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- tool-server.mjs: extractElements() scrapes all interactive elements with coordinates
- tool-server.mjs: formatElements() returns numbered list for LLM to read
- tool-server.mjs: click/type now support {index: N} for element-based interaction
- tool-server.mjs: new /api/browser/elements and /api/browser/keypress endpoints
- browser-tool.ts: updated schema with index, key params and elements/keypress actions
- browser-tool.ts: elementsText included in every LLM response so model can see the page
- browser-tool.ts: detailed workflow instructions in tool description
- Enables text-only models (Llama 3.3 etc) to navigate and interact with web pages
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| server | ||
| src | ||
| .gitignore | ||
| docker-compose.yml | ||
| Dockerfile | ||
| index.html | ||
| package.json | ||
| README.md | ||
| tsconfig.json | ||
| vite.config.ts | ||
Pi Web UI - Example
This is a minimal example showing how to use @jaeswift/jae-web-ui in a web application.
Setup
npm install
Development
npm run dev
Open http://localhost:5173 in your browser.
What's Included
This example demonstrates:
- ChatPanel - The main chat interface component
- System Prompt - Custom configuration for the AI assistant
- Tools - JavaScript REPL and artifacts tool
Configuration
API Keys
The example uses Direct Mode by default, which means it calls AI provider APIs directly from the browser.
To use the chat:
- Click the settings icon (⚙️) in the chat interface
- Click "Manage API Keys"
- Add your API key for your preferred provider:
- Anthropic: Get a key from console.anthropic.com
- OpenAI: Get a key from platform.openai.com
- Google: Get a key from makersuite.google.com
API keys are stored in your browser's localStorage and never sent to any server except the AI provider's API.
Project Structure
example/
├── src/
│ ├── main.ts # Main application entry point
│ └── app.css # Tailwind CSS configuration
├── index.html # HTML entry point
├── package.json # Dependencies
├── vite.config.ts # Vite configuration
└── tsconfig.json # TypeScript configuration