Openui Forge Csharp

OpenUI Forge — C#

Build generative UI apps with a React frontend + C# backend. Streams OpenAI API responses directly via an ASP.NET Core Minimal API (.NET 10 LTS) using HttpClient.

Activation Triggers

• "openui csharp", "openui c#", "openui dotnet", "openui aspnet"
• "generative ui csharp", "c# streaming ui backend", "asp.net core openui"

Prerequisites

• Node.js >= 22 (24 LTS recommended) + React >= 18.3.1 (19+ recommended) (frontend)
• .NET SDK 10.0 (backend; .NET 10 is the current LTS, supported until Nov 2028. .NET 8 LTS also works but reaches end of support Nov 2026.)
• OPENAI_API_KEY environment variable set

Quick Start

1. Create the React frontend and install OpenUI deps:

npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod

2. Generate the system prompt:

npx @openuidev/cli generate ./src/lib/library.ts --out backend/system-prompt.txt

3. Create the C# backend (see Full Code below)
4. Run: dotnet run on :5000, frontend on :3000

Full Code

Backend: backend/openui-backend.csproj

<Project Sdk="Microsoft.NET.Sdk.Web">
  <PropertyGroup>
    <TargetFramework>net10.0</TargetFramework>
    <Nullable>enable</Nullable>
    <ImplicitUsings>enable</ImplicitUsings>
  </PropertyGroup>
</Project>

No NuGet packages required. ASP.NET Core, HttpClient/IHttpClientFactory, and System.Text.Json all ship in the .NET 10 shared framework referenced by Microsoft.NET.Sdk.Web.

Backend: backend/Program.cs

using System.Text;
using System.Text.Json;
using System.Text.Json.Serialization;

var builder = WebApplication.CreateBuilder(args);

// Pooled, correctly-disposed HttpClient instances. Infinite timeout because
// this is a long-lived streaming proxy; client disconnects cancel the request.
builder.Services.AddHttpClient("openai", client =>
{
    client.Timeout = Timeout.InfiniteTimeSpan;
});

// CORS: lock to the configured frontend origin. Do NOT use AllowAnyOrigin —
// a wildcard would let any site call this backend and burn your API key.
var frontendOrigin =
    Environment.GetEnvironmentVariable("FRONTEND_ORIGIN") ?? "http://localhost:3000";

builder.Services.AddCors(options =>
{
    options.AddDefaultPolicy(policy =>
        policy.WithOrigins(frontendOrigin)
              .WithMethods("POST", "OPTIONS")
              .AllowAnyHeader());
});

var app = builder.Build();

app.UseCors();

// Load the generated system prompt ONCE at startup; fail fast if missing.
var promptPath = Path.Combine(Directory.GetCurrentDirectory(), "system-prompt.txt");
if (!File.Exists(promptPath))
{
    throw new FileNotFoundException(
        "system-prompt.txt not found. Generate it with: " +
        "npx @openuidev/cli generate ./src/lib/library.ts --out system-prompt.txt",
        promptPath);
}
var systemPrompt = await File.ReadAllTextAsync(promptPath);

var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY");
var baseUrl = (Environment.GetEnvironmentVariable("OPENAI_BASE_URL") ?? "https://api.openai.com/v1")
    .TrimEnd('/');
var model = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-5.5";

app.MapPost("/api/chat", async (ChatRequest req, IHttpClientFactory httpClientFactory, HttpContext ctx) =>
{
    if (string.IsNullOrEmpty(apiKey))
        return Results.Json(new { error = "OPENAI_API_KEY not set" }, statusCode: 500);
    if (req.Messages is null || req.Messages.Length == 0)
        return Results.Json(new { error = "messages must be a non-empty array" }, statusCode: 400);

    // Prepend the server-side system prompt; never trust the client to supply it.
    var messages = new List<ChatMessage> { new("system", systemPrompt) };
    messages.AddRange(req.Messages);

    var payload = JsonSerializer.Serialize(new OpenAiRequest(model, true, messages));

    using var upstreamRequest = new HttpRequestMessage(
        HttpMethod.Post, $"{baseUrl}/chat/completions")
    {
        Content = new StringContent(payload, Encoding.UTF8, "application/json"),
    };
    upstreamRequest.Headers.Add("Authorization", $"Bearer {apiKey}");

    var client = httpClientFactory.CreateClient("openai");

    // ResponseHeadersRead returns as soon as headers arrive, so we read the
    // body incrementally off the socket instead of buffering it into memory.
    var upstream = await client.SendAsync(
        upstreamRequest, HttpCompletionOption.ResponseHeadersRead, ctx.RequestAborted);

    if (!upstream.IsSuccessStatusCode)
    {
        var errorBody = await upstream.Content.ReadAsStringAsync(ctx.RequestAborted);
        upstream.Dispose();
        return Results.Json(
            new { error = $"OpenAI returned {(int)upstream.StatusCode}: {errorBody}" },
            statusCode: (int)upstream.StatusCode);
    }

    return Results.Extensions.SseProxy(upstream);
});

app.Run();

// SSE passthrough: forward OpenAI's native `data: {chunk}\n\n` lines verbatim,
// flushing after each so tokens appear as they arrive. Pair with openAIAdapter().
//
// Idiomatic .NET 10 alternative: if you parse each chunk into a typed payload,
// return TypedResults.ServerSentEvents(IAsyncEnumerable<SseItem<T>>) from
// System.Net.ServerSentEvents — the framework writes the SSE framing for you.
// We keep the raw passthrough because the upstream is ALREADY valid SSE.
static class ResultExtensions
{
    public static IResult SseProxy(this IResultExtensions _, HttpResponseMessage upstream)
        => new SseProxyResult(upstream);
}

sealed class SseProxyResult(HttpResponseMessage upstream) : IResult
{
    public async Task ExecuteAsync(HttpContext httpContext)
    {
        var response = httpContext.Response;
        response.StatusCode = 200;
        response.ContentType = "text/event-stream";
        response.Headers.CacheControl = "no-cache";
        response.Headers.Connection = "keep-alive";
        response.Headers["X-Accel-Buffering"] = "no"; // defeat proxy buffering

        try
        {
            await using var upstreamStream =
                await upstream.Content.ReadAsStreamAsync(httpContext.RequestAborted);
            using var reader = new StreamReader(upstreamStream, Encoding.UTF8);

            while (await reader.ReadLineAsync(httpContext.RequestAborted) is { } line)
            {
                if (line.Length == 0) continue; // re-emit our own framing below

                await response.WriteAsync(line + "\n", httpContext.RequestAborted);
                if (line.StartsWith("data:", StringComparison.Ordinal))
                    await response.WriteAsync("\n", httpContext.RequestAborted);
                await response.Body.FlushAsync(httpContext.RequestAborted);

                if (line == "data: [DONE]") break;
            }
        }
        catch (OperationCanceledException)
        {
            // Client aborted — nothing to do.
        }
        finally
        {
            upstream.Dispose();
        }
    }
}

// JsonPropertyName pins wire names to lowercase: incoming binding is
// case-insensitive, but Serialize defaults to PascalCase and OpenAI needs
// lowercase role/content/model.
record ChatMessage(
    [property: JsonPropertyName("role")] string Role,
    [property: JsonPropertyName("content")] string Content);

record ChatRequest(
    [property: JsonPropertyName("messages")] ChatMessage[] Messages);

record OpenAiRequest(
    [property: JsonPropertyName("model")] string Model,
    [property: JsonPropertyName("stream")] bool Stream,
    [property: JsonPropertyName("messages")] List<ChatMessage> Messages);

Frontend: app/chat/page.tsx

"use client";
import { FullScreen } from "@openuidev/react-ui";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import {
  openAIAdapter,
  openAIMessageFormat,
} from "@openuidev/react-headless";

export default function ChatPage() {
  return (
    <FullScreen
      componentLibrary={openuiChatLibrary}
      streamProtocol={openAIAdapter()}
      messageFormat={openAIMessageFormat}
      apiUrl="http://localhost:5000/api/chat"
    />
  );
}

The C# backend forwards OpenAI's SSE stream line-by-line with a StreamReader loop, calling Response.Body.FlushAsync() after each line (no CopyToAsync buffering), so the client sees tokens as they arrive. Pair it with openAIAdapter() on the frontend. openAIReadableStreamAdapter() is for NDJSON (no data: prefix) and will silently produce no output here.

HttpCompletionOption.ResponseHeadersRead is the key to incremental streaming: it returns control once the upstream headers arrive instead of buffering the whole response body into memory first.

An official OpenAI .NET SDK exists (OpenAI on NuGet) as an alternative to hand-rolling the HTTP call. This skill keeps raw HttpClient as the dependency-free default (everything used here ships in the .NET 10 shared framework). .NET 10 also added a native typed SSE result, TypedResults.ServerSentEvents (from System.Net.ServerSentEvents), which writes the data: framing for you when you yield strongly-typed SseItem<T> values — use it if you want to parse and reshape chunks rather than pass them through.

System Prompt Generation

npx @openuidev/cli generate ./src/lib/library.ts --out backend/system-prompt.txt

Validation Checklist

• system-prompt.txt exists in the C# backend directory (next to the .csproj)
• OPENAI_API_KEY is set in environment (.env is not auto-loaded; export it or use dotnet user-secrets)
• OPENAI_BASE_URL honored for OpenAI-compatible providers (defaults to https://api.openai.com/v1)
• CORS policy allows the frontend origin via WithOrigins(FRONTEND_ORIGIN) (not AllowAnyOrigin)
• Response streams SSE directly from OpenAI API (passthrough), Content-Type: text/event-stream
• HttpCompletionOption.ResponseHeadersRead used so the body is not buffered
• Response.Body.FlushAsync() called after each line
• Frontend apiUrl points to http://localhost:5000/api/chat
• Frontend uses streamProtocol={openAIAdapter()} and openAIMessageFormat
• componentLibrary={openuiChatLibrary} prop passed to FullScreen
• CSS import in root layout (@openuidev/react-ui/components.css)

Error Patterns