syncfusion-winforms-ai-assistview

Q: How do I install syncfusion-winforms-ai-assistview?

Run npx skills add https://github.com/syncfusion/winforms-ui-components-skills --skill syncfusion-winforms-ai-assistview in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/syncfusion-winforms-ai-assistview/ (personal) or .claude/skills/syncfusion-winforms-ai-assistview/ (project).

by syncfusionAI & Agents

Guide for implementing Syncfusion Windows Forms AI AssistView (SfAIAssistView) for building conversational AI interfaces in desktop applications. Use this when creating chat interfaces, AI assistants, or chatbots with Windows Forms. Supports OpenAI and Azure OpenAI integration, typing indicators, chat suggestions, message bubbles, and custom views for interactive messaging experiences.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/syncfusion/winforms-ui-components-skills --skill syncfusion-winforms-ai-assistview

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads syncfusion-winforms-ai-assistview automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Implementing AI AssistView

The Syncfusion Windows Forms AI AssistView (SfAIAssistView) is a sophisticated conversational interface control for building AI-powered chat applications with support for suggestions, typing indicators, custom views, and seamless OpenAI/ChatGPT integration.

When to Use This Skill

Use this skill when the user needs to:

Build AI-powered chat interfaces in Windows Forms applications
Integrate OpenAI, ChatGPT, or Azure OpenAI services into desktop apps
Create conversational UI with message bubbles and chat history
Display AI-driven response suggestions for quick user responses
Show typing indicators during async AI response generation
Customize chat message appearance with custom BotView and UserView
Handle user prompts with validation and custom actions
Build intelligent assistants with banner customization
Implement real-time chat experiences with data binding

Component Overview

Key Features:

Suggestions: Display selectable response suggestions to expedite conversation flow
Typing Indicator: Show loading animation during AI processing
Banner Customization: Customizable header with welcome messages and AI service info
Custom Views: Create custom BotView and UserView for message presentation
Theme Support: Automatic light/dark theme adaptation
OpenAI Integration: Seamless connection with OpenAI services via Semantic Kernel
Events: PromptRequest event for input validation and custom actions
Data Binding: Full support for ObservableCollection and INotifyPropertyChanged

Documentation and Navigation Guide

Getting Started

📄 Read: references/getting-started.md

Assembly deployment and NuGet packages
Creating Windows Forms project with SfAIAssistView
Adding control via Designer and Code
Creating ViewModel with message collection
Message binding and Author configuration
Basic chat implementation

Suggestions

📄 Read: references/suggestions.md

Displaying AI-driven suggestions
Binding suggestions to ViewModel
Quick response scenarios
Dynamic suggestion updates

Typing Indicator

📄 Read: references/typing-indicator.md

ShowTypingIndicator property
Async communication feedback
Customizing indicator appearance
Author and DisplayText configuration

Customization

📄 Read: references/customization.md

BannerView customization with SetBannerView
Creating custom BotView with SetBotView
Creating custom UserView with SetUserView
Interactive buttons in bot responses
Custom styling and layouts

Events

📄 Read: references/events.md

PromptRequest event handling
Input validation
Custom action triggers
Handled property usage

OpenAI Integration

📄 Read: references/openai-integration.md

Connecting to OpenAI/ChatGPT
Microsoft Semantic Kernel setup
API credentials configuration
NonStreamingChat implementation
Async response handling
Complete working example

Quick Start Example

Basic Chat Interface

using Syncfusion.WinForms.AIAssistView;
using System.ComponentModel;
using System.Collections.ObjectModel;

namespace AIAssistViewDemo
{
    public partial class Form1 : Form
    {
        ViewModel viewModel;
        
        public Form1()
        {
            InitializeComponent();
            viewModel = new ViewModel();
            
            // Create AI AssistView
            SfAIAssistView sfAIAssistView1 = new SfAIAssistView();
            sfAIAssistView1.Dock = DockStyle.Fill;
            this.Controls.Add(sfAIAssistView1);
            
            // Bind messages
            sfAIAssistView1.DataBindings.Add("Messages", viewModel, "Chats", 
                true, DataSourceUpdateMode.OnPropertyChanged);
        }
    }
    
    // ViewModel
    public class ViewModel : INotifyPropertyChanged
    {
        private ObservableCollection<object> chats;
        private Author currentUser;
        
        public ViewModel()
        {
            this.Chats = new ObservableCollection<object>();
            this.CurrentUser = new Author { Name = "John" };
            this.GenerateMessages();
        }
        
        private async void GenerateMessages()
        {
            // User message
            this.Chats.Add(new TextMessage 
            { 
                Author = CurrentUser, 
                Text = "What is Windows Forms?" 
            });
            
            await Task.Delay(1000);
            
            // Bot response
            this.Chats.Add(new TextMessage 
            { 
                Author = new Author { Name = "Bot" }, 
                Text = "Windows Forms is a GUI framework for building Windows desktop applications." 
            });
        }
        
        public ObservableCollection<object> Chats
        {
            get => this.chats;
            set
            {
                this.chats = value;
                RaisePropertyChanged("Chats");
            }
        }
        
        public Author CurrentUser
        {
            get => this.currentUser;
            set
            {
                this.currentUser = value;
                RaisePropertyChanged("CurrentUser");
            }
        }
        
        public event PropertyChangedEventHandler PropertyChanged;
        
        public void RaisePropertyChanged(string propName)
        {
            PropertyChanged?.Invoke(this, new PropertyChangedEventArgs(propName));
        }
    }
}

Common Patterns

Pattern 1: Chat with Suggestions

// In ViewModel
private IEnumerable<string> suggestion;

public IEnumerable<string> Suggestion
{
    get => this.suggestion;
    set
    {
        this.suggestion = value;
        RaisePropertyChanged("Suggestion");
    }
}

// Set suggestions after bot response
Suggestion = new ObservableCollection<string> 
{ 
    "Tell me more", 
    "What are alternatives?" 
};

// In Form
sfAIAssistView1.DataBindings.Add("Suggestions", viewModel, "Suggestion", 
    true, DataSourceUpdateMode.OnPropertyChanged);

Pattern 2: Typing Indicator During AI Processing

// In ViewModel
private bool showTypingIndicator;

public bool ShowTypingIndicator
{
    get => this.showTypingIndicator;
    set
    {
        this.showTypingIndicator = value;
        RaisePropertyChanged("ShowTypingIndicator");
    }
}

// Usage
ShowTypingIndicator = true;
var response = await GetAIResponse(userMessage);
Chats.Add(new TextMessage { Author = botAuthor, Text = response });
ShowTypingIndicator = false;

// In Form
sfAIAssistView1.DataBindings.Add("ShowTypingIndicator", viewModel, 
    "ShowTypingIndicator", true, DataSourceUpdateMode.OnPropertyChanged);
    
sfAIAssistView1.TypingIndicator.Author = new Author 
{ 
    Name = "Bot", 
    AvatarImage = Image.FromFile(@"Assets\bot.png") 
};
sfAIAssistView1.TypingIndicator.DisplayText = "Typing";

Pattern 3: Custom Banner

BannerStyle customStyle = new BannerStyle
{
    TitleFont = new Font("Segoe UI", 14F, FontStyle.Bold),
    SubTitleFont = new Font("Segoe UI", 12F, FontStyle.Italic),
    ImageSize = AvatarSize.Medium,
    SubTitleColor = Color.Gray,
    TitleColor = Color.DarkBlue
};

string title = "AI Assistant";
string subTitle = "Powered by OpenAI";
sfAIAssistView1.SetBannerView(title, subTitle, 
    Image.FromFile(@"Assets\ai-icon.png"), customStyle);

Pattern 4: Prompt Validation

sfAIAssistView1.PromptRequest += (sender, e) =>
{
    var message = e.Message as TextMessage;
    if (message == null) return;
    
    // Validate input
    if (string.IsNullOrWhiteSpace(message.Text))
    {
        e.Handled = true; // Prevent adding to messages
        MessageBox.Show("Please enter a message.");
        return;
    }
    
    // Custom processing
    LogUserInput(message.Text);
};

Key Properties and Methods

Property/Method	Type	Description
`Messages`	ObservableCollection<object>	Chat message collection
`Suggestions`	IEnumerable<string>	Response suggestion items
`ShowTypingIndicator`	bool	Shows/hides typing indicator
`TypingIndicator`	TypingIndicator	Typing indicator configuration
`User`	Author	Current user information
`SetBannerView()`	Method	Customize banner appearance
`SetBotView()`	Method	Set custom bot message view
`SetUserView()`	Method	Set custom user message view
`PromptRequest`	Event	Fires when user submits prompt

Common Use Cases

Use Case 1: Customer Support Chatbot

Build an AI-powered customer support interface with suggestion chips for common questions and typing indicators during response generation.

Use Case 2: Virtual Assistant

Create an intelligent desktop assistant with custom branded banner, personalized bot responses, and OpenAI integration for natural conversations.

Use Case 3: Interactive Documentation

Implement a conversational documentation browser where users ask questions about software features and receive AI-generated explanations.

Use Case 4: Training Simulator

Build interactive training applications where AI guides users through procedures with step-by-step conversational instructions.

Installation

Install-Package Syncfusion.SfAIAssistView.WinForms

For OpenAI integration:

Install-Package Microsoft.SemanticKernel

Troubleshooting

Messages not displaying:

Verify data binding is set correctly
Ensure ObservableCollection is used (not List<T>)
Check that RaisePropertyChanged is called on collection updates

Typing indicator not showing:

Set ShowTypingIndicator = true before async operation
Configure TypingIndicator.Author property
Ensure binding is established for ShowTypingIndicator

Suggestions not appearing:

Bind Suggestions property to ViewModel
Use IEnumerable<string> type
Update suggestions after bot responses

OpenAI connection issues:

Verify API key is valid and not expired
Check API endpoint URL is correct
Ensure Microsoft.SemanticKernel NuGet is installed
Confirm network connectivity

FAQ

What does the syncfusion-winforms-ai-assistview skill do?

How do I install syncfusion-winforms-ai-assistview?

Run npx skills add https://github.com/syncfusion/winforms-ui-components-skills --skill syncfusion-winforms-ai-assistview in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/syncfusion-winforms-ai-assistview/ (personal) or .claude/skills/syncfusion-winforms-ai-assistview/ (project).

Which AI agents can use syncfusion-winforms-ai-assistview?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is syncfusion-winforms-ai-assistview safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains syncfusion-winforms-ai-assistview?

It is published by syncfusion in syncfusion/winforms-ui-components-skills. It has 79 recorded installs.