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ea795b4
Add Bedrock Agent to .Net SDK
TaoChenOSU 61fecf1
Merge branch 'main' into TaoChenOSU/add-bedrock-agent-dotnet
TaoChenOSU e311fe6
Simple invoke is working
TaoChenOSU 441207b
Kernel function WIP
TaoChenOSU 9a8e06c
Kernel function done
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Merge branch 'main' into TaoChenOSU/add-bedrock-agent-dotnet
TaoChenOSU 5f1279d
Formatting
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Reformat usings
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Bedrock agent trace
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Example output
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Knowledge base
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Bedrock agent channel
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Remove unit test files
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Fix input ordering
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Remove import
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Add project reference to fix build
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READMEs
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Fix non-streaming invoke
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Minor updates
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Add array type support
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Merge branch 'main' into TaoChenOSU/add-bedrock-agent-dotnet
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Merge branch 'main' into TaoChenOSU/add-bedrock-agent-dotnet
crickman 9c20a80
Address comments 1st batch
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Merge branch 'main' into TaoChenOSU/add-bedrock-agent-dotnet
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38 changes: 38 additions & 0 deletions
38
dotnet/samples/GettingStartedWithAgents/BedrockAgent/README.md
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| # Concept samples on how to use AWS Bedrock agents | ||
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| ## Pre-requisites | ||
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| 1. You need to have an AWS account and [access to the foundation models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-permissions.html) | ||
| 2. [AWS CLI installed](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) and [configured](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html#configuration) | ||
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| ## Before running the samples | ||
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| You need to set up some user secrets to run the samples. | ||
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| ### `BedrockAgent:AgentResourceRoleArn` | ||
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| On your AWS console, go to the IAM service and go to **Roles**. Find the role you want to use and click on it. You will find the ARN in the summary section. | ||
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| ``` | ||
| dotnet user-secrets set "BedrockAgent:AgentResourceRoleArn" "arn:aws:iam::...:role/..." | ||
| ``` | ||
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| ### `BedrockAgent:FoundationModel` | ||
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| You need to make sure you have permission to access the foundation model. You can find the model ID in the [AWS documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html). To see the models you have access to, find the policy attached to your role you should see a list of models you have access to under the `Resource` section. | ||
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| ``` | ||
| dotnet user-secrets set "BedrockAgent:FoundationModel" "..." | ||
| ``` | ||
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| ### How to add the `bedrock:InvokeModelWithResponseStream` action to an IAM policy | ||
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| 1. Open the [IAM console](https://console.aws.amazon.com/iam/). | ||
| 2. On the left navigation pane, choose `Roles` under `Access management`. | ||
| 3. Find the role you want to edit and click on it. | ||
| 4. Under the `Permissions policies` tab, click on the policy you want to edit. | ||
| 5. Under the `Permissions defined in this policy` section, click on the service. You should see **Bedrock** if you already have access to the Bedrock agent service. | ||
| 6. Click on the service, and then click `Edit`. | ||
| 7. On the right, you will be able to add an action. Find the service and search for `InvokeModelWithResponseStream`. | ||
| 8. Check the box next to the action and then scroll all the way down and click `Next`. | ||
| 9. Follow the prompts to save the changes. |
73 changes: 73 additions & 0 deletions
73
dotnet/samples/GettingStartedWithAgents/BedrockAgent/Step01_BedrockAgent.cs
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| // Copyright (c) Microsoft. All rights reserved. | ||
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| using Microsoft.SemanticKernel.Agents.Bedrock; | ||
| using Microsoft.SemanticKernel.Agents.Bedrock.Extensions; | ||
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| namespace GettingStarted.BedrockAgents; | ||
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| /// <summary> | ||
| /// This example demonstrates how to interact with a <see cref="BedrockAgent"/> in the most basic way. | ||
| /// </summary> | ||
| public class Step01_BedrockAgent(ITestOutputHelper output) : BaseBedrockAgentTest(output) | ||
| { | ||
| private const string UserQuery = "Why is the sky blue in one sentence?"; | ||
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| /// <summary> | ||
| /// Demonstrates how to create a new <see cref="BedrockAgent"/> and interact with it. | ||
| /// The agent will respond to the user query. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task UseNewAgentAsync() | ||
| { | ||
| // Create the agent | ||
| var bedrockAgent = await this.CreateAgentAsync("Step01_BedrockAgent"); | ||
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| // Respond to user input | ||
| try | ||
| { | ||
| var responses = bedrockAgent.InvokeAsync(BedrockAgent.CreateSessionId(), UserQuery, null); | ||
| await foreach (var response in responses) | ||
| { | ||
| this.Output.WriteLine(response.Content); | ||
| } | ||
| } | ||
| finally | ||
| { | ||
| await this.Client.DeleteAgentAsync(new() { AgentId = bedrockAgent.Id }); | ||
| } | ||
| } | ||
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| /// <summary> | ||
| /// Demonstrates how to create a new <see cref="BedrockAgent"/> and interact with it using streaming. | ||
| /// The agent will respond to the user query. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task UseNewAgentStreamingAsync() | ||
| { | ||
| // Create the agent | ||
| var bedrockAgent = await this.CreateAgentAsync("Step01_BedrockAgent_Streaming"); | ||
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| // Respond to user input | ||
| try | ||
| { | ||
| var streamingResponses = bedrockAgent.InvokeStreamingAsync(BedrockAgent.CreateSessionId(), UserQuery, null); | ||
| await foreach (var response in streamingResponses) | ||
| { | ||
| this.Output.WriteLine(response.Content); | ||
| } | ||
| } | ||
| finally | ||
| { | ||
| await this.Client.DeleteAgentAsync(new() { AgentId = bedrockAgent.Id }); | ||
| } | ||
| } | ||
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| protected override async Task<BedrockAgent> CreateAgentAsync(string agentName) | ||
| { | ||
| // Create a new agent on the Bedrock Agent service and prepare it for use | ||
| var agentModel = await this.Client.CreateAndPrepareAgentAsync(this.GetCreateAgentRequest(agentName)); | ||
| // Create a new BedrockAgent instance with the agent model and the client | ||
| // so that we can interact with the agent using Semantic Kernel contents. | ||
| return new BedrockAgent(agentModel, this.Client); | ||
| } | ||
| } | ||
90 changes: 90 additions & 0 deletions
90
dotnet/samples/GettingStartedWithAgents/BedrockAgent/Step02_BedrockAgent_CodeInterpreter.cs
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| // Copyright (c) Microsoft. All rights reserved. | ||
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| using System.Reflection; | ||
| using Microsoft.SemanticKernel; | ||
| using Microsoft.SemanticKernel.Agents.Bedrock; | ||
| using Microsoft.SemanticKernel.Agents.Bedrock.Extensions; | ||
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| namespace GettingStarted.BedrockAgents; | ||
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| /// <summary> | ||
| /// This example demonstrates how to interact with a <see cref="BedrockAgent"/> with code interpreter enabled. | ||
| /// </summary> | ||
| public class Step02_BedrockAgent_CodeInterpreter(ITestOutputHelper output) : BaseBedrockAgentTest(output) | ||
| { | ||
| private const string UserQuery = @"Create a bar chart for the following data: | ||
| Panda 5 | ||
| Tiger 8 | ||
| Lion 3 | ||
| Monkey 6 | ||
| Dolphin 2"; | ||
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| /// <summary> | ||
| /// Demonstrates how to create a new <see cref="BedrockAgent"/> with code interpreter enabled and interact with it. | ||
| /// The agent will respond to the user query by creating a Python code that will be executed by the code interpreter. | ||
| /// The output of the code interpreter will be a file containing the bar chart, which will be returned to the user. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task UseAgentWithCodeInterpreterAsync() | ||
| { | ||
| // Create the agent | ||
| var bedrockAgent = await this.CreateAgentAsync("Step02_BedrockAgent_CodeInterpreter"); | ||
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| // Respond to user input | ||
| try | ||
| { | ||
| BinaryContent? binaryContent = null; | ||
| var responses = bedrockAgent.InvokeAsync(BedrockAgent.CreateSessionId(), UserQuery, null); | ||
| await foreach (var response in responses) | ||
| { | ||
| if (response.Content != null) | ||
| { | ||
| this.Output.WriteLine(response.Content); | ||
| } | ||
| if (binaryContent == null && response.Items.Count > 0) | ||
| { | ||
| binaryContent = response.Items.OfType<BinaryContent>().FirstOrDefault(); | ||
| } | ||
| } | ||
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| if (binaryContent == null) | ||
| { | ||
| throw new InvalidOperationException("No file found in the response."); | ||
| } | ||
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| // Save the file to the same directory as the test assembly | ||
| var filePath = Path.Combine( | ||
| Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location)!, | ||
| binaryContent.Metadata!["Name"]!.ToString()!); | ||
| this.Output.WriteLine($"Saving file to {filePath}"); | ||
| binaryContent.WriteToFile(filePath, overwrite: true); | ||
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| // Expected output: | ||
| // Here is the bar chart for the given data: | ||
| // [A bar chart showing the following data: | ||
| // Panda 5 | ||
| // Tiger 8 | ||
| // Lion 3 | ||
| // Monkey 6 | ||
| // Dolphin 2] | ||
| // Saving file to ... | ||
| } | ||
| finally | ||
| { | ||
| await this.Client.DeleteAgentAsync(new() { AgentId = bedrockAgent.Id }); | ||
| } | ||
| } | ||
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| protected override async Task<BedrockAgent> CreateAgentAsync(string agentName) | ||
| { | ||
| // Create a new agent on the Bedrock Agent service and prepare it for use | ||
| var agentModel = await this.Client.CreateAndPrepareAgentAsync(this.GetCreateAgentRequest(agentName)); | ||
| // Create a new BedrockAgent instance with the agent model and the client | ||
| // so that we can interact with the agent using Semantic Kernel contents. | ||
| var bedrockAgent = new BedrockAgent(agentModel, this.Client); | ||
| // Create the code interpreter action group and prepare the agent for interaction | ||
| await bedrockAgent.CreateCodeInterpreterActionGroupAsync(); | ||
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| return bedrockAgent; | ||
| } | ||
| } |
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