AWS | Community | How to use Reasoning with Claude 3.7 Sonnet on Amazon Bedrock

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Have you ever wondered what goes on inside Claude when answering a complex question? With Claude 3.7 Sonnet's new reasoning feature, you can now peek behind the curtain and see the AI's step-by-step thought process. This capability offers unprecedented transparency into how Claude approaches problems, breaks them down, and reaches conclusions.

In this guide, we'll build a C# application that taps into this powerful capability through Amazon Bedrock. You'll learn how to enable reasoning, allocate appropriate computational resources for it, and process the structured responses that include both Claude's internal reasoning and its final answer. Whether you're debugging prompts, verifying calculations, or using Claude as an educational tool, understanding its reasoning process can significantly enhance your AI interactions.

👨‍💻 Want to jump straight to the code? If you're familiar with Claude and Amazon Bedrock and just need the technical details, skip directly to the step-by-step implementation guide.

What is Reasoning?

Reasoning is Claude's ability to explicitly work through complex problems step by step before providing an answer. When enabled, Claude doesn't just give you the final response – it reveals its complete thought process, similar to how a human might think aloud when solving a problem.

This feature allows Claude to:

Break down complex questions into manageable components
Explore multiple approaches to solving a problem
Analyze information systematically and draw logical conclusions
Show its work, particularly valuable for mathematical or logical problems
Identify potential flaws in its own thinking

Reasoning is particularly useful for problems that require multi-step thinking, such as complex mathematical calculations, logical puzzles, or nuanced analytical questions. By exposing Claude's internal thought process, you gain transparency into how the AI arrives at its conclusions, which can help build trust and provide educational value.

When reasoning is enabled, Claude allocates a portion of its computational resources (specified by your token budget) to this explicit thinking process, which is then returned to you alongside the final answer. This gives you unprecedented visibility into the AI's problem-solving approach.

Prerequisites

Before we begin, make sure you have:

An AWS account with access to Amazon Bedrock
.NET 8.0 or later installed
The AWS CLI installed and configured
Access to Claude 3.7 Sonnet enabled in your account¹

¹ At the time of writing, Claude 3.7 is available in us-east-1, us-east-2, and us-west-2.

Setting Up Dependencies

You'll need to add the AWS SDK for .NET to your project. Here's how to include the required NuGet packages:

Using the .NET CLI:

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dotnet add package AWSSDK.BedrockRuntime

Or add the following to your .csproj file:

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<ItemGroup>
  <PackageReference Include="AWSSDK.BedrockRuntime" Version="3.7.413" />
  <PackageReference Include="AWSSDK.Core" Version="3.7.402.6" />
</ItemGroup>

Step 1: Create a Basic File Structure

Start by creating a C# console application and adding the necessary using statements:

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using Amazon;
using Amazon.BedrockRuntime;
using Amazon.BedrockRuntime.Model;
using Amazon.Runtime.Documents;

public class Program
{
    public static async Task Main(string[] args)
    {
        // We'll call our reasoning method here
    }

    private static async Task<ReasoningResponse> ReasoningExample()
    {
        // We'll implement this method in the next steps
        return null;
    }
}

// Record to hold both reasoning and final response
public record ReasoningResponse(ReasoningContentBlock? Reasoning, string? Text);

Step 2: Set Up the Amazon Bedrock Client

First, we need to create a Bedrock runtime client that will handle our API requests. Add the following to the ReasoningExample() method:

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// Create the Amazon Bedrock runtime client
using var client = new AmazonBedrockRuntimeClient(RegionEndpoint.USEast1);

// Specify the model ID for Claude 3.7 Sonnet
const string modelId = "us.anthropic.claude-3-7-sonnet-20250219-v1:0";

Step 3: Create a Message for Claude

Next, we'll create a simple message to send to Claude:

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// Create the message with the user's prompt
const string userMessage = "Describe the purpose of a 'hello world' program in one line.";

var message = new Message
{
    Role = ConversationRole.User,
    Content = [new ContentBlock { Text = userMessage }]
};

Step 4: Configure Reasoning Parameters

Here's where the magic happens - we need to enable reasoning and set a token budget for it:

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// Configure reasoning parameters with a 2000 token budget
Document reasoningConfig = Document.FromObject(new
{
    thinking = new
    {
        type = "enabled",
        budget_tokens = 2000
    }
});

The budget_tokens parameter defines the maximum number of tokens Claude can use for its reasoning process. Adjust this value based on the complexity of your prompt.

Step 5: Send the Request to Claude

Now we'll send our prompt along with the reasoning configuration:

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// Send message and reasoning configuration to the model
var response = await client.ConverseAsync(new ConverseRequest
{
    ModelId = modelId,
    Messages = [message],
    AdditionalModelRequestFields = reasoningConfig
});

The AdditionalModelRequestFields parameter is what allows us to pass the reasoning configuration.

Step 6: Process the Response

Claude will return both its reasoning and final response, which we need to extract:

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// Extract and return the reasoning and text from the response
ReasoningContentBlock? reasoning = null;
string? text = null;

// Process each content block to find reasoning and response text
foreach (var block in response.Output.Message.Content)
{
    if (block.ReasoningContent is not null)
        reasoning = block.ReasoningContent;
    else if (block.Text is not null)
        text = block.Text;
}

return new ReasoningResponse(reasoning, text);

The response contains multiple content blocks, with the reasoning in one block and the final response text in another.

Step 7: Display the Results

Finally, we'll display both the reasoning process and the final answer. Add the following to the Main() method:

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// Execute the example and display reasoning and final response
var response = await ReasoningExample();

Console.WriteLine("\n<thinking>");
Console.WriteLine(response.Reasoning?.ReasoningText.Text);
Console.WriteLine("</thinking>\n");
Console.WriteLine(response.Text);

Complete Example

Here's the complete working example:

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using Amazon;
using Amazon.BedrockRuntime;
using Amazon.BedrockRuntime.Model;
using Amazon.Runtime.Documents;

namespace Reasoning;

/**
 * This example demonstrates how to use Anthropic Claude 3.7 Sonnet's reasoning capability
 * with Amazon Bedrock. It shows how to:
 * - Set up the Amazon Bedrock runtime client
 * - Create a message
 * - Configure reasoning parameters
 * - Send a request with reasoning enabled
 * - Process both the reasoning output and final response
 */
public class Program
{
    public static async Task Main(string[] args)
    {
        // Execute the example and display reasoning and final response
        var response = await ReasoningExample();

        Console.WriteLine("\n<thinking>");
        Console.WriteLine(response.Reasoning?.ReasoningText.Text);
        Console.WriteLine("</thinking>\n");
        Console.WriteLine(response.Text);
    }

    private static async Task<ReasoningResponse> ReasoningExample()
    {
        // Create the Amazon Bedrock runtime client
        using var client = new AmazonBedrockRuntimeClient(RegionEndpoint.USEast1);

        // Specify the model ID. For the latest available models, see:
        // https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
        const string modelId = "us.anthropic.claude-3-7-sonnet-20250219-v1:0";

        // Create the message with the user's prompt
        const string userMessage = "Describe the purpose of a 'hello world' program in one line.";

        var message = new Message
        {
            Role = ConversationRole.User,
            Content = [new ContentBlock { Text = userMessage }]
        };

        // Configure reasoning parameters with a 2000 token budget
        Document reasoningConfig = Document.FromObject(new
        {
            thinking = new
            {
                type = "enabled",
                budget_tokens = 2000
            }
        });

        try
        {
            // Send message and reasoning configuration to the model
            var response = await client.ConverseAsync(new ConverseRequest
            {
                ModelId = modelId,
                Messages = [message],
                AdditionalModelRequestFields = reasoningConfig
            });

            ReasoningContentBlock? reasoning = null;
            string? text = null;

            // Process each content block to find reasoning and response text
            foreach (var block in response.Output.Message.Content)
            {
                if (block.ReasoningContent is not null)
                    reasoning = block.ReasoningContent;
                else if (block.Text is not null)
                    text = block.Text;
            }

            return new ReasoningResponse(reasoning, text);
        }
        catch (AmazonBedrockRuntimeException e)
        {
            Console.WriteLine($"ERROR: Can't invoke '{modelId}'. Reason: {e.Message}");
            throw;
        }
    }
}

// Record to hold both reasoning and final response
public record ReasoningResponse(ReasoningContentBlock? Reasoning, string? Text);

Example Output

When you run this code, you'll see output similar to:

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<thinking>
I need to explain the purpose of a "Hello World" program in a single line.

A "Hello World" program is typically the simplest program that can be written in
a programming language. Its purpose is to:
1. Verify that the programming environment is set up correctly
2. Demonstrate the minimal syntax needed to create a functioning program
3. Provide a simple introduction to the language
4. Output the text "Hello, World!" or a similar message

I need to condense this information into a concise, one-line description that
captures the essence of what a "Hello World" program is for.
</thinking>

A "Hello World" program serves as the simplest introduction to a programming
language by demonstrating basic syntax while verifying the environment works correctly.

Summary and next steps

The reasoning capability transforms how we interact with AI by providing valuable insight into the model's thinking process. By following the steps in this guide, you can now access and leverage this powerful feature through Amazon Bedrock using C#.

The reasoning feature opens up exciting possibilities to enhance trust, improve outcomes, and gain deeper insights from your AI interactions. For more advanced use cases, consider:

Adjusting the token budget based on your problem complexity – more complex problems may benefit from larger reasoning budgets
Using the reasoning output to validate multi-step calculations or complex analytical processes
Comparing different reasoning approaches by adjusting your prompts
Integrating reasoning with other Claude capabilities like function calling for powerful, transparent AI solutions
Using reasoning as an educational tool to understand expert-level problem-solving approaches

By incorporating reasoning into your applications, you're not just getting answers – you're gaining insight into the full problem-solving journey. This transparency can help build trust with users and provide richer, more valuable AI interactions.

Happy coding!

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

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How to use Reasoning with Claude 3.7 Sonnet on Amazon Bedrock - C#/.NET Edition

Learn how to use Claude 3.7 Sonnet's step-by-step thinking process with the AWS SDK for .NET. This tutorial walks you through a practical example to receive Claude's internal thought process in your own applications.