agents-starter

A starter kit for building ai agents on Cloudflare

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A starter template for building AI-powered chat agents using Cloudflare's Agent platform, powered by agents-sdk. It provides a foundation for creating interactive chat experiences with AI, complete with a modern UI and tool integration capabilities. Features include interactive chat interface with AI, built-in tool system with human-in-the-loop confirmation, advanced task scheduling, dark/light theme support, real-time streaming responses, state management, and chat history. Prerequisites include a Cloudflare account and OpenAI API key. The project structure includes components for chat UI implementation, chat agent logic, tool definitions, and helper functions. Customization guide covers adding new tools, modifying the UI, and example use cases for customer support, development assistant, data analysis assistant, personal productivity assistant, and scheduling assistant.

README:

🤖 Chat Agent Starter Kit

A starter template for building AI-powered chat agents using Cloudflare's Agent platform, powered by agents. This project provides a foundation for creating interactive chat experiences with AI, complete with a modern UI and tool integration capabilities.

Features

💬 Interactive chat interface with AI
🛠️ Built-in tool system with human-in-the-loop confirmation
📅 Advanced task scheduling (one-time, delayed, and recurring via cron)
🌓 Dark/Light theme support
⚡️ Real-time streaming responses
🔄 State management and chat history
🎨 Modern, responsive UI

Prerequisites

Cloudflare account
OpenAI API key

Quick Start

Create a new project:

npx create-cloudflare@latest --template cloudflare/agents-starter

Install dependencies:

npm install

Set up your environment:

Create a .dev.vars file:

OPENAI_API_KEY=your_openai_api_key

Run locally:

npm start

Deploy:

npm run deploy

Project Structure

├── src/
│   ├── app.tsx        # Chat UI implementation
│   ├── server.ts      # Chat agent logic
│   ├── tools.ts       # Tool definitions
│   ├── utils.ts       # Helper functions
│   └── styles.css     # UI styling

Customization Guide

Adding New Tools

Add new tools in tools.ts using the tool builder:

// Example of a tool that requires confirmation
const searchDatabase = tool({
  description: "Search the database for user records",
  parameters: z.object({
    query: z.string(),
    limit: z.number().optional()
  })
  // No execute function = requires confirmation
});

// Example of an auto-executing tool
const getCurrentTime = tool({
  description: "Get current server time",
  parameters: z.object({}),
  execute: async () => new Date().toISOString()
});

// Scheduling tool implementation
const scheduleTask = tool({
  description:
    "schedule a task to be executed at a later time. 'when' can be a date, a delay in seconds, or a cron pattern.",
  parameters: z.object({
    type: z.enum(["scheduled", "delayed", "cron"]),
    when: z.union([z.number(), z.string()]),
    payload: z.string()
  }),
  execute: async ({ type, when, payload }) => {
    // ... see the implementation in tools.ts
  }
});

To handle tool confirmations, add execution functions to the executions object:

export const executions = {
  searchDatabase: async ({
    query,
    limit
  }: {
    query: string;
    limit?: number;
  }) => {
    // Implementation for when the tool is confirmed
    const results = await db.search(query, limit);
    return results;
  }
  // Add more execution handlers for other tools that require confirmation
};

Tools can be configured in two ways:

With an execute function for automatic execution
Without an execute function, requiring confirmation and using the executions object to handle the confirmed action. NOTE: The keys in executions should match toolsRequiringConfirmation in app.tsx.

Use a different AI model provider

The starting server.ts implementation uses the ai-sdk and the OpenAI provider, but you can use any AI model provider by:

Installing an alternative AI provider for the ai-sdk, such as the workers-ai-provider or anthropic provider:
Replacing the AI SDK with the OpenAI SDK
Using the Cloudflare Workers AI + AI Gateway binding API directly

For example, to use the workers-ai-provider, install the package:

npm install workers-ai-provider

Add an ai binding to wrangler.jsonc:

// rest of file
  "ai": {
    "binding": "AI"
  }
// rest of file

Replace the @ai-sdk/openai import and usage with the workers-ai-provider:

// server.ts
// Change the imports
- import { openai } from "@ai-sdk/openai";
+ import { createWorkersAI } from 'workers-ai-provider';

// Create a Workers AI instance
+ const workersai = createWorkersAI({ binding: env.AI });

// Use it when calling the streamText method (or other methods)
// from the ai-sdk
- const model = openai("gpt-4o-2024-11-20");
+ const model = workersai("@cf/deepseek-ai/deepseek-r1-distill-qwen-32b")

Commit your changes and then run the agents-starter as per the rest of this README.

Modifying the UI

The chat interface is built with React and can be customized in app.tsx:

Modify the theme colors in styles.css
Add new UI components in the chat container
Customize message rendering and tool confirmation dialogs
Add new controls to the header

Example Use Cases

Customer Support Agent
- Add tools for:
  - Ticket creation/lookup
  - Order status checking
  - Product recommendations
  - FAQ database search
Development Assistant
- Integrate tools for:
  - Code linting
  - Git operations
  - Documentation search
  - Dependency checking
Data Analysis Assistant
- Build tools for:
  - Database querying
  - Data visualization
  - Statistical analysis
  - Report generation
Personal Productivity Assistant
- Implement tools for:
  - Task scheduling with flexible timing options
  - One-time, delayed, and recurring task management
  - Task tracking with reminders
  - Email drafting
  - Note taking
Scheduling Assistant
- Build tools for:
  - One-time event scheduling using specific dates
  - Delayed task execution (e.g., "remind me in 30 minutes")
  - Recurring tasks using cron patterns
  - Task payload management
  - Flexible scheduling patterns

Each use case can be implemented by:

Adding relevant tools in tools.ts
Customizing the UI for specific interactions
Extending the agent's capabilities in server.ts
Adding any necessary external API integrations

Learn More

License

MIT

For Tasks:

Click tags to check more tools for each tasks

create ticket code linting database querying task scheduling event scheduling

For Jobs:

customer support agent development assistant data analysis assistant personal productivity assistant scheduling assistant

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