Creating an AI Agent with AIPE.NOW
I'll help you build an AI agent using the AIPE.NOW platform shown in your screenshot. Let's create a complete implementation that allows users to configure and interact with an AI agent.
How It Works
I've created a Next.js application that replicates the AIPE.NOW interface for creating AI agents. Here's what the implementation includes:
Main Layout:
- A dark-themed interface with a sidebar and main content area
- Purple accent colors matching the original design
Identity Section:
- Fields for agent name and age
- File upload area for agent avatar/image
Personality Configuration:
- Text areas for description, personality traits, first message
- Additional fields for lore, style, adjectives, and knowledge
- NSFW toggle switch
API & Features:
- Integration options for Twitter, Telegram, Voice Generation
- Agent Training, Discord Integration, and Image Generation
- Each with a checkbox and description
State Management:
- React state hooks to track all form inputs
- Toggle functionality for all switches and checkboxes
The interface closely matches the screenshot you provided, with the same dark color scheme, purple accents, and layout structure.
How to Use
- Fill in the agent's identity details (name, age, and upload an image)
- Configure the personality by completing the text areas for description, personality traits, etc.
- Select which integrations you want to enable for your agent
- Click the "Create Agent" button to generate your AI agent
This implementation provides a complete UI for configuring an AI agent. To make it fully functional, you would need to connect it to a backend service that can process the agent configuration and create the actual AI agent.
How to Integrate the AIPE.NOW Agent Creator into Your Existing Project
Here's a step-by-step guide to add the AIPE.NOW agent creation interface to your existing Next.js project:
1. Install Required Dependencies
First, make sure you have the necessary dependencies installed:
npm install lucide-reactIf you don't already have shadcn/ui components installed, you'll need to set those up:
npx shadcn@latest initThen install the specific components we're using:
npx shadcn@latest add button input textarea switch card label checkbox2. Copy the Components
3. Update Your Tailwind Configuration
If your existing project uses a different color scheme, you might want to update your tailwind.config.js to include the dark purple colors used in the AIPE interface:
// Add these colors to your tailwind.config.js
theme: {
extend: {
colors: {
// Your existing colors...
aipe: {
dark: '#0e0e1a',
card: '#1e1e2d',
input: '#13131f',
purple: '#9333ea',
},
},
},
},4. Integrate with Your AI Backend
To make the agent creator functional, you'll need to connect it to your AI backend. Here's how to handle the form submission:
// In your page component
import { AgentCreator } from "@/components/aipe/agent-creator"
export default function YourPage() {
const handleCreateAgent = async (agentData) => {
try {
// Send the agent data to your backend
const response = await fetch('/api/agents', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(agentData),
})
if (!response.ok) {
throw new Error('Failed to create agent')
}
const data = await response.json()
console.log('Agent created:', data)
// Handle success (redirect, show message, etc.)
} catch (error) {
console.error('Error creating agent:', error)
// Handle error
}
}
return (
<div className="your-container">
<h1>Create an AI Agent</h1>
<AgentCreator onSubmit={handleCreateAgent} />
</div>
)
}5. Create an API Route (if using Next.js)
// app/api/agents/route.ts
import { NextResponse } from 'next/server'
export async function POST(request: Request) {
try {
const agentData = await request.json()
// Process the agent data
// This is where you would connect to your AI service
// For example, using the AI SDK to create an agent
// Example with AI SDK (pseudocode)
// import { createAgent } from 'your-ai-service'
// const agent = await createAgent({
// name: agentData.identity.name,
// description: agentData.personality.description,
// // other properties
// })
// For now, just return the data
return NextResponse.json({
success: true,
message: 'Agent created successfully',
agent: agentData
})
} catch (error) {
console.error('Error creating agent:', error)
return NextResponse.json(
{ success: false, message: 'Failed to create agent' },
{ status: 500 }
)
}
}6. Add File Upload Functionality
To handle the agent image upload:
// Add this to your agent-creator.tsx component
import { useState } from "react"
// Inside your component
const [agentImage, setAgentImage] = useState(null)
const [previewUrl, setPreviewUrl] = useState("")
const handleImageUpload = (e) => {
const file = e.target.files[0]
if (file) {
setAgentImage(file)
setPreviewUrl(URL.createObjectURL(file))
}
}
// Replace the upload div with:
<div className="border border-dashed border-gray-600 rounded-md p-4 text-center">
<input
type="file"
id="agent-image"
accept="image/png,image/jpeg,image/gif,image/svg+xml"
className="hidden"
onChange={handleImageUpload}
/>
<label htmlFor="agent-image" className="cursor-pointer">
{previewUrl ? (
<img src={previewUrl || "/placeholder.svg"} alt="Agent preview" className="mx-auto h-32 object-contain" />
) : (
<>
<Upload className="mx-auto h-6 w-6 text-gray-400 mb-2" />
<p className="text-sm text-gray-400">
Click to upload or drag and drop SVG, PNG, JPG or GIF (max 800x400px)
</p>
</>
)}
</label>
</div>7. Connecting to an AI Model
If you want to use the AI SDK to power your agent, you can integrate it like this:
// app/api/agents/chat/route.ts
import { NextResponse } from 'next/server'
import { generateText } from 'ai'
import { openai } from '@ai-sdk/openai'
export async function POST(request: Request) {
try {
const { message, agentData } = await request.json()
// Create a system prompt based on the agent's personality
const systemPrompt = `
You are ${agentData.identity.name}, a ${agentData.identity.age} year old AI agent.
Description: ${agentData.personality.description}
Personality: ${agentData.personality.personality}
Style: ${agentData.personality.style}
Knowledge: ${agentData.personality.knowledge}
Always stay in character and respond as ${agentData.identity.name} would.
`
// Generate a response using the AI SDK
const { text } = await generateText({
model: openai('gpt-4o'),
system: systemPrompt,
prompt: message,
})
return NextResponse.json({
response: text,
agent: agentData.identity.name
})
} catch (error) {
console.error('Error generating response:', error)
return NextResponse.json(
{ error: 'Failed to generate response' },
{ status: 500 }
)
}
}8. Testing Your Integration
After implementing these components, you can test your integration by:
- Navigating to your agent creation page
- Filling out the form with agent details
- Submitting the form to create the agent
- Testing the agent's responses using your chat interface
Additional Considerations
- Authentication: Consider adding authentication to protect your agent creation and usage
- Validation: Add form validation to ensure all required fields are filled correctly
- Error Handling: Implement proper error handling for API calls and form submissions
- Persistence: Store created agents in a database for future use
- Customization: Adjust the styling to match your existing application's design
By following these steps, you'll have successfully integrated the AIPE.NOW agent creation interface into your existing project, allowing your users to create and interact with customized AI agents.