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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.
A means to measure network responsiveness and throughput
Iperf here is a means of measuring networks - capacity & latency (including ECN) over sockets both TCP and UDP. The goals include maintaining an active iperf code base across a broad set of platforms and operating systems. This is a multi-threaded design that scales with the number of CPUs or cores within a system. It supports both high impact and low impact techniques to obtain and report network performance.
Current release: 2.2.1, Nov 4th, 2024
About iperf 2 and iperf3: Read...
Builds and images, yet to be tested, both stable and unstable from several different custom ROMs, with different changes in source code for further experimentations to fix build bugs and issues. If installing on your own personal device, proceed with caution, and kindly follow instructions given by builder.
AOSP-based Operating System (On phone tap on "Try to download anyway")
halogenOS test builds (release builds are just a leftover)
The test builds and modules are supposed to be only used by our testers. But if you are not a tester, and use these builds anyways, don't expect support if you get problems. You can report the bugs, but you have to be experienced enough to know how to revert back to a working state and how to report bugs and provide logs.
Accessing EXEHDA's contextual information from Android devices.
This work has as central objective the conception of an architecture for the information access from a Context Awareness Service of EXEHDA, from mobile devices.
This architecture, named EXEHDA-AD, will be distributed with some software components dedicated to the integration with the EXEHDA services, and others to promote the functionalities to the users of mobile devices.
Was selected the Android platform for the development of the mobile part of the EXEHDA-DA software...
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