What It Does
Community member Nick Nance has created something special with agentuity-chat - a sleek Next.js web application that demonstrates the power of combining modern frontend development with Agentuity's cloud-hosted agents.
The project showcases how easy it is to build a production-ready chat interface using Vercel's AI SDK while leveraging Agentuity agents running in the cloud as the backend intelligence. It's a perfect example of "chat on the front, party on the back" - beautiful, front-end tech powered by sophisticated AI agents.
How It Works
The magic happens through the seamless integration between Vercel's useChat
hook and Agentuity's agent infrastructure. Here's how the pieces fit together:
Frontend: Next.js with Vercel AI SDK
The frontend leverages Vercel's powerful useChat
hook. It can be directly connected to your deployed Agentuity agent via the AGENTUITY_URL
environment variable. The Vercel AI SDK handles all the complexity of streaming responses and message management.
Backend: Agentuity Agents in the Cloud
The backend consists of Agentuity agents deployed to the cloud that handle the actual AI processing. Here's the actual agent code from Nick's project:
This simple LLM code demonstrates the potential power of the integration:
- Agentuity SDK Integration: Uses
AgentRequest
to receive structured data from the frontend - Vercel AI SDK Compatibility: Leverages
streamText
for streaming responses - Model Flexibility: Easy to swap between different AI providers (here using Anthropic's Claude)
- Streaming Support: Returns a data stream response for real-time chat experience
The agents are deployed using Agentuity's cloud infrastructure, which provides:
- Automatic scaling and management
- Built-in monitoring and analytics
- Secure agent-to-agent communication
- Easy deployment via the Agentuity CLI
- Deployment that is serverless without the downsides (your agents can run for as long as they need to)
- A really awesome dev mode for testing your agents locally
The beauty is in the simplicity - your frontend just sends messages to the deployed Agentuity agent URL, and the agent handles all the AI processing, model management, and response generation in the cloud.
How to Use It
Getting started with Nick's project is straightforward. Check the README for more details and to make it your own on Agentuity. It's as simple as:
-
Clone the repo`
-
agentuity project import
-
agentuity deploy
Community Spotlight
Nick Nance has created an excellent example of how to build modern AI applications with clean separation of concerns. His project demonstrates the power of combining best-in-class frontend tools with Agentuity's agent infrastructure.
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