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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net10.0</TargetFramework>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Anthropic\Microsoft.Agents.AI.Anthropic.csproj" />
</ItemGroup>
</Project>

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// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to create and use a simple AI agent with Anthropic as the backend.
using Anthropic;
using Anthropic.Core;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
var apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY") ?? throw new InvalidOperationException("ANTHROPIC_API_KEY is not set.");
var model = Environment.GetEnvironmentVariable("ANTHROPIC_MODEL") ?? "claude-haiku-4-5";
AIAgent agent = new AnthropicClient(new ClientOptions { APIKey = apiKey })
.AsAIAgent(model: model, instructions: "You are good at telling jokes.", name: "Joker");
// Invoke the agent and output the text result.
var response = await agent.RunAsync("Tell me a joke about a pirate.");
Console.WriteLine(response);
// Invoke the agent with streaming support.
await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate."))
{
Console.WriteLine(update);
}

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# Running a simple agent with Anthropic
This sample demonstrates how to create and run a basic agent with Anthropic Claude models.
## What this sample demonstrates
- Creating an AI agent with Anthropic Claude
- Running a simple agent with instructions
- Managing agent lifecycle
## Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 8.0 SDK or later
- Anthropic API key configured
**Note**: This sample uses Anthropic Claude models. For more information, see [Anthropic documentation](https://docs.anthropic.com/).
Set the following environment variables:
```powershell
$env:ANTHROPIC_API_KEY="your-anthropic-api-key" # Replace with your Anthropic API key
$env:ANTHROPIC_MODEL="your-anthropic-model" # Replace with your Anthropic model
```
## Run the sample
Navigate to the AgentWithAnthropic sample directory and run:
```powershell
cd dotnet\samples\GettingStarted\AgentWithAnthropic
dotnet run --project .\Agent_Anthropic_Step01_Running
```
## Expected behavior
The sample will:
1. Create an agent with Anthropic Claude
2. Run the agent with a simple prompt
3. Display the agent's response

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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net10.0</TargetFramework>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Anthropic\Microsoft.Agents.AI.Anthropic.csproj" />
</ItemGroup>
</Project>

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// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to create and use an AI agent with reasoning capabilities.
using Anthropic;
using Anthropic.Core;
using Anthropic.Models.Messages;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
var apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY") ?? throw new InvalidOperationException("ANTHROPIC_API_KEY is not set.");
var model = Environment.GetEnvironmentVariable("ANTHROPIC_MODEL") ?? "claude-haiku-4-5";
var maxTokens = 4096;
var thinkingTokens = 2048;
var agent = new AnthropicClient(new ClientOptions { APIKey = apiKey })
.AsAIAgent(
model: model,
clientFactory: (chatClient) => chatClient
.AsBuilder()
.ConfigureOptions(
options => options.RawRepresentationFactory = (_) => new MessageCreateParams()
{
Model = options.ModelId ?? model,
MaxTokens = options.MaxOutputTokens ?? maxTokens,
Messages = [],
Thinking = new ThinkingConfigParam(new ThinkingConfigEnabled(budgetTokens: thinkingTokens))
})
.Build());
Console.WriteLine("1. Non-streaming:");
var response = await agent.RunAsync("Solve this problem step by step: If a train travels 60 miles per hour and needs to cover 180 miles, how long will the journey take? Show your reasoning.");
Console.WriteLine("#### Start Thinking ####");
Console.WriteLine($"\e[92m{string.Join("\n", response.Messages.SelectMany(m => m.Contents.OfType<TextReasoningContent>().Select(c => c.Text)))}\e[0m");
Console.WriteLine("#### End Thinking ####");
Console.WriteLine("\n#### Final Answer ####");
Console.WriteLine(response.Text);
Console.WriteLine("Token usage:");
Console.WriteLine($"Input: {response.Usage?.InputTokenCount}, Output: {response.Usage?.OutputTokenCount}, {string.Join(", ", response.Usage?.AdditionalCounts ?? [])}");
Console.WriteLine();
Console.WriteLine("2. Streaming");
await foreach (var update in agent.RunStreamingAsync("Explain the theory of relativity in simple terms."))
{
foreach (var item in update.Contents)
{
if (item is TextReasoningContent reasoningContent)
{
Console.WriteLine($"\e[92m{reasoningContent.Text}\e[0m");
}
else if (item is TextContent textContent)
{
Console.WriteLine(textContent.Text);
}
}
}

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# Using reasoning with Anthropic agents
This sample demonstrates how to use extended thinking/reasoning capabilities with Anthropic Claude agents.
## What this sample demonstrates
- Creating an AI agent with Anthropic Claude extended thinking
- Using reasoning capabilities for complex problem solving
- Extracting thinking and response content from agent output
- Managing agent lifecycle
## Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 8.0 SDK or later
- Anthropic API key configured
- Access to Anthropic Claude models with extended thinking support
**Note**: This sample uses Anthropic Claude models with extended thinking. For more information, see [Anthropic documentation](https://docs.anthropic.com/).
Set the following environment variables:
```powershell
$env:ANTHROPIC_API_KEY="your-anthropic-api-key" # Replace with your Anthropic API key
$env:ANTHROPIC_MODEL="your-anthropic-model" # Replace with your Anthropic model
```
## Run the sample
Navigate to the AgentWithAnthropic sample directory and run:
```powershell
cd dotnet\samples\GettingStarted\AgentWithAnthropic
dotnet run --project .\Agent_Anthropic_Step02_Reasoning
```
## Expected behavior
The sample will:
1. Create an agent with Anthropic Claude extended thinking enabled
2. Run the agent with a complex reasoning prompt
3. Display the agent's thinking process
4. Display the agent's final response

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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net10.0</TargetFramework>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Anthropic\Microsoft.Agents.AI.Anthropic.csproj" />
</ItemGroup>
</Project>

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// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use an agent with function tools.
// It shows both non-streaming and streaming agent interactions using weather-related tools.
using System.ComponentModel;
using Anthropic;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
var apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY") ?? throw new InvalidOperationException("ANTHROPIC_API_KEY is not set.");
var model = Environment.GetEnvironmentVariable("ANTHROPIC_MODEL") ?? "claude-haiku-4-5";
[Description("Get the weather for a given location.")]
static string GetWeather([Description("The location to get the weather for.")] string location)
=> $"The weather in {location} is cloudy with a high of 15°C.";
const string AssistantInstructions = "You are a helpful assistant that can get weather information.";
const string AssistantName = "WeatherAssistant";
// Define the agent with function tools.
AITool tool = AIFunctionFactory.Create(GetWeather);
// Get anthropic client to create agents.
AIAgent agent = new AnthropicClient { APIKey = apiKey }
.AsAIAgent(model: model, instructions: AssistantInstructions, name: AssistantName, tools: [tool]);
// Non-streaming agent interaction with function tools.
AgentThread thread = await agent.GetNewThreadAsync();
Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?", thread));
// Streaming agent interaction with function tools.
thread = await agent.GetNewThreadAsync();
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread))
{
Console.WriteLine(update);
}

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# Using Function Tools with Anthropic agents
This sample demonstrates how to use function tools with Anthropic Claude agents, allowing agents to call custom functions to retrieve information.
## What this sample demonstrates
- Creating function tools using AIFunctionFactory
- Passing function tools to an Anthropic Claude agent
- Running agents with function tools (text output)
- Running agents with function tools (streaming output)
- Managing agent lifecycle
## Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 8.0 SDK or later
- Anthropic API key configured
**Note**: This sample uses Anthropic Claude models. For more information, see [Anthropic documentation](https://docs.anthropic.com/).
Set the following environment variables:
```powershell
$env:ANTHROPIC_API_KEY="your-anthropic-api-key" # Replace with your Anthropic API key
$env:ANTHROPIC_MODEL="your-anthropic-model" # Replace with your Anthropic model
```
## Run the sample
Navigate to the AgentWithAnthropic sample directory and run:
```powershell
cd dotnet\samples\GettingStarted\AgentWithAnthropic
dotnet run --project .\Agent_Anthropic_Step03_UsingFunctionTools
```
## Expected behavior
The sample will:
1. Create an agent named "WeatherAssistant" with a GetWeather function tool
2. Run the agent with a text prompt asking about weather
3. The agent will invoke the GetWeather function tool to retrieve weather information
4. Run the agent again with streaming to display the response as it's generated
5. Clean up resources by deleting the agent

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# Getting started with agents using Anthropic
The getting started with agents using Anthropic samples demonstrate the fundamental concepts and functionalities
of single agents using Anthropic as the AI provider.
These samples use Anthropic Claude models as the AI provider and use ChatCompletion as the type of service.
For other samples that demonstrate how to create and configure each type of agent that come with the agent framework,
see the [How to create an agent for each provider](../AgentProviders/README.md) samples.
## Getting started with agents using Anthropic prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 8.0 SDK or later
- Anthropic API key configured
- User has access to Anthropic Claude models
**Note**: These samples use Anthropic Claude models. For more information, see [Anthropic documentation](https://docs.anthropic.com/).
## Using Anthropic with Azure Foundry
To use Anthropic with Azure Foundry, you can check the sample [AgentProviders/Agent_With_Anthropic](../AgentProviders/Agent_With_Anthropic/README.md) for more details.
## Samples
|Sample|Description|
|---|---|
|[Running a simple agent](./Agent_Anthropic_Step01_Running/)|This sample demonstrates how to create and run a basic agent with Anthropic Claude|
|[Using reasoning with an agent](./Agent_Anthropic_Step02_Reasoning/)|This sample demonstrates how to use extended thinking/reasoning capabilities with Anthropic Claude agents|
|[Using function tools with an agent](./Agent_Anthropic_Step03_UsingFunctionTools/)|This sample demonstrates how to use function tools with an Anthropic Claude agent|
## Running the samples from the console
To run the samples, navigate to the desired sample directory, e.g.
```powershell
cd Agent_Anthropic_Step01_Running
```
Set the following environment variables:
```powershell
$env:ANTHROPIC_API_KEY="your-anthropic-api-key" # Replace with your Anthropic API key
```
If the variables are not set, you will be prompted for the values when running the samples.
Execute the following command to build the sample:
```powershell
dotnet build
```
Execute the following command to run the sample:
```powershell
dotnet run --no-build
```
Or just build and run in one step:
```powershell
dotnet run
```
## Running the samples from Visual Studio
Open the solution in Visual Studio and set the desired sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`.
You will be prompted for any required environment variables if they are not already set.