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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.
An educational demo of how sorting algorithms work.
...The user can modify the speed of execution and the type of data to sort and execute it step by step. The tooltip of each algorithm's box shows the source code that is executed and a little explanation got from wikipedia.
This application is aided to computer science students who want to better understand how the algorithms work.
Extract a Term Concept Map from Wikipedia. It takes an export of the Wikipedia and imports it into a database. The extracted term concept map can then serve as a basis for semantically enhancing applications, with the depth and bredth of the Wikipedia.
LiMa means Lightweight Markup Language. It is a parser for an easy to use ASCII/Text-based markup - comparable to Markdown or the Wikipedia-Markup language with special configurable extensions in defining Links and image-resources.