AWS Bedrock with .NET: Conversational AI Converse API

using Amazon.BedrockRuntime;
using Amazon.BedrockRuntime.Model;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;

public class BedrockCustomerSupportService
{
    private readonly AmazonBedrockRuntimeClient _client;
    // NOTE: Verify the latest Claude model ID in the AWS Bedrock console.
    // This example uses Claude 3 Haiku as of Jan 2026 — model IDs may change.
    private const string ModelId = "anthropic.claude-3-haiku-20240307-v1:0";

    public BedrockCustomerSupportService()
    {
        _client = new AmazonBedrockRuntimeClient(Amazon.RegionEndpoint.USEast1);
    }

    /// <summary>
    /// Simulates an AI customer support staff in a multi-turn conversation using the Bedrock Converse API (no tools).
    /// </summary>
    /// <param name="conversationHistory">The full conversation history as a list of Message objects (user and assistant turns).</param>
    /// <returns>AI-generated customer support response as plain text.</returns>
    public async Task<string> GetSupportResponse(List<Message> conversationHistory)
    {
        var converseRequest = new ConverseRequest
        {
            System = new List<SystemContentBlock>
            {
                new SystemContentBlock
                {
                    Text = "You are an AI customer support staff. Be polite, helpful, and concise. Address the customer's issue and provide clear next steps or solutions. Maintain context across the conversation."
                }
            },
            ModelId = ModelId,
            Messages = conversationHistory
        };

        var response = await _client.ConverseAsync(converseRequest);

        var responseText = string.Empty;
        foreach (var content in response.Output.Message.Content)
        {
            if (content.Text != null)
            {
                responseText += content.Text;
            }
        }

        return responseText;
    }
}
            

    // Example conversation history — showing 5+ turns to demonstrate context retention
    var conversationHistory = new List<Message>
    {
        new Message { Role = "user", Content = new List<ContentBlock> { new ContentBlock { Text = "My order hasn't arrived yet. I ordered it last week." } } },
        new Message { Role = "assistant", Content = new List<ContentBlock> { new ContentBlock { Text = "I'm sorry to hear that. Can you provide your order number? And what's your delivery address region?" } } },
        new Message { Role = "user", Content = new List<ContentBlock> { new ContentBlock { Text = "It's order 12345, and I'm in the East Coast region." } } },
        new Message { Role = "assistant", Content = new List<ContentBlock> { new ContentBlock { Text = "Thanks! Order 12345 was shipped 5 days ago to the East Coast. It should arrive within 2-3 days. Would you like me to track it further or escalate this?" } } },
        new Message { Role = "user", Content = new List<ContentBlock> { new ContentBlock { Text = "Can you escalate this to a human agent? I'm concerned since it's been a week." } } }
    };

    var service = new BedrockCustomerSupportService();
    string response = await service.GetSupportResponse(conversationHistory);
    Console.WriteLine(response);
            

    // Customer support chat demo
    async Task RunBedrockCustomerSupportChat()
    {
        try
        {
            var supportService = new BedrockCustomerSupportService();
            var conversation = new List<Amazon.BedrockRuntime.Model.Message>();
            Console.WriteLine("\nWelcome to AI Customer Support! Type 'Exit Chat' to end the conversation.\n");
            while (true)
            {
                Console.Write("You: ");
                var userInput = Console.ReadLine();
                if (string.Equals(userInput, "Exit Chat", StringComparison.OrdinalIgnoreCase))
                {
                    Console.WriteLine("\nThank you for chatting with AI Customer Support. Goodbye!\n");
                    break;
                }
                // Add user message to conversation
                conversation.Add(new Amazon.BedrockRuntime.Model.Message
                {
                    Role = "user",
                    Content = new List<Amazon.BedrockRuntime.Model.ContentBlock>
                    {
                        new Amazon.BedrockRuntime.Model.ContentBlock { Text = userInput }
                    }
                });

                // Get AI response
                var response = await supportService.GetSupportResponse(conversation);

                // Add assistant response to conversation
                conversation.Add(new Amazon.BedrockRuntime.Model.Message
                {
                    Role = "assistant",
                    Content = new List<Amazon.BedrockRuntime.Model.ContentBlock>
                    {
                        new Amazon.BedrockRuntime.Model.ContentBlock { Text = response }
                    }
                });

                Console.WriteLine($"AI: {response}\n");
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine($"Error: {ex.Message}");
            Console.WriteLine(ex.StackTrace);
        }
    }