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https://github.com/microsoft/agent-framework.git
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Merge branch 'main' into feature-harness
This commit is contained in:
westey
GitHub
@@ -5,16 +5,16 @@
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// This is provided for demonstration purposes only.
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using System.Diagnostics;
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using System.Text.Json;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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/// <summary>
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/// Executes file-based skill scripts as local subprocesses.
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/// </summary>
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/// <remarks>
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/// This runner uses the script's absolute path, converts the arguments
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/// to CLI flags, and returns captured output. It is intended for
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/// demonstration purposes only.
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/// This runner uses the script's absolute path and converts the arguments
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/// to CLI arguments. When the LLM sends a JSON array, each element is used
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/// as a positional argument. It is intended for demonstration purposes only.
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/// </remarks>
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internal static class SubprocessScriptRunner
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{
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@@ -24,7 +24,8 @@ internal static class SubprocessScriptRunner
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public static async Task<object?> RunAsync(
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AgentFileSkill skill,
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AgentFileSkillScript script,
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AIFunctionArguments arguments,
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JsonElement? arguments,
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IServiceProvider? serviceProvider,
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CancellationToken cancellationToken)
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{
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if (!File.Exists(script.FullPath))
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@@ -61,24 +62,27 @@ internal static class SubprocessScriptRunner
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startInfo.FileName = script.FullPath;
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}
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if (arguments is not null)
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if (arguments is { ValueKind: JsonValueKind.Array } json)
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{
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foreach (var (key, value) in arguments)
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// Positional CLI arguments
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foreach (var element in json.EnumerateArray())
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{
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if (value is bool boolValue)
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if (element.ValueKind != JsonValueKind.String)
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{
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if (boolValue)
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{
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startInfo.ArgumentList.Add(NormalizeKey(key));
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}
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}
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else if (value is not null)
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{
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startInfo.ArgumentList.Add(NormalizeKey(key));
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startInfo.ArgumentList.Add(value.ToString()!);
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throw new InvalidOperationException(
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$"File-based skill scripts only accept string CLI arguments but received a JSON element of kind '{element.ValueKind}'. " +
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"All array elements must be JSON strings.");
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}
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startInfo.ArgumentList.Add(element.GetString()!);
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}
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}
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else if (arguments is not null && arguments.Value.ValueKind != JsonValueKind.Null && arguments.Value.ValueKind != JsonValueKind.Undefined)
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{
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throw new InvalidOperationException(
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$"Expected a JSON array of CLI arguments but received {arguments.Value.ValueKind}. " +
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"File-based skill scripts expect positional arguments as a JSON array of strings.");
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}
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Process? process = null;
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try
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@@ -128,10 +132,4 @@ internal static class SubprocessScriptRunner
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process?.Dispose();
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}
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}
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/// <summary>
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/// Normalizes a parameter key to a consistent --flag format.
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/// Models may return keys with or without leading dashes (e.g., "value" vs "--value").
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/// </summary>
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private static string NormalizeKey(string key) => "--" + key.TrimStart('-');
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}
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@@ -0,0 +1,38 @@
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFrameworks>net10.0</TargetFrameworks>
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<Nullable>enable</Nullable>
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<ImplicitUsings>enable</ImplicitUsings>
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</PropertyGroup>
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<PropertyGroup>
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<InjectIsExternalInitOnLegacy>true</InjectIsExternalInitOnLegacy>
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<InjectSharedFoundryAgents>true</InjectSharedFoundryAgents>
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<InjectSharedWorkflowsExecution>true</InjectSharedWorkflowsExecution>
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<InjectSharedWorkflowsSettings>true</InjectSharedWorkflowsSettings>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Microsoft.Extensions.Configuration" />
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<PackageReference Include="Microsoft.Extensions.Configuration.Binder" />
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<PackageReference Include="Microsoft.Extensions.Configuration.EnvironmentVariables" />
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<PackageReference Include="Microsoft.Extensions.Configuration.Json" />
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<PackageReference Include="Microsoft.Extensions.Configuration.UserSecrets" />
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<PackageReference Include="Microsoft.Extensions.DependencyInjection" />
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<PackageReference Include="Microsoft.Extensions.Logging" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Workflows.Declarative\Microsoft.Agents.AI.Workflows.Declarative.csproj" />
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<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Workflows.Declarative.Foundry\Microsoft.Agents.AI.Workflows.Declarative.Foundry.csproj" />
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</ItemGroup>
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<ItemGroup>
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<None Include="InvokeHttpRequest.yaml">
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<CopyToOutputDirectory>Always</CopyToOutputDirectory>
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</None>
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</ItemGroup>
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</Project>
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@@ -0,0 +1,76 @@
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#
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# This workflow demonstrates using HttpRequestAction to call a REST API directly
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# from the workflow without going through an AI agent first.
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#
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# HttpRequestAction allows workflows to:
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# - Fetch data from external HTTP endpoints
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# - Store the parsed response in workflow variables for later use
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# - Add the response body to the conversation so a downstream agent can
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# answer questions based on it
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#
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# This sample fetches public metadata for the dotnet/runtime repository from
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# the GitHub REST API (no authentication required) and uses an agent to
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# answer follow-up questions about it.
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#
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# Example input:
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# How many subscribers does the repository have?
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#
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kind: Workflow
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trigger:
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kind: OnConversationStart
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id: workflow_invoke_http_request_demo
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actions:
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# Capture the original user message for input to the follow-up agent.
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- kind: SetVariable
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id: set_user_message
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variable: Local.InputMessage
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value: =System.LastMessage
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# Set the repository org/name used to form the request URL.
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- kind: SetVariable
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id: set_repo_name
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variable: Local.RepoName
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value: microsoft/agent-framework
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# Invoke the GitHub repo API. The response body is parsed into Local.RepoInfo
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# and also added to the conversation (via conversationId) so the agent below
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# can answer questions based on it.
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- kind: HttpRequestAction
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id: fetch_repo_info
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conversationId: =System.ConversationId
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method: GET
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url: =Concatenate("https://api.github.com/repos/", Local.RepoName)
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headers:
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Accept: application/vnd.github+json
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User-Agent: agent-framework-sample
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response: Local.RepoInfo
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# Display a confirmation message showing key fields from the parsed response.
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- kind: SendMessage
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id: show_repo_summary
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message: "Fetched repo: visibility={Local.RepoInfo.visibility}, description={Local.RepoInfo.description}"
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# Use the agent to summarize the repo using the conversation context.
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- kind: InvokeAzureAgent
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id: summarize_repo
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conversationId: =System.ConversationId
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agent:
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name: GitHubRepoInfoAgent
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input:
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messages: =UserMessage("Please provide a brief summary of this GitHub repository based on the data already in the conversation.")
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output:
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autoSend: true
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messages: Local.AgentResponse
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# Allow the user to ask follow-up questions about the repo in a loop.
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- kind: InvokeAzureAgent
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id: invoke_followup
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conversationId: =System.ConversationId
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agent:
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name: GitHubRepoInfoAgent
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input:
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messages: =Local.InputMessage
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externalLoop:
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when: =Upper(System.LastMessage.Text) <> "EXIT"
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@@ -0,0 +1,95 @@
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// Copyright (c) Microsoft. All rights reserved.
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using Azure.AI.Projects;
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using Azure.AI.Projects.Agents;
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using Azure.Identity;
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using Microsoft.Agents.AI.Workflows.Declarative;
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using Microsoft.Extensions.Configuration;
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using Shared.Foundry;
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using Shared.Workflows;
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namespace Demo.Workflows.Declarative.InvokeHttpRequest;
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/// <summary>
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/// Demonstrates a workflow that uses HttpRequestAction to call a REST API
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/// directly from the workflow.
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/// </summary>
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/// <remarks>
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/// <para>
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/// The HttpRequestAction allows workflows to issue HTTP requests and:
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/// </para>
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/// <list type="bullet">
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/// <item>Fetch data from external REST endpoints</item>
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/// <item>Store the parsed response in workflow variables</item>
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/// <item>Add the response body to the conversation so an agent can answer
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/// questions based on it</item>
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/// </list>
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/// <para>
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/// This sample fetches public metadata for the dotnet/runtime repository from
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/// the GitHub REST API (no authentication required) and uses a Foundry agent
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/// to answer follow-up questions about it. Type "EXIT" to end the conversation.
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/// </para>
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/// <para>
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/// See the README.md file in the parent folder (../README.md) for detailed
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/// information about the configuration required to run this sample.
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/// </para>
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/// </remarks>
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internal sealed class Program
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{
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public static async Task Main(string[] args)
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{
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// Initialize configuration
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IConfiguration configuration = Application.InitializeConfig();
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Uri foundryEndpoint = new(configuration.GetValue(Application.Settings.FoundryEndpoint));
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// Ensure sample agent exists in Foundry. The agent has no tools - it answers
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// questions about the GitHub repository using only the JSON data that the
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// HttpRequestAction adds to the conversation.
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await CreateAgentAsync(foundryEndpoint, configuration);
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// Get input from command line or console
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string workflowInput = Application.GetInput(args);
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// The default HttpRequestHandler is sufficient for this sample because the
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// GitHub REST endpoint used here does not require authentication. For
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// authenticated endpoints, supply a custom Func<HttpRequestInfo, ..., HttpClient?>
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// to DefaultHttpRequestHandler so each request can be routed through a
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// pre-configured (cached) HttpClient with the appropriate credentials.
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await using DefaultHttpRequestHandler httpRequestHandler = new();
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// Create the workflow factory with the HTTP request handler
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WorkflowFactory workflowFactory = new("InvokeHttpRequest.yaml", foundryEndpoint)
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{
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HttpRequestHandler = httpRequestHandler
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};
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// Execute the workflow
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WorkflowRunner runner = new() { UseJsonCheckpoints = true };
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await runner.ExecuteAsync(workflowFactory.CreateWorkflow, workflowInput);
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}
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private static async Task CreateAgentAsync(Uri foundryEndpoint, IConfiguration configuration)
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{
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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AIProjectClient aiProjectClient = new(foundryEndpoint, new DefaultAzureCredential());
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await aiProjectClient.CreateAgentAsync(
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agentName: "GitHubRepoInfoAgent",
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agentDefinition: DefineAgent(configuration),
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agentDescription: "Answers questions about a GitHub repository using HTTP response data in the conversation");
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}
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private static DeclarativeAgentDefinition DefineAgent(IConfiguration configuration)
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{
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return new DeclarativeAgentDefinition(configuration.GetValue(Application.Settings.FoundryModel))
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{
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Instructions =
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"""
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Answer the user's questions about the GitHub repository using only the
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JSON data already present in the conversation history.
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If the answer is not contained in the conversation, say so plainly
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rather than guessing. Be concise and helpful.
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"""
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};
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}
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}
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Reference in New Issue
Block a user