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{
  "autoentities": {
    "public-api": {
      "patterns": {
        "include": [ "dbo.%" ],
        "exclude": [ "dbo.internal%", "dbo.__migration%" ],
        "name": "{schema}_{object}"
      },
      "template": {
        "rest": { "enabled": true },

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<!--Update the SDK version below 👇-->
<Project Sdk="Aspire.AppHost.Sdk/13.2.2">
 
  <PropertyGroup>
    <OutputType>Exe</OutputType>
    <TargetFramework>net10.0</TargetFramework>
    <ImplicitUsings>enable</ImplicitUsings>
    <Nullable>enable</Nullable>
  </PropertyGroup>
 

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app.MapPost("/api/workflow/run", async (WorkflowRequest request, [FromKeyedServices("ContentReviewWorkflow")] Workflow workflow) =>
{
    Run run = await InProcessExecution.RunAsync(workflow, request.Input);
    WorkflowEvent result = null;
    foreach (WorkflowEvent evt in run.OutgoingEvents)
    {
        if (evt is WorkflowOutputEvent response)
        {
            result = evt;
        }

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var reviewerAgentName = "Reviewer";
var reviewerInstructions = "You are a content editor. Give 2-3 bullet points of actionable feedback on the draft you receive. Be specific and concise.";
var writerAgentName = "Writer";
var writerInstructions = "You are a content writer. Write a clear, engaging paragraph on the topic provided. Be concise — 3-5 sentences.";

var reviewerAgentBuilder = builder.AddAIAgent(reviewerAgentName, reviewerInstructions);
var writerAgentBuilder = builder.AddAIAgent(writerAgentName, writerInstructions);


// The workflow name shows up in the DevUI sidebar

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// ── 1. Configure the chat client (Ollama endpoint) ──────────
// Configuration - Ollama endpoint and model selection
var endpoint = "http://localhost:11434";  // Default Ollama endpoint
var modelName = "llama3.2";              // Model to use for AI responses
using OllamaApiClient chatClient = new(new Uri(endpoint), modelName);
builder.Services.AddChatClient(chatClient);

// ── 2. Create agents for the workflow ───────────────────────────
var reviewerAgentName = "Reviewer";
var reviewerInstructions = "You are a content editor. Give 2-3 bullet points of actionable feedback on the draft you receive. Be specific and concise.";

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using Microsoft.Agents.AI.Workflows;

namespace AgentFramework.DevUI.Example
{
    internal sealed partial class FormatterExecutor(): Executor("FormatterExecutor")
    {
        protected override ProtocolBuilder ConfigureProtocol(ProtocolBuilder protocolBuilder)
        {
            return protocolBuilder;
        }

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using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Workflows;

namespace AgentFramework.DevUI.Example
{
    internal sealed partial class ReviewerExecutor(AIAgent agent): Executor("ReviewerExecutor")
    {
        protected override ProtocolBuilder ConfigureProtocol(ProtocolBuilder protocolBuilder)
        {
            return protocolBuilder;

wullemsb

using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Workflows;
using Microsoft.Extensions.AI;
namespace AgentFramework.DevUI.Example
{
    internal sealed partial class WriterExecutor(AIAgent agent) : Executor("WriterExecutor")
    {
        protected override ProtocolBuilder ConfigureProtocol(ProtocolBuilder protocolBuilder)
        {
            return protocolBuilder;

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// Define tool functions
static string GetWeather(string city) => $"Weather in {city}: 18°C, partly cloudy."; // Replace with real API call
static string GetForecast(string city, int days) => $"{days}-day forecast for {city}: mostly sunny with occasional showers.";

// Create tool descriptors
var weatherTools = new[]
{
    AIFunctionFactory.Create(GetWeather, "get_weather", "Get the current weather for a city"),
    AIFunctionFactory.Create(GetForecast, "get_forecast", "Get a multi-day weather forecast"),
};

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using Microsoft.Agents.AI.DevUI;
using Microsoft.Agents.AI.Hosting;
using Microsoft.AspNetCore.Mvc.ModelBinding;
using Microsoft.Extensions.AI;
using OllamaSharp;
using OpenTelemetry.Resources;
using System.Net;

var builder = WebApplication.CreateBuilder(args);