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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 graphical tool for designing finite state machines and exporting them to Hardware Description Languages, such as VHDL, AHDL, Verilog, or Ragel/SMC files for C, C++, Objective-C, Java, Python, PHP, Perl, Lua code generation.
lib_data_io is a set of PHP libraries designed to easily move complex sets of data between PHP array data structures and a variety of sources and destinations including JSON, XML, ICAL, MySQL, HTML, Trac WIKI, text, LDIF, and plot images.
An interactive binary search tree. The user may interact with the tree by performing rotations, balancing, insertions, and deletions. For educational purposes
Our new software release will dramatically improve your medspa business performance while enhancing the customer experience
AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
A PHP webapp to upload taxonomic checklists as Excel or CSV files to be served as TDWG TCS XML/RDF. It can handle multiple checklists, has a Tapir light webservice and a taxonomic tree of species names created from taxonomy in a checklist can be browsed.
Numerically estimate an efficiency of code construction algorithms. Randomly generate n binary words of length m with minimum Hamming distance d and create a prefix code (= retrieval tree) from them. Based on PhD work.