Python: Introducing the Anthropic Client (#1819)

* initial version of anthropic connector

* updated implementation and added tests

* fix type and readme

* mypy fix and int tests enabled

* add integration test setup

* updated based on comments

* improved function result handling

* added extra unordered test

* updated from review

* fix tool choice handling

* same fix for chat client

python/samples/README.md

@@ -14,7 +14,8 @@ This directory contains samples demonstrating the capabilities of Microsoft Agen
 
 | File | Description |
 |------|-------------|
-| [`getting_started/agents/anthropic/anthropic_with_openai_chat_client.py`](./getting_started/agents/anthropic/anthropic_with_openai_chat_client.py) | Anthropic with OpenAI Chat Client Example |
+| [`getting_started/agents/anthropic/anthropic_basic.py`](./getting_started/agents/anthropic/anthropic_basic.py) | Agent with Anthropic Client |
+| [`getting_started/agents/anthropic/anthropic_advanced.py`](./getting_started/agents/anthropic/anthropic_advanced.py) | Advanced sample with `thinking` and hosted tools. |
 
 ### Azure AI
 

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

@@ -6,12 +6,12 @@ This folder contains examples demonstrating how to use Anthropic's Claude models
 
 | File | Description |
 |------|-------------|
-| [`anthropic_with_openai_chat_client.py`](anthropic_with_openai_chat_client.py) | Demonstrates how to configure OpenAI Chat Client to use Anthropic's Claude models. Shows both streaming and non-streaming responses with tool calling capabilities. |
+| [`anthropic_basic.py`](anthropic_basic.py) | Demonstrates how to setup a simple agent using the AnthropicClient, with both streaming and non-streaming responses. |
+| [`anthropic_advanced.py`](anthropic_advanced.py) | Shows advanced usage of the AnthropicClient, including hosted tools and `thinking`. |
 
 ## Environment Variables
 
 Set the following environment variables before running the examples:
 
 - `ANTHROPIC_API_KEY`: Your Anthropic API key (get one from [Anthropic Console](https://console.anthropic.com/))
-- `ANTHROPIC_MODEL`: The Claude model to use (e.g., `claude-3-5-sonnet-20241022`, `claude-3-haiku-20240307`)
-
+- `ANTHROPIC_MODEL`: The Claude model to use (e.g., `claude-haiku-4-5`, `claude-sonnet-4-5-20250929`)

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

@@ -0,0 +1,58 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import HostedMCPTool, HostedWebSearchTool, TextReasoningContent, UsageContent
+from agent_framework.anthropic import AnthropicClient
+
+"""
+Anthropic Chat Agent Example
+
+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.
+"""
+
+
+async def streaming_example() -> None:
+    """Example of streaming response (get results as they are generated)."""
+    agent = AnthropicClient().create_agent(
+        name="DocsAgent",
+        instructions="You are a helpful agent for both Microsoft docs questions and general questions.",
+        tools=[
+            HostedMCPTool(
+                name="Microsoft Learn MCP",
+                url="https://learn.microsoft.com/api/mcp",
+            ),
+            HostedWebSearchTool(),
+        ],
+        # anthropic needs a value for the max_tokens parameter
+        # we set it to 1024, but you can override like this:
+        max_tokens=20000,
+        additional_chat_options={"thinking": {"type": "enabled", "budget_tokens": 10000}},
+    )
+
+    query = "Can you compare Python decorators with C# attributes?"
+    print(f"User: {query}")
+    print("Agent: ", end="", flush=True)
+    async for chunk in agent.run_stream(query):
+        for content in chunk.contents:
+            if isinstance(content, TextReasoningContent):
+                print(f"\033[32m{content.text}\033[0m", end="", flush=True)
+            if isinstance(content, UsageContent):
+                print(f"\n\033[34m[Usage so far: {content.details}]\033[0m\n", end="", flush=True)
+        if chunk.text:
+            print(chunk.text, end="", flush=True)
+
+    print("\n")
+
+
+async def main() -> None:
+    print("=== Anthropic Example ===")
+
+    await streaming_example()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

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

@@ -1,17 +1,15 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
-import os
 from random import randint
 from typing import Annotated
 
-from agent_framework.openai import OpenAIChatClient
+from agent_framework.anthropic import AnthropicClient
 
 """
-Anthropic with OpenAI Chat Client Example
+Anthropic Chat Agent Example
 
-This sample demonstrates using Anthropic models through OpenAI Chat Client by
-configuring the base URL to point to Anthropic's API for cross-provider compatibility.
+This sample demonstrates using Anthropic with an agent and a single custom tool.
 """
 
 
@@ -27,10 +25,7 @@ async def non_streaming_example() -> None:
     """Example of non-streaming response (get the complete result at once)."""
     print("=== Non-streaming Response Example ===")
 
-    agent = OpenAIChatClient(
-        api_key=os.getenv("ANTHROPIC_API_KEY"),
-        base_url="https://api.anthropic.com/v1/",
-        model_id=os.getenv("ANTHROPIC_MODEL"),
+    agent = AnthropicClient(
     ).create_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
@@ -47,17 +42,14 @@ async def streaming_example() -> None:
     """Example of streaming response (get results as they are generated)."""
     print("=== Streaming Response Example ===")
 
-    agent = OpenAIChatClient(
-        api_key=os.getenv("ANTHROPIC_API_KEY"),
-        base_url="https://api.anthropic.com/v1/",
-        model_id=os.getenv("ANTHROPIC_MODEL"),
+    agent = AnthropicClient(
     ).create_agent(
         name="WeatherAgent",
         instructions="You are a helpful weather agent.",
         tools=get_weather,
     )
 
-    query = "What's the weather like in Portland?"
+    query = "What's the weather like in Portland and in Paris?"
     print(f"User: {query}")
     print("Agent: ", end="", flush=True)
     async for chunk in agent.run_stream(query):
@@ -67,10 +59,10 @@ async def streaming_example() -> None:
 
 
 async def main() -> None:
-    print("=== Anthropic with OpenAI Chat Client Agent Example ===")
+    print("=== Anthropic Example ===")
 
-    await non_streaming_example()
     await streaming_example()
+    await non_streaming_example()
 
 
 if __name__ == "__main__":