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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 command-line tool for data-driven fuzzy modelling
Input 1 - A training dataset (multiple observations) of up to four variables (predictors) against one (response variable)
Input 2 - A test dataset (multiple observations) of the same four variables with unknown response variable
Output - Calculation of the response variable for each test observation using fuzzy logic or fuzzy rule-based Bayesian algorithms
HABFUZZ is a habitat model, which can be used in ecohydraulic modelling applications for the calculation of the instream habitat suitability in various discharge scenarios in a simulated river reach. ...
FORTRAN Unit Test Framework FRUIT - TDD in FORTRAN
FORTRAN Unit Test Framework, written in FORTRAN 95. So that all FORTRAN features can be tested. FRUIT has assertion, fixture, setup, teardown, report, spec, driver generation. Rake used as build tool. Tutorials at http://fortranxunit.wiki.sourceforge.net
The core testing part is in FORTRAN, this part can be used independent of the Ruby codes.