syncfusion-react-inline-ai-assist

Integrate inline AI assistants with streaming prompts into React applications.

3|8|Updated Mar 25, 2026

Search Tags:#frontend #react #llm #syncfusion #prompt-management #ai-assist #inline-ai

Ready to run

npx skills add https://github.com/syncfusion/react-ui-components-skills --skill syncfusion-react-inline-ai-assist

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: syncfusion-react-inline-ai-assist
Source: https://github.com/syncfusion/react-ui-components-skills/tree/main/skills/syncfusion-react-inline-ai-assist
Command: npx skills add https://github.com/syncfusion/react-ui-components-skills --skill syncfusion-react-inline-ai-assist

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Inline AI Assist component solves the challenge of embedding AI-driven prompts directly inside React UIs, enabling real-time AI suggestions, content generation, and interactive prompts within your app without leaving the editing flow.

Core Features & Use Cases

Multi-AI service integrations: OpenAI, Google Gemini, Lite-LLM, and Ollama support for flexible backends.
Real-time prompt-response: Streaming capabilities to display content as it’s generated.
Command & Response actions: Predefined commands and custom response actions to automate tasks.
Inline toolbars and modes: Inline and popup response displays with customizable toolbars for richer interactions.
Event-driven patterns: Lifecycle events (created, promptRequest, open, close) and programmatic methods for fine-grained control.
Theming and i18n: Support for different themes and right-to-left languages.
Extensibility: Editor/template customization via editorTemplate, responseTemplate, and inline toolbar settings.

Quick Start

Install the Syncfusion Inline AI Assist into your React project and wire promptRequest to your AI backend to begin generating inline AI suggestions.

Frequently Asked Questions about syncfusion-react-inline-ai-assist

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I embed an inline AI assistant in a React application?▼

You can embed an inline AI assistant in a React application by installing the component, wiring the promptRequest event to your AI backend, and configuring templates. It supports streaming responses and customizable inline toolbars.

Can I use Google Gemini and Ollama for real-time AI prompts in React?▼

Yes, the component supports multi-AI service integrations including OpenAI, Google Gemini, Lite-LLM, and Ollama. You can wire the promptRequest event to your chosen provider to generate real-time AI prompts and streaming responses.

What is the best way to customize AI prompt responses and toolbars in React?▼

The best way to customize AI prompt responses and toolbars in React is using editorTemplate and responseTemplate extensibility options. You can define predefined commands, custom response actions, and configure inline or popup response displays with customizable toolbars.

Does this inline AI component support streaming responses and lifecycle events?▼

Yes, the inline AI component supports streaming responses to display content as it is generated and exposes lifecycle events including created, promptRequest, open, and close. These event-driven patterns provide fine-grained programmatic control over the assistant workflow.

How do I automate tasks with predefined commands in a React AI assistant?▼

You can automate tasks with predefined commands in a React AI assistant by configuring command and response actions within the component. This enables automated end-to-end workflows across modern web apps using programmatic methods and event-driven patterns.

Are there limitations when integrating multiple AI providers into a React UI?▼

The component does not impose inherent limitations when integrating multiple AI providers into a React UI, supporting OpenAI, Gemini, Lite-LLM, and Ollama. It also provides theming, internationalization, and right-to-left language support for diverse application contexts.