cool-tool-692 / components /ChatInterface.js
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import { useState, useRef, useEffect } from 'react'
import { Send, Loader2, MessageCircle } from 'lucide-react'
import ReactMarkdown from 'react-markdown'
import rehypeHighlight from 'rehype-highlight'
export default function ChatInterface() {
const [messages, setMessages] = useState([
{
id: 1,
role: 'assistant',
content: "Hello! I'm your AI assistant. I can help you with questions, have conversations, provide explanations, and assist with various topics. What would you like to talk about?",
timestamp: new Date().toISOString()
}
])
const [inputMessage, setInputMessage] = useState('')
const [isLoading, setIsLoading] = useState(false)
const messagesEndRef = useRef(null)
const inputRef = useRef(null)
const scrollToBottom = () => {
messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' })
}
useEffect(() => {
scrollToBottom()
}, [messages])
const handleSubmit = async (e) => {
e.preventDefault()
if (!inputMessage.trim() || isLoading) return
const userMessage = {
id: Date.now(),
role: 'user',
content: inputMessage.trim(),
timestamp: new Date().toISOString()
}
setMessages(prev => [...prev, userMessage])
setInputMessage('')
setIsLoading(true)
try {
const response = await fetch('/api/chat', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
message: userMessage.content,
messages: messages.filter(m => m.role !== 'system')
}),
})
if (!response.ok) {
throw new Error('Failed to get response')
}
const data = await response.json()
const assistantMessage = {
id: Date.now() + 1,
role: 'assistant',
content: data.message,
timestamp: data.timestamp || new Date().toISOString()
}
setMessages(prev => [...prev, assistantMessage])
} catch (error) {
console.error('Chat error:', error)
const errorMessage = {
id: Date.now() + 1,
role: 'assistant',
content: "I apologize, but I'm having trouble connecting right now. Please try again in a moment.",
timestamp: new Date().toISOString()
}
setMessages(prev => [...prev, errorMessage])
} finally {
setIsLoading(false)
inputRef.current?.focus()
}
}
const handleKeyPress = (e) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault()
handleSubmit(e)
}
}
const formatTime = (timestamp) => {
return new Date(timestamp).toLocaleTimeString([], {
hour: '2-digit',
minute: '2-digit'
})
}
return (
<div className="flex flex-col h-[600px]">
{/* Messages Area */}
<div className="flex-1 overflow-y-auto p-4 space-y-4 scrollbar-hide">
{messages.length === 0 && (
<div className="flex items-center justify-center h-full text-gray-500">
<div className="text-center">
<MessageCircle className="w-12 h-12 mx-auto mb-3 text-gray-400" />
<p>Start a conversation with the AI assistant</p>
</div>
</div>
)}
{messages.map((message) => (
<div
key={message.id}
className={`flex ${message.role === 'user' ? 'justify-end' : 'justify-start'}`}
>
<div
className={`message-bubble ${
message.role === 'user'
? 'message-user'
: 'message-assistant'
}`}
>
<div className="prose prose-sm max-w-none">
<ReactMarkdown
rehypePlugins={[rehypeHighlight]}
components={{
p: ({ children }) => <p className="mb-2 last:mb-0">{children}</p>,
code: ({ children, className }) => {
const isInline = !className
return isInline ? (
<code className="bg-gray-100 px-1 py-0.5 rounded text-sm">
{children}
</code>
) : (
<code className="block bg-gray-100 p-2 rounded text-sm overflow-x-auto">
{children}
</code>
)
}
>
{message.content}
</ReactMarkdown>
</div>
<div className={`text-xs mt-2 ${
message.role === 'user' ? 'text-blue-100' : 'text-gray-500'
}`}>
{formatTime(message.timestamp)}
</div>
</div>
</div>
))}
{isLoading && (
<div className="flex justify-start">
<div className="message-bubble message-assistant">
<div className="flex items-center space-x-2">
<Loader2 className="w-4 h-4 animate-spin" />
<span className="text-gray-600">Thinking...</span>
</div>
</div>
</div>
)}
<div ref={messagesEndRef} />
</div>
{/* Input Area */}
<div className="border-t border-gray-200 p-4">
<form onSubmit={handleSubmit} className="flex space-x-3">
<div className="flex-1">
<textarea
ref={inputRef}
value={inputMessage}
onChange={(e) => setInputMessage(e.target.value)}
onKeyPress={handleKeyPress}
placeholder="Type your message... (Press Enter to send, Shift+Enter for new line)"
className="w-full px-4 py-3 border border-gray-300 rounded-lg focus:ring-2 focus:ring-primary-500 focus:border-transparent resize-none"
rows={1}
style={{
minHeight: '48px',
maxHeight: '120px',
height: 'auto'
onInput={(e) => {
e.target.style.height = 'auto'
e.target.style.height = e.target.scrollHeight + 'px'
disabled={isLoading}
/>
</div>
<button
type="submit"
disabled={!inputMessage.trim() || isLoading}
className="px-6 py-3 bg-primary-500 text-white rounded-lg hover:bg-primary-600 focus:ring-2 focus:ring-primary-500 focus:ring-offset-2 disabled:opacity-50 disabled:cursor-not-allowed transition-colors flex items-center space-x-2"
>
{isLoading ? (
<Loader2 className="w-5 h-5 animate-spin" />
) : (
<Send className="w-5 h-5" />
)}
<span className="hidden sm:inline">Send</span>
</button>
</form>
<div className="mt-2 text-xs text-gray-500 text-center">
Press Enter to send, Shift+Enter for new line
</div>
</div>
</div>
)
}
This chatbot application includes:
**Key Features:**
- **Modern UI**: Clean, responsive design with Tailwind CSS
- **Real-time Chat**: Smooth messaging interface with loading states
- **Markdown Support**: Rich text formatting with code highlighting
- **Keyboard Shortcuts**: Enter to send, Shift+Enter for new lines
- **Error Handling**: Graceful error handling and retry mechanisms
- **Accessibility**: Proper ARIA labels and keyboard navigation
- **Mobile Responsive**: Works perfectly on all screen sizes
**Technical Implementation:**
- **Next.js 14** with app router architecture
- **API Route** for chat backend logic
- **React Hooks** for state management
- **Lucide React** icons for modern UI elements
- **React Markdown** for rich text rendering
- **Tailwind CSS** for styling
- **Docker** configuration for HuggingFace Spaces deployment
**The "Built with anycoder" link** is prominently displayed in the header as requested, linking to the specified HuggingFace Spaces page.
The application is ready for deployment and provides a complete, professional chatbot experience!