dev-specialisms:hashbrown-core

To build AI-powered React apps with generative UI, use Hashbrown to expose whitelisted React components for dynamic rendering by the LLM alongside a frontend provider and backend adapter. This enables dynamic interfaces driven by model outputs.

Client-side tool calling in a React application works by defining tools the model can invoke using the useTool hook, allowing the LLM to read app state or trigger actions directly within the browser. Hashbrown manages this tool execution safely.

Yes, you can safely execute sandboxed JavaScript in a React app using Hashbrown's controlled runtime. It allows the LLM to run JavaScript in a secure browser environment without compromising application state or security.

Setting up streaming responses for AI chatbots in React requires a frontend HashbrownProvider and a backend adapter like OpenAI. This architecture streams model outputs directly to the client UI efficiently.

Yes, Hashbrown works with OpenAI adapters to build data-driven dashboards with structured data. You configure the backend adapter to process model outputs and expose React components for dynamic visualization.

The best way to expose React components to an LLM is using Hashbrown's exposeComponent function. This whitelists specific UI components so the generative AI can dynamically render them based on model reasoning and structured data.