Showing 4 open source projects for "ai linux"

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    LLM Tornado

    LLM Tornado

    The .NET library to build AI agents with 30+ built-in connectors

    LLM Tornado is a provider-agnostic .NET SDK designed to build, orchestrate, and deploy AI agents and workflows with a strong focus on flexibility and integration. It provides a unified interface that connects to more than 30 AI providers and vector databases, allowing developers to switch between models and services without rewriting application logic. The framework introduces a powerful orchestration system based on graph-like structures, where agents, tasks, and transitions can be defined...
    Downloads: 5 This Week
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  • 2
    Librelancer

    Librelancer

    A re-implementation of Freelancer

    Librelancer is an open-source reimplementation of the engine behind Freelancer, the iconic 2003 space trading and combat simulation game by Microsoft. Written in C# and powered by OpenGL and modern game development practices, Librelancer faithfully replicates the original gameplay while providing a flexible codebase for modding, analysis, and future enhancements. It supports original assets and is designed to be both a preservation project and a foundation for new space simulation games...
    Downloads: 1 This Week
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  • 3
    LangChain for .NET

    LangChain for .NET

    C# implementation of LangChain

    LangChain .NET is a C# implementation of the LangChain framework that enables developers to build LLM-powered applications using the .NET ecosystem. The project aims to replicate the core abstractions of LangChain, such as chains, agents, and vector stores, while adapting them to the conventions and strengths of C#. It emphasizes composability, allowing developers to build complex workflows by combining modular components that interact with language models and external data sources. The...
    Downloads: 2 This Week
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  • 4
    NeuronDotNet is a neural network engine written in C#. It provides an interface for advanced AI programmers to design various types of artificial neural networks and use them.
    Downloads: 0 This Week
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