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## 🚀 **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 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(OpenAIGroqGeminiAzure,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(SmartScraperSearchSpeechScriptCreator… | ScrapeExtractSearchCrawlMonitorHistory |
| **搭建工作量** | 配置较多 | 最少——API 密钥 + 一次调用 |
| **许可证** | MIT | SDK MITAPI 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 LLMOllama)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 SDKhttps://github.com/ScrapeGraphAI/scrapegraph-py
- JS/TS SDKhttps://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 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 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)
[ScrapeGraph AI](https://scrapegraphai.com) 用 ❤️ 打造
[Scarf tracking](https://static.scarf.sh/a.png?x-pxid=102d4b8c-cd6a-4b9e-9a16-d6d141b9212d)