// Copyright (c) Microsoft. All rights reserved.

// Translation Chain Workflow Agent — demonstrates how to compose multiple AI agents
// into a sequential workflow pipeline. Three translation agents are connected:
// English → French → Spanish → English, showing how agents can be orchestrated
// as workflow executors in a hosted agent.

using Azure.AI.Projects;
using Azure.Core;
using Azure.Identity;
using DotNetEnv;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Foundry.Hosting;
using Microsoft.Agents.AI.Workflows;
using Microsoft.Extensions.AI;

// Load .env file if present (for local development)
Env.TraversePath().Load();

string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
    ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o";

// Use a chained credential: try a temporary dev token first (for local Docker debugging),
// then fall back to DefaultAzureCredential (for local dev via dotnet run / managed identity in production).
TokenCredential credential = new ChainedTokenCredential(
    new DevTemporaryTokenCredential(),
    new DefaultAzureCredential());

// Create a chat client from the Foundry project
IChatClient chatClient = new AIProjectClient(new Uri(endpoint), credential)
    .GetProjectOpenAIClient()
    .GetChatClient(deploymentName)
    .AsIChatClient();

// Create translation agents
AIAgent frenchAgent = chatClient.AsAIAgent("You are a translation assistant that translates the provided text to French.");
AIAgent spanishAgent = chatClient.AsAIAgent("You are a translation assistant that translates the provided text to Spanish.");
AIAgent englishAgent = chatClient.AsAIAgent("You are a translation assistant that translates the provided text to English.");

// Build the sequential workflow: French → Spanish → English
AIAgent agent = new WorkflowBuilder(frenchAgent)
    .AddEdge(frenchAgent, spanishAgent)
    .AddEdge(spanishAgent, englishAgent)
    .Build()
    .AsAIAgent(
        name: Environment.GetEnvironmentVariable("AGENT_NAME") ?? "hosted-workflows");

// Host the workflow agent as a Foundry Hosted Agent using the Responses API.
var builder = WebApplication.CreateBuilder(args);
builder.Services.AddFoundryResponses(agent);

var app = builder.Build();
app.MapFoundryResponses();

if (app.Environment.IsDevelopment())
{
    app.MapFoundryResponses("openai/v1");
}

app.Run();

/// <summary>
/// A <see cref="TokenCredential"/> for local Docker debugging only.
/// Reads a pre-fetched bearer token from the <c>AZURE_BEARER_TOKEN</c> environment variable
/// once at startup. This should NOT be used in production.
///
/// Generate a token on your host and pass it to the container:
///   export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
///   docker run -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN ...
/// </summary>
internal sealed class DevTemporaryTokenCredential : TokenCredential
{
    private const string EnvironmentVariable = "AZURE_BEARER_TOKEN";
    private readonly string? _token;

    public DevTemporaryTokenCredential()
    {
        this._token = Environment.GetEnvironmentVariable(EnvironmentVariable);
    }

    public override AccessToken GetToken(TokenRequestContext requestContext, CancellationToken cancellationToken)
        => this.GetAccessToken();

    public override ValueTask<AccessToken> GetTokenAsync(TokenRequestContext requestContext, CancellationToken cancellationToken)
        => new(this.GetAccessToken());

    private AccessToken GetAccessToken()
    {
        if (string.IsNullOrEmpty(this._token) || this._token == "DefaultAzureCredential")
        {
            throw new CredentialUnavailableException($"{EnvironmentVariable} environment variable is not set.");
        }

        return new AccessToken(this._token, DateTimeOffset.UtcNow.AddHours(1));
    }
}