Rust LLM Inference Tools

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Browse free open source Rust LLM Inference Tools and projects below. Use the toggles on the left to filter open source Rust LLM Inference Tools by OS, license, language, programming language, and project status.

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  • 1
    Artificial Intelligence Controller

    Artificial Intelligence Controller

    AICI: Prompts as (Wasm) Programs

    AICI is a framework that allows developers to build controllers that constrain and direct the output of Large Language Models (LLMs). By treating prompts as WebAssembly (Wasm) programs, AICI enables more precise and controlled interactions with LLMs, enhancing their utility in various applications. This approach allows for the creation of more reliable and predictable AI-driven systems.
    Downloads: 1 This Week
    Last Update:
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  • 2
    pipeless

    pipeless

    A computer vision framework to create and deploy apps in minutes

    Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new video frames and Pipeless takes care of everything else. You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud.
    Downloads: 1 This Week
    Last Update:
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  • 3
    Arch Gateway

    Arch Gateway

    The AI-native (edge and LLM) proxy for agents

    Arch is an AI-native proxy designed to facilitate the development of agentic applications by handling complex tasks such as input clarification, agent routing, and seamless integration of prompts with tools for common tasks. It provides unified access and observability of Large Language Models (LLMs), enabling developers to build applications more efficiently. Arch supports both edge and LLM deployments, offering flexibility in various environments.
    Downloads: 0 This Week
    Last Update:
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