diff --git a/README.md b/README.md
index 491f5c1..c2c8cb9 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,14 @@
-## 🚀 **Looking for an even faster and simpler way to scrape at scale (only 5 lines of code)?** Check out our enhanced version at [**ScrapeGraphAI.com**](https://scrapegraphai.com/?utm_source=github&utm_medium=readme&utm_campaign=oss_cta&ut#m_content=top_banner)! 🚀
+<!-- WEHUB_ZH_README -->
+> [!NOTE]
+> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。  
+> [English](./README.en.md) · [原始项目](https://github.com/ScrapeGraphAI/Scrapegraph-ai) · [上游 README](https://github.com/ScrapeGraphAI/Scrapegraph-ai/blob/HEAD/README.md)  
+> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
+
+## 🚀 **想要一种更快、更简单的规模化爬取方式（仅需 5 行代码）？** 请访问我们的增强版：[**ScrapeGraphAI.com**](https://scrapegraphai.com/?utm_source=github&utm_medium=readme&utm_campaign=oss_cta&ut#m_content=top_banner)! 🚀
 
 ---
 
-# 🕷️ ScrapeGraphAI: You Only Scrape Once
+# 🕷️ ScrapeGraphAI：只需爬取一次
 
 <p align="center">
   <a href="https://scrapegraphai.com">
@@ -30,10 +36,10 @@
 
 [ScrapeGraphAI](https://scrapegraphai.com) is a *web scraping* python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.).
 
-Just say which information you want to extract and the library will do it for you!
+只需说明你想提取哪些信息，库会替你完成！
 
-## 🚀 Integrations
-ScrapeGraphAI offers seamless integration with popular frameworks and tools to enhance your scraping capabilities. Whether you're building with Python or Node.js, using LLM frameworks, or working with no-code platforms, we've got you covered with our comprehensive integration options..
+## 🚀 集成
+ScrapeGraphAI 可与主流框架和工具无缝集成，增强你的爬取能力。无论你使用 Python 或 Node.js 开发、使用 LLM 框架，还是与无代码平台协作，我们都提供全面的集成选项..
 
 <p align="center">
   <a href="https://scrapegraphai.com">
@@ -41,9 +47,9 @@ ScrapeGraphAI offers seamless integration with popular frameworks and tools to e
   </a>
 </p>
 
-You can find more informations at the following [link](https://scrapegraphai.com)
+更多信息请参阅以下[链接](https://scrapegraphai.com)
 
-**Integrations**:
+**集成**：
 - **API**: [Documentation](https://docs.scrapegraphai.com/introduction)
 - **SDKs**: [Python](https://docs.scrapegraphai.com/sdks/python), [Node](https://docs.scrapegraphai.com/sdks/javascript)
 - **LLM Frameworks**: [Langchain](https://docs.scrapegraphai.com/integrations/langchain), [Llama Index](https://docs.scrapegraphai.com/integrations/llamaindex), [Crew.ai](https://docs.scrapegraphai.com/integrations/crewai), [Agno](https://docs.scrapegraphai.com/integrations/agno), [CamelAI](https://github.com/camel-ai/camel)
@@ -51,9 +57,9 @@ You can find more informations at the following [link](https://scrapegraphai.com
 - **MCP server**:  [Link](https://smithery.ai/server/@ScrapeGraphAI/scrapegraph-mcp)
 
 
-## 🚀 Quick install
+## 🚀 快速安装
 
-The reference page for Scrapegraph-ai is available on the official page of PyPI: [pypi](https://pypi.org/project/scrapegraphai/).
+Scrapegraph-ai 的参考页面可在 PyPI 官方页面查看：[pypi](https://pypi.org/project/scrapegraphai/).
 
 ```bash
 pip install scrapegraphai
@@ -62,13 +68,13 @@ pip install scrapegraphai
 playwright install
 ```
 
-**Note**: it is recommended to install the library in a virtual environment to avoid conflicts with other libraries 🐱
+**注意**：建议在虚拟环境中安装本库，以避免与其他库发生冲突 🐱
 
 
-## 💻 Usage
-There are multiple standard scraping pipelines that can be used to extract information from a website (or local file).
+## 💻 用法
+有多种标准爬取流水线可用于从网站（或本地文件）提取信息。
 
-The most common one is the `SmartScraperGraph`, which extracts information from a single page given a user prompt and a source URL.
+最常用的是 `SmartScraperGraph`，它根据用户提示和源 URL 从单个页面提取信息。
 
 
 ```python
@@ -100,7 +106,7 @@ print(json.dumps(result, indent=4))
 ```
 
 > [!NOTE]
-> For OpenAI and other models you just need to change the llm config!
+> 对于 OpenAI 及其他模型，你只需修改 llm 配置！
 > ```python
 >graph_config = {
 >    "llm": {
@@ -113,7 +119,7 @@ print(json.dumps(result, indent=4))
 >```
 
 
-The output will be a dictionary like the following:
+输出将如下所示的字典：
 
 ```python
 {
@@ -142,88 +148,89 @@ The output will be a dictionary like the following:
     }
 }
 ```
-There are other pipelines that can be used to extract information from multiple pages, generate Python scripts, or even generate audio files.
+还有其他流水线可用于从多个页面提取信息、生成 Python 脚本，甚至生成音频文件。
 
-| Pipeline Name           | Description                                                                                                      |
+| 流水线名称           | 说明                                                                                                      |
 |-------------------------|------------------------------------------------------------------------------------------------------------------|
-| SmartScraperGraph       | Single-page scraper that only needs a user prompt and an input source.                                           |
-| SearchGraph             | Multi-page scraper that extracts information from the top n search results of a search engine.                  |
-| SpeechGraph             | Single-page scraper that extracts information from a website and generates an audio file.                       |
-| ScriptCreatorGraph      | Single-page scraper that extracts information from a website and generates a Python script.                     |
-| SmartScraperMultiGraph  | Multi-page scraper that extracts information from multiple pages given a single prompt and a list of sources.    |
-| ScriptCreatorMultiGraph | Multi-page scraper that generates a Python script for extracting information from multiple pages and sources.     |
+| SmartScraperGraph       | 单页爬取器，仅需用户提示和输入源。                                           |
+| SearchGraph             | 多页爬取器，从搜索引擎前 n 条搜索结果中提取信息。                  |
+| SpeechGraph             | 单页爬取器，从网站提取信息并生成音频文件。                       |
+| ScriptCreatorGraph      | 单页爬取器，从网站提取信息并生成 Python 脚本。                     |
+| SmartScraperMultiGraph  | 多页爬取器，根据单一提示和源列表从多个页面提取信息。    |
+| ScriptCreatorMultiGraph | 多页爬取器，生成用于从多个页面和源提取信息的 Python 脚本。     |
 
-For each of these graphs there is the multi version. It allows to make calls of the LLM in parallel.
+这些图（graph）各自都有 multi 版本，可并行调用 LLM。
 
-It is possible to use different LLM through APIs, such as **OpenAI**, **Groq**, **Azure**, **Gemini**, **MiniMax** and more, or local models using **Ollama**.
+可通过 API 使用不同的 LLM，例如 **OpenAI**、**Groq**、**Azure**、**Gemini**、**MiniMax** 等，也可通过 **Ollama** 使用本地模型。
 
-Remember to have [Ollama](https://ollama.com/) installed and download the models using the **ollama pull** command, if you want to use local models.
+若要使用本地模型，请确保已安装 [Ollama](https://ollama.com/)，并使用 **ollama pull** 命令下载模型。
 
 
-## 📖 Documentation
+## 📖 文档
 
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1sEZBonBMGP44CtO6GQTwAlL0BGJXjtfd?usp=sharing)
 
-The documentation for ScrapeGraphAI can be found [here](https://docs.scrapegraphai.com/introduction).
-## 🆚 Open Source vs Managed API
+ScrapeGraphAI 文档见[此处](https://docs.scrapegraphai.com/introduction).
 
-ScrapeGraphAI comes in two flavours: **this open-source library**, which you run yourself, and the **managed cloud API** (used via the [Python](https://github.com/ScrapeGraphAI/scrapegraph-py) and [JS/TS](https://github.com/ScrapeGraphAI/scrapegraph-js) SDKs). This table explains the difference so you can pick the right one.
+## 🆚 开源版 vs 托管 API
 
-| | Open Source (`scrapegraphai`) | Managed API (`scrapegraph-py` / `scrapegraph-js`) |
+ScrapeGraphAI 提供两种形态：**本开源库**由你自行部署运行，以及通过 [Python](https://github.com/ScrapeGraphAI/scrapegraph-py) 和 [JS/TS](https://github.com/ScrapeGraphAI/scrapegraph-js) SDK 调用的**托管云 API**。下表说明两者的差异，便于你选择合适方案。
+
+| | 开源版 (`scrapegraphai`) | 托管 API (`scrapegraph-py` / `scrapegraph-js`) |
 |---|---|---|
-| **What it is** | A Python library you run yourself | A hosted cloud service you call via SDK |
-| **Where it runs** | Your own infrastructure (self-hosted) | ScrapeGraphAI cloud |
-| **LLM** | Bring your own (OpenAI, Groq, Gemini, Azure, local via Ollama) | Managed for you |
-| **Browser / JS rendering** | You configure it (Playwright) | Managed (stealth, `auto`/`fast`/`js` modes) |
-| **Proxies & anti-bot** | Your responsibility | Included |
-| **Scaling & maintenance** | Your responsibility | Fully managed |
-| **Cost model** | LLM tokens + your own infra | Pay-as-you-go credits |
-| **Auth** | Your own LLM keys | `SGAI_API_KEY` |
-| **Capabilities** | Graph pipelines (SmartScraper, Search, Speech, ScriptCreator…) | Scrape, Extract, Search, Crawl, Monitor, History |
-| **Setup effort** | More configuration | Minimal — API key + one call |
-| **License** | MIT | SDK is MIT; the API service is paid |
+| **它是什么** | 由你自行运行的 Python 库 | 通过 SDK 调用的托管云服务 |
+| **运行位置** | 你自己的基础设施（自托管） | ScrapeGraphAI 云端 |
+| **LLM** | 自带（OpenAI、Groq、Gemini、Azure，或通过 Ollama 本地运行） | 由平台托管 |
+| **浏览器 / JS 渲染** | 自行配置（Playwright） | 托管（隐身模式，`auto`/`fast`/`js` 模式） |
+| **代理与反爬** | 自行负责 | 已包含 |
+| **扩展与维护** | 自行负责 | 全托管 |
+| **成本模式** | LLM token + 自有基础设施 | 按用量付费积分 |
+| **认证** | 使用你自己的 LLM 密钥 | `SGAI_API_KEY` |
+| **能力** | 图流水线（SmartScraper、Search、Speech、ScriptCreator…） | Scrape、Extract、Search、Crawl、Monitor、History |
+| **搭建工作量** | 配置较多 | 最少——API 密钥 + 一次调用 |
+| **许可证** | MIT | SDK 为 MIT；API 服务为付费 |
 
-**Choose the open-source library** if you want full control, on-prem/self-hosted data, local LLMs (Ollama), or fine-grained cost tuning — and you're happy to manage browsers, proxies and scaling yourself.
+**选择开源库**，若你需要完全控制、本地/自托管数据、本地 LLM（Ollama）或精细成本调优——并愿意自行管理浏览器、代理与扩展。
 
-**Choose the managed API** if you want zero infrastructure, managed JS rendering & anti-bot, built-in **Crawl** and scheduled **Monitor** jobs, and the fastest path to production — billed per credit.
+**选择托管 API**，若你需要零基础设施、托管 JS 渲染与反爬、内置 **Crawl** 与定时 **Monitor** 任务，以及最快上线路径——按积分计费。
 
-- Open-source library: https://github.com/ScrapeGraphAI/Scrapegraph-ai
-- Python SDK: https://github.com/ScrapeGraphAI/scrapegraph-py
-- JS/TS SDK: https://github.com/ScrapeGraphAI/scrapegraph-js
-- API docs: https://docs.scrapegraphai.com/introduction
+- 开源库：https://github.com/ScrapeGraphAI/Scrapegraph-ai
+- Python SDK：https://github.com/ScrapeGraphAI/scrapegraph-py
+- JS/TS SDK：https://github.com/ScrapeGraphAI/scrapegraph-js
+- API 文档：https://docs.scrapegraphai.com/introduction
 
-## 🤝 Contributing
+## 🤝 参与贡献
 
-Feel free to contribute and join our Discord server to discuss with us improvements and give us suggestions!
+欢迎贡献并加入我们的 Discord 服务器，与我们讨论改进并向我们提出建议！
 
-Please see the [contributing guidelines](https://github.com/ScrapeGraphAI/Scrapegraph-ai/blob/main/CONTRIBUTING.md).
+请参阅[贡献指南](https://github.com/ScrapeGraphAI/Scrapegraph-ai/blob/main/CONTRIBUTING.md).
 
 [![My Skills](https://skillicons.dev/icons?i=discord)](https://discord.gg/uJN7TYcpNa)
 [![My Skills](https://skillicons.dev/icons?i=linkedin)](https://www.linkedin.com/company/scrapegraphai/)
 [![My Skills](https://skillicons.dev/icons?i=twitter)](https://twitter.com/scrapegraphai)
 
-## 🔗 ScrapeGraph API & SDKs
-If you are looking for a quick solution to integrate ScrapeGraph in your system, check out our powerful API [here!](https://scrapegraphai.com)
+## 🔗 ScrapeGraph API 与 SDK
+若你正在寻找将 ScrapeGraph 集成到系统中的快捷方案，请查看我们强大的 API [这里！](https://scrapegraphai.com)
 
 [![API Banner](https://raw.githubusercontent.com/ScrapeGraphAI/Scrapegraph-ai/main/docs/assets/api_banner.png)](https://scrapegraphai.com)
 
-We offer SDKs in both Python and Node.js, making it easy to integrate into your projects. Check them out below:
+我们提供 Python 和 Node.js 两套 SDK，便于集成到你的项目中。请在下方查看：
 
-| SDK       | Language | GitHub Link                                                                 |
+| SDK       | 语言 | GitHub 链接                                                                 |
 |-----------|----------|-----------------------------------------------------------------------------|
 | Python SDK | Python   | [scrapegraph-py](https://docs.scrapegraphai.com/sdks/python) |
 | Node.js SDK | Node.js  | [scrapegraph-js](https://docs.scrapegraphai.com/sdks/javascript) |
 
-The Official API Documentation can be found [here](https://docs.scrapegraphai.com/introduction).
+官方 API 文档可在此查看 [这里](https://docs.scrapegraphai.com/introduction).
 
-## 📈 Telemetry
-We collect anonymous usage metrics to enhance our package's quality and user experience. The data helps us prioritize improvements and ensure compatibility. If you wish to opt-out, set the environment variable SCRAPEGRAPHAI_TELEMETRY_ENABLED=false. For more information, please refer to the documentation [here](https://docs.scrapegraphai.com/introduction).
+## 📈 遥测（Telemetry）
+我们收集匿名使用指标以提升软件包质量与用户体验。这些数据帮助我们优先改进并确保兼容性。若要退出，请设置环境变量 SCRAPEGRAPHAI_TELEMETRY_ENABLED=false。更多信息请参阅文档 [这里](https://docs.scrapegraphai.com/introduction).
 
-## ❤️ Contributors
+## ❤️ 贡献者
 [![Contributors](https://contrib.rocks/image?repo=ScrapeGraphAI/Scrapegraph-ai)](https://github.com/ScrapeGraphAI/Scrapegraph-ai/graphs/contributors)
 
-## 🎓 Citations
-If you have used our library for research purposes please quote us with the following reference:
+## 🎓 引用
+若你在研究中使用了本库，请使用以下文献引用我们：
 ```text
   @misc{scrapegraph-ai,
     author = {Lorenzo Padoan, Marco Vinciguerra},
@@ -233,22 +240,22 @@ If you have used our library for research purposes please quote us with the foll
     note = {A Python library for scraping leveraging large language models}
   }
 ```
-## Authors
+## 作者
 
-|                    | Contact Info         |
+|                    | 联系方式         |
 |--------------------|----------------------|
 | Marco Vinciguerra  | [![Linkedin Badge](https://img.shields.io/badge/-Linkedin-blue?style=flat&logo=Linkedin&logoColor=white)](https://www.linkedin.com/in/marco-vinciguerra-7ba365242/)    |
 | Lorenzo Padoan     | [![Linkedin Badge](https://img.shields.io/badge/-Linkedin-blue?style=flat&logo=Linkedin&logoColor=white)](https://www.linkedin.com/in/lorenzo-padoan-4521a2154/)  |
 
-## 📜 License
+## 📜 许可证
 
-ScrapeGraphAI is licensed under the MIT License. See the [LICENSE](https://github.com/ScrapeGraphAI/Scrapegraph-ai/blob/main/LICENSE) file for more information.
+ScrapeGraphAI 采用 MIT 许可证。更多信息请参阅 [LICENSE](https://github.com/ScrapeGraphAI/Scrapegraph-ai/blob/main/LICENSE) 文件。
 
-## Acknowledgements
+## 致谢
 
-- We would like to thank all the contributors to the project and the open-source community for their support.
-- ScrapeGraphAI is meant to be used for data exploration and research purposes only. We are not responsible for any misuse of the library.
+- 感谢所有项目贡献者及开源社区的支持。
+- ScrapeGraphAI 仅用于数据探索与研究目的。我们不对库的滥用承担责任。
 
-Made with ❤️ by [ScrapeGraph AI](https://scrapegraphai.com)
+由 [ScrapeGraph AI](https://scrapegraphai.com) 用 ❤️ 打造
 
 [Scarf tracking](https://static.scarf.sh/a.png?x-pxid=102d4b8c-cd6a-4b9e-9a16-d6d141b9212d)