• Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
    Try for free
  • Desktop and Mobile Device Management Software Icon
    Desktop and Mobile Device Management Software

    It's a modern take on desktop management that can be scaled as per organizational needs.

    Desktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
    Learn More
  • 1
    diff2html

    diff2html

    Pretty diff to html javascript library (diff2html)

    Each diff provides a comprehensive visualization of the code changes, helping developers identify problems and better understand the changes. Each diff features a line-by-line and side-by-side preview of your changes. All the code changes are syntax highlighted using highlight.js, providing more readability. Similar lines are paired, allowing for easier change tracking. We work hard to make sure you can have your diffs in a simple and flexible way. The AI community building the future....
    Downloads: 2 This Week
    Last Update:
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  • 2
    torchtext

    torchtext

    Data loaders and abstractions for text and NLP

    ...Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. When building from source, make sure that you have the same C++ compiler as the one used to build PyTorch. A simple way is to build PyTorch from source and use the same environment to build torchtext. If you are using the nightly build of PyTorch, check out the environment it was built with conda (here) and pip (here). ...
    Downloads: 0 This Week
    Last Update:
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