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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.
Manage node sets, node groups and execute commands on cluster nodes in parallel. Provides an event-based Python library to improve administration of large compute clusters or server farms. Command line tools: clush and nodeset included.
Scalable, distributed monitoring system for high-performance computing
Ganglia is a scalable distributed monitoring system for high-performance computing systems such as clusters and Grids. It is based on a hierarchical design targeted at federations of clusters. Supports clusters up to 2000 nodes in size.
GGI stands for "General Graphics Interface", and it is a project that aims to develop a reliable, stable and fast graphics system that works everywhere. We want to allow any program using GGI to run on any platform requiring at most a recompile.
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.
ActiveGrid is an Enterprise Web 2.0 solution that allows the composition of code-free applications that comply with corporate IT standards. Technologies include Python, Java, XForm, Xpath, WSDL, CSS, XML Schema (XSD), XACML, and BPEL.
The Distribulator: Distributed Computing For The Rest Of Us. This is an SSH-based command execution and file transfer utility that includes support for batch, console, and shell integration modes, multiple server enviornments, and full audit logs.
General purpose client/server python execution code. This code allows a server to serve a list of python codes to clients for execution. The client then sends the result (literally the value of the variable converted to a string) back to the server.