wehub-resource-sync
87 lines
3.4 KiB
C#
Executable File
87 lines
3.4 KiB
C#
Executable File
#!/usr/bin/dotnet run
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#:package Microsoft.Extensions.AI.Abstractions@9.9.1
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#:package Azure.AI.Agents.Persistent@1.2.0-beta.4
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#:package Azure.AI.OpenAI@2.1.0
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#:package Azure.Identity@1.15.0
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#:package System.Linq.Async@6.0.3
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#:package Microsoft.Extensions.AI@9.9.1
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#:package DotNetEnv@3.1.1
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#:package OpenTelemetry.Api@1.12.0
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#:package Microsoft.Agents.AI.Workflows@1.0.0-preview.251001.3
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#:package Microsoft.Agents.AI.OpenAI@1.0.0-preview.251001.2
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using System;
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using System.Text.Json;
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using System.Text.Json.Serialization;
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using Microsoft.Extensions.AI;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Workflows;
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using Azure.AI.OpenAI;
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using Azure.Identity;
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using DotNetEnv;
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// Load environment variables
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Env.Load("../../../.env");
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// Azure OpenAI with the Responses API (stable v1 endpoint). Sign in with `az login`.
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var azureEndpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
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?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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var deployment = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT") ?? "gpt-4o-mini";
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var azureClient = new AzureOpenAIClient(new Uri(azureEndpoint), new AzureCliCredential());
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// Define agent roles and instructions
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const string REVIEWER_NAME = "Concierge";
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const string REVIEWER_INSTRUCTIONS = @"""
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You are an are hotel concierge who has opinions about providing the most local and authentic experiences for travelers.
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The goal is to determine if the front desk travel agent has recommended the best non-touristy experience for a traveler.
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If so, state that it is approved.
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If not, provide insight on how to refine the recommendation without using a specific example.
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""";
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const string FRONTDESK_NAME = "FrontDesk";
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const string FRONTDESK_INSTRUCTIONS = @"""
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You are a Front Desk Travel Agent with ten years of experience and are known for brevity as you deal with many customers.
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The goal is to provide the best activities and locations for a traveler to visit.
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Only provide a single recommendation per response.
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You're laser focused on the goal at hand.
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Don't waste time with chit chat.
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Consider suggestions when refining an idea.
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""";
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// Create agent options
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ChatClientAgentOptions frontdeskAgentOptions = new(name: FRONTDESK_NAME, instructions: FRONTDESK_INSTRUCTIONS);
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ChatClientAgentOptions reviewerAgentOptions = new(name: REVIEWER_NAME, instructions: REVIEWER_INSTRUCTIONS);
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// Create agents
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AIAgent reviewerAgent = azureClient.GetOpenAIResponseClient(deployment).CreateAIAgent(
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reviewerAgentOptions);
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AIAgent frontdeskAgent = azureClient.GetOpenAIResponseClient(deployment).CreateAIAgent(
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frontdeskAgentOptions);
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// Build workflow with agent coordination
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var workflow = new WorkflowBuilder(frontdeskAgent)
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.AddEdge(frontdeskAgent, reviewerAgent)
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.Build();
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// Execute workflow with streaming
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StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, "I would like to go to Paris."));
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await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
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string strResult = "";
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// Process streaming events
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await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false))
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{
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if (evt is AgentRunUpdateEvent executorComplete)
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{
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strResult += executorComplete.Data;
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Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
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}
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}
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// Display final result
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Console.WriteLine("\nFinal Result:");
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Console.WriteLine(strResult);
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