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This commit is contained in:
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// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates a HarnessAgent with ALL features enabled, plus:
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// - Hyperlight CodeAct (HyperlightCodeActProvider) for sandboxed Python code execution
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// - Skills (AgentSkillsProvider) discovering a local "regex-tester" skill
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//
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// The agent can plan tasks with todos, manage modes, store memories, read/write files,
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// search the web, approve sensitive tools, discover and use skills, and execute arbitrary
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// Python code in a Hyperlight sandbox — all pre-configured by the HarnessAgent.
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//
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// Try asking: "Help me write a regex that matches valid email addresses, then test it."
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//
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// Special commands:
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// /todos — Display the current todo list without invoking the agent.
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// /mode — Get or set the current agent mode.
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// /exit — End the session.
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#pragma warning disable OPENAI001 // Suppress experimental API warnings for Responses API usage.
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#pragma warning disable MAAI001 // Suppress experimental API warnings for Agents AI experiments.
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using System.ClientModel.Primitives;
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using Azure.AI.Projects;
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using Azure.Identity;
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using Harness.Shared.Console;
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using HyperlightSandbox.Guest.Python;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Hyperlight;
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using Microsoft.Extensions.AI;
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var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4";
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const int MaxContextWindowTokens = 1_050_000;
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const int MaxOutputTokens = 128_000;
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const string TracingSourceName = "Harness.CodeExecution";
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// Set up OpenTelemetry tracing that writes spans to a text file.
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using var tracerProvider = HarnessTracing.CreateFileTracerProvider(TracingSourceName);
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// Create the HyperlightCodeActProvider with the Python/Wasm backend.
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// The guest module path is resolved automatically from the Hyperlight.HyperlightSandbox.Guest.Python NuGet package.
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using var codeAct = new HyperlightCodeActProvider(
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HyperlightCodeActProviderOptions.CreateForWasm(PythonGuestModule.GetModulePath()));
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var instructions =
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"""
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## Technical Assistant Instructions
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You are a code-powered technical assistant. You can execute Python code in a sandboxed environment
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to solve problems precisely rather than guessing. You also have access to skills that provide
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structured workflows for specific technical tasks.
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### Code Execution
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When a problem requires computation, validation, or testing:
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- Write Python code and use `execute_code` to run it in the sandbox.
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- Always verify results by running the code rather than reasoning about what would happen.
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- If code fails, read the error message carefully, fix the issue, and retry.
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### Skills
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You have access to discoverable skills. When a task matches a skill's description:
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- Follow the skill's instructions carefully.
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- Use the skill's reference materials for context.
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- Combine the skill's workflow with code execution when appropriate.
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### Planning and Research
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For complex tasks:
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- Break the problem into steps using your todo list.
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- Research background information using web search when needed.
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- Save important findings to file memory for later reference.
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### Presenting Results
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- Show your work: include the code you ran and its output.
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- Explain what each part of your solution does.
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- If applicable, save final results to file memory.
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""";
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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// Create the agent with ALL HarnessAgent features enabled plus Hyperlight CodeAct.
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// No Disable* flags are set — TodoProvider, AgentModeProvider, FileMemory, FileAccess,
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// ToolApproval, WebSearch, and AgentSkillsProvider are all active.
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AIAgent agent =
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new AIProjectClient(
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new Uri(endpoint),
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new DefaultAzureCredential(),
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new AIProjectClientOptions { RetryPolicy = new ClientRetryPolicy(3) })
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.GetProjectOpenAIClient()
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.GetResponsesClient()
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.AsIChatClient(deploymentName)
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.AsHarnessAgent(new HarnessAgentOptions
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{
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MaxContextWindowTokens = MaxContextWindowTokens,
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MaxOutputTokens = MaxOutputTokens,
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Name = "CodeExecutionAgent",
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Description = "A technical assistant with sandboxed code execution and skill-based workflows.",
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OpenTelemetrySourceName = TracingSourceName,
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// Point the file memory at a local folder for persistent memory across sessions.
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FileMemoryStore = new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "agent-files")),
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// Add the HyperlightCodeActProvider so the agent can execute Python code in a sandbox.
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AIContextProviders = [codeAct],
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ChatOptions = new ChatOptions
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{
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Instructions = instructions,
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MaxOutputTokens = MaxOutputTokens,
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Reasoning = new() { Effort = ReasoningEffort.Medium },
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},
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});
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// Run the interactive console session using the shared HarnessConsole helper.
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await HarnessConsole.RunAgentAsync(
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agent,
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userPrompt: "Ask me a technical question, or try: \"Help me write a regex that matches valid email addresses.\"",
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new HarnessConsoleOptions
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{
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Observers = HarnessConsoleOptions.BuildObserversWithPlanning(
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agent,
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planModeName: "plan",
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executionModeName: "execute",
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maxContextWindowTokens: MaxContextWindowTokens,
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maxOutputTokens: MaxOutputTokens),
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CommandHandlers = HarnessConsoleOptions.BuildDefaultCommandHandlers(agent),
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});
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