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Gen AI apps are built with MongoDB Atlas
Build gen AI apps with an all-in-one modern database: MongoDB Atlas
MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
HyperSQL is like a doxygen plus javadoc for SQL, hypermapping SQL views, packages, procedures, and functions to HTML source code listings and showing all code locations where these are used.
The pydoc module, distributed bundled with python, proved extremely helpful in handling documentation strings included in pythonscripts. This project proposes a clean up of the code as well as add new capabilities, with python version 2.6 as a target.
POST (Python Obviously Simple Text) provides support for
simple, flexible dynamic document generation in multiple output
formats. Supports inputs in text or XML, outputs
in HTML, PDF, RTF, LaTeX source, nroff source, postscript,
and plain text.
Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.