# 翻译结果 Durable Objects Skill: Build Chatrooms, Collaboration and Stateful RPC According to Official Conventions
### 正式翻译（符合技术文档译法，兼顾准确性与行业惯例）： The official Cloudflare durable-objects Skill is used to create and review Durable Objects: sharding by chat rooms, game sessions or tenants, routing via `getByName`, carrying stateful edge logic with SQLite, RPC, alarms and WebSockets, and testing with Vitest. This article verifies the installation, configuration and anti-patterns against the original GitHub source and official documentation, and notes that while the Skill example still uses migrations, the current getting-started documentation recommends declaring SQLite classes via `exports`.
Read MoreWrangler Skill: Enable AI Assistants to Deploy Cloudflare Workers Correctly
This article introduces Cloudflare's official Agent Skill "wrangler": it guides AI programming assistants to prioritize retrieving official documentation and configuration schemas before deploying and managing resources such as Workers, KV, R2, D1, etc., to avoid outdated commands and incorrect bindings. The article covers the positioning of the Skill, its core capabilities, installation and activation in tools including Cursor, Claude Code, Codex and other platforms, typical examples of wrangler.jsonc and commonly used commands, as well as precautions such as key security and local remote binding.
Read More# cloudflare-deploy: Let AI Agents Deploy Applications to Cloudflare Edge Network
`cloudflare-deploy` is an Agent Skill under the OpenAI openai/skills curated directory. It guides AI Agents to complete full-stack deployments on Cloudflare, including Workers, Pages, and services like KV/D1/R2, via decision trees and reference documents. This article verifies the official SKILL.md, introduces its differences from vercel-deploy, the installation methods for Codex/Cursor, the Wrangler authentication process and typical deployment commands, which is suitable for developers who need edge Serverless and multi-cloud deployments.
Read MoreMy New Book, "Introduction to and Practical Guide of PaddlePaddle Fluid Deep Learning" Has Been Published!
This book provides a detailed introduction to deep learning development using PaddlePaddle, covering the entire process from environment setup to practical project applications. The content includes environment setup, quick start, linear regression algorithm, practical cases of convolutional neural networks and recurrent neural networks, generative adversarial networks, reinforcement learning, etc. Additionally, it explains model saving and usage, transfer learning, and the application of the mobile framework Paddle-Lite. This book is suitable for beginners to get started and can help solve practical problems such as flower species recognition and news headline classification projects. All the code in the book has been tested, and there are supporting resources.
Read MorePaddlePaddle From Beginner to "Alchemy" - Part 15: Deploying Prediction Models to Android Phones
Thank you for your sharing and detailed notes, which provide a great reference for developers who want to learn how to integrate PaddlePaddle for image recognition in Android applications. Below, I will summarize the information you provided and add some content that may help with understanding: ### 1. Environment Preparation - **Development Environment**: Ensure the latest version of Android Studio is installed. - **Permission Configuration**: Add necessary permissions in `AndroidManifest.xml`, such as read and write access to external storage.
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