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54 lines
2.6 KiB
C#
54 lines
2.6 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to use HyperlightCodeActProvider with provider-owned
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// tools (exposed inside the sandbox via `call_tool(...)`). The model can
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// orchestrate those tools in a single Python block, reducing round-trips. A
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// sensitive tool (`send_email`) is additionally wrapped in
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// ApprovalRequiredAIFunction so any code that reaches it requires user approval
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// for the entire execute_code invocation.
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using Azure.AI.Projects;
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using Azure.Identity;
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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-mini";
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var guestPath = Environment.GetEnvironmentVariable("HYPERLIGHT_PYTHON_GUEST_PATH") ?? throw new InvalidOperationException("HYPERLIGHT_PYTHON_GUEST_PATH is not set.");
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AIFunction fetchDocs = AIFunctionFactory.Create(
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(string topic) => $"Docs for {topic}: (...)",
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name: "fetch_docs",
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description: "Fetch documentation for a given topic.");
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AIFunction queryData = AIFunctionFactory.Create(
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(string query) => $"Rows for `{query}`: []",
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name: "query_data",
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description: "Run a read-only SQL-like query against the sample store.");
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AIFunction sendEmail = new ApprovalRequiredAIFunction(
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AIFunctionFactory.Create(
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(string to, string subject) => $"Sent '{subject}' to {to}.",
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name: "send_email",
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description: "Send an email on behalf of the user."));
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var options = HyperlightCodeActProviderOptions.CreateForWasm(guestPath);
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options.Tools = [fetchDocs, queryData, sendEmail];
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using var codeAct = new HyperlightCodeActProvider(options);
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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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AIAgent agent = new AIProjectClient(
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new Uri(endpoint),
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new DefaultAzureCredential())
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.AsAIAgent(new ChatClientAgentOptions()
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{
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ChatOptions = new() { ModelId = deploymentName, Instructions = "You are a helpful assistant. Prefer orchestrating your work in a single `execute_code` block using `call_tool(...)` over issuing many direct tool calls." },
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AIContextProviders = [codeAct],
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});
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Console.WriteLine(await agent.RunAsync("Look up docs on 'retries' and query the 'orders' table, then summarize."));
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