Python: [BREAKING] update to v1.0.0 (#5062)

* updates to final deprecated pieces and versions

* fix mypy

* fix readme links

python/samples/02-agents/providers/anthropic/anthropic_advanced.py

@@ -1,8 +1,9 @@
 # Copyright (c) Microsoft. All rights reserved.
 import asyncio
+import os
 
 from agent_framework import Agent
-from agent_framework.anthropic import AnthropicChatOptions, AnthropicClient
+from agent_framework.anthropic import AnthropicClient
 from dotenv import load_dotenv
 
 # Load environment variables from .env file
@@ -15,12 +16,20 @@ This sample demonstrates using Anthropic with:
 - Setting up an Anthropic-based agent with hosted tools.
 - Using the `thinking` feature.
 - Displaying both thinking and usage information during streaming responses.
+
+Environment variables:
+    ANTHROPIC_API_KEY    — Your Anthropic API key
+    ANTHROPIC_CHAT_MODEL — The Anthropic model to use (e.g., "claude-sonnet-4-6")
+
 """
 
 
 async def main() -> None:
     """Example of streaming response (get results as they are generated)."""
-    client = AnthropicClient[AnthropicChatOptions]()
+    client = AnthropicClient(
+        api_key=os.getenv("ANTHROPIC_API_KEY"),
+        model=os.getenv("ANTHROPIC_CHAT_MODEL"),
+    )
 
     # Create MCP tool configuration using instance method
     mcp_tool = client.get_mcp_tool(

python/samples/02-agents/providers/azure/openai_client_with_session.py

@@ -76,19 +76,19 @@ 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")
 
@@ -114,7 +114,7 @@ async def example_with_existing_session_id() -> None:
 
     query1 = "What's the weather in Paris?"
     print(f"User: {query1}")
-    result1 = await agent.run(query1, session=session)
+    result1 = await agent.run(query1, session=session, options={"store": False})
     print(f"Agent: {result1.text}")
 
     # The session ID is set after the first response

python/samples/02-agents/providers/foundry/README.md

@@ -9,7 +9,6 @@ This folder contains Azure AI Foundry and Foundry Local samples for Agent Framew
 | [`foundry_agent_basic.py`](foundry_agent_basic.py) | Foundry Agent basic example |
 | [`foundry_agent_custom_client.py`](foundry_agent_custom_client.py) | Foundry Agent custom client configuration |
 | [`foundry_agent_hosted.py`](foundry_agent_hosted.py) | Foundry Agent for hosted agents |
-| [`foundry_agent_with_env_vars.py`](foundry_agent_with_env_vars.py) | Foundry Agent using environment variables |
 | [`foundry_agent_with_function_tools.py`](foundry_agent_with_function_tools.py) | Foundry Agent with local function tools |
 
 ## FoundryChatClient Samples

python/samples/02-agents/providers/foundry/foundry_agent_custom_client.py

@@ -1,11 +1,13 @@
 # Copyright (c) Microsoft. All rights reserved.
-
 import asyncio
+import os
 
 from agent_framework import Agent
 from agent_framework.foundry import FoundryAgent, RawFoundryAgentChatClient
 from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
 
+load_dotenv()
 """
 Foundry Agent — Custom client configuration
 
@@ -25,9 +27,9 @@ Environment variables:
 async def main() -> None:
     # Option 1: Default — full middleware on both agent and client
     agent = FoundryAgent(
-        project_endpoint="https://your-project.services.ai.azure.com",
-        agent_name="my-agent",
-        agent_version="1.0",
+        project_endpoint=os.getenv("FOUNDRY_PROJECT_ENDPOINT"),
+        agent_name=os.getenv("FOUNDRY_AGENT_NAME"),
+        agent_version=os.getenv("FOUNDRY_AGENT_VERSION"),
         credential=AzureCliCredential(),
     )
     result = await agent.run("Hello from the default setup!")
@@ -35,9 +37,9 @@ async def main() -> None:
 
     # Option 2: Raw client — no client-level middleware (agent middleware still active)
     agent_raw_client = FoundryAgent(
-        project_endpoint="https://your-project.services.ai.azure.com",
-        agent_name="my-agent",
-        agent_version="1.0",
+        project_endpoint=os.getenv("FOUNDRY_PROJECT_ENDPOINT"),
+        agent_name=os.getenv("FOUNDRY_AGENT_NAME"),
+        agent_version=os.getenv("FOUNDRY_AGENT_VERSION"),
         credential=AzureCliCredential(),
         client_type=RawFoundryAgentChatClient,
     )
@@ -47,9 +49,9 @@ async def main() -> None:
     # Option 3: Composition — use Agent(client=...) directly
     # this will not run the checks that the `FoundryAgent` does on things like tools.
     client = RawFoundryAgentChatClient(
-        project_endpoint="https://your-project.services.ai.azure.com",
-        agent_name="my-agent",
-        agent_version="1.0",
+        project_endpoint=os.getenv("FOUNDRY_PROJECT_ENDPOINT"),
+        agent_name=os.getenv("FOUNDRY_AGENT_NAME"),
+        agent_version=os.getenv("FOUNDRY_AGENT_VERSION"),
         credential=AzureCliCredential(),
     )
     agent_composed = Agent(client=client)

python/samples/02-agents/providers/foundry/foundry_agent_hosted.py

@@ -1,9 +1,13 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
+import os
 
 from agent_framework.foundry import FoundryAgent
 from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+load_dotenv()
 
 """
 Foundry Agent — Connect to a HostedAgent (no version needed)
@@ -20,8 +24,8 @@ Environment variables:
 async def main() -> None:
     # HostedAgents don't need agent_version
     agent = FoundryAgent(
-        project_endpoint="https://your-project.services.ai.azure.com",
-        agent_name="my-hosted-agent",
+        project_endpoint=os.getenv("FOUNDRY_PROJECT_ENDPOINT"),
+        agent_name=os.getenv("FOUNDRY_AGENT_NAME"),
         credential=AzureCliCredential(),
     )
 

python/samples/02-agents/providers/foundry/foundry_agent_with_env_vars.py

@@ -1,40 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-import asyncio
-import os
-
-from agent_framework.foundry import FoundryAgent
-from azure.identity import AzureCliCredential
-
-"""
-Foundry Agent with Environment Variables
-
-This sample shows the recommended pattern for advanced samples that use
-environment variables for configuration.
-
-Environment variables:
-    FOUNDRY_PROJECT_ENDPOINT — Azure AI Foundry project endpoint
-    FOUNDRY_AGENT_NAME       — Name of the agent in Foundry
-    FOUNDRY_AGENT_VERSION    — Version of the agent (optional, for PromptAgents)
-"""
-
-
-async def main() -> None:
-    agent = FoundryAgent(
-        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
-        agent_name=os.environ["FOUNDRY_AGENT_NAME"],
-        agent_version=os.environ.get("FOUNDRY_AGENT_VERSION"),
-        credential=AzureCliCredential(),
-    )
-
-    session = agent.create_session()
-
-    result = await agent.run("Hello! My name is Alice.", session=session)
-    print(f"Agent: {result}\n")
-
-    result = await agent.run("What's my name?", session=session)
-    print(f"Agent: {result}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

python/samples/02-agents/providers/foundry/foundry_agent_with_function_tools.py

@@ -1,13 +1,14 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
+import os
 from typing import Annotated
 
-from agent_framework import tool
 from agent_framework.foundry import FoundryAgent
 from azure.identity import AzureCliCredential
-from pydantic import Field
+from dotenv import load_dotenv
 
+load_dotenv()
 """
 Foundry Agent with Local Function Tools
 
@@ -25,9 +26,8 @@ Environment variables:
 """
 
 
-@tool(approval_mode="never_require")
 def get_weather(
-    location: Annotated[str, Field(description="The city to get weather for.")],
+    location: Annotated[str, "The city to get weather for."],
 ) -> str:
     """Get the current weather for a location."""
     return f"The weather in {location} is sunny, 22°C."
@@ -35,11 +35,11 @@ def get_weather(
 
 async def main() -> None:
     agent = FoundryAgent(
-        project_endpoint="https://your-project.services.ai.azure.com",
-        agent_name="my-weather-agent",
-        agent_version="1.0",
+        project_endpoint=os.getenv("FOUNDRY_PROJECT_ENDPOINT"),
+        agent_name=os.getenv("FOUNDRY_AGENT_NAME"),
+        agent_version=os.getenv("FOUNDRY_AGENT_VERSION"),
         credential=AzureCliCredential(),
-        tools=[get_weather],
+        tools=get_weather,
     )
 
     result = await agent.run("What's the weather in Paris?")

python/samples/02-agents/providers/foundry/foundry_chat_client_code_interpreter_files.py

@@ -8,9 +8,8 @@ from agent_framework import Agent
 from agent_framework.foundry import FoundryChatClient
 from azure.identity import AzureCliCredential
 from dotenv import load_dotenv
-from openai import AsyncAzureOpenAI
+from openai import AsyncOpenAI
 
-# Load environment variables from .env file
 load_dotenv()
 
 """
@@ -18,12 +17,16 @@ Foundry Chat Client with Code Interpreter and Files Example
 
 This sample demonstrates using get_code_interpreter_tool() with Responses on Foundry
 for Python code execution and data analysis with uploaded files.
+
+Environment variables:
+    FOUNDRY_PROJECT_ENDPOINT — Foundry project endpoint
+    FOUNDRY_MODEL            — Foundry model to use (e.g. "gpt-4o-mini")
 """
 
 # Helper functions
 
 
-async def create_sample_file_and_upload(openai_client: AsyncAzureOpenAI) -> tuple[str, str]:
+async def create_sample_file_and_upload(openai_client: AsyncOpenAI) -> tuple[str, str]:
     """Create a sample CSV file and upload it for Foundry code interpreter use."""
     csv_data = """name,department,salary,years_experience
 Alice Johnson,Engineering,95000,5
@@ -51,7 +54,7 @@ Frank Wilson,Engineering,88000,6
     return temp_file_path, uploaded_file.id
 
 
-async def cleanup_files(openai_client: AsyncAzureOpenAI, temp_file_path: str, file_id: str) -> None:
+async def cleanup_files(openai_client: AsyncOpenAI, temp_file_path: str, file_id: str) -> None:
     """Clean up both local temporary file and uploaded file."""
     # Clean up: delete the uploaded file
     await openai_client.files.delete(file_id)
@@ -65,39 +68,29 @@ async def cleanup_files(openai_client: AsyncAzureOpenAI, temp_file_path: str, fi
 async def main() -> None:
     print("=== Foundry Chat Client with Code Interpreter and File Upload ===")
 
-    # Initialize the underlying OpenAI client for file operations
-    credential = AzureCliCredential()
-
-    async def get_token():
-        token = credential.get_token("https://cognitiveservices.azure.com/.default")
-        return token.token
-
-    openai_client = AsyncAzureOpenAI(
-        azure_ad_token_provider=get_token,
-        api_version="2024-05-01-preview",
+    # Create the FoundryChatClient
+    client = FoundryChatClient(
+        project_endpoint=os.getenv("FOUNDRY_PROJECT_ENDPOINT"),
+        model=os.getenv("FOUNDRY_MODEL"),
+        credential=AzureCliCredential(),
     )
-
+    # use the openai client from the foundry client to upload files for the code interpreter tool
+    openai_client = client.project_client.get_openai_client()
     temp_file_path, file_id = await create_sample_file_and_upload(openai_client)
-
-    # Create agent using FoundryChatClient
-    client = FoundryChatClient(credential=credential)
-
-    # Create code interpreter tool with file access
-    code_interpreter_tool = client.get_code_interpreter_tool(file_ids=[file_id])
-
+    # Create agent with code interpreter tool with file access
     agent = Agent(
         client=client,
         instructions="You are a helpful assistant that can analyze data files using Python code.",
-        tools=[code_interpreter_tool],
+        tools=FoundryChatClient.get_code_interpreter_tool(file_ids=[file_id]),
     )
-
-    # Test the code interpreter with the uploaded file
-    query = "Analyze the employee data in the uploaded CSV file. Calculate average salary by department."
-    print(f"User: {query}")
-    result = await agent.run(query)
-    print(f"Agent: {result.text}")
-
-    await cleanup_files(openai_client, temp_file_path, file_id)
+    try:
+        # Test the code interpreter with the uploaded file
+        query = "Analyze the employee data in the uploaded CSV file. Calculate average salary by department."
+        print(f"User: {query}")
+        result = await agent.run(query)
+        print(f"Agent: {result.text}")
+    finally:
+        await cleanup_files(openai_client, temp_file_path, file_id)
 
 
 if __name__ == "__main__":

python/samples/02-agents/providers/ollama/ollama_chat_client.py

@@ -35,7 +35,7 @@ def get_time():
 async def main() -> None:
     client = OllamaChatClient()
     message = "What time is it? Use a tool call"
-    messages = [Message(role="user", text=message)]
+    messages = [Message(role="user", contents=[message])]
     stream = False
     print(f"User: {message}")
     if stream: