=session, options={"store": False})
     print(f"Agent: {result3.text}")
     print("Note: The agent remembers context from previous messages in the same session.\n")
 
diff --git a/python/samples/02-agents/skills/code_defined_skill/code_defined_skill.py b/python/samples/02-agents/skills/code_defined_skill/code_defined_skill.py
@@ -151,7 +151,7 @@ async def main() -> None:
         print("-" * 60)
         response = await agent.run(
             "How many kilometers is a marathon (26.2 miles)? And how many pounds is 75 kilograms?",
-            precision=2,
+            function_invocation_kwargs={"precision": 2},
         )
         print(f"Agent: {response}\n")
 
diff --git a/python/samples/02-agents/tools/agent_as_tool_with_session_propagation.py b/python/samples/02-agents/tools/agent_as_tool_with_session_propagation.py
@@ -4,7 +4,7 @@
 from collections.abc import Awaitable, Callable
 
 from agent_framework import Agent, AgentContext, AgentSession, FunctionInvocationContext, tool
-from agent_framework.openai import OpenAIResponsesClient
+from agent_framework.openai import OpenAIChatClient
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -63,7 +63,7 @@ def recall_findings(ctx: FunctionInvocationContext) -> str:
 async def main() -> None:
     print("=== Agent-as-Tool: Session Propagation ===\n")
 
-    client = OpenAIResponsesClient()
+    client = OpenAIChatClient()
 
     research_agent = Agent(
         client=client,
diff --git a/python/samples/02-agents/tools/control_total_tool_executions.py b/python/samples/02-agents/tools/control_total_tool_executions.py
@@ -4,7 +4,7 @@
 from typing import Annotated
 
 from agent_framework import Agent, tool
-from agent_framework.openai import OpenAIResponsesClient
+from agent_framework.openai import OpenAIChatClient
 from dotenv import load_dotenv
 
 # Load environment variables from .env file
@@ -81,7 +81,7 @@ async def scenario_max_iterations():
     print("Scenario 1: max_iterations — limit LLM roundtrips")
     print("=" * 60)
 
-    client = OpenAIResponsesClient()
+    client = OpenAIChatClient()
 
     # 1. Set max_iterations to 3 — the tool loop will run at most 3 roundtrips
     #    to the model before forcing a text response.
@@ -116,7 +116,7 @@ async def scenario_max_function_calls():
     print("Scenario 2: max_function_calls — limit total tool executions")
     print("=" * 60)
 
-    client = OpenAIResponsesClient()
+    client = OpenAIChatClient()
 
     # 1. Allow many iterations but cap total function calls to 4.
     #    If the model requests 3 parallel searches per iteration, after 2
@@ -158,7 +158,7 @@ async def scenario_max_invocations():
     print("=" * 60)
 
     agent = Agent(
-        client=OpenAIResponsesClient(),
+        client=OpenAIChatClient(),
         name="APIAgent",
         instructions="Use call_expensive_api when asked to analyze something.",
         tools=[call_expensive_api],
@@ -214,7 +214,7 @@ def _do_lookup(query: Annotated[str, "Search query."]) -> str:
     agent_a_lookup = tool(name="lookup", approval_mode="never_require", max_invocations=2)(_do_lookup)
     agent_b_lookup = tool(name="lookup", approval_mode="never_require", max_invocations=5)(_do_lookup)
 
-    client = OpenAIResponsesClient()
+    client = OpenAIChatClient()
     agent_a = Agent(
         client=client,
         name="AgentA",
@@ -259,7 +259,7 @@ async def scenario_combined():
     print("Scenario 5: Combined — all mechanisms together")
     print("=" * 60)
 
-    client = OpenAIResponsesClient()
+    client = OpenAIChatClient()
 
     # 1. Configure the client with both iteration and function call limits.
     client.function_invocation_configuration["max_iterations"] = 5  # max 5 LLM roundtrips
diff --git a/python/samples/02-agents/tools/function_tool_recover_from_failures.py b/python/samples/02-agents/tools/function_tool_recover_from_failures.py
@@ -4,7 +4,7 @@
 from typing import Annotated
 
 from agent_framework import Agent, tool
-from agent_framework.openai import OpenAIResponsesClient
+from agent_framework.openai import OpenAIChatClient
 from dotenv import load_dotenv
 
 # Load environment variables from .env file
@@ -46,7 +46,7 @@ def safe_divide(
 async def main():
     # tools = Tools()
     agent = Agent(
-        client=OpenAIResponsesClient(),
+        client=OpenAIChatClient(),
         name="ToolAgent",
         instructions="Use the provided tools.",
         tools=[greet, safe_divide],
diff --git a/python/samples/02-agents/tools/function_tool_with_approval.py b/python/samples/02-agents/tools/function_tool_with_approval.py
@@ -5,7 +5,7 @@
 from typing import TYPE_CHECKING, Annotated, Any
 
 from agent_framework import Agent, AgentResponse, Message, tool
-from agent_framework.openai import OpenAIResponsesClient
+from agent_framework.openai import OpenAIChatClient
 from dotenv import load_dotenv
 
 if TYPE_CHECKING:
@@ -134,7 +134,7 @@ async def run_weather_agent_with_approval(stream: bool) -> None:
     print(f"\n=== Weather Agent with Approval Required ({'Streaming' if stream else 'Non-Streaming'}) ===\n")
 
     async with Agent(
-        client=OpenAIResponsesClient(),
+        client=OpenAIChatClient(),
         name="WeatherAgent",
         instructions=("You are a helpful weather assistant. Use the get_weather tool to provide weather information."),
         tools=[get_weather, get_weather_detail],
diff --git a/python/samples/02-agents/typed_options.py b/python/samples/02-agents/typed_options.py
@@ -1,11 +1,9 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
-from typing import Literal
 
 from agent_framework import Agent, Message
 from agent_framework.anthropic import AnthropicClient
-from agent_framework.foundry import FoundryChatClient
 from agent_framework.openai import OpenAIChatClient, OpenAIChatOptions
 from dotenv import load_dotenv
 
@@ -46,10 +44,10 @@ async def demo_anthropic_chat_client() -> None:
     response = await client.get_response(
         [Message("user", text="What is the capital of France?")],
         options={
-            "temperature": 0.5,
-            "max_tokens": 1000,
+            "temperature": 1,  # Must be 1 when thinking is enabled
+            "max_tokens": 2048,
             # Anthropic-specific options:
-            "thinking": {"type": "enabled", "budget_tokens": 1000},
+            "thinking": {"type": "enabled", "budget_tokens": 1024},
             # "top_k": 40,  # <-- Uncomment for Anthropic-specific option
         },
     )
@@ -91,18 +89,12 @@ class OpenAIReasoningChatOptions(OpenAIChatOptions, total=False):
     Examples:
         .. code-block:: python
 
-            from agent_framework.openai import OpenAIReasoningChatOptions
-
             options: OpenAIReasoningChatOptions = {
-                "model_id": "o3",
-                "reasoning_effort": "high",
+                "reasoning": {"effort": "high"},
                 "max_tokens": 4096,
             }
     """
 
-    # Reasoning-specific parameters
-    reasoning_effort: Literal["none", "minimal", "low", "medium", "high", "xhigh"]
-
     # Unsupported parameters for reasoning models (override with None)
     temperature: None
     top_p: None
@@ -129,7 +121,7 @@ async def demo_openai_chat_client_reasoning_models() -> None:
             "max_tokens": 100,
             "allow_multiple_tool_calls": True,
             # OpenAI-specific options work:
-            "reasoning_effort": "medium",
+            "reasoning": {"effort": "medium"},
             # Unsupported options are caught by type checker (uncomment to see):
             # "temperature": 0.7,
             # "random": 234,
@@ -149,15 +141,15 @@ async def demo_openai_agent() -> None:
     # or on the client when constructing the client instance:
     #   client = OpenAIChatClient[OpenAIReasoningChatOptions]()
     agent = Agent[OpenAIReasoningChatOptions](
-        client=FoundryChatClient(model="o3"),
+        client=OpenAIChatClient(model="o3"),
         name="weather-assistant",
         instructions="You are a helpful assistant. Answer concisely.",
         # Options can be set at construction time
         default_options={
             "max_tokens": 100,
             "allow_multiple_tool_calls": True,
             # OpenAI-specific options work:
-            "reasoning_effort": "medium",
+            "reasoning": {"effort": "medium"},
             # Unsupported options are caught by type checker (uncomment to see):
             # "temperature": 0.7,
             # "random": 234,
@@ -168,7 +160,7 @@ async def demo_openai_agent() -> None:
     response = await agent.run(
         "What is 25 * 47?",
         options={
-            "reasoning_effort": "high",  # Override for a run
+            "reasoning": {"effort": "high"},  # Override for a run
         },
     )
 

Original file line number	Diff line number	Diff line change
`@@ -50,7 +50,7 @@ async def handle_approvals_with_session(query: str, agent: "SupportsAgentRun", s`
`50`	`50`	`"""Here we let the session deal with the previous responses, and we just rerun with the approval."""`
`51`	`51`	`from agent_framework import Message`
`52`	`52`
`53`		`- result = await agent.run(query, session=session, store=True)`
	`53`	`+ result = await agent.run(query, session=session, options={"store": True})`
`54`	`54`	`while len(result.user_input_requests) > 0:`
`55`	`55`	`new_input: list[Any] = []`
`56`	`56`	`for user_input_needed in result.user_input_requests:`
`@@ -65,7 +65,7 @@ async def handle_approvals_with_session(query: str, agent: "SupportsAgentRun", s`
`65`	`65`	`contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")],`
`66`	`66`	`)`
`67`	`67`	`)`
`68`		`- result = await agent.run(new_input, session=session, store=True)`
	`68`	`+ result = await agent.run(new_input, session=session, options={"store": True})`
`69`	`69`	`return result`
`70`	`70`
`71`	`71`
Original file line number	Diff line number	Diff line change
`@@ -151,7 +151,7 @@ async def main() -> None:`
`151`	`151`	`print("-" * 60)`
`152`	`152`	`response = await agent.run(`
`153`	`153`	`"How many kilometers is a marathon (26.2 miles)? And how many pounds is 75 kilograms?",`
`154`		`- precision=2,`
	`154`	`+ function_invocation_kwargs={"precision": 2},`
`155`	`155`	`)`
`156`	`156`	`print(f"Agent: {response}\n")`
`157`	`157`