---
title: AI Changelog
image: https://developers.cloudflare.com/cf-twitter-card.png
---

> Documentation Index  
> Fetch the complete documentation index at: https://developers.cloudflare.com/changelog/llms.txt  
> Use this file to discover all available pages before exploring further. 

[Skip to content](#%5Ftop) 

# Changelog

New updates and improvements at Cloudflare.

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AI

![hero image](https://developers.cloudflare.com/_astro/hero.CVYJHPAd_26AMqX.svg) 

Nov 10, 2025
1. ### [Crawler drilldowns with extended actions menu](https://developers.cloudflare.com/changelog/post/2025-11-10-ai-crawl-control-crawler-info/)  
[ AI Crawl Control ](https://developers.cloudflare.com/ai-crawl-control/)  
AI Crawl Control now supports per-crawler drilldowns with an extended actions menu and status code analytics. Drill down into Metrics, Cloudflare Radar, and Security Analytics, or export crawler data for use in [WAF custom rules](https://developers.cloudflare.com/waf/custom-rules/), [Redirect Rules](https://developers.cloudflare.com/rules/url-forwarding/), and robots.txt files.  
#### What's new  
#### Status code distribution chart  
The **Metrics** tab includes a status code distribution chart showing HTTP response codes (2xx, 3xx, 4xx, 5xx) over time. Filter by individual crawler, category, operator, or time range to analyze how specific crawlers interact with your site.  
![AI Crawl Control status code distribution chart](https://developers.cloudflare.com/_astro/ai-crawl-control-status-codes.DESJcAiK_TSrPM.webp)  
#### Extended actions menu  
Each crawler row includes a three-dot menu with per-crawler actions:

  * **View Metrics** — Filter the AI Crawl Control Metrics page to the selected crawler.
  * **View on Cloudflare Radar** — Access verified crawler details on Cloudflare Radar.
  * **Copy User Agent** — Copy user agent strings for use in WAF custom rules, Redirect Rules, or robots.txt files.
  * **View in Security Analytics** — Filter Security Analytics by detection IDs (Bot Management customers).
  * **Copy Detection ID** — Copy detection IDs for use in WAF custom rules (Bot Management customers).  
![AI Crawl Control crawler actions menu](https://developers.cloudflare.com/_astro/ai-crawl-control-crawler-info.Dwc39LqI_182so6.webp)  
#### Get started

  1. Log in to the Cloudflare dashboard, and select your account and domain.
  2. Go to **AI Crawl Control** \> **Metrics** to access the status code distribution chart.
  3. Go to **AI Crawl Control** \> **Crawlers** and select the three-dot menu for any crawler to access per-crawler actions.
  4. Select multiple crawlers to use bulk copy buttons for user agents or detection IDs.  
Learn more about [AI Crawl Control](https://developers.cloudflare.com/ai-crawl-control/).

Oct 31, 2025
1. ### [Workers WebSocket message size limit increased from 1 MiB to 32 MiB](https://developers.cloudflare.com/changelog/post/2025-10-31-increased-websocket-message-size-limit/)  
[ Workers ](https://developers.cloudflare.com/workers/)[ Durable Objects ](https://developers.cloudflare.com/durable-objects/)[ Browser Run ](https://developers.cloudflare.com/browser-run/)  
Workers, including those using [Durable Objects](https://developers.cloudflare.com/durable-objects/) and [Browser Rendering](https://developers.cloudflare.com/browser-run/), may now process WebSocket messages up to 32 MiB in size. Previously, this limit was 1 MiB.  
This change allows Workers to handle use cases requiring large message sizes, such as processing Chrome Devtools Protocol messages.  
For more information, please see the [Durable Objects startup limits](https://developers.cloudflare.com/durable-objects/platform/limits/#sqlite-backed-durable-objects-general-limits).

Oct 28, 2025
1. ### [Reranking and API-based system prompt configuration in AI Search](https://developers.cloudflare.com/changelog/post/2025-10-27-ai-search-reranking-system-prompt/)  
[ AI Search ](https://developers.cloudflare.com/ai-search/)  
[AI Search](https://developers.cloudflare.com/ai-search/) now supports reranking for improved retrieval quality and allows you to set the system prompt directly in your API requests.  
#### Rerank for more relevant results  
You can now enable [reranking](https://developers.cloudflare.com/ai-search/configuration/retrieval/reranking/) to reorder retrieved documents based on their semantic relevance to the user’s query. Reranking helps improve accuracy, especially for large or noisy datasets where vector similarity alone may not produce the optimal ordering.  
You can enable and configure reranking in the dashboard or directly in your API requests:  
JavaScript  
```  
const answer = await env.AI.autorag("my-autorag").aiSearch({  query: "How do I train a llama to deliver coffee?",  model: "@cf/meta/llama-3.3-70b-instruct-fp8-fast",  reranking: {    enabled: true,    model: "@cf/baai/bge-reranker-base",  },});  
```  
#### Set system prompts in API  
Previously, [system prompts](https://developers.cloudflare.com/ai-search/configuration/retrieval/system-prompt/) could only be configured in the dashboard. You can now define them directly in your API requests, giving you per-query control over behavior. For example:  
JavaScript  
```  
// Dynamically set query and system prompt in AI Searchasync function getAnswer(query, tone) {  const systemPrompt = `You are a ${tone} assistant.`;  
  const response = await env.AI.autorag("my-autorag").aiSearch({    query: query,    system_prompt: systemPrompt,  });  
  return response;}  
// Example usageconst query = "What is Cloudflare?";const tone = "friendly";  
const answer = await getAnswer(query, tone);console.log(answer);  
```  
Learn more about [Reranking](https://developers.cloudflare.com/ai-search/configuration/retrieval/reranking/) and [System Prompt](https://developers.cloudflare.com/ai-search/configuration/retrieval/system-prompt/) in AI Search.

Oct 23, 2025
1. ### [Workers AI Markdown Conversion: New endpoint to list supported formats](https://developers.cloudflare.com/changelog/post/2025-10-23-new-markdown-conversion-endpoint/)  
[ Workers AI ](https://developers.cloudflare.com/workers-ai/)  
Developers can now programmatically retrieve a list of all file formats supported by the [Markdown Conversion utility](https://developers.cloudflare.com/workers-ai/features/markdown-conversion/) in Workers AI.  
You can use the [env.AI](https://developers.cloudflare.com/workers-ai/configuration/bindings/) binding:  
TypeScript  
```  
await env.AI.toMarkdown().supported()  
```  
Or call the REST API:  
Terminal window  
```  
curl https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/tomarkdown/supported \  -H 'Authorization: Bearer {API_TOKEN}'  
```  
Both return a list of file formats that users can convert into Markdown:  
```  
[  {    "extension": ".pdf",    "mimeType": "application/pdf",  },  {    "extension": ".jpeg",    "mimeType": "image/jpeg",  },  ...]  
```  
Learn more about our [Markdown Conversion utility](https://developers.cloudflare.com/workers-ai/features/markdown-conversion/).

Oct 21, 2025
1. ### [New Robots.txt tab for tracking crawler compliance](https://developers.cloudflare.com/changelog/post/2025-10-21-track-robots-txt/)  
[ AI Crawl Control ](https://developers.cloudflare.com/ai-crawl-control/)  
AI Crawl Control now includes a **Robots.txt** tab that provides insights into how AI crawlers interact with your `robots.txt` files.  
#### What's new  
The Robots.txt tab allows you to:

  * Monitor the health status of `robots.txt` files across all your hostnames, including HTTP status codes, and identify hostnames that need a `robots.txt` file.
  * Track the total number of requests to each `robots.txt` file, with breakdowns of successful versus unsuccessful requests.
  * Check whether your `robots.txt` files contain [Content Signals ↗](https://contentsignals.org/) directives for AI training, search, and AI input.
  * Identify crawlers that request paths explicitly disallowed by your `robots.txt` directives, including the crawler name, operator, violated path, specific directive, and violation count.
  * Filter `robots.txt` request data by crawler, operator, category, and custom time ranges.  
#### Take action  
When you identify non-compliant crawlers, you can:

  * Block the crawler in the [Crawlers tab](https://developers.cloudflare.com/ai-crawl-control/features/manage-ai-crawlers/)
  * Create custom [WAF rules](https://developers.cloudflare.com/waf/) for path-specific security
  * Use [Redirect Rules](https://developers.cloudflare.com/rules/url-forwarding/) to guide crawlers to appropriate areas of your site  
To get started, go to **AI Crawl Control** \> **Robots.txt** in the Cloudflare dashboard. Learn more in the [Track robots.txt documentation](https://developers.cloudflare.com/ai-crawl-control/features/track-robots-txt/).

Oct 14, 2025
1. ### [Enhanced AI Crawl Control metrics with new drilldowns and filters](https://developers.cloudflare.com/changelog/post/2025-10-14-enhanced-metrics-drilldowns/)  
[ AI Crawl Control ](https://developers.cloudflare.com/ai-crawl-control/)  
AI Crawl Control now provides enhanced metrics and CSV data exports to help you better understand AI crawler activity across your sites.  
#### What's new  
#### Track crawler requests over time  
Visualize crawler activity patterns over time, and group data by different dimensions:

  * **By Crawler** — Track activity from individual AI crawlers (GPTBot, ClaudeBot, Bytespider)
  * **By Category** — Analyze crawler purpose or type
  * **By Operator** — Discover which companies (OpenAI, Anthropic, ByteDance) are crawling your site
  * **By Host** — Break down activity across multiple subdomains
  * **By Status Code** — Monitor HTTP response codes to crawlers (200s, 300s, 400s, 500s)  
![AI Crawl Control requests over time chart with grouping tabs](https://developers.cloudflare.com/_astro/ai-crawl-control-requests-over-time.BtRyz0OT_ZpotRm.webp "Interactive chart showing crawler requests over time with filterable dimensions")  
Interactive chart showing crawler requests over time with filterable dimensions  
#### Analyze referrer data (Paid plans)  
Identify traffic sources with referrer analytics:

  * View top referrers driving traffic to your site
  * Understand discovery patterns and content popularity from AI operators  
![AI Crawl Control top referrers breakdown](https://developers.cloudflare.com/_astro/ai-crawl-control-top-referrers.CEUAwpd8_YrhT4.webp "Bar chart showing top referrers and their respective traffic volumes")  
Bar chart showing top referrers and their respective traffic volumes  
#### Export data  
Download your filtered view as a CSV:

  * Includes all applied filters and groupings
  * Useful for custom reporting and deeper analysis  
#### Get started

  1. Log in to the Cloudflare dashboard, and select your account and domain.
  2. Go to **AI Crawl Control** \> **Metrics**.
  3. Use the grouping tabs to explore different views of your data.
  4. Apply filters to focus on specific crawlers, time ranges, or response codes.
  5. Select **Download CSV** to export your filtered data for further analysis.  
Learn more about [AI Crawl Control](https://developers.cloudflare.com/ai-crawl-control).

Oct 02, 2025
1. ### [New Deepgram Flux model available on Workers AI](https://developers.cloudflare.com/changelog/post/2025-10-02-deepgram-flux/)  
[ Workers AI ](https://developers.cloudflare.com/workers-ai/)  
Deepgram's newest Flux model [@cf/deepgram/flux](https://developers.cloudflare.com/workers-ai/models/flux/) is now available on Workers AI, hosted directly on Cloudflare's infrastructure. We're excited to be a launch partner with Deepgram and offer their new Speech Recognition model built specifically for enabling voice agents. Check out [Deepgram's blog ↗](https://deepgram.com/flux) for more details on the release.  
The Flux model can be used in conjunction with Deepgram's speech-to-text model [@cf/deepgram/nova-3](https://developers.cloudflare.com/workers-ai/models/nova-3/) and text-to-speech model [@cf/deepgram/aura-1](https://developers.cloudflare.com/workers-ai/models/aura-1/) to build end-to-end voice agents. Having Deepgram on Workers AI takes advantage of our edge GPU infrastructure, for ultra low latency voice AI applications.  
#### Promotional Pricing  
For the month of October 2025, Deepgram's Flux model will be free to use on Workers AI. Official pricing will be announced soon and charged after the promotional pricing period ends on October 31, 2025\. Check out the [model page](https://developers.cloudflare.com/workers-ai/models/flux/) for pricing details in the future.  
#### Example Usage  
The new Flux model is WebSocket only as it requires live bi-directional streaming in order to recognize speech activity.

  1. Create a worker that establishes a websocket connection with `@cf/deepgram/flux`  
JavaScript  
```  
export default {  async fetch(request, env, ctx): Promise<Response> {    const resp = await env.AI.run("@cf/deepgram/flux", {      encoding: "linear16",      sample_rate: "16000"    }, {      websocket: true    });    return resp;  },} satisfies ExportedHandler<Env>;  
```

  1. Deploy your worker  
Terminal window  
```  
npx wrangler deploy  
```

  1. Write a client script to connect to your worker and start sending random audio bytes to it  
JavaScript  
```  
const ws = new WebSocket('wss://<your-worker-url.com>');  
ws.onopen = () => {  console.log('Connected to WebSocket');  
  // Generate and send random audio bytes  // You can replace this part with a function  // that reads from your mic or other audio source  const audioData = generateRandomAudio();  ws.send(audioData);  console.log('Audio data sent');};  
ws.onmessage = (event) => {  // Transcription will be received here  // Add your custom logic to parse the data  console.log('Received:', event.data);};  
ws.onerror = (error) => {  console.error('WebSocket error:', error);};  
ws.onclose = () => {  console.log('WebSocket closed');};  
// Generate random audio data (1 second of noise at 44.1kHz, mono)function generateRandomAudio() {  const sampleRate = 44100;  const duration = 1;  const numSamples = sampleRate * duration;  const buffer = new ArrayBuffer(numSamples * 2);  const view = new Int16Array(buffer);  
  for (let i = 0; i < numSamples; i++) {    view[i] = Math.floor(Math.random() * 65536 - 32768);  }  
  return buffer;}  
```

Sep 25, 2025
1. ### [Browser Rendering Playwright GA, Stagehand support (Beta), and higher limits](https://developers.cloudflare.com/changelog/post/2025-09-25-br-playwright-ga-stagehand-limits/)  
[ Browser Run ](https://developers.cloudflare.com/browser-run/)  
We’re shipping three updates to Browser Rendering:

  * Playwright support is now Generally Available and synced with [Playwright v1.55 ↗](https://playwright.dev/docs/release-notes#version-155), giving you a stable foundation for critical automation and AI-agent workflows.
  * We’re also adding [Stagehand support (Beta)](https://developers.cloudflare.com/browser-run/stagehand/) so you can combine code with natural language instructions to build more resilient automations.
  * Finally, we’ve tripled [limits](https://developers.cloudflare.com/browser-run/limits/#workers-paid) for paid plans across both the [REST API](https://developers.cloudflare.com/browser-run/quick-actions/) and [Browser Sessions](https://developers.cloudflare.com/browser-run/#integration-methods) to help you scale.  
To get started with Stagehand, refer to the [Stagehand](https://developers.cloudflare.com/browser-run/stagehand/) example that uses Stagehand and [Workers AI](https://developers.cloudflare.com/workers-ai/) to search for a movie on this [example movie directory ↗](https://demo.playwright.dev/movies), extract its details using natural language (title, year, rating, duration, and genre), and return the information along with a screenshot of the webpage.  
Stagehand example  
```  
const stagehand = new Stagehand({  env: "LOCAL",  localBrowserLaunchOptions: { cdpUrl: endpointURLString(env.BROWSER) },  llmClient: new WorkersAIClient(env.AI),  verbose: 1,});  
await stagehand.init();const page = stagehand.page;  
await page.goto("https://demo.playwright.dev/movies");  
// if search is a multi-step action, stagehand will return an array of actions it needs to act onconst actions = await page.observe('Search for "Furiosa"');for (const action of actions) await page.act(action);  
await page.act("Click the search result");  
// normal playwright functions work as expectedawait page.waitForSelector(".info-wrapper .cast");  
let movieInfo = await page.extract({  instruction: "Extract movie information",  schema: z.object({    title: z.string(),    year: z.number(),    rating: z.number(),    genres: z.array(z.string()),    duration: z.number().describe("Duration in minutes"),  }),});  
await stagehand.close();  
```  
![Stagehand video](https://developers.cloudflare.com/images/browser-run/speedystagehand.gif)

Sep 25, 2025
1. ### [AI Search (formerly AutoRAG) now with More Models To Choose From](https://developers.cloudflare.com/changelog/post/2025-09-25-ai-search-more-models/)  
[ AI Search ](https://developers.cloudflare.com/ai-search/)  
AutoRAG is now AI Search! The new name marks a new and bigger mission: to make world-class search infrastructure available to every developer and business.  
With AI Search you can now use models from different providers like OpenAI and Anthropic. By attaching your provider keys to the AI Gateway linked to your AI Search instance, you can use many more models for both embedding and inference.  
To use AI Search with other [model providers](https://developers.cloudflare.com/ai-search/configuration/models/):

  1. **Add provider keys to AI Gateway**  
    1. Go to AI > AI Gateway in the dashboard.
    2. Select or create an AI gateway.
    3. In Provider Keys, choose your provider, click Add, and enter the key.
  2. **Connect a gateway to AI Search**: When creating a new AI Search, select the AI Gateway with your provider keys. For an existing AI Search, go to Settings and switch to a gateway that has your keys under Resources.
  3. **Select models**: Embedding models are only available to be changed when creating a new AI Search. Generation model can be selected when creating a new AI Search and can be changed at any time in Settings.  
Once configured, your AI Search instance will be able to reference models available through your AI Gateway when making a `/ai-search` request:  
JavaScript  
```  
export default {  async fetch(request, env) {  
    // Query your AI Search instance with a natural language question to an OpenAI model    const result = await env.AI.autorag("my-ai-search").aiSearch({      query: "What's new for Cloudflare Birthday Week?",      model: "openai/gpt-5"    });  
    // Return only the generated answer as plain text    return new Response(result.response, {      headers: { "Content-Type": "text/plain" },    });  },};  
```  
In the coming weeks we will also roll out updates to align the APIs with the new name. The existing APIs will continue to be supported for the time being. Stay tuned to the [AI Search Changelog](https://developers.cloudflare.com/changelog/product/ai-search/) and [Discord ↗](https://discord.cloudflare.com/) for more updates!

Sep 19, 2025
1. ### [New Metrics View in AutoRAG](https://developers.cloudflare.com/changelog/post/2025-09-19-autorag-metrics/)  
[ AI Search ](https://developers.cloudflare.com/ai-search/)  
[AutoRAG](https://developers.cloudflare.com/ai-search/) now includes a **Metrics** tab that shows how your data is indexed and searched. Get a clear view of the health of your indexing pipeline, compare usage between `ai-search` and `search`, and see which files are retrieved most often.  
![Metrics](https://developers.cloudflare.com/_astro/metrics.BBUwKIos_zR8bd.webp)  
You can find these metrics within each AutoRAG instance:

  * Indexing: Track how files are ingested and see status changes over time.
  * Search breakdown: Compare usage between `ai-search` and `search` endpoints.
  * Top file retrievals: Identify which files are most frequently retrieved in a given period.  
Try it today in [AutoRAG](https://developers.cloudflare.com/ai-search/get-started/).

Sep 10, 2025
1. ### [Agents SDK v0.1.0 and workers-ai-provider v2.0.0 with AI SDK v5 support](https://developers.cloudflare.com/changelog/post/2025-09-03-agents-sdk-beta-v5/)  
[ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/)  
We've shipped a new release for the [Agents SDK ↗](https://github.com/cloudflare/agents) bringing full compatibility with [AI SDK v5 ↗](https://ai-sdk.dev/docs/introduction) and introducing automatic message migration that handles all legacy formats transparently.  
This release includes improved streaming and tool support, tool confirmation detection (for "human in the loop" systems), enhanced React hooks with automatic tool resolution, improved error handling for streaming responses, and seamless migration utilities that work behind the scenes.  
This makes it ideal for building production AI chat interfaces with Cloudflare Workers AI models, agent workflows, human-in-the-loop systems, or any application requiring reliable message handling across SDK versions — all while maintaining backward compatibility.  
Additionally, we've updated workers-ai-provider v2.0.0, the official provider for Cloudflare Workers AI models, to be compatible with AI SDK v5.  
#### useAgentChat(options)  
Creates a new chat interface with enhanced v5 capabilities.  
TypeScript  
```  
// Basic chat setupconst { messages, sendMessage, addToolResult } = useAgentChat({  agent,  experimental_automaticToolResolution: true,  tools,});  
// With custom tool confirmationconst chat = useAgentChat({  agent,  experimental_automaticToolResolution: true,  toolsRequiringConfirmation: ["dangerousOperation"],});  
```  
#### Automatic Tool Resolution  
Tools are automatically categorized based on their configuration:  
TypeScript  
```  
const tools = {  // Auto-executes (has execute function)  getLocalTime: {    description: "Get current local time",    inputSchema: z.object({}),    execute: async () => new Date().toLocaleString(),  },  
  // Requires confirmation (no execute function)  deleteFile: {    description: "Delete a file from the system",    inputSchema: z.object({      filename: z.string(),    }),  },  
  // Server-executed (no client confirmation)  analyzeData: {    description: "Analyze dataset on server",    inputSchema: z.object({ data: z.array(z.number()) }),    serverExecuted: true,  },} satisfies Record<string, AITool>;  
```  
#### Message Handling  
Send messages using the new v5 format with parts array:  
TypeScript  
```  
// Text messagesendMessage({  role: "user",  parts: [{ type: "text", text: "Hello, assistant!" }],});  
// Multi-part message with filesendMessage({  role: "user",  parts: [    { type: "text", text: "Analyze this image:" },    { type: "image", image: imageData },  ],});  
```  
#### Tool Confirmation Detection  
Simplified logic for detecting pending tool confirmations:  
TypeScript  
```  
const pendingToolCallConfirmation = messages.some((m) =>  m.parts?.some(    (part) => isToolUIPart(part) && part.state === "input-available",  ),);  
// Handle tool confirmationif (pendingToolCallConfirmation) {  await addToolResult({    toolCallId: part.toolCallId,    tool: getToolName(part),    output: "User approved the action",  });}  
```  
#### Automatic Message Migration  
Seamlessly handle legacy message formats without code changes.  
TypeScript  
```  
// All these formats are automatically converted:  
// Legacy v4 string contentconst legacyMessage = {  role: "user",  content: "Hello world",};  
// Legacy v4 with tool callsconst legacyWithTools = {  role: "assistant",  content: "",  toolInvocations: [    {      toolCallId: "123",      toolName: "weather",      args: { city: "SF" },      state: "result",      result: "Sunny, 72°F",    },  ],};  
// Automatically becomes v5 format:// {//   role: "assistant",//   parts: [{//     type: "tool-call",//     toolCallId: "123",//     toolName: "weather",//     args: { city: "SF" },//     state: "result",//     result: "Sunny, 72°F"//   }]// }  
```  
#### Tool Definition Updates  
Migrate tool definitions to use the new `inputSchema` property.  
TypeScript  
```  
// Before (AI SDK v4)const tools = {  weather: {    description: "Get weather information",    parameters: z.object({      city: z.string(),    }),    execute: async (args) => {      return await getWeather(args.city);    },  },};  
// After (AI SDK v5)const tools = {  weather: {    description: "Get weather information",    inputSchema: z.object({      city: z.string(),    }),    execute: async (args) => {      return await getWeather(args.city);    },  },};  
```  
#### Cloudflare Workers AI Integration  
Seamless integration with Cloudflare Workers AI models through the updated workers-ai-provider v2.0.0.  
#### Model Setup with Workers AI  
Use Cloudflare Workers AI models directly in your agent workflows:  
TypeScript  
```  
import { createWorkersAI } from "workers-ai-provider";import { useAgentChat } from "agents/ai-react";  
// Create Workers AI model (v2.0.0 - same API, enhanced v5 internals)const model = createWorkersAI({  binding: env.AI,})("@cf/meta/llama-3.2-3b-instruct");  
```  
#### Enhanced File and Image Support  
Workers AI models now support v5 file handling with automatic conversion:  
TypeScript  
```  
// Send images and files to Workers AI modelssendMessage({  role: "user",  parts: [    { type: "text", text: "Analyze this image:" },    {      type: "file",      data: imageBuffer,      mediaType: "image/jpeg",    },  ],});  
// Workers AI provider automatically converts to proper format  
```  
#### Streaming with Workers AI  
Enhanced streaming support with automatic warning detection:  
TypeScript  
```  
// Streaming with Workers AI modelsconst result = await streamText({  model: createWorkersAI({ binding: env.AI })("@cf/meta/llama-3.2-3b-instruct"),  messages,  onChunk: (chunk) => {    // Enhanced streaming with warning handling    console.log(chunk);  },});  
```  
#### Import Updates  
Update your imports to use the new v5 types:  
TypeScript  
```  
// Before (AI SDK v4)import type { Message } from "ai";import { useChat } from "ai/react";  
// After (AI SDK v5)import type { UIMessage } from "ai";// or alias for compatibilityimport type { UIMessage as Message } from "ai";import { useChat } from "@ai-sdk/react";  
```  
#### Resources

  * [Migration Guide ↗](https://github.com/cloudflare/agents/blob/main/docs/migration-to-ai-sdk-v5.md) \- Comprehensive migration documentation
  * [AI SDK v5 Documentation ↗](https://ai-sdk.dev/docs/migration-guides/migration-guide-5-0) \- Official AI SDK migration guide
  * [An Example PR showing the migration from AI SDK v4 to v5 ↗](https://github.com/cloudflare/agents-starter/pull/105)
  * [GitHub Issues ↗](https://github.com/cloudflare/agents/issues) \- Report bugs or request features  
#### Feedback Welcome  
We'd love your feedback! We're particularly interested in feedback on:

  * **Migration experience** \- How smooth was the upgrade process?
  * **Tool confirmation workflow** \- Does the new automatic detection work as expected?
  * **Message format handling** \- Any edge cases with legacy message conversion?

Sep 05, 2025
1. ### [Introducing EmbeddingGemma from Google on Workers AI](https://developers.cloudflare.com/changelog/post/2025-09-05-embeddinggemma/)  
[ Workers AI ](https://developers.cloudflare.com/workers-ai/)  
We're excited to be a launch partner alongside [Google ↗](https://developers.googleblog.com/en/introducing-embeddinggemma/) to bring their newest embedding model, **EmbeddingGemma**, to Workers AI that delivers best-in-class performance for its size, enabling RAG and semantic search use cases.  
[@cf/google/embeddinggemma-300m](https://developers.cloudflare.com/workers-ai/models/embeddinggemma-300m/) is a 300M parameter embedding model from Google, built from Gemma 3 and the same research used to create Gemini models. This multilingual model supports 100+ languages, making it ideal for RAG systems, semantic search, content classification, and clustering tasks.

**Using EmbeddingGemma in AI Search:**Now you can leverage EmbeddingGemma directly through AI Search for your RAG pipelines. EmbeddingGemma's multilingual capabilities make it perfect for global applications that need to understand and retrieve content across different languages with exceptional accuracy.  
To use EmbeddingGemma for your AI Search projects:

  1. Go to **Create** in the [AI Search dashboard ↗](https://dash.cloudflare.com/?to=/:account/ai/ai-search)
  2. Follow the setup flow for your new RAG instance
  3. In the **Generate Index** step, open up **More embedding models** and select `@cf/google/embeddinggemma-300m` as your embedding model
  4. Complete the setup to create an AI Search  
Try it out and let us know what you think!

Aug 27, 2025
1. ### [Enhanced crawler insights and custom 402 responses](https://developers.cloudflare.com/changelog/post/2025-08-27-ai-crawl-control-launch/)  
[ AI Crawl Control ](https://developers.cloudflare.com/ai-crawl-control/)  
We improved AI crawler management with detailed analytics and introduced custom HTTP 402 responses for blocked crawlers. AI Audit has been renamed to AI Crawl Control and is now generally available.

**Enhanced Crawlers tab:**

  * View total allowed and blocked requests for each AI crawler
  * Trend charts show crawler activity over your selected time range per crawler  
![Updated AI Crawl Control table showing request counts and trend charts](https://developers.cloudflare.com/_astro/ai-crawl-control-table.BDr0Qd-5_ZKex0W.webp)  

**Custom block responses (paid plans):**You can now return HTTP 402 "Payment Required" responses when blocking AI crawlers, enabling direct communication with crawler operators about licensing terms.  
For users on paid plans, when blocking AI crawlers you can configure:

  * **Response code:** Choose between 403 Forbidden or 402 Payment Required
  * **Response body:** Add a custom message with your licensing contact information  
![AI Crawl Control block response configuration interface](https://developers.cloudflare.com/_astro/ai-crawl-control-block-response.L4duQj7-_Z2mHb4X.webp)  
Example 402 response:  
```  
HTTP 402 Payment RequiredDate: Mon, 24 Aug 2025 12:56:49 GMTContent-type: application/jsonServer: cloudflareCf-Ray: 967e8da599d0c3fa-EWRCf-Team: 2902f6db750000c3fa1e2ef400000001  
{  "message": "Please contact the site owner for access."}  
```

Aug 27, 2025
1. ### [Deepgram and Leonardo partner models now available on Workers AI](https://developers.cloudflare.com/changelog/post/2025-08-27-partner-models/)  
[ Workers AI ](https://developers.cloudflare.com/workers-ai/)  
New state-of-the-art models have landed on Workers AI! This time, we're introducing new **partner models** trained by our friends at [Deepgram ↗](https://deepgram.com) and [Leonardo ↗](https://leonardo.ai), hosted on Workers AI infrastructure.  
As well, we're introuding a new turn detection model that enables you to detect when someone is done speaking — useful for building voice agents!  
Read the [blog ↗](https://blog.cloudflare.com/workers-ai-partner-models) for more details and check out some of the new models on our platform:

  * [@cf/deepgram/aura-1](https://developers.cloudflare.com/workers-ai/models/aura-1) is a text-to-speech model that allows you to input text and have it come to life in a customizable voice
  * [@cf/deepgram/nova-3](https://developers.cloudflare.com/workers-ai/models/nova-3) is speech-to-text model that transcribes multilingual audio at a blazingly fast speed
  * [@cf/pipecat-ai/smart-turn-v2](https://developers.cloudflare.com/workers-ai/models/smart-turn-v2) helps you detect when someone is done speaking
  * [@cf/leonardo/lucid-origin](https://developers.cloudflare.com/workers-ai/models/lucid-origin) is a text-to-image model that generates images with sharp graphic design, stunning full-HD renders, or highly specific creative direction
  * [@cf/leonardo/phoenix-1.0](https://developers.cloudflare.com/workers-ai/models/phoenix-1.0) is a text-to-image model with exceptional prompt adherence and coherent text  
You can filter out new partner models with the `Partner` capability on our [Models](https://developers.cloudflare.com/workers-ai/models) page.  
As well, we're introducing WebSocket support for some of our audio models, which you can filter though the `Realtime` capability on our [Models](https://developers.cloudflare.com/workers-ai/models) page. WebSockets allows you to create a bi-directional connection to our inference server with low latency — perfect for those that are building voice agents.  
An example python snippet on how to use WebSockets with our new Aura model:  
```  
import jsonimport osimport asyncioimport websockets  
uri = f"wss://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/deepgram/aura-1"  
input = [    "Line one, out of three lines that will be provided to the aura model.",    "Line two, out of three lines that will be provided to the aura model.",    "Line three, out of three lines that will be provided to the aura model. This is a last line.",]  
async def text_to_speech():    async with websockets.connect(uri, additional_headers={"Authorization": os.getenv("CF_TOKEN")}) as websocket:        print("connection established")        for line in input:            print(f"sending `{line}`")            await websocket.send(json.dumps({"type": "Speak", "text": line}))  
            print("line was sent, flushing")            await websocket.send(json.dumps({"type": "Flush"}))            print("flushed, recving")            resp = await websocket.recv()            print(f"response received {resp}")  
if __name__ == "__main__":    asyncio.run(text_to_speech())  
```

Aug 26, 2025
1. ### [List all vectors in a Vectorize index with the new list-vectors operation](https://developers.cloudflare.com/changelog/post/2025-08-26-vectorize-list-vectors/)  
[ Vectorize ](https://developers.cloudflare.com/vectorize/)  
You can now list all vector identifiers in a Vectorize index using the new `list-vectors` operation. This enables bulk operations, auditing, and data migration workflows through paginated requests that maintain snapshot consistency.  
The operation is available via Wrangler CLI and REST API. Refer to the [list-vectors best practices guide](https://developers.cloudflare.com/vectorize/best-practices/list-vectors/) for detailed usage guidance.

Aug 25, 2025
1. ### [Manage and deploy your AI provider keys through Bring Your Own Key (BYOK) with AI Gateway, now powered by Cloudflare Secrets Store](https://developers.cloudflare.com/changelog/post/2025-08-25-secrets-store-ai-gateway/)  
[ Secrets Store ](https://developers.cloudflare.com/secrets-store/)[ AI Gateway ](https://developers.cloudflare.com/ai-gateway/)[ SSL/TLS ](https://developers.cloudflare.com/ssl/)  
Cloudflare Secrets Store is now integrated with AI Gateway, allowing you to store, manage, and deploy your AI provider keys in a secure and seamless configuration through [Bring Your Own Key ↗](https://developers.cloudflare.com/ai-gateway/configuration/bring-your-own-keys/). Instead of passing your AI provider keys directly in every request header, you can centrally manage each key with Secrets Store and deploy in your gateway configuration using only a reference, rather than passing the value in plain text.  
You can now create a secret directly from your AI Gateway [in the dashboard ↗](http://dash.cloudflare.com/?to=/:account/ai-gateway) by navigating into your gateway -> **Provider Keys** \-> **Add**.  
![Import repo or choose template](https://developers.cloudflare.com/_astro/add-secret-ai-gateway.B-SIPr6s_jJjDD.webp)  
You can also create your secret with the newly available **ai\_gateway** scope via [wrangler ↗](https://developers.cloudflare.com/workers/wrangler/commands/), the [Secrets Store dashboard ↗](http://dash.cloudflare.com/?to=/:account/secrets-store), or the [API ↗](https://developers.cloudflare.com/api/resources/secrets%5Fstore/).  
Then, pass the key in the request header using its Secrets Store reference:  
Terminal window  
```  
curl -X POST https://gateway.ai.cloudflare.com/v1/<ACCOUNT_ID>/my-gateway/anthropic/v1/messages \ --header 'cf-aig-authorization: ANTHROPIC_KEY_1 \ --header 'anthropic-version: 2023-06-01' \ --header 'Content-Type: application/json' \ --data  '{"model": "claude-3-opus-20240229", "messages": [{"role": "user", "content": "What is Cloudflare?"}]}'  
```  
Or, using Javascript:  
```  
import Anthropic from '@anthropic-ai/sdk';  
const anthropic = new Anthropic({ apiKey: "ANTHROPIC_KEY_1", baseURL: "https://gateway.ai.cloudflare.com/v1/<ACCOUNT_ID>/my-gateway/anthropic",});  
const message = await anthropic.messages.create({ model: 'claude-3-opus-20240229', messages: [{role: "user", content: "What is Cloudflare?"}], max_tokens: 1024});  
```  
For more information, check out the [blog ↗](https://blog.cloudflare.com/ai-gateway-aug-2025-refresh)!

Aug 05, 2025
1. ### [Agents SDK adds MCP Elicitation support, http-streamable support, task queues, email integration and more](https://developers.cloudflare.com/changelog/post/2025-08-05-agents-mcp-update/)  
[ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/)  
The latest releases of [@cloudflare/agents ↗](https://github.com/cloudflare/agents) brings major improvements to MCP transport protocols support and agents connectivity. Key updates include:  
#### MCP elicitation support  
MCP servers can now request user input during tool execution, enabling interactive workflows like confirmations, forms, and multi-step processes. This feature uses durable storage to preserve elicitation state even during agent hibernation, ensuring seamless user interactions across agent lifecycle events.  
TypeScript  
```  
// Request user confirmation via elicitationconst confirmation = await this.elicitInput({  message: `Are you sure you want to increment the counter by ${amount}?`,  requestedSchema: {    type: "object",    properties: {      confirmed: {        type: "boolean",        title: "Confirm increment",        description: "Check to confirm the increment",      },    },    required: ["confirmed"],  },});  
```  
Check out our [demo ↗](https://github.com/whoiskatrin/agents/tree/main/examples/mcp-elicitation-demo) to see elicitation in action.  
#### HTTP streamable transport for MCP  
MCP now supports HTTP streamable transport which is recommended over SSE. This transport type offers:

  * **Better performance**: More efficient data streaming and reduced overhead
  * **Improved reliability**: Enhanced connection stability and error recover- **Automatic fallback**: If streamable transport is not available, it gracefully falls back to SSE  
TypeScript  
```  
export default MyMCP.serve("/mcp", {  binding: "MyMCP",});  
```  
The SDK automatically selects the best available transport method, gracefully falling back from streamable-http to SSE when needed.  
#### Enhanced MCP connectivity  
Significant improvements to MCP server connections and transport reliability:

  * **Auto transport selection**: Automatically determines the best transport method, falling back from streamable-http to SSE as needed
  * **Improved error handling**: Better connection state management and error reporting for MCP servers
  * **Reliable prop updates**: Centralized agent property updates ensure consistency across different contexts  
#### Lightweight .queue for fast task deferral  
You can use `.queue()` to enqueue background work — ideal for tasks like processing user messages, sending notifications etc.  
TypeScript  
```  
class MyAgent extends Agent {  doSomethingExpensive(payload) {    // a long running process that you want to run in the background  }  
  queueSomething() {    await this.queue("doSomethingExpensive", somePayload); // this will NOT block further execution, and runs in the background    await this.queue("doSomethingExpensive", someOtherPayload); // the callback will NOT run until the previous callback is complete    // ... call as many times as you want  }}  
```  
Want to try it yourself? Just define a method like processMessage in your agent, and you’re ready to scale.  
#### New email adapter  
Want to build an AI agent that can receive and respond to emails automatically? With the new email adapter and onEmail lifecycle method, now you can.  
TypeScript  
```  
export class EmailAgent extends Agent {  async onEmail(email: AgentEmail) {    const raw = await email.getRaw();    const parsed = await PostalMime.parse(raw);  
    // create a response based on the email contents    // and then send a reply  
    await this.replyToEmail(email, {      fromName: "Email Agent",      body: `Thanks for your email! You've sent us "${parsed.subject}". We'll process it shortly.`,    });  }}  
```  
You route incoming mail like this:  
TypeScript  
```  
export default {  async email(email, env) {    await routeAgentEmail(email, env, {      resolver: createAddressBasedEmailResolver("EmailAgent"),    });  },};  
```  
You can find a full example [here ↗](https://github.com/cloudflare/agents/tree/main/examples/email-agent).  
#### Automatic context wrapping for custom methods  
Custom methods are now automatically wrapped with the agent's context, so calling `getCurrentAgent()` should work regardless of where in an agent's lifecycle it's called. Previously this would not work on RPC calls, but now just works out of the box.  
TypeScript  
```  
export class MyAgent extends Agent {  async suggestReply(message) {    // getCurrentAgent() now correctly works, even when called inside an RPC method    const { agent } = getCurrentAgent()!;    return generateText({      prompt: `Suggest a reply to: "${message}" from "${agent.name}"`,      tools: [replyWithEmoji],    });  }}  
```  
Try it out and tell us what you build!

Aug 05, 2025
1. ### [Cloudflare Sandbox SDK adds streaming, code interpreter, Git support, process control and more](https://developers.cloudflare.com/changelog/post/2025-08-05-sandbox-sdk-major-update/)  
[ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/)  
We’ve shipped a major release for the [@cloudflare/sandbox ↗](https://github.com/cloudflare/sandbox-sdk) SDK, turning it into a full-featured, container-based execution platform that runs securely on Cloudflare Workers.  
This update adds live streaming of output, persistent Python and JavaScript code interpreters with rich output support (charts, tables, HTML, JSON), file system access, Git operations, full background process control, and the ability to expose running services via public URLs.  
This makes it ideal for building AI agents, CI runners, cloud REPLs, data analysis pipelines, or full developer tools — all without managing infrastructure.  
#### Code interpreter (Python, JS, TS)  
Create persistent code contexts with support for rich visual + structured outputs.  
#### createCodeContext(options)  
Creates a new code execution context with persistent state.  
TypeScript  
```  
// Create a Python contextconst pythonCtx = await sandbox.createCodeContext({ language: "python" });  
// Create a JavaScript contextconst jsCtx = await sandbox.createCodeContext({ language: "javascript" });  
```  
Options:

  * language: Programming language ('python' | 'javascript' | 'typescript')
  * cwd: Working directory (default: /workspace)
  * envVars: Environment variables for the context  
#### runCode(code, options)  
Executes code with optional streaming callbacks.  
TypeScript  
```  
// Simple executionconst execution = await sandbox.runCode('print("Hello World")', {  context: pythonCtx,});  
// With streaming callbacksawait sandbox.runCode(  `for i in range(5):    print(f"Step {i}")    time.sleep(1)`,  {    context: pythonCtx,    onStdout: (output) => console.log("Real-time:", output.text),    onResult: (result) => console.log("Result:", result),  },);  
```  
Options:

  * language: Programming language ('python' | 'javascript' | 'typescript')
  * cwd: Working directory (default: /workspace)
  * envVars: Environment variables for the context  
#### Real-time streaming output  
Returns a streaming response for real-time processing.  
TypeScript  
```  
const stream = await sandbox.runCodeStream(  "import time; [print(i) for i in range(10)]",);// Process the stream as needed  
```  
#### Rich output handling  
Interpreter outputs are auto-formatted and returned in multiple formats:

  * text
  * html (e.g., Pandas tables)
  * png, svg (e.g., Matplotlib charts)
  * json (structured data)
  * chart (parsed visualizations)  
TypeScript  
```  
const result = await sandbox.runCode(  `import seaborn as snsimport matplotlib.pyplot as plt  
data = sns.load_dataset("flights")pivot = data.pivot("month", "year", "passengers")sns.heatmap(pivot, annot=True, fmt="d")plt.title("Flight Passengers")plt.show()  
pivot.to_dict()`,  { context: pythonCtx },);  
if (result.png) {  console.log("Chart output:", result.png);}  
```  
#### Preview URLs from Exposed Ports  
Start background processes and expose them with live URLs.  
TypeScript  
```  
await sandbox.startProcess("python -m http.server 8000");const preview = await sandbox.exposePort(8000);  
console.log("Live preview at:", preview.url);  
```  
#### Full process lifecycle control  
Start, inspect, and terminate long-running background processes.  
TypeScript  
```  
const process = await sandbox.startProcess("node server.js");console.log(`Started process ${process.id} with PID ${process.pid}`);  
// Monitor the processconst logStream = await sandbox.streamProcessLogs(process.id);for await (const log of parseSSEStream<LogEvent>(logStream)) {  console.log(`Server: ${log.data}`);}  
```

  * listProcesses() - List all running processes
  * getProcess(id) - Get detailed process status
  * killProcess(id, signal) - Terminate specific processes
  * killAllProcesses() - Kill all processes
  * streamProcessLogs(id, options) - Stream logs from running processes
  * getProcessLogs(id) - Get accumulated process output  
#### Git integration  
Clone Git repositories directly into the sandbox.  
TypeScript  
```  
await sandbox.gitCheckout("https://github.com/user/repo", {  branch: "main",  targetDir: "my-project",});  
```  
Sandboxes are still experimental. We're using them to explore how isolated, container-like workloads might scale on Cloudflare — and to help define the developer experience around them.

Aug 05, 2025
1. ### [OpenAI open models now available on Workers AI](https://developers.cloudflare.com/changelog/post/2025-08-05-openai-open-models/)  
[ Agents ](https://developers.cloudflare.com/agents/)[ Workers AI ](https://developers.cloudflare.com/workers-ai/)  
We're thrilled to be a Day 0 partner with [OpenAI ↗](http://openai.com/index/introducing-gpt-oss) to bring their [latest open models ↗](https://openai.com/index/gpt-oss-model-card/) to Workers AI, including support for Responses API, Code Interpreter, and Web Search (coming soon).  
Get started with the new models at `@cf/openai/gpt-oss-120b` and `@cf/openai/gpt-oss-20b`. Check out the [blog ↗](https://blog.cloudflare.com/openai-gpt-oss-on-workers-ai) for more details about the new models, and the [gpt-oss-120b](https://developers.cloudflare.com/workers-ai/models/gpt-oss-120b) and [gpt-oss-20b](https://developers.cloudflare.com/workers-ai/models/gpt-oss-20b) model pages for more information about pricing and context windows.  
#### Responses API  
If you call the model through:

  * Workers Binding, it will accept/return Responses API – `env.AI.run(“@cf/openai/gpt-oss-120b”)`
  * REST API on `/run` endpoint, it will accept/return Responses API – `https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/run/@cf/openai/gpt-oss-120b`
  * REST API on new `/responses` endpoint, it will accept/return Responses API – `https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/v1/responses`
  * REST API for OpenAI Compatible endpoint, it will return Chat Completions (coming soon) – `https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/v1/chat/completions`  
```  
curl https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/v1/responses \  -H "Content-Type: application/json" \  -H "Authorization: Bearer $CLOUDFLARE_API_KEY" \  -d '{    "model": "@cf/openai/gpt-oss-120b",    "reasoning": {"effort": "medium"},    "input": [      {        "role": "user",        "content": "What are the benefits of open-source models?"      }    ]  }'  
```  
#### Code Interpreter  
The model is natively trained to support stateful code execution, and we've implemented support for this feature using our [Sandbox SDK ↗](https://github.com/cloudflare/sandbox-sdk) and [Containers ↗](https://blog.cloudflare.com/containers-are-available-in-public-beta-for-simple-global-and-programmable/). Cloudflare's Developer Platform is uniquely positioned to support this feature, so we're very excited to bring our products together to support this new use case.  
#### Web Search (coming soon)  
We are working to implement Web Search for the model, where users can bring their own Exa API Key so the model can browse the Internet.

Jul 28, 2025
1. ### [Introducing pricing for the Browser Rendering API — $0.09 per browser hour](https://developers.cloudflare.com/changelog/post/2025-07-28-br-pricing/)  
[ Browser Run ](https://developers.cloudflare.com/browser-run/)  
We’ve launched pricing for [Browser Rendering](https://developers.cloudflare.com/browser-run/), including a free tier and a pay-as-you-go model that scales with your needs. Starting **August 20, 2025**, Cloudflare will begin billing for Browser Rendering.  
There are two ways to use Browser Rendering. Depending on the method you use, here’s how billing will work:

  * [**REST API**](https://developers.cloudflare.com/browser-run/quick-actions/): Charged for **Duration** only ($/browser hour)
  * [**Browser Sessions**](https://developers.cloudflare.com/browser-run/#integration-methods): Charged for both **Duration** and **Concurrency** ($/browser hour and # of concurrent browsers)  
Included usage and pricing by plan

| Plan             | Included duration  | Included concurrency                      | Price (beyond included)                                                                                                                                  |
| ---------------- | ------------------ | ----------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Workers Free** | 10 minutes per day | 3 concurrent browsers                     | N/A                                                                                                                                                      |
| **Workers Paid** | 10 hours per month | 10 concurrent browsers (averaged monthly) | **1\. REST API**: $0.09 per additional browser hour **2\. Workers Bindings**: $0.09 per additional browser hour  $2.00 per additional concurrent browser |  
What you need to know:

  * **Workers Free Plan:** 10 minutes of browser usage per day with 3 concurrent browsers at no charge.
  * **Workers Paid Plan:** 10 hours of browser usage per month with 10 concurrent browsers (averaged monthly) at no charge. Additional usage is charged as shown above.  
You can monitor usage via the [Cloudflare dashboard ↗](https://dash.cloudflare.com/?to=/:account/workers/browser-run). Go to **Compute** \> **Browser Run**.  
![Browser Rendering dashboard](https://developers.cloudflare.com/_astro/dashboard.BQnX87lT_39GAT.webp)  
If you've been using Browser Rendering and do not wish to incur charges, ensure your usage stays within your plan's [included usage](https://developers.cloudflare.com/browser-run/pricing/). To estimate costs, take a look at these [example pricing scenarios](https://developers.cloudflare.com/browser-run/pricing/#examples-of-workers-paid-pricing).

Jul 22, 2025
1. ### [Browser Rendering now supports local development](https://developers.cloudflare.com/changelog/post/2025-07-22-br-local-dev/)  
[ Browser Run ](https://developers.cloudflare.com/browser-run/)  
You can now run your Browser Rendering locally using `npx wrangler dev`, which spins up a browser directly on your machine before deploying to Cloudflare's global network. By running tests locally, you can quickly develop, debug, and test changes without needing to deploy or worry about usage costs.  
Get started with this [example guide](https://developers.cloudflare.com/browser-run/how-to/deploy-worker/) that shows how to use Cloudflare's [fork of Puppeteer](https://developers.cloudflare.com/browser-run/puppeteer/) (you can also use [Playwright](https://developers.cloudflare.com/browser-run/playwright/)) to take screenshots of webpages and store the results in [Workers KV](https://developers.cloudflare.com/kv/).

Jul 08, 2025
1. ### [Faster indexing and new Jobs view in AutoRAG](https://developers.cloudflare.com/changelog/post/2025-07-08-autorag-jobs-view/)  
[ AI Search ](https://developers.cloudflare.com/ai-search/)  
You can now expect **3-5× faster indexing** in AutoRAG, and with it, a brand new **Jobs view** to help you monitor indexing progress.  
With each AutoRAG, indexing jobs are automatically triggered to sync your data source (i.e. R2 bucket) with your Vectorize index, ensuring new or updated files are reflected in your query results. You can also trigger jobs manually via the [Sync API](https://developers.cloudflare.com/api/resources/ai-search/subresources/rags/) or by clicking “Sync index” in the dashboard.  
With the new jobs observability, you can now:

  * View the status, job ID, source, start time, duration and last sync time for each indexing job
  * Inspect real-time logs of job events (e.g. `Starting indexing data source...`)
  * See a history of past indexing jobs under the Jobs tab of your AutoRAG  
This makes it easier to understand what’s happening behind the scenes.

**Coming soon:** We’re adding APIs to programmatically check indexing status, making it even easier to integrate AutoRAG into your workflows.  
Try it out today on the [Cloudflare dashboard ↗](https://dash.cloudflare.com/?to=/:account/ai/autorag).

Jul 01, 2025
1. ### [Introducing Pay Per Crawl (private beta)](https://developers.cloudflare.com/changelog/post/2025-07-01-pay-per-crawl/)  
[ AI Crawl Control ](https://developers.cloudflare.com/ai-crawl-control/)  
We are introducing a new feature of [AI Crawl Control](https://developers.cloudflare.com/ai-crawl-control/) — Pay Per Crawl. [Pay Per Crawl](https://developers.cloudflare.com/ai-crawl-control/features/pay-per-crawl/what-is-pay-per-crawl/) enables site owners to require payment from AI crawlers every time the crawlers access their content, thereby fostering a fairer Internet by enabling site owners to control and monetize how their content gets used by AI.  
![Pay per crawl](https://developers.cloudflare.com/_astro/pay-per-crawl.B5bv2nwT_1TH6vv.webp)  

**For Site Owners:**

  * Set pricing and select which crawlers to charge for content access
  * Manage payments via Stripe
  * Monitor analytics on successful content deliveries

**For AI Crawler Owners:**

  * Use HTTP headers to request and accept pricing
  * Receive clear confirmations on charges for accessed content  
Learn more in the [Pay Per Crawl documentation](https://developers.cloudflare.com/ai-crawl-control/features/pay-per-crawl/what-is-pay-per-crawl/).

Jul 01, 2025
1. ### [AI Crawl Control refresh](https://developers.cloudflare.com/changelog/post/2025-07-01-refresh/)  
[ AI Crawl Control ](https://developers.cloudflare.com/ai-crawl-control/)  
We redesigned the AI Crawl Control dashboard to provide more intuitive and granular control over AI crawlers.

  * From the new **AI Crawlers** tab: block specific AI crawlers.
  * From the new **Metrics** tab: view AI Crawl Control metrics.  
![Block AI crawlers](https://developers.cloudflare.com/_astro/manage-ai-crawlers.6UgS8dSG_Z1HRWpI.webp) ![Analyze AI crawler activity](https://developers.cloudflare.com/_astro/analyze-metrics.C52pJZVg_1C7hti.webp)  
To get started, explore:

  * [Manage AI crawlers](https://developers.cloudflare.com/ai-crawl-control/features/manage-ai-crawlers/).
  * [Analyze AI traffic](https://developers.cloudflare.com/ai-crawl-control/features/analyze-ai-traffic/).

Jun 25, 2025
1. ### [Run AI-generated code on-demand with Code Sandboxes (new)](https://developers.cloudflare.com/changelog/post/2025-06-24-announcing-sandboxes/)  
[ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/)[ Workflows ](https://developers.cloudflare.com/workflows/)  
AI is supercharging app development for everyone, but we need a safe way to run untrusted, LLM-written code. We’re introducing [Sandboxes ↗](https://www.npmjs.com/package/@cloudflare/sandbox), which let your Worker run actual processes in a secure, container-based environment.  
TypeScript  
```  
import { getSandbox } from "@cloudflare/sandbox";export { Sandbox } from "@cloudflare/sandbox";  
export default {  async fetch(request: Request, env: Env) {    const sandbox = getSandbox(env.Sandbox, "my-sandbox");    return sandbox.exec("ls", ["-la"]);  },};  
```  
#### Methods

  * `exec(command: string, args: string[], options?: { stream?: boolean })`:Execute a command in the sandbox.
  * `gitCheckout(repoUrl: string, options: { branch?: string; targetDir?: string; stream?: boolean })`: Checkout a git repository in the sandbox.
  * `mkdir(path: string, options: { recursive?: boolean; stream?: boolean })`: Create a directory in the sandbox.
  * `writeFile(path: string, content: string, options: { encoding?: string; stream?: boolean })`: Write content to a file in the sandbox.
  * `readFile(path: string, options: { encoding?: string; stream?: boolean })`: Read content from a file in the sandbox.
  * `deleteFile(path: string, options?: { stream?: boolean })`: Delete a file from the sandbox.
  * `renameFile(oldPath: string, newPath: string, options?: { stream?: boolean })`: Rename a file in the sandbox.
  * `moveFile(sourcePath: string, destinationPath: string, options?: { stream?: boolean })`: Move a file from one location to another in the sandbox.
  * `ping()`: Ping the sandbox.  
Sandboxes are still experimental. We're using them to explore how isolated, container-like workloads might scale on Cloudflare — and to help define the developer experience around them.  
You can try it today from your Worker, with just a few lines of code. Let us know what you build.

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