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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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AIGC

@aigcrubbish · Post #16 · 12/25/2024, 06:34 PM

libxml2 在 2.11.9、2.12.9 和 2.13.3 之前的版本中存在一个安全漏洞,SAX 解析器在自定义 SAX 处理程序尝试通过设置 "checked" 来覆盖实体内容时,仍然会为外部实体生成事件。这使得经典的 XXE(XML 外部实体注入)攻击成为可能。 该漏洞已在后续版本中修复,建议用户尽快升级到最新版本以避免潜在的安全风险。 参考链接: - [GitHub 安全公告](https://github.com/advisories/GHSA-6c2p-rqx3-w4px) - [NVD 漏洞详情](https://nvd.nist.gov/vuln/detail/CVE-2024-40896) - [libxml2 修复提交](https://gitlab.gnome.org/GNOME/libxml2/-/commit/1a8932303969907f6572b1b6aac4081c56adb5c6) - [libxml2 问题报告](https://gitlab.gnome.org/GNOME/libxml2/-/issues/761) #安全漏洞#XXE#libxml2#SAX解析器 #AIGC

djangoproject

@djangoproject · Post #551 · 01/23/2018, 04:28 PM

http://lxml.de/ #lxml is the most feature-rich and easy-to-use library for processing #XML and #HTML in the Python language. The lxml XML toolkit is a Pythonic binding for the #C libraries #libxml2 and #libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python #API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all #CPython versions from 2.6 to 3.6. See the introduction for more information about background and goals of the lxml project. Some common questions are answered in the FAQ.