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Gen AI apps are built with MongoDB Atlas
Build gen AI apps with an all-in-one modern database: MongoDB Atlas
MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
Odigos supports any application written in Java, Python, .NET, Node.js and Go. Historically, compiled languages like Go have been difficult to instrument without code changes. Odigos solves this problem by uniquely leveraging eBPF. Odigos currently supports all the popular managed and open source destinations. By producing data in the OpenTelemetry format, Odigos can be used with any observability tool that supports OTLP.
...It currently incorporates six prioritization modules, based on gene sequence, protein-protein interactions, gene expression, disease-causing probabilities, genomic context).
GEPETTO is written in Java/Python and supported by an advanced modular architecture, which means that it can easily be modified and extended by the user, in order to include alternative scoring methods and new data sources. We intend to extend the system from gene-level to variant-level prioritization, by exploiting the variant data in the MSV3D database.
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Framework for making Windows applications that are one .exe file in AutoHotKey_L,C++,C#, VB.NET,Java,Groovy,Common Lisp,Nemerle,Ruby,Python,PHP,Lua,Tcl,Perl,Jint,S#,WSH VBScript,HTML/JavaScript/CSS,COM, PowerShell without compiling . For .NET 4.