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New updates and improvements at Cloudflare.

Agents
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  1. npm i agents

    agents-sdk -> agents Updated

    📝 We've renamed the Agents package to agents!

    If you've already been building with the Agents SDK, you can update your dependencies to use the new package name, and replace references to agents-sdk with agents:

    Terminal window
    # Install the new package
    npm i agents
    Terminal window
    # Remove the old (deprecated) package
    npm uninstall agents-sdk
    # Find instances of the old package name in your codebase
    grep -r 'agents-sdk' .
    # Replace instances of the old package name with the new one
    # (or use find-replace in your editor)
    sed -i 's/agents-sdk/agents/g' $(grep -rl 'agents-sdk' .)

    All future updates will be pushed to the new agents package, and the older package has been marked as deprecated.

    Agents SDK updates New

    We've added a number of big new features to the Agents SDK over the past few weeks, including:

    • You can now set cors: true when using routeAgentRequest to return permissive default CORS headers to Agent responses.
    • The regular client now syncs state on the agent (just like the React version).
    • useAgentChat bug fixes for passing headers/credentials, including properly clearing cache on unmount.
    • Experimental /schedule module with a prompt/schema for adding scheduling to your app (with evals!).
    • Changed the internal zod schema to be compatible with the limitations of Google's Gemini models by removing the discriminated union, allowing you to use Gemini models with the scheduling API.

    We've also fixed a number of bugs with state synchronization and the React hooks.

    JavaScript
    // via https://github.com/cloudflare/agents/tree/main/examples/cross-domain
    export default {
    async fetch(request, env) {
    return (
    // Set { cors: true } to enable CORS headers.
    (await routeAgentRequest(request, env, { cors: true })) ||
    new Response("Not found", { status: 404 })
    );
    },
    };

    Call Agent methods from your client code New

    We've added a new @unstable_callable() decorator for defining methods that can be called directly from clients. This allows you call methods from within your client code: you can call methods (with arguments) and get native JavaScript objects back.

    JavaScript
    // server.ts
    import { unstable_callable, Agent } from "agents";
    export class Rpc extends Agent {
    // Use the decorator to define a callable method
    @unstable_callable({
    description: "rpc test",
    })
    async getHistory() {
    return this.sql`SELECT * FROM history ORDER BY created_at DESC LIMIT 10`;
    }
    }

    agents-starter Updated

    We've fixed a number of small bugs in the agents-starter project — a real-time, chat-based example application with tool-calling & human-in-the-loop built using the Agents SDK. The starter has also been upgraded to use the latest wrangler v4 release.

    If you're new to Agents, you can install and run the agents-starter project in two commands:

    Terminal window
    # Install it
    $ npm create cloudflare@latest agents-starter -- --template="cloudflare/agents-starter"
    # Run it
    $ npm run start

    You can use the starter as a template for your own Agents projects: open up src/server.ts and src/client.tsx to see how the Agents SDK is used.

    More documentation Updated

    We've heard your feedback on the Agents SDK documentation, and we're shipping more API reference material and usage examples, including:

    • Expanded API reference documentation, covering the methods and properties exposed by the Agents SDK, as well as more usage examples.
    • More Client API documentation that documents useAgent, useAgentChat and the new @unstable_callable RPC decorator exposed by the SDK.
    • New documentation on how to route requests to agents and (optionally) authenticate clients before they connect to your Agents.

    Note that the Agents SDK is continually growing: the type definitions included in the SDK will always include the latest APIs exposed by the agents package.

    If you're still wondering what Agents are, read our blog on building AI Agents on Cloudflare and/or visit the Agents documentation to learn more.

  1. We've released the Agents SDK, a package and set of tools that help you build and ship AI Agents.

    You can get up and running with a chat-based AI Agent (and deploy it to Workers) that uses the Agents SDK, tool calling, and state syncing with a React-based front-end by running the following command:

    Terminal window
    npm create cloudflare@latest agents-starter -- --template="cloudflare/agents-starter"
    # open up README.md and follow the instructions

    You can also add an Agent to any existing Workers application by installing the agents package directly

    Terminal window
    npm i agents

    ... and then define your first Agent:

    TypeScript
    import { Agent } from "agents";
    export class YourAgent extends Agent<Env> {
    // Build it out
    // Access state on this.state or query the Agent's database via this.sql
    // Handle WebSocket events with onConnect and onMessage
    // Run tasks on a schedule with this.schedule
    // Call AI models
    // ... and/or call other Agents.
    }

    Head over to the Agents documentation to learn more about the Agents SDK, the SDK APIs, as well as how to test and deploying agents to production.

  1. We've added an example prompt to help you get started with building AI agents and applications on Cloudflare Workers, including Workflows, Durable Objects, and Workers KV.

    You can use this prompt with your favorite AI model, including Claude 3.5 Sonnet, OpenAI's o3-mini, Gemini 2.0 Flash, or Llama 3.3 on Workers AI. Models with large context windows will allow you to paste the prompt directly: provide your own prompt within the <user_prompt></user_prompt> tags.

    Terminal window
    {paste_prompt_here}
    <user_prompt>
    user: Build an AI agent using Cloudflare Workflows. The Workflow should run when a new GitHub issue is opened on a specific project with the label 'help' or 'bug', and attempt to help the user troubleshoot the issue by calling the OpenAI API with the issue title and description, and a clear, structured prompt that asks the model to suggest 1-3 possible solutions to the issue. Any code snippets should be formatted in Markdown code blocks. Documentation and sources should be referenced at the bottom of the response. The agent should then post the response to the GitHub issue. The agent should run as the provided GitHub bot account.
    </user_prompt>

    This prompt is still experimental, but we encourage you to try it out and provide feedback.